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Zoteva V, De Meulenaere V, Vanhove C, Leybaert L, Raedt R, Pieters L, Vral A, Boterberg T, Deblaere K. Integrating and optimizing tonabersat in standard glioblastoma therapy: A preclinical study. PLoS One 2024; 19:e0300552. [PMID: 38489314 PMCID: PMC10942024 DOI: 10.1371/journal.pone.0300552] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2024] [Accepted: 02/28/2024] [Indexed: 03/17/2024] Open
Abstract
Glioblastoma (GB), a highly aggressive primary brain tumor, presents a poor prognosis despite the current standard therapy, including radiotherapy and temozolomide (TMZ) chemotherapy. Tumor microtubes involving connexin 43 (Cx43) contribute to glioma progression and therapy resistance, suggesting Cx43 inhibition as a potential treatment strategy. This research aims to explore the adjuvant potential of tonabersat, a Cx43 gap junction modulator and blood-brain barrier-penetrating compound, in combination with the standard of care for GB. In addition, different administration schedules and timings to optimize tonabersat's therapeutic window are investigated. The F98 Fischer rat model will be utilized to investigate tonabersat's impact in a clinically relevant setting, by incorporating fractionated radiotherapy (three fractions of 9 Gy) and TMZ chemotherapy (29 mg/kg). This study will evaluate tonabersat's impact on tumor growth, survival, and treatment response through advanced imaging (CE T1-w MRI) and histological analysis. Results show extended survival in rats receiving tonabersat with standard care, highlighting its adjuvant potential. Daily tonabersat administration, both preceding and following radiotherapy, emerges as a promising approach for maximizing survival outcomes. The study suggests tonabersat's potential to reduce tumor invasiveness, providing a new avenue for GB treatment. In conclusion, this preclinical investigation highlights tonabersat's potential as an effective adjuvant treatment for GB, and its established safety profile from clinical trials in migraine treatment presents a promising foundation for further exploration.
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Affiliation(s)
| | | | | | - Luc Leybaert
- Physiology Group, Department of Basic and Applied Medical Sciences, Ghent University, Ghent, Belgium
| | - Robrecht Raedt
- Department of Head and Skin, Ghent University, Ghent, Belgium
| | - Leen Pieters
- Department of Human Structure and Repair, Ghent University, Ghent, Belgium
| | - Anne Vral
- Department of Human Structure and Repair, Ghent University, Ghent, Belgium
| | - Tom Boterberg
- Department of Radiation Oncology, Ghent University Hospital, Ghent, Belgium
| | - Karel Deblaere
- Department of Radiology, Ghent University, Ghent, Belgium
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Muller FM, Vervenne B, Maebe J, Blankemeyer E, Sellmyer MA, Zhou R, Karp JS, Vanhove C, Vandenberghe S. Image Denoising of Low-Dose PET Mouse Scans with Deep Learning: Validation Study for Preclinical Imaging Applicability. Mol Imaging Biol 2024; 26:101-113. [PMID: 37875748 DOI: 10.1007/s11307-023-01866-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2023] [Revised: 10/09/2023] [Accepted: 10/12/2023] [Indexed: 10/26/2023]
Abstract
PURPOSE Positron emission tomography (PET) image quality can be improved by higher injected activity and/or longer acquisition time, but both may often not be practical in preclinical imaging. Common preclinical radioactive doses (10 MBq) have been shown to cause deterministic changes in biological pathways. Reducing the injected tracer activity and/or shortening the scan time inevitably results in low-count acquisitions which poses a challenge because of the inherent noise introduction. We present an image-based deep learning (DL) framework for denoising lower count micro-PET images. PROCEDURES For 36 mice, a 15-min [18F]FDG (8.15 ± 1.34 MBq) PET scan was acquired at 40 min post-injection on the Molecubes β-CUBE (in list mode). The 15-min acquisition (high-count) was parsed into smaller time fractions of 7.50, 3.75, 1.50, and 0.75 min to emulate images reconstructed at 50, 25, 10, and 5% of the full counts, respectively. A 2D U-Net was trained with mean-squared-error loss on 28 high-low count image pairs. RESULTS The DL algorithms were visually and quantitatively compared to spatial and edge-preserving denoising filters; the DL-based methods effectively removed image noise and recovered image details much better while keeping quantitative (SUV) accuracy. The largest improvement in image quality was seen in the images reconstructed with 10 and 5% of the counts (equivalent to sub-1 MBq or sub-1 min mouse imaging). The DL-based denoising framework was also successfully applied on the NEMA-NU4 phantom and different tracer studies ([18F]PSMA, [18F]FAPI, and [68 Ga]FAPI). CONCLUSION Visual and quantitative results support the superior performance and robustness in image denoising of the implemented DL models for low statistics micro-PET. This offers much more flexibility in optimizing preclinical, longitudinal imaging protocols with reduced tracer doses or shorter durations.
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Affiliation(s)
- Florence M Muller
- Medical Image and Signal Processing (MEDISIP), Department of Electronics and Information Systems, Faculty of Engineering and Architecture, Ghent University, 9000, Ghent, Belgium.
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA19104, USA.
| | - Boris Vervenne
- Medical Image and Signal Processing (MEDISIP), Department of Electronics and Information Systems, Faculty of Engineering and Architecture, Ghent University, 9000, Ghent, Belgium
| | - Jens Maebe
- Medical Image and Signal Processing (MEDISIP), Department of Electronics and Information Systems, Faculty of Engineering and Architecture, Ghent University, 9000, Ghent, Belgium
| | - Eric Blankemeyer
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA19104, USA
| | - Mark A Sellmyer
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA19104, USA
| | - Rong Zhou
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA19104, USA
| | - Joel S Karp
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA19104, USA
| | - Christian Vanhove
- Medical Image and Signal Processing (MEDISIP), Department of Electronics and Information Systems, Faculty of Engineering and Architecture, Ghent University, 9000, Ghent, Belgium
| | - Stefaan Vandenberghe
- Medical Image and Signal Processing (MEDISIP), Department of Electronics and Information Systems, Faculty of Engineering and Architecture, Ghent University, 9000, Ghent, Belgium
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Zoteva V, De Meulenaere V, De Boeck M, Vanhove C, Leybaert L, Raedt R, Pieters L, Vral A, Boterberg T, Deblaere K. An improved F98 glioblastoma rat model to evaluate novel treatment strategies incorporating the standard of care. PLoS One 2024; 19:e0296360. [PMID: 38165944 PMCID: PMC10760731 DOI: 10.1371/journal.pone.0296360] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2023] [Accepted: 12/11/2023] [Indexed: 01/04/2024] Open
Abstract
Glioblastoma (GB) is the most common and malignant primary brain tumor in adults with a median survival of 12-15 months. The F98 Fischer rat model is one of the most frequently used animal models for GB studies. However, suboptimal inoculation leads to extra-axial and extracranial tumor formations, affecting its translational value. We aim to improve the F98 rat model by incorporating MRI-guided (hypo)fractionated radiotherapy (3 x 9 Gy) and concomitant temozolomide chemotherapy, mimicking the current standard of care. To minimize undesired tumor growth, we reduced the number of inoculated cells (starting from 20 000 to 500 F98 cells), slowed the withdrawal of the syringe post-inoculation, and irradiated the inoculation track separately. Our results reveal that reducing the number of F98 GB cells correlates with a diminished risk of extra-axial and extracranial tumor growth. However, this introduces higher variability in days until GB confirmation and uniformity in GB growth. To strike a balance, the model inoculated with 5000 F98 cells displayed the best results and was chosen as the most favorable. In conclusion, our improved model offers enhanced translational potential, paving the way for more accurate and reliable assessments of novel adjuvant therapeutic approaches for GB.
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Affiliation(s)
| | | | | | | | - Luc Leybaert
- Physiology Group, Department of Basic and Applied Medical Sciences, Ghent University, Ghent, Belgium
| | - Robrecht Raedt
- Department of Head and Skin, Ghent University, Ghent, Belgium
| | - Leen Pieters
- Department of Human Structure and Repair, Ghent University, Ghent, Belgium
| | - Anne Vral
- Department of Human Structure and Repair, Ghent University, Ghent, Belgium
| | - Tom Boterberg
- Department of Radiation Oncology, Ghent University Hospital, Ghent, Belgium
| | - Karel Deblaere
- Department of Radiology, Ghent University, Ghent, Belgium
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Braet H, Fransen PP, Mariën R, Lollo G, Ceelen W, Vervaet C, Balcaen L, Vanhaecke F, Vanhove C, van der Vegte S, Gasthuys E, Vermeulen A, Dankers PYW, De Smedt SC, Remaut K. CO 2-Driven Nebulization of pH-Sensitive Supramolecular Polymers for Intraperitoneal Hydrogel Formation and the Treatment of Peritoneal Metastasis. ACS Appl Mater Interfaces 2023; 15:49022-49034. [PMID: 37819736 DOI: 10.1021/acsami.3c11274] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/13/2023]
Abstract
Because peritoneal metastasis (PM) from ovarian cancer is characterized by non-specific symptoms, it is often diagnosed at advanced stages. Pressurized intraperitoneal aerosol chemotherapy (PIPAC) can be considered a promising drug delivery method for unresectable PM. Currently, the efficacy of intraperitoneal (IP) drug delivery is limited by the off-label use of IV chemotherapeutic solutions, which are rapidly cleared from the IP cavity. Hence, this research aimed to improve PM treatment by evaluating a nanoparticle-loaded, pH-switchable supramolecular polymer hydrogel as a controlled release drug delivery system that can be IP nebulized. Moreover, a multidirectional nozzle was developed to allow nebulization of viscous materials such as hydrogels and to reach an even IP gel deposition. We demonstrated that acidification of the nebulized hydrogelator solution by carbon dioxide, used to inflate the IP cavity during laparoscopic surgery, stimulated the in situ gelation, which prolonged the IP hydrogel retention. In vitro experiments indicated that paclitaxel nanocrystals were gradually released from the hydrogel depot formed, which sustained the cytotoxicity of the formulation for 10 days. Finally, after aerosolization of this material in a xenograft model of PM, tumor progression could successfully be delayed, while the overall survival time was significantly increased compared to non-treated animals.
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Affiliation(s)
- Helena Braet
- Department of Pharmaceutics, Ghent University, Ghent 9000, Belgium
- CRIG - Cancer Research Institute Ghent, Ghent 9000, Belgium
| | | | - Remco Mariën
- Department of Pharmaceutics, Ghent University, Ghent 9000, Belgium
| | - Giovanna Lollo
- Laboratoire d'Automatique, de Génie des Procédés et de Génie Pharmaceutique (LAGEPP), Université Claude Bernard Lyon 1, Lyon 69622, France
| | - Wim Ceelen
- CRIG - Cancer Research Institute Ghent, Ghent 9000, Belgium
- Department of Human Structure and Repair, Ghent University, Ghent 9000, Belgium
| | - Chris Vervaet
- Department of Pharmaceutics, Ghent University, Ghent 9000, Belgium
| | - Lieve Balcaen
- Department of Chemistry, Ghent University, Ghent 9000, Belgium
| | - Frank Vanhaecke
- CRIG - Cancer Research Institute Ghent, Ghent 9000, Belgium
- Department of Chemistry, Ghent University, Ghent 9000, Belgium
| | - Christian Vanhove
- CRIG - Cancer Research Institute Ghent, Ghent 9000, Belgium
- Department of Electronics and Information Systems, Ghent University, Ghent 9000, Belgium
| | | | - Elke Gasthuys
- Department of Bioanalysis, Ghent University, Ghent 9000, Belgium
| | - An Vermeulen
- Department of Bioanalysis, Ghent University, Ghent 9000, Belgium
| | - Patricia Y W Dankers
- Department of Biomedical Engineering and Institute for Complex Molecular Systems, Eindhoven University of Technology, Eindhoven 5600 MB, The Netherlands
| | - Stefaan C De Smedt
- Department of Pharmaceutics, Ghent University, Ghent 9000, Belgium
- CRIG - Cancer Research Institute Ghent, Ghent 9000, Belgium
| | - Katrien Remaut
- Department of Pharmaceutics, Ghent University, Ghent 9000, Belgium
- CRIG - Cancer Research Institute Ghent, Ghent 9000, Belgium
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Thiran A, Petta I, Blancke G, Thorp M, Planckaert G, Jans M, Andries V, Barbry K, Gilis E, Coudenys J, Hochepied T, Vanhove C, Gracey E, Dumas E, Manuelo T, Josipovic I, van Loo G, Elewaut D, Vereecke L. Sterile triggers drive joint inflammation in TNF- and IL-1β-dependent mouse arthritis models. EMBO Mol Med 2023; 15:e17691. [PMID: 37694693 PMCID: PMC10565626 DOI: 10.15252/emmm.202317691] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2023] [Revised: 08/21/2023] [Accepted: 08/22/2023] [Indexed: 09/12/2023] Open
Abstract
Arthritis is the most common extra-intestinal complication in inflammatory bowel disease (IBD). Conversely, arthritis patients are at risk for developing IBD and often display subclinical gut inflammation. These observations suggest a shared disease etiology, commonly termed "the gut-joint-axis." The clinical association between gut and joint inflammation is further supported by the success of common therapeutic strategies and microbiota dysbiosis in both conditions. Most data, however, support a correlative relationship between gut and joint inflammation, while causative evidence is lacking. Using two independent transgenic mouse arthritis models, either TNF- or IL-1β dependent, we demonstrate that arthritis develops independently of the microbiota and intestinal inflammation, since both lines develop full-blown articular inflammation under germ-free conditions. In contrast, TNF-driven gut inflammation is fully rescued in germ-free conditions, indicating that the microbiota is driving TNF-induced gut inflammation. Together, our study demonstrates that although common inflammatory pathways may drive both gut and joint inflammation, the molecular triggers initiating such pathways are distinct in these tissues.
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Vandenberghe S, Muller FM, Withofs N, Dadgar M, Maebe J, Vervenne B, Akl MA, Xue S, Shi K, Sportelli G, Belcari N, Hustinx R, Vanhove C, Karp JS. Walk-through flat panel total-body PET: a patient-centered design for high throughput imaging at lower cost using DOI-capable high-resolution monolithic detectors. Eur J Nucl Med Mol Imaging 2023; 50:3558-3571. [PMID: 37466650 PMCID: PMC10547652 DOI: 10.1007/s00259-023-06341-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2023] [Accepted: 07/07/2023] [Indexed: 07/20/2023]
Abstract
PURPOSE Long axial field-of-view (LAFOV) systems have a much higher sensitivity than standard axial field-of-view (SAFOV) PET systems for imaging the torso or full body, which allows faster and/or lower dose imaging. Despite its very high sensitivity, current total-body PET (TB-PET) throughput is limited by patient handling (positioning on the bed) and often a shortage of available personnel. This factor, combined with high system costs, makes it hard to justify the implementation of these systems for many academic and nearly all routine nuclear medicine departments. We, therefore, propose a novel, cost-effective, dual flat panel TB-PET system for patients in upright standing positions to avoid the time-consuming positioning on a PET-CT table; the walk-through (WT) TB-PET. We describe a patient-centered, flat panel PET design that offers very efficient patient throughput and uses monolithic detectors (with BGO or LYSO) with depth-of-interaction (DOI) capabilities and high intrinsic spatial resolution. We compare system sensitivity, component costs, and patient throughput of the proposed WT-TB-PET to a SAFOV (= 26 cm) and a LAFOV (= 106 cm) LSO PET systems. METHODS Patient width, height (= top head to start of thighs) and depth (= distance from the bed to front of patient) were derived from 40 randomly selected PET-CT scans to define the design dimensions of the WT-TB-PET. We compare this new PET system to the commercially available Siemens Biograph Vision 600 (SAFOV) and Siemens Quadra (LAFOV) PET-CT in terms of component costs, system sensitivity, and patient throughput. System cost comparison was based on estimating the cost of the two main components in the PET system (Silicon Photomultipliers (SiPMs) and scintillators). Sensitivity values were determined using Gate Monte Carlo simulations. Patient throughput times (including CT and scout scan, patient positioning on bed and transfer) were recorded for 1 day on a Siemens Vision 600 PET. These timing values were then used to estimate the expected patient throughput (assuming an equal patient radiotracer injected activity to patients and considering differences in system sensitivity and time-of-flight information) for WT-TB-PET, SAFOV and LAFOV PET. RESULTS The WT-TB-PET is composed of two flat panels; each is 70 cm wide and 106 cm high, with a 50-cm gap between both panels. These design dimensions were justified by the patient sizes measured from the 40 random PET-CT scans. Each panel consists of 14 × 20 monolithic BGO detector blocks that are 50 × 50 × 16 mm in size and are coupled to a readout with 6 × 6 mm SiPMs arrays. For the WT-TB-PET, the detector surface is reduced by a factor of 1.9 and the scintillator volume by a factor of 2.2 compared to LAFOV PET systems, while demonstrating comparable sensitivity and much better uniform spatial resolution (< 2 mm in all directions over the FOV). The estimated component cost for the WT-TB-PET is 3.3 × lower than that of a 106 cm LAFOV system and only 20% higher than the PET component costs of a SAFOV. The estimated maximum number of patients scanned on a standard 8-h working day increases from 28 (for SAFOV) to 53-60 (for LAFOV in limited/full acceptance) to 87 (for the WT-TB-PET). By scanning faster (more patients), the amount of ordered activity per patient can be reduced drastically: the WT-TB-PET requires 66% less ordered activity per patient than a SAFOV. CONCLUSIONS We propose a monolithic BGO or LYSO-based WT-TB-PET system with DOI measurements that departs from the classical patient positioning on a table and allows patients to stand upright between two flat panels. The WT-TB-PET system provides a solution to achieve a much lower cost TB-PET approaching the cost of a SAFOV system. High patient throughput is increased by fast patient positioning between two vertical flat panel detectors of high sensitivity. High spatial resolution (< 2 mm) uniform over the FOV is obtained by using DOI-capable monolithic scintillators.
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Affiliation(s)
- Stefaan Vandenberghe
- Medical Image and Signal Processing, Department of Electronics and Information Systems, Faculty of Engineering and Architecture, Ghent University, Corneel Heymanslaan 10, 9000, Ghent, Belgium.
| | - Florence M Muller
- Medical Image and Signal Processing, Department of Electronics and Information Systems, Faculty of Engineering and Architecture, Ghent University, Corneel Heymanslaan 10, 9000, Ghent, Belgium
| | - Nadia Withofs
- Division of Nuclear Medicine and Oncological Imaging, Department of Medical Physics, CHU of Liege, Quartier Hôpital, Avenue de Hôpital, 1, 4000, Liège 1, Belgium
| | - Meysam Dadgar
- Medical Image and Signal Processing, Department of Electronics and Information Systems, Faculty of Engineering and Architecture, Ghent University, Corneel Heymanslaan 10, 9000, Ghent, Belgium
| | - Jens Maebe
- Medical Image and Signal Processing, Department of Electronics and Information Systems, Faculty of Engineering and Architecture, Ghent University, Corneel Heymanslaan 10, 9000, Ghent, Belgium
| | - Boris Vervenne
- Medical Image and Signal Processing, Department of Electronics and Information Systems, Faculty of Engineering and Architecture, Ghent University, Corneel Heymanslaan 10, 9000, Ghent, Belgium
| | - Maya Abi Akl
- Medical Image and Signal Processing, Department of Electronics and Information Systems, Faculty of Engineering and Architecture, Ghent University, Corneel Heymanslaan 10, 9000, Ghent, Belgium
| | - Song Xue
- Department of Nuclear Medicine, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Kuangyu Shi
- Division of Nuclear Medicine and Oncological Imaging, Department of Medical Physics, CHU of Liege, Quartier Hôpital, Avenue de Hôpital, 1, 4000, Liège 1, Belgium
| | - Giancarlo Sportelli
- Dipartimento Di Fisica "E. Fermi", Università Di Pisa, Italy and with the Instituto Nazionale Di Fisica Nucleare, Sezione Di Pisa, 56127, Pisa, Italy
| | - Nicola Belcari
- Dipartimento Di Fisica "E. Fermi", Università Di Pisa, Italy and with the Instituto Nazionale Di Fisica Nucleare, Sezione Di Pisa, 56127, Pisa, Italy
| | - Roland Hustinx
- Division of Nuclear Medicine and Oncological Imaging, Department of Medical Physics, CHU of Liege, Quartier Hôpital, Avenue de Hôpital, 1, 4000, Liège 1, Belgium
| | - Christian Vanhove
- Medical Image and Signal Processing, Department of Electronics and Information Systems, Faculty of Engineering and Architecture, Ghent University, Corneel Heymanslaan 10, 9000, Ghent, Belgium
| | - Joel S Karp
- Physics and Instrumentation, Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA
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Maes B, Fayazpour F, Catrysse L, Lornet G, Van De Velde E, De Wolf C, De Prijck S, Van Moorleghem J, Vanheerswynghels M, Deswarte K, Descamps B, Vanhove C, Van der Schueren B, Vangoitsenhoven R, Hammad H, Janssens S, Lambrecht BN. STE20 kinase TAOK3 regulates type 2 immunity and metabolism in obesity. J Exp Med 2023; 220:e20210788. [PMID: 37347461 PMCID: PMC10287548 DOI: 10.1084/jem.20210788] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2021] [Revised: 03/31/2023] [Accepted: 06/02/2023] [Indexed: 06/23/2023] Open
Abstract
Healthy adipose tissue (AT) contains ST2+ Tregs, ILC2s, and alternatively activated macrophages that are lost in mice or humans on high caloric diet. Understanding how this form of type 2 immunity is regulated could improve treatment of obesity. The STE20 kinase Thousand And One amino acid Kinase-3 (TAOK3) has been linked to obesity in mice and humans, but its precise function is unknown. We found that ST2+ Tregs are upregulated in visceral epididymal white AT (eWAT) of Taok3-/- mice, dependent on IL-33 and the kinase activity of TAOK3. Upon high fat diet feeding, metabolic dysfunction was attenuated in Taok3-/- mice. ST2+ Tregs disappeared from eWAT in obese wild-type mice, but this was not the case in Taok3-/- mice. Mechanistically, AT Taok3-/- Tregs were intrinsically more responsive to IL-33, through higher expression of ST2, and expressed more PPARγ and type 2 cytokines. Thus, TAOK3 inhibits adipose tissue Tregs and regulates immunometabolism under excessive caloric intake.
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Affiliation(s)
- Bastiaan Maes
- Laboratory of Immunoregulation and Mucosal Immunology, VIB-UGent Center for Inflammation Research, Ghent, Belgium
- Department of Internal Medicine and Pediatrics, Ghent University, Ghent, Belgium
- Laboratory for Endoplasmic Reticulum Stress and Inflammation, VIB-UGent Center for Inflammation Research, Ghent, Belgium
| | - Farzaneh Fayazpour
- Department of Internal Medicine and Pediatrics, Ghent University, Ghent, Belgium
- Laboratory for Endoplasmic Reticulum Stress and Inflammation, VIB-UGent Center for Inflammation Research, Ghent, Belgium
| | - Leen Catrysse
- Cellular and Molecular (Patho)Physiology, VIB-UGent Center for Inflammation Research, Ghent, Belgium
- Department of Biomedical Molecular Biology, Ghent University, Ghent, Belgium
| | - Guillaume Lornet
- Laboratory of Immunoregulation and Mucosal Immunology, VIB-UGent Center for Inflammation Research, Ghent, Belgium
| | - Evelien Van De Velde
- Department of Internal Medicine and Pediatrics, Ghent University, Ghent, Belgium
- Laboratory for Endoplasmic Reticulum Stress and Inflammation, VIB-UGent Center for Inflammation Research, Ghent, Belgium
| | - Caroline De Wolf
- Laboratory of Immunoregulation and Mucosal Immunology, VIB-UGent Center for Inflammation Research, Ghent, Belgium
- Department of Internal Medicine and Pediatrics, Ghent University, Ghent, Belgium
| | - Sofie De Prijck
- Laboratory of Immunoregulation and Mucosal Immunology, VIB-UGent Center for Inflammation Research, Ghent, Belgium
- Department of Internal Medicine and Pediatrics, Ghent University, Ghent, Belgium
| | - Justine Van Moorleghem
- Laboratory of Immunoregulation and Mucosal Immunology, VIB-UGent Center for Inflammation Research, Ghent, Belgium
- Department of Internal Medicine and Pediatrics, Ghent University, Ghent, Belgium
| | - Manon Vanheerswynghels
- Laboratory of Immunoregulation and Mucosal Immunology, VIB-UGent Center for Inflammation Research, Ghent, Belgium
- Department of Internal Medicine and Pediatrics, Ghent University, Ghent, Belgium
| | - Kim Deswarte
- Laboratory of Immunoregulation and Mucosal Immunology, VIB-UGent Center for Inflammation Research, Ghent, Belgium
- Department of Internal Medicine and Pediatrics, Ghent University, Ghent, Belgium
| | - Benedicte Descamps
- Department of Electronics and Information Systems, IBiTech-MEDISIP-Infinity Lab, Ghent University, Ghent, Belgium
| | - Christian Vanhove
- Department of Electronics and Information Systems, IBiTech-MEDISIP-Infinity Lab, Ghent University, Ghent, Belgium
| | - Bart Van der Schueren
- Department of Chronic Diseases and Metabolism, Clinical and Experimental Endocrinology, KU Leuven, Leuven, Belgium
- Department of Endocrinology, University Hospitals Leuven, Leuven, Belgium
| | - Roman Vangoitsenhoven
- Department of Chronic Diseases and Metabolism, Clinical and Experimental Endocrinology, KU Leuven, Leuven, Belgium
- Department of Endocrinology, University Hospitals Leuven, Leuven, Belgium
| | - Hamida Hammad
- Laboratory of Immunoregulation and Mucosal Immunology, VIB-UGent Center for Inflammation Research, Ghent, Belgium
- Department of Internal Medicine and Pediatrics, Ghent University, Ghent, Belgium
| | - Sophie Janssens
- Department of Internal Medicine and Pediatrics, Ghent University, Ghent, Belgium
- Laboratory for Endoplasmic Reticulum Stress and Inflammation, VIB-UGent Center for Inflammation Research, Ghent, Belgium
| | - Bart N. Lambrecht
- Laboratory of Immunoregulation and Mucosal Immunology, VIB-UGent Center for Inflammation Research, Ghent, Belgium
- Department of Internal Medicine and Pediatrics, Ghent University, Ghent, Belgium
- Department of Pulmonary Medicine, Erasmus University Medical Center Rotterdam, Rotterdam Netherlands
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8
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Muller FM, Maebe J, Vanhove C, Vandenberghe S. Dose reduction and image enhancement in micro-CT using deep learning. Med Phys 2023; 50:5643-5656. [PMID: 36994779 DOI: 10.1002/mp.16385] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2022] [Revised: 02/14/2023] [Accepted: 03/09/2023] [Indexed: 03/31/2023] Open
Abstract
BACKGROUND In preclinical settings, micro-computed tomography (CT) provides a powerful tool to acquire high resolution anatomical images of rodents and offers the advantage to in vivo non-invasively assess disease progression and therapy efficacy. Much higher resolutions are needed to achieve scale-equivalent discriminatory capabilities in rodents as those in humans. High resolution imaging however comes at the expense of increased scan times and higher doses. Specifically, with preclinical longitudinal imaging, there are concerns that dose accumulation may affect experimental outcomes of animal models. PURPOSE Dose reduction efforts under the ALARA (as low as reasonably achievable) principles are thus a key point of attention. However, low dose CT acquisitions inherently induce higher noise levels which deteriorate image quality and negatively impact diagnostic performance. Many denoising techniques already exist, and deep learning (DL) has become increasingly popular for image denoising, but research has mostly focused on clinical CT with limited studies conducted on preclinical CT imaging. We investigate the potential of convolutional neural networks (CNN) for restoring high quality micro-CT images from low dose (noisy) images. The novelty of the CNN denoising frameworks presented in this work consists of utilizing image pairs with realistic CT noise present in the input as well as the target image used for the model training; a noisier image acquired with a low dose protocol is matched to a less noisy image acquired with a higher dose scan of the same mouse. METHODS Low and high dose ex vivo micro-CT scans of 38 mice were acquired. Two CNN models, based on a 2D and 3D four-layer U-Net, were trained with mean absolute error (30 training, 4 validation and 4 test sets). To assess denoising performance, ex vivo mice and phantom data were used. Both CNN approaches were compared to existing methods, like spatial filtering (Gaussian, Median, Wiener) and iterative total variation image reconstruction algorithm. Image quality metrics were derived from the phantom images. A first observer study (n = 23) was set-up to rank overall quality of differently denoised images. A second observer study (n = 18) estimated the dose reduction factor of the investigated 2D CNN method. RESULTS Visual and quantitative results show that both CNN algorithms exhibit superior performance in terms of noise suppression, structural preservation and contrast enhancement over comparator methods. The quality scoring by 23 medical imaging experts also indicates that the investigated 2D CNN approach is consistently evaluated as the best performing denoising method. Results from the second observer study and quantitative measurements suggest that CNN-based denoising could offer a 2-4× dose reduction, with an estimated dose reduction factor of about 3.2 for the considered 2D network. CONCLUSIONS Our results demonstrate the potential of DL in micro-CT for higher quality imaging at low dose acquisition settings. In the context of preclinical research, this offers promising future prospects for managing the cumulative severity effects of radiation in longitudinal studies.
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Affiliation(s)
- Florence M Muller
- Medical Image and Signal Processing (MEDISIP), Department of Electronics and Information Systems, Faculty of Engineering and Architecture, Ghent University, Ghent, Belgium
| | - Jens Maebe
- Medical Image and Signal Processing (MEDISIP), Department of Electronics and Information Systems, Faculty of Engineering and Architecture, Ghent University, Ghent, Belgium
| | - Christian Vanhove
- Medical Image and Signal Processing (MEDISIP), Department of Electronics and Information Systems, Faculty of Engineering and Architecture, Ghent University, Ghent, Belgium
| | - Stefaan Vandenberghe
- Medical Image and Signal Processing (MEDISIP), Department of Electronics and Information Systems, Faculty of Engineering and Architecture, Ghent University, Ghent, Belgium
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9
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Chen Q, Xu Y, Christiaen E, Wu GR, De Witte S, Vanhove C, Saunders J, Peremans K, Baeken C. Structural connectome alterations in anxious dogs: a DTI-based study. Sci Rep 2023; 13:9946. [PMID: 37337053 DOI: 10.1038/s41598-023-37121-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2023] [Accepted: 06/15/2023] [Indexed: 06/21/2023] Open
Abstract
Anxiety and fear are dysfunctional behaviors commonly observed in domesticated dogs. Although dogs and humans share psychopathological similarities, little is known about how dysfunctional fear behaviors are represented in brain networks in dogs diagnosed with anxiety disorders. A combination of diffusion tensor imaging (DTI) and graph theory was used to investigate the underlying structural connections of dysfunctional anxiety in anxious dogs and compared with healthy dogs with normal behavior. The degree of anxiety was assessed using the Canine Behavioral Assessment & Research Questionnaire (C-BARQ), a widely used, validated questionnaire for abnormal behaviors in dogs. Anxious dogs showed significantly decreased clustering coefficient ([Formula: see text]), decreased global efficiency ([Formula: see text]), and increased small-worldness (σ) when compared with healthy dogs. The nodal parameters that differed between the anxious dogs and healthy dogs were mainly located in the posterior part of the brain, including the occipital lobe, posterior cingulate gyrus, hippocampus, mesencephalon, and cerebellum. Furthermore, the nodal degree ([Formula: see text]) of the left cerebellum was significantly negatively correlated with "excitability" in the C-BARQ of anxious dogs. These findings could contribute to the understanding of a disrupted brain structural connectome underlying the pathological mechanisms of anxiety-related disorders in dogs.
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Affiliation(s)
- Qinyuan Chen
- Ghent Experimental Psychiatry (GHEP) Lab, Department of Head and Skin, Faculty of Medicine and Health Sciences, Ghent University, Ghent, Belgium.
| | - Yangfeng Xu
- Ghent Experimental Psychiatry (GHEP) Lab, Department of Head and Skin, Faculty of Medicine and Health Sciences, Ghent University, Ghent, Belgium
- Department of Morphology, Imaging, Orthopedics, Rehabilitation and Nutrition, Faculty of Veterinary Medicine, Ghent University, Merelbeke, Belgium
| | - Emma Christiaen
- Medical Image and Signal Processing (MEDISIP), Department of Electronics and Information Systems, Faculty of Engineering and Architecture, Ghent University, Ghent, Belgium
| | - Guo-Rong Wu
- Key Laboratory of Cognition and Personality, Faculty of Psychology, Southwest University, Chongqing, China
- School of Psychology, Jiangxi Normal University, Nanchang, China
| | - Sara De Witte
- Ghent Experimental Psychiatry (GHEP) Lab, Department of Head and Skin, Faculty of Medicine and Health Sciences, Ghent University, Ghent, Belgium
- Department of Neurology and Bru-BRAIN, University Hospital (UZ Brussel), Brussels, Belgium
- Neuroprotection & Neuromodulation Research Group (NEUR), Center for Neurosciences (C4N), Vrije Universiteit Brussel (VUB), Brussels, Belgium
| | - Christian Vanhove
- Medical Image and Signal Processing (MEDISIP), Department of Electronics and Information Systems, Faculty of Engineering and Architecture, Ghent University, Ghent, Belgium
| | - Jimmy Saunders
- Department of Morphology, Imaging, Orthopedics, Rehabilitation and Nutrition, Faculty of Veterinary Medicine, Ghent University, Merelbeke, Belgium
| | - Kathelijne Peremans
- Department of Morphology, Imaging, Orthopedics, Rehabilitation and Nutrition, Faculty of Veterinary Medicine, Ghent University, Merelbeke, Belgium
| | - Chris Baeken
- Ghent Experimental Psychiatry (GHEP) Lab, Department of Head and Skin, Faculty of Medicine and Health Sciences, Ghent University, Ghent, Belgium
- Vrije Universiteit Brussel (VUB), Department of Psychiatry, University Hospital (UZ Brussel), Brussels, Belgium
- Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands
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10
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Tavares AAS, Mezzanotte L, McDougald W, Bernsen MR, Vanhove C, Aswendt M, Ielacqua GD, Gremse F, Moran CM, Warnock G, Kuntner C, Huisman MC. Community Survey Results Show that Standardisation of Preclinical Imaging Techniques Remains a Challenge. Mol Imaging Biol 2023; 25:560-568. [PMID: 36482032 PMCID: PMC10172263 DOI: 10.1007/s11307-022-01790-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2022] [Revised: 11/15/2022] [Accepted: 11/16/2022] [Indexed: 12/13/2022]
Abstract
PURPOSE To support acquisition of accurate, reproducible and high-quality preclinical imaging data, various standardisation resources have been developed over the years. However, it is unclear the impact of those efforts in current preclinical imaging practices. To better understand the status quo in the field of preclinical imaging standardisation, the STANDARD group of the European Society of Molecular Imaging (ESMI) put together a community survey and a forum for discussion at the European Molecular Imaging Meeting (EMIM) 2022. This paper reports on the results from the STANDARD survey and the forum discussions that took place at EMIM2022. PROCEDURES The survey was delivered to the community by the ESMI office and was promoted through the Society channels, email lists and webpages. The survey contained seven sections organised as generic questions and imaging modality-specific questions. The generic questions focused on issues regarding data acquisition, data processing, data storage, publishing and community awareness of international guidelines for animal research. Specific questions on practices in optical imaging, PET, CT, SPECT, MRI and ultrasound were further included. RESULTS Data from the STANDARD survey showed that 47% of survey participants do not have or do not know if they have QC/QA guidelines at their institutes. Additionally, a large variability exists in the ways data are acquired, processed and reported regarding general aspects as well as modality-specific aspects. Moreover, there is limited awareness of the existence of international guidelines on preclinical (imaging) research practices. CONCLUSIONS Standardisation of preclinical imaging techniques remains a challenge and hinders the transformative potential of preclinical imaging to augment biomedical research pipelines by serving as an easy vehicle for translation of research findings to the clinic. Data collected in this project show that there is a need to promote and disseminate already available tools to standardise preclinical imaging practices.
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Affiliation(s)
- Adriana A S Tavares
- BHF-University Centre for Cardiovascular Science, University of Edinburgh, Edinburgh, UK.
- Edinburgh Imaging, University of Edinburgh, Edinburgh, UK.
| | - Laura Mezzanotte
- Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Wendy McDougald
- BHF-University Centre for Cardiovascular Science, University of Edinburgh, Edinburgh, UK
- Siemens, Molecular Imaging, Hoffman Estates, IL, USA
| | - Monique R Bernsen
- AMIE Core Facility, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Christian Vanhove
- Faculty of Engineering and Architecture, Department of Electronics and Information Systems, Ghent University, Ghent, Belgium
| | - Markus Aswendt
- Faculty of Medicine, Dept. of Neurology, University of Cologne, and University Hospital Cologne, Cologne, Germany
| | - Giovanna D Ielacqua
- Max-Delbrück Center for Molecular Medicine, in the Helmholtz Association, Berlin, Germany
| | - Felix Gremse
- Gremse-IT GmbH, Aachen, Germany
- Experimental Molecular Imaging, RWTH Aachen University Clinic, Aachen, Germany
| | - Carmel M Moran
- BHF-University Centre for Cardiovascular Science, University of Edinburgh, Edinburgh, UK
- Edinburgh Imaging, University of Edinburgh, Edinburgh, UK
| | | | - Claudia Kuntner
- Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Marc C Huisman
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Cancer Center Amsterdam, Amsterdam, The Netherlands
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11
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Debacker JM, Maris L, Cordier F, Creytens D, Deron P, Descamps B, D'Asseler Y, De Man K, Keereman V, Libbrecht S, Schelfhout V, Van de Vijver K, Vanhove C, Huvenne W. Direct co-registration of [ 18F]FDG uptake and histopathology in surgically excised malignancies of the head and neck: a feasibility study. Eur J Nucl Med Mol Imaging 2023; 50:2127-2139. [PMID: 36854863 DOI: 10.1007/s00259-023-06153-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2022] [Accepted: 02/13/2023] [Indexed: 03/02/2023]
Abstract
PURPOSE Recent technical advancements in PET imaging have improved sensitivity and spatial resolution. Consequently, clinical nuclear medicine will be confronted with PET images on a previously unfamiliar resolution. To better understand [18F]FDG distribution at submillimetric scale, a direct correlation of radionuclide-imaging and histopathology is required. METHODS A total of five patients diagnosed with a malignancy of the head and neck were injected with a clinical activity of [18F]FDG before undergoing surgical resection. The resected specimen was imaged using a preclinical high-resolution PET/CT, followed by slicing of the specimen. Multiple slices were rescanned using a micro-PET/CT device, and one of the slices was snap-frozen for frozen sections. Frozen sections were placed on an autoradiographic film, followed by haematoxylin and eosin staining to prepare them for histopathological assessment. The results from both autoradiography and histopathology were co-registered using an iterative co-registration algorithm, and regions of interest were identified to study radiotracer uptake. RESULTS The co-registration between the autoradiographs and their corresponding histopathology was successful in all specimens. The use of this novel methodology allowed direct comparison of autoradiography and histopathology and enabled the visualisation of uncharted heterogeneity in [18F]FDG uptake in both benign and malignant tissue. CONCLUSION We here describe a novel methodology enabling the direct co-registration of [18F]FDG autoradiography with the gold standard of histopathology in human malignant tissue. The future use of the current methodology could further increase our understanding of the distribution of radionuclides in surgically excised malignancies and hence, improve the integration of pathology and molecular imaging in a multiscale perspective. TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT05068687.
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Affiliation(s)
- Jens M Debacker
- Department of Head and Skin, Ghent University, Ghent, Belgium.
- Department of Head and Neck Surgery, Ghent University Hospital, Ghent, Belgium.
- Department of Nuclear Medicine, UZ Brussel, Brussels, Belgium.
- In vivo Cellular and Molecular Imaging Laboratory (ICMI), Vrije Universiteit Brussel, Brussels, Belgium.
- Cancer Research Institute Ghent, Ghent, Belgium.
| | - Luna Maris
- Department of Electronics and Information Systems, Ghent University, Ghent, Belgium
- XEOS Medical, Ghent, Belgium
| | - Fleur Cordier
- Department of Pathology, Ghent University Hospital, Ghent, Belgium
| | - David Creytens
- Cancer Research Institute Ghent, Ghent, Belgium
- Department of Pathology, Ghent University Hospital, Ghent, Belgium
- Department of Diagnostic Sciences, Ghent University, Ghent, Belgium
| | - Philippe Deron
- Department of Head and Skin, Ghent University, Ghent, Belgium
- Department of Head and Neck Surgery, Ghent University Hospital, Ghent, Belgium
| | - Benedicte Descamps
- Cancer Research Institute Ghent, Ghent, Belgium
- Department of Electronics and Information Systems, Ghent University, Ghent, Belgium
- INFINITY Lab, Ghent University, Ghent, Belgium
| | - Yves D'Asseler
- Department of Diagnostic Sciences, Ghent University, Ghent, Belgium
- Department of Medical Imaging, Nuclear Medicine, Ghent University Hospital, Ghent, Belgium
| | - Kathia De Man
- Department of Medical Imaging, Nuclear Medicine, Ghent University Hospital, Ghent, Belgium
| | - Vincent Keereman
- Department of Electronics and Information Systems, Ghent University, Ghent, Belgium
- XEOS Medical, Ghent, Belgium
| | - Sasha Libbrecht
- Department of Pathology, Antwerp University Hospital, Edegem, Belgium
| | - Vanessa Schelfhout
- Department of Diagnostic Sciences, Ghent University, Ghent, Belgium
- Department of Medical Imaging, Nuclear Medicine, Ghent University Hospital, Ghent, Belgium
| | - Koen Van de Vijver
- Cancer Research Institute Ghent, Ghent, Belgium
- Department of Pathology, Ghent University Hospital, Ghent, Belgium
- Department of Diagnostic Sciences, Ghent University, Ghent, Belgium
| | - Christian Vanhove
- Cancer Research Institute Ghent, Ghent, Belgium
- Department of Electronics and Information Systems, Ghent University, Ghent, Belgium
- INFINITY Lab, Ghent University, Ghent, Belgium
| | - Wouter Huvenne
- Department of Head and Skin, Ghent University, Ghent, Belgium
- Department of Head and Neck Surgery, Ghent University Hospital, Ghent, Belgium
- Cancer Research Institute Ghent, Ghent, Belgium
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12
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Grandjean J, Desrosiers-Gregoire G, Anckaerts C, Angeles-Valdez D, Ayad F, Barrière DA, Blockx I, Bortel A, Broadwater M, Cardoso BM, Célestine M, Chavez-Negrete JE, Choi S, Christiaen E, Clavijo P, Colon-Perez L, Cramer S, Daniele T, Dempsey E, Diao Y, Doelemeyer A, Dopfel D, Dvořáková L, Falfán-Melgoza C, Fernandes FF, Fowler CF, Fuentes-Ibañez A, Garin CM, Gelderman E, Golden CEM, Guo CCG, Henckens MJAG, Hennessy LA, Herman P, Hofwijks N, Horien C, Ionescu TM, Jones J, Kaesser J, Kim E, Lambers H, Lazari A, Lee SH, Lillywhite A, Liu Y, Liu YY, López-Castro A, López-Gil X, Ma Z, MacNicol E, Madularu D, Mandino F, Marciano S, McAuslan MJ, McCunn P, McIntosh A, Meng X, Meyer-Baese L, Missault S, Moro F, Naessens DMP, Nava-Gomez LJ, Nonaka H, Ortiz JJ, Paasonen J, Peeters LM, Pereira M, Perez PD, Pompilus M, Prior M, Rakhmatullin R, Reimann HM, Reinwald J, Del Rio RT, Rivera-Olvera A, Ruiz-Pérez D, Russo G, Rutten TJ, Ryoke R, Sack M, Salvan P, Sanganahalli BG, Schroeter A, Seewoo BJ, Selingue E, Seuwen A, Shi B, Sirmpilatze N, Smith JAB, Smith C, Sobczak F, Stenroos PJ, Straathof M, Strobelt S, Sumiyoshi A, Takahashi K, Torres-García ME, Tudela R, van den Berg M, van der Marel K, van Hout ATB, Vertullo R, Vidal B, Vrooman RM, Wang VX, Wank I, Watson DJG, Yin T, Zhang Y, Zurbruegg S, Achard S, Alcauter S, Auer DP, Barbier EL, Baudewig J, Beckmann CF, Beckmann N, Becq GJPC, Blezer ELA, Bolbos R, Boretius S, Bouvard S, Budinger E, Buxbaum JD, Cash D, Chapman V, Chuang KH, Ciobanu L, Coolen BF, Dalley JW, Dhenain M, Dijkhuizen RM, Esteban O, Faber C, Febo M, Feindel KW, Forloni G, Fouquet J, Garza-Villarreal EA, Gass N, Glennon JC, Gozzi A, Gröhn O, Harkin A, Heerschap A, Helluy X, Herfert K, Heuser A, Homberg JR, Houwing DJ, Hyder F, Ielacqua GD, Jelescu IO, Johansen-Berg H, Kaneko G, Kawashima R, Keilholz SD, Keliris GA, Kelly C, Kerskens C, Khokhar JY, Kind PC, Langlois JB, Lerch JP, López-Hidalgo MA, Manahan-Vaughan D, Marchand F, Mars RB, Marsella G, Micotti E, Muñoz-Moreno E, Near J, Niendorf T, Otte WM, Pais-Roldán P, Pan WJ, Prado-Alcalá RA, Quirarte GL, Rodger J, Rosenow T, Sampaio-Baptista C, Sartorius A, Sawiak SJ, Scheenen TWJ, Shemesh N, Shih YYI, Shmuel A, Soria G, Stoop R, Thompson GJ, Till SM, Todd N, Van Der Linden A, van der Toorn A, van Tilborg GAF, Vanhove C, Veltien A, Verhoye M, Wachsmuth L, Weber-Fahr W, Wenk P, Yu X, Zerbi V, Zhang N, Zhang BB, Zimmer L, Devenyi GA, Chakravarty MM, Hess A. Author Correction: A consensus protocol for functional connectivity analysis in the rat brain. Nat Neurosci 2023:10.1038/s41593-023-01328-1. [PMID: 37072562 DOI: 10.1038/s41593-023-01328-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/20/2023]
Affiliation(s)
- Joanes Grandjean
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands.
- Department for Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands.
| | - Gabriel Desrosiers-Gregoire
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Verdun, QC, Canada
- Integrated Program in Neuroscience, McGill University, Montreal, QC, Canada
| | - Cynthia Anckaerts
- Bio-imaging Lab, University of Antwerp, Antwerp, Belgium
- µNEURO Research Centre of Excellence, University of Antwerp, Antwerp, Belgium
| | - Diego Angeles-Valdez
- Instituto de Neurobiología, Universidad Nacional Autónoma de México, Campus Juriquilla, Querétaro, Mexico
| | - Fadi Ayad
- Biological and Biomedical Engineering, McGill University, Montreal, QC, Canada
- McConnell Brain Imaging Centre, McGill University, Montreal, QC, Canada
- Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - David A Barrière
- UMR INRAE/CNRS 7247 Physiologie des Comportements et de la Reproduction, Physiologie de la reproduction et des comportements, Centre de recherche INRAE de Nouzilly, Tours, France
| | - Ines Blockx
- Bio-imaging Lab, University of Antwerp, Antwerp, Belgium
- µNEURO Research Centre of Excellence, University of Antwerp, Antwerp, Belgium
| | - Aleksandra Bortel
- McConnell Brain Imaging Centre, McGill University, Montreal, QC, Canada
- Montreal Neurological Institute, McGill University, Montreal, QC, Canada
- Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
| | - Margaret Broadwater
- Center for Animal MRI, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Neurology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Beatriz M Cardoso
- Preclinical MRI, Champalimaud Research, Champalimaud Centre for the Unknown, Lisbon, Portugal
| | - Marina Célestine
- Laboratoire des Maladies Neurodégénératives, Molecular Imaging Research Center (MIRCen), Université Paris-Saclay, Commissariat à l'Énergie Atomique et aux Énergies Alternatives (CEA), CNRS, Fontenay-aux-Roses, France
| | - Jorge E Chavez-Negrete
- Departamento de Neurobiología Conductual y Cognitiva, Instituto de Neurobiología, Universidad Nacional Autónoma de México, Campus Juriquilla, Querétaro, México
| | - Sangcheon Choi
- Translational Neuroimaging and Neural Control Group, High-Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Tuebingen, Germany
- Graduate Training Centre of Neuroscience, International Max Planck Research School, University of Tuebingen, Tuebingen, Germany
| | - Emma Christiaen
- Institute Biomedical Technology (IBiTech), Electronics and Information Systems (ELIS), Ghent University, Gent, Belgium
| | - Perrin Clavijo
- Department of Biomedical Engineering, Emory University/Georgia Institute of Technology, Atlanta, GA, USA
| | - Luis Colon-Perez
- Department of Pharmacology & Neuroscience, University of North Texas Health Science Center, Fort Worth, TX, USA
| | - Samuel Cramer
- Translational Neuroimaging and Systems Neuroscience Lab, Biomedical Engineering, Pennsylvania State University, University Park, PA, USA
| | - Tolomeo Daniele
- Centre for Advanced Biomedical Imaging, University College London, London, UK
| | - Elaine Dempsey
- Neuropsychopharmacology Research Group, School of Pharmacy and Pharmaceutical Sciences, Trinity College Dublin, Dublin, Ireland
- Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
| | - Yujian Diao
- CIBM Center for Biomedical Imaging, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
- Laboratory for Functional and Metabolic Imaging, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Arno Doelemeyer
- Musculoskeletal Diseases Department, Novartis Institutes for BioMedical Research, Basel, Switzerland
| | - David Dopfel
- Translational Neuroimaging and Systems Neuroscience Lab, Biomedical Engineering, Pennsylvania State University, University Park, PA, USA
| | - Lenka Dvořáková
- Biomedical Imaging Unit, A.I.V. Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
| | - Claudia Falfán-Melgoza
- Translational Imaging, Department of Neuroimaging, Central Institute of Mental Health, Medical Faculty Mannheim, Mannheim, Germany
| | - Francisca F Fernandes
- Preclinical MRI, Champalimaud Research, Champalimaud Centre for the Unknown, Lisbon, Portugal
| | - Caitlin F Fowler
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Verdun, QC, Canada
- Biological and Biomedical Engineering, McGill University, Montreal, QC, Canada
| | - Antonio Fuentes-Ibañez
- Departamento de Neurobiología Conductual y Cognitiva, Instituto de Neurobiología, Universidad Nacional Autónoma de México, Campus Juriquilla, Querétaro, México
| | - Clément M Garin
- Laboratoire des Maladies Neurodégénératives, Molecular Imaging Research Center (MIRCen), Université Paris-Saclay, Commissariat à l'Énergie Atomique et aux Énergies Alternatives (CEA), CNRS, Fontenay-aux-Roses, France
| | - Eveline Gelderman
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
| | - Carla E M Golden
- Seaver Autism Center for Research & Treatment, Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York City, NY, USA
| | - Chao C G Guo
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
| | - Marloes J A G Henckens
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
- Department of Neuroscience and Pharmacology, Rudolf Magnus Institute of Neuroscience, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Lauren A Hennessy
- Experimental and Regenerative Neurosciences, School of Biological Sciences, University of Western Australia, Crawley, WA, Australia
- Brain Plasticity Group, Perron Institute for Neurological and Translational Science, Nedlands, WA, Australia
| | - Peter Herman
- Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, CT, USA
- Quantitative Neuroscience with Magnetic Resonance (QNMR) Core Center, Yale University School of Medicine, New Haven, CT, USA
| | - Nita Hofwijks
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
| | - Corey Horien
- Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, CT, USA
| | - Tudor M Ionescu
- Werner Siemens Imaging Center, Department of Preclinical Imaging and Radiopharmacy, University of Tuebingen, Tuebingen, Germany
| | - Jolyon Jones
- Department of Psychology, University of Cambridge, Cambridge, UK
| | - Johannes Kaesser
- Institute of Experimental and Clinical Pharmacology and Toxicology, FAU Erlangen-Nürnberg, Erlangen, Germany
| | - Eugene Kim
- Biomarker Research And Imaging in Neuroscience (BRAIN) Centre, Department of Neuroimaging King's College London, London, UK
| | - Henriette Lambers
- Experimental Magnetic Resonance Group, Clinic of Radiology, University of Münster, Münster, Germany
| | - Alberto Lazari
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging, FMRIB, University of Oxford, John Radcliffe Hospital, Headington, Oxford, UK
| | - Sung-Ho Lee
- Center for Animal MRI, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Neurology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Amanda Lillywhite
- School of Life Sciences, University of Nottingham, Nottingham, UK
- Pain Centre Versus Arthritis, University of Nottingham, Nottingham, UK
| | - Yikang Liu
- Translational Neuroimaging and Systems Neuroscience Lab, Biomedical Engineering, Pennsylvania State University, University Park, PA, USA
| | - Yanyan Y Liu
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing, China
| | - Alejandra López-Castro
- Instituto de Neurobiología, Universidad Nacional Autónoma de México, Campus Juriquilla, Querétaro, Mexico
| | - Xavier López-Gil
- Magnetic Imaging Resonance Core Facility, Institut d'Investigacions Biomèdiques August Pi I Sunyer (IDIBAPS), Barcelona, Spain
| | - Zilu Ma
- Translational Neuroimaging and Systems Neuroscience Lab, Biomedical Engineering, Pennsylvania State University, University Park, PA, USA
| | - Eilidh MacNicol
- Biomarker Research And Imaging in Neuroscience (BRAIN) Centre, Department of Neuroimaging King's College London, London, UK
| | - Dan Madularu
- Biological and Biomedical Engineering, McGill University, Montreal, QC, Canada
- Center for Translational Neuroimaging, Northeastern University, Boston, MA, USA
| | - Francesca Mandino
- Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, CT, USA
| | - Sabina Marciano
- Werner Siemens Imaging Center, Department of Preclinical Imaging and Radiopharmacy, University of Tuebingen, Tuebingen, Germany
| | - Matthew J McAuslan
- Neuropsychopharmacology Research Group, School of Pharmacy and Pharmaceutical Sciences, Trinity College Dublin, Dublin, Ireland
| | - Patrick McCunn
- Khokhar Lab, Department of Anatomy and Cell Biology, Western University, London, ON, Canada
| | - Alison McIntosh
- Neuropsychopharmacology Research Group, School of Pharmacy and Pharmaceutical Sciences, Trinity College Dublin, Dublin, Ireland
- Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
| | - Xianzong Meng
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
| | - Lisa Meyer-Baese
- Department of Biomedical Engineering, Emory University/Georgia Institute of Technology, Atlanta, GA, USA
| | - Stephan Missault
- Bio-imaging Lab, University of Antwerp, Antwerp, Belgium
- µNEURO Research Centre of Excellence, University of Antwerp, Antwerp, Belgium
| | - Federico Moro
- Laboratory of Acute Brain Injury and Therapeutic Strategies, Department of NeuroscienceIstituto di Ricerche Farmacologiche Mario Negri, IRCCS, Milan, Italy
| | - Daphne M P Naessens
- Biomedical Engineering and Physics, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Laura J Nava-Gomez
- Facultad de Medicina, Universidad Autónoma de Querétaro, Querétaro, México
- Escuela Nacional de Estudios Superiores, Juriquilla, Universidad Nacional Autónoma de México, Querétaro, México
| | - Hiroi Nonaka
- Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan
| | - Juan J Ortiz
- Departamento de Neurobiología Conductual y Cognitiva, Instituto de Neurobiología, Universidad Nacional Autónoma de México, Campus Juriquilla, Querétaro, México
| | - Jaakko Paasonen
- Biomedical Imaging Unit, A.I.V. Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
| | - Lore M Peeters
- Bio-imaging Lab, University of Antwerp, Antwerp, Belgium
- µNEURO Research Centre of Excellence, University of Antwerp, Antwerp, Belgium
| | - Mickaël Pereira
- Lyon Neuroscience Research Center, Université Claude Bernard Lyon 1, INSERM, CNRS, Lyon, France
| | - Pablo D Perez
- Translational Neuroimaging and Systems Neuroscience Lab, Biomedical Engineering, Pennsylvania State University, University Park, PA, USA
| | - Marjory Pompilus
- Febo Laboratory, Department of Psychiatry, University of Florida, Gainesville, FL, USA
| | - Malcolm Prior
- School of Medicine, University of Nottingham, Nottingham, UK
| | | | - Henning M Reimann
- Berlin Ultrahigh Field Facility (B.U.F.F.), Max-Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany
| | - Jonathan Reinwald
- Translational Imaging, Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Rodrigo Triana Del Rio
- Psychiatric neurosciences, Center for Psychiatric Neuroscience, Lausanne University and University Hospital Center, Unicentre, Lausanne, Switzerland
| | - Alejandro Rivera-Olvera
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
| | | | - Gabriele Russo
- Department of Neurophysiology, Medical Faculty, Ruhr University Bochum, Bochum, Germany
| | - Tobias J Rutten
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
| | - Rie Ryoke
- Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan
| | - Markus Sack
- Translational Imaging, Department of Neuroimaging, Central Institute of Mental Health, Medical Faculty Mannheim, Mannheim, Germany
| | - Piergiorgio Salvan
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging, FMRIB, University of Oxford, John Radcliffe Hospital, Headington, Oxford, UK
| | - Basavaraju G Sanganahalli
- Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, CT, USA
- Quantitative Neuroscience with Magnetic Resonance (QNMR) Core Center, Yale University School of Medicine, New Haven, CT, USA
| | - Aileen Schroeter
- Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland
| | - Bhedita J Seewoo
- Experimental and Regenerative Neurosciences, School of Biological Sciences, University of Western Australia, Crawley, WA, Australia
- Brain Plasticity Group, Perron Institute for Neurological and Translational Science, Nedlands, WA, Australia
- Centre for Microscopy, Characterisation & Analysis, Research Infrastructure Centres, University of Western Australia, Nedlands, WA, Australia
| | | | - Aline Seuwen
- Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland
| | - Bowen Shi
- iHuman Institute, ShanghaiTech University, Shanghai, China
| | - Nikoloz Sirmpilatze
- Functional Imaging Laboratory, German Primate Center - Leibniz Institute for Primate Research, Göttingen, Germany
- Faculty of Biology and Psychology, Georg-August University of Göttingen, Göttingen, Germany
- DFG Research Center for Nanoscale Microscopy and Molecular Physiology of the Brain (CNMPB), Göttingen, Germany
| | - Joanna A B Smith
- Simons Initiative for the Developing Brain, University of Edinburgh, Edinburgh, UK
- Patrick Wild Centre, University of Edinburgh, Edinburgh, UK
- Centre for Discovery Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Corrie Smith
- Department of Biomedical Engineering, Emory University/Georgia Institute of Technology, Atlanta, GA, USA
| | - Filip Sobczak
- Translational Neuroimaging and Neural Control Group, High-Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Tuebingen, Germany
- Graduate Training Centre of Neuroscience, International Max Planck Research School, University of Tuebingen, Tuebingen, Germany
| | - Petteri J Stenroos
- Univ. Grenoble Alpes, Inserm, U1216, Grenoble Institut Neurosciences, Grenoble, France
| | - Milou Straathof
- Biomedical MR Imaging and Spectroscopy Group, Center for Image Sciences, University Medical Center Utrecht & Utrecht University, Utrecht, The Netherlands
| | - Sandra Strobelt
- Institute of Experimental and Clinical Pharmacology and Toxicology, FAU Erlangen-Nürnberg, Erlangen, Germany
| | - Akira Sumiyoshi
- Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan
- National Institutes for Quantum Science and Technology, Chiba, Japan
| | - Kengo Takahashi
- Translational Neuroimaging and Neural Control Group, High-Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Tuebingen, Germany
- Graduate Training Centre of Neuroscience, International Max Planck Research School, University of Tuebingen, Tuebingen, Germany
| | - Maria E Torres-García
- Departamento de Neurobiología Conductual y Cognitiva, Instituto de Neurobiología, Universidad Nacional Autónoma de México, Campus Juriquilla, Querétaro, México
| | - Raul Tudela
- Group of Biomedical Imaging, Consorcio Centro de Investigación Biomédica en Red (CIBER) de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), University of Barcelona, Barcelona, Spain
| | - Monica van den Berg
- Bio-imaging Lab, University of Antwerp, Antwerp, Belgium
- µNEURO Research Centre of Excellence, University of Antwerp, Antwerp, Belgium
| | - Kajo van der Marel
- Biomedical MR Imaging and Spectroscopy Group, Center for Image Sciences, University Medical Center Utrecht & Utrecht University, Utrecht, The Netherlands
| | - Aran T B van Hout
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
| | - Roberta Vertullo
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
| | - Benjamin Vidal
- Lyon Neuroscience Research Center, Université Claude Bernard Lyon 1, INSERM, CNRS, Lyon, France
| | - Roël M Vrooman
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
| | - Victora X Wang
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York City, NY, USA
| | - Isabel Wank
- Institute of Experimental and Clinical Pharmacology and Toxicology, FAU Erlangen-Nürnberg, Erlangen, Germany
| | - David J G Watson
- School of Life Sciences, University of Nottingham, Nottingham, UK
| | - Ting Yin
- Animal Imaging and Technology Section, Center for Biomedical Imaging, École polytechnique fédérale de Lausanne, Lausanne, Switzerland
| | - Yongzhi Zhang
- Focused Ultrasound Laboratory, Department of Radiology Brigham and Women's Hospital, Boston, MA, USA
| | - Stefan Zurbruegg
- Neurosciences Department, Novartis Institutes for BioMedical Research, Basel, Switzerland
| | - Sophie Achard
- Inria, University Grenoble Alpes, CNRS, Grenoble, France
| | - Sarael Alcauter
- Departamento de Neurobiología Conductual y Cognitiva, Instituto de Neurobiología, Universidad Nacional Autónoma de México, Campus Juriquilla, Querétaro, México
| | - Dorothee P Auer
- School of Medicine, University of Nottingham, Nottingham, UK
- NIHR Biomedical Research Centre, University of Nottingham, Nottingham, UK
| | - Emmanuel L Barbier
- Univ. Grenoble Alpes, Inserm, U1216, Grenoble Institut Neurosciences, Grenoble, France
| | - Jürgen Baudewig
- Functional Imaging Laboratory, German Primate Center - Leibniz Institute for Primate Research, Göttingen, Germany
| | - Christian F Beckmann
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging, FMRIB, University of Oxford, John Radcliffe Hospital, Headington, Oxford, UK
| | - Nicolau Beckmann
- Musculoskeletal Diseases Department, Novartis Institutes for BioMedical Research, Basel, Switzerland
| | | | - Erwin L A Blezer
- Biomedical MR Imaging and Spectroscopy Group, Center for Image Sciences, University Medical Center Utrecht & Utrecht University, Utrecht, The Netherlands
| | | | - Susann Boretius
- Functional Imaging Laboratory, German Primate Center - Leibniz Institute for Primate Research, Göttingen, Germany
- Faculty of Biology and Psychology, Georg-August University of Göttingen, Göttingen, Germany
- DFG Research Center for Nanoscale Microscopy and Molecular Physiology of the Brain (CNMPB), Göttingen, Germany
| | - Sandrine Bouvard
- Lyon Neuroscience Research Center, Université Claude Bernard Lyon 1, INSERM, CNRS, Lyon, France
| | - Eike Budinger
- Combinatorial NeuroImaging Core Facility, Leibniz Institute for Neurobiology, Magdeburg, Germany
- Center for Behavioral Brain Sciences, Magdeburg, Germany
| | - Joseph D Buxbaum
- Seaver Autism Center for Research & Treatment, Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York City, NY, USA
| | - Diana Cash
- Biomarker Research And Imaging in Neuroscience (BRAIN) Centre, Department of Neuroimaging King's College London, London, UK
| | - Victoria Chapman
- School of Life Sciences, University of Nottingham, Nottingham, UK
- Pain Centre Versus Arthritis, University of Nottingham, Nottingham, UK
- NIHR Biomedical Research Centre, University of Nottingham, Nottingham, UK
| | - Kai-Hsiang Chuang
- Queensland Brain Institute and Centre for Advanced Imaging, University of Queensland, St. Lucia, QLD, Australia
| | | | - Bram F Coolen
- Biomedical Engineering and Physics, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Jeffrey W Dalley
- Department of Psychology, University of Cambridge, Cambridge, UK
| | - Marc Dhenain
- Laboratoire des Maladies Neurodégénératives, Molecular Imaging Research Center (MIRCen), Université Paris-Saclay, Commissariat à l'Énergie Atomique et aux Énergies Alternatives (CEA), CNRS, Fontenay-aux-Roses, France
| | - Rick M Dijkhuizen
- Biomedical MR Imaging and Spectroscopy Group, Center for Image Sciences, University Medical Center Utrecht & Utrecht University, Utrecht, The Netherlands
| | - Oscar Esteban
- Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Cornelius Faber
- Experimental Magnetic Resonance Group, Clinic of Radiology, University of Münster, Münster, Germany
| | - Marcelo Febo
- Febo Laboratory, Department of Psychiatry, University of Florida, Gainesville, FL, USA
| | - Kirk W Feindel
- Centre for Microscopy, Characterisation & Analysis, Research Infrastructure Centres, University of Western Australia, Nedlands, WA, Australia
| | - Gianluigi Forloni
- Biology of Neurodogenerative Disorders, Department of Neuroscience Istituto di Ricerche Farmacologiche Mario Negri, IRCCS, Milan, Italy
| | - Jérémie Fouquet
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Verdun, QC, Canada
| | - Eduardo A Garza-Villarreal
- Instituto de Neurobiología, Universidad Nacional Autónoma de México, Campus Juriquilla, Querétaro, Mexico
| | - Natalia Gass
- Translational Imaging, Department of Neuroimaging, Central Institute of Mental Health, Medical Faculty Mannheim, Mannheim, Germany
| | - Jeffrey C Glennon
- Conway Institute of Biomedical and Biomolecular Sciences, School of Medicine, University College Dublin, Dublin, Ireland
| | - Alessandro Gozzi
- Functional Neuroimaging Laboratory, Center for Neuroscience and Cognitive Systems, Istituto Italiano di Tecnologia, Rovereto, Italy
| | - Olli Gröhn
- Biomedical Imaging Unit, A.I.V. Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
| | - Andrew Harkin
- Neuropsychopharmacology Research Group, School of Pharmacy and Pharmaceutical Sciences, Trinity College Dublin, Dublin, Ireland
- Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
| | - Arend Heerschap
- Department for Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Xavier Helluy
- Department of Neurophysiology, Medical Faculty, Ruhr University Bochum, Bochum, Germany
- Department of Biopsychology, Institute of Cognitive Neuroscience, Ruhr University Bochum, Bochum, Germany
| | - Kristina Herfert
- Werner Siemens Imaging Center, Department of Preclinical Imaging and Radiopharmacy, University of Tuebingen, Tuebingen, Germany
| | - Arnd Heuser
- Max-Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany
| | - Judith R Homberg
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
| | - Danielle J Houwing
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
| | - Fahmeed Hyder
- Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, CT, USA
- Quantitative Neuroscience with Magnetic Resonance (QNMR) Core Center, Yale University School of Medicine, New Haven, CT, USA
| | | | - Ileana O Jelescu
- CIBM Center for Biomedical Imaging, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Heidi Johansen-Berg
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging, FMRIB, University of Oxford, John Radcliffe Hospital, Headington, Oxford, UK
| | - Gen Kaneko
- School of Arts & Sciences, University of Houston-Victoria, Victoria, TX, USA
| | - Ryuta Kawashima
- Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan
| | - Shella D Keilholz
- Department of Biomedical Engineering, Emory University/Georgia Institute of Technology, Atlanta, GA, USA
| | - Georgios A Keliris
- Bio-imaging Lab, University of Antwerp, Antwerp, Belgium
- µNEURO Research Centre of Excellence, University of Antwerp, Antwerp, Belgium
| | - Clare Kelly
- Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
- School of Psychology, Trinity College Dublin, Dublin, Ireland
- Department of Psychiatry, School of Medicine, Trinity College Dublin, Dublin, Ireland
| | - Christian Kerskens
- Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
- Trinity Centre for Biomedical Engineering, School of Medicine, Trinity College Dublin, Dublin, Ireland
| | - Jibran Y Khokhar
- Khokhar Lab, Department of Anatomy and Cell Biology, Western University, London, ON, Canada
| | - Peter C Kind
- Simons Initiative for the Developing Brain, University of Edinburgh, Edinburgh, UK
- Patrick Wild Centre, University of Edinburgh, Edinburgh, UK
- Centre for Discovery Brain Sciences, University of Edinburgh, Edinburgh, UK
- Centre for Brain Development and Repair, Institute for Stem Cell Biology and Regenerative Medicine, Bangalore, India
| | | | - Jason P Lerch
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging, FMRIB, University of Oxford, John Radcliffe Hospital, Headington, Oxford, UK
- Department of Medical Biophysics, University of Toronto, Toronto, QC, Canada
| | - Monica A López-Hidalgo
- Escuela Nacional de Estudios Superiores, Juriquilla, Universidad Nacional Autónoma de México, Querétaro, México
| | | | - Fabien Marchand
- Université Clermont Auvergne, Inserm U1107 Neuro-Dol, Pharmacologie Fondamentale et Clinique de la Douleur, Clermont-Ferrand, France
| | - Rogier B Mars
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging, FMRIB, University of Oxford, John Radcliffe Hospital, Headington, Oxford, UK
| | - Gerardo Marsella
- Animal Care Unit, Istituto di Ricerche Farmacologiche Mario Negri, IRCCS, Milan, Italy
| | - Edoardo Micotti
- Biology of Neurodogenerative Disorders, Department of Neuroscience Istituto di Ricerche Farmacologiche Mario Negri, IRCCS, Milan, Italy
| | - Emma Muñoz-Moreno
- Magnetic Imaging Resonance Core Facility, Institut d'Investigacions Biomèdiques August Pi I Sunyer (IDIBAPS), Barcelona, Spain
| | - Jamie Near
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Verdun, QC, Canada
- Physical Sciences Platform, Sunnybrook Research Institute, Toronto, QC, Canada
| | - Thoralf Niendorf
- Berlin Ultrahigh Field Facility (B.U.F.F.), Max-Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany
- Experimental and Clinical Research Center, A Joint Cooperation Between the Charité Medical Faculty and the Max-Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany
| | - Willem M Otte
- Biomedical MR Imaging and Spectroscopy Group, Center for Image Sciences, University Medical Center Utrecht & Utrecht University, Utrecht, The Netherlands
- Department of Pediatric Neurology, UMC Utrecht Brain Center, University Medical Center Utrecht & Utrecht University, Utrecht, The Netherlands
| | - Patricia Pais-Roldán
- Translational Neuroimaging and Neural Control Group, High-Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Tuebingen, Germany
- Medical Imaging Physics (INM-4), Institute of Neuroscience and Medicine, Forschungszentrum Juelich, Juelich, Germany
| | - Wen-Ju Pan
- Department of Biomedical Engineering, Emory University/Georgia Institute of Technology, Atlanta, GA, USA
| | - Roberto A Prado-Alcalá
- Departamento de Neurobiología Conductual y Cognitiva, Instituto de Neurobiología, Universidad Nacional Autónoma de México, Campus Juriquilla, Querétaro, México
| | - Gina L Quirarte
- Departamento de Neurobiología Conductual y Cognitiva, Instituto de Neurobiología, Universidad Nacional Autónoma de México, Campus Juriquilla, Querétaro, México
| | - Jennifer Rodger
- Experimental and Regenerative Neurosciences, School of Biological Sciences, University of Western Australia, Crawley, WA, Australia
- Brain Plasticity Group, Perron Institute for Neurological and Translational Science, Nedlands, WA, Australia
| | - Tim Rosenow
- Centre for Microscopy, Characterisation and Analysis, University of Western Australia, Crawley, WA, Australia
| | - Cassandra Sampaio-Baptista
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging, FMRIB, University of Oxford, John Radcliffe Hospital, Headington, Oxford, UK
- School of Psychology and Neuroscience, University of Glasgow, Glasgow, UK
| | - Alexander Sartorius
- Translational Imaging, Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Stephen J Sawiak
- Translational Neuroimaging Laboratory, Physiology, Development and Neuroscience, University of Cambridge, Cambridge, UK
| | - Tom W J Scheenen
- Department for Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands
- Erwin L. Hahn Institute for MR Imaging, University of Duisburg-Essen, Essen, Germany
| | - Noam Shemesh
- Preclinical MRI, Champalimaud Research, Champalimaud Centre for the Unknown, Lisbon, Portugal
| | - Yen-Yu Ian Shih
- Center for Animal MRI, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Neurology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Biomedical Engineering, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Amir Shmuel
- Biological and Biomedical Engineering, McGill University, Montreal, QC, Canada
- McConnell Brain Imaging Centre, McGill University, Montreal, QC, Canada
- Montreal Neurological Institute, McGill University, Montreal, QC, Canada
- Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
- Department of Physiology, McGill University, Montreal, QC, Canada
| | - Guadalupe Soria
- Laboratory of Surgical Neuroanatomy, Institute of Neuroscience, University of Barcelona, Barcelona, Spain
| | - Ron Stoop
- Psychiatric neurosciences, Center for Psychiatric Neuroscience, Lausanne University and University Hospital Center, Unicentre, Lausanne, Switzerland
| | | | - Sally M Till
- Simons Initiative for the Developing Brain, University of Edinburgh, Edinburgh, UK
- Patrick Wild Centre, University of Edinburgh, Edinburgh, UK
- Centre for Discovery Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Nick Todd
- Focused Ultrasound Laboratory, Department of Radiology Brigham and Women's Hospital, Boston, MA, USA
| | - Annemie Van Der Linden
- Bio-imaging Lab, University of Antwerp, Antwerp, Belgium
- µNEURO Research Centre of Excellence, University of Antwerp, Antwerp, Belgium
| | - Annette van der Toorn
- Biomedical MR Imaging and Spectroscopy Group, Center for Image Sciences, University Medical Center Utrecht & Utrecht University, Utrecht, The Netherlands
| | - Geralda A F van Tilborg
- Biomedical MR Imaging and Spectroscopy Group, Center for Image Sciences, University Medical Center Utrecht & Utrecht University, Utrecht, The Netherlands
| | - Christian Vanhove
- Institute Biomedical Technology (IBiTech), Electronics and Information Systems (ELIS), Ghent University, Gent, Belgium
| | - Andor Veltien
- Department for Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Marleen Verhoye
- Bio-imaging Lab, University of Antwerp, Antwerp, Belgium
- µNEURO Research Centre of Excellence, University of Antwerp, Antwerp, Belgium
| | - Lydia Wachsmuth
- Experimental Magnetic Resonance Group, Clinic of Radiology, University of Münster, Münster, Germany
| | - Wolfgang Weber-Fahr
- Translational Imaging, Department of Neuroimaging, Central Institute of Mental Health, Medical Faculty Mannheim, Mannheim, Germany
| | - Patricia Wenk
- Combinatorial NeuroImaging Core Facility, Leibniz Institute for Neurobiology, Magdeburg, Germany
| | - Xin Yu
- Translational Neuroimaging and Neural Control Group, High-Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Tuebingen, Germany
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA
| | - Valerio Zerbi
- Neuro-X Institute, School of Engineering (STI), EPFL, Lausanne, Switzerland
- Centre for Biomedical Imaging (CIBM), Lausanne, Switzerland
| | - Nanyin Zhang
- Translational Neuroimaging and Systems Neuroscience Lab, Biomedical Engineering, Pennsylvania State University, University Park, PA, USA
| | - Baogui B Zhang
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing, China
| | - Luc Zimmer
- Lyon Neuroscience Research Center, Université Claude Bernard Lyon 1, INSERM, CNRS, Lyon, France
- CERMEP - Imagerie du vivant, Lyon, France
- Hospices Civils de Lyon, Lyon, France
| | - Gabriel A Devenyi
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Verdun, QC, Canada
- Department of Psychiatry, McGill University, Montreal, QC, Canada
| | - M Mallar Chakravarty
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Verdun, QC, Canada
- Biological and Biomedical Engineering, McGill University, Montreal, QC, Canada
- Department of Psychiatry, McGill University, Montreal, QC, Canada
| | - Andreas Hess
- Institute of Experimental and Clinical Pharmacology and Toxicology, FAU Erlangen-Nürnberg, Erlangen, Germany
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Rathinam E, Rajasekharan S, Declercq H, Vanhove C, De Coster P, Martens L. Effect of Intracoronal Sealing Biomaterials on the Histological Outcome of Endodontic Revitalisation in Immature Sheep Teeth-A Pilot Study. J Funct Biomater 2023; 14:jfb14040214. [PMID: 37103304 PMCID: PMC10144940 DOI: 10.3390/jfb14040214] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Revised: 03/17/2023] [Accepted: 04/08/2023] [Indexed: 04/28/2023] Open
Abstract
The influence of intracoronal sealing biomaterials on the newly formed regenerative tissue after endodontic revitalisation therapy remains unexplored. The objective of this study was to compare the gene expression profiles of two different tricalcium silicate-based biomaterials alongside the histological outcomes of endodontic revitalisation therapy in immature sheep teeth. The messenger RNA expression of TGF-β, BMP2, BGLAP, VEGFA, WNT5A, MMP1, TNF-α and SMAD6 was evaluated after 1 day with qRT-PCR. For evaluation of histological outcomes, revitalisation therapy was performed using Biodentine (n = 4) or ProRoot white mineral trioxide aggregate (WMTA) (n = 4) in immature sheep according to the European Society of Endodontology position statement. After 6 months' follow-up, one tooth in the Biodentine group was lost to avulsion. Histologically, extent of inflammation, presence or absence of tissue with cellularity and vascularity inside the pulp space, area of tissue with cellularity and vascularity, length of odontoblast lining attached to the dentinal wall, number and area of blood vessels and area of empty root canal space were measured by two independent investigators. All continuous data were subjected to statistical analysis using Wilcoxon matched-pairs signed rank test at a significance level of p < 0.05. Biodentine and ProRoot WMTA upregulated the genes responsible for odontoblast differentiation, mineralisation and angiogenesis. Biodentine induced the formation of a significantly larger area of neoformed tissue with cellularity, vascularity and increased length of odontoblast lining attached to the dentinal walls compared to ProRoot WMTA (p < 0.05), but future studies with larger sample size and adequate power as estimated by the results of this pilot study would confirm the effect of intracoronal sealing biomaterials on the histological outcome of endodontic revitalisation.
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Affiliation(s)
- Elanagai Rathinam
- ELOHA (Equal Lifelong Oral Health for All) Research Group, Paediatric Dentistry, Oral Health Sciences, Ghent University Hospital, 9000 Ghent, Belgium
| | - Sivaprakash Rajasekharan
- ELOHA (Equal Lifelong Oral Health for All) Research Group, Paediatric Dentistry, Oral Health Sciences, Ghent University Hospital, 9000 Ghent, Belgium
| | - Heidi Declercq
- Tissue Engineering and Biomaterials Group, Department of Human Structure and Repair, Ghent University Hospital, Ghent University, 9000 Ghent, Belgium
- Tissue Engineering Laboratory, Department of Development and Regeneration, KU Leuven, 8500 Kortrijk, Belgium
| | - Christian Vanhove
- Medical Imaging & Signal Processing, Infinity Laboratory, Ghent University Hospital, Ghent University, 9000 Ghent, Belgium
| | - Peter De Coster
- Department of Reconstructive Dentistry and Oral Biology, Dental School, Ghent University Hospital, Ghent University, 9000 Ghent, Belgium
| | - Luc Martens
- ELOHA (Equal Lifelong Oral Health for All) Research Group, Paediatric Dentistry, Oral Health Sciences, Ghent University Hospital, 9000 Ghent, Belgium
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Grandjean J, Desrosiers-Gregoire G, Anckaerts C, Angeles-Valdez D, Ayad F, Barrière DA, Blockx I, Bortel A, Broadwater M, Cardoso BM, Célestine M, Chavez-Negrete JE, Choi S, Christiaen E, Clavijo P, Colon-Perez L, Cramer S, Daniele T, Dempsey E, Diao Y, Doelemeyer A, Dopfel D, Dvořáková L, Falfán-Melgoza C, Fernandes FF, Fowler CF, Fuentes-Ibañez A, Garin CM, Gelderman E, Golden CEM, Guo CCG, Henckens MJAG, Hennessy LA, Herman P, Hofwijks N, Horien C, Ionescu TM, Jones J, Kaesser J, Kim E, Lambers H, Lazari A, Lee SH, Lillywhite A, Liu Y, Liu YY, López-Castro A, López-Gil X, Ma Z, MacNicol E, Madularu D, Mandino F, Marciano S, McAuslan MJ, McCunn P, McIntosh A, Meng X, Meyer-Baese L, Missault S, Moro F, Naessens DMP, Nava-Gomez LJ, Nonaka H, Ortiz JJ, Paasonen J, Peeters LM, Pereira M, Perez PD, Pompilus M, Prior M, Rakhmatullin R, Reimann HM, Reinwald J, Del Rio RT, Rivera-Olvera A, Ruiz-Pérez D, Russo G, Rutten TJ, Ryoke R, Sack M, Salvan P, Sanganahalli BG, Schroeter A, Seewoo BJ, Selingue E, Seuwen A, Shi B, Sirmpilatze N, Smith JAB, Smith C, Sobczak F, Stenroos PJ, Straathof M, Strobelt S, Sumiyoshi A, Takahashi K, Torres-García ME, Tudela R, van den Berg M, van der Marel K, van Hout ATB, Vertullo R, Vidal B, Vrooman RM, Wang VX, Wank I, Watson DJG, Yin T, Zhang Y, Zurbruegg S, Achard S, Alcauter S, Auer DP, Barbier EL, Baudewig J, Beckmann CF, Beckmann N, Becq GJPC, Blezer ELA, Bolbos R, Boretius S, Bouvard S, Budinger E, Buxbaum JD, Cash D, Chapman V, Chuang KH, Ciobanu L, Coolen BF, Dalley JW, Dhenain M, Dijkhuizen RM, Esteban O, Faber C, Febo M, Feindel KW, Forloni G, Fouquet J, Garza-Villarreal EA, Gass N, Glennon JC, Gozzi A, Gröhn O, Harkin A, Heerschap A, Helluy X, Herfert K, Heuser A, Homberg JR, Houwing DJ, Hyder F, Ielacqua GD, Jelescu IO, Johansen-Berg H, Kaneko G, Kawashima R, Keilholz SD, Keliris GA, Kelly C, Kerskens C, Khokhar JY, Kind PC, Langlois JB, Lerch JP, López-Hidalgo MA, Manahan-Vaughan D, Marchand F, Mars RB, Marsella G, Micotti E, Muñoz-Moreno E, Near J, Niendorf T, Otte WM, Pais-Roldán P, Pan WJ, Prado-Alcalá RA, Quirarte GL, Rodger J, Rosenow T, Sampaio-Baptista C, Sartorius A, Sawiak SJ, Scheenen TWJ, Shemesh N, Shih YYI, Shmuel A, Soria G, Stoop R, Thompson GJ, Till SM, Todd N, Van Der Linden A, van der Toorn A, van Tilborg GAF, Vanhove C, Veltien A, Verhoye M, Wachsmuth L, Weber-Fahr W, Wenk P, Yu X, Zerbi V, Zhang N, Zhang BB, Zimmer L, Devenyi GA, Chakravarty MM, Hess A. A consensus protocol for functional connectivity analysis in the rat brain. Nat Neurosci 2023; 26:673-681. [PMID: 36973511 PMCID: PMC10493189 DOI: 10.1038/s41593-023-01286-8] [Citation(s) in RCA: 19] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2022] [Accepted: 02/15/2023] [Indexed: 03/29/2023]
Abstract
Task-free functional connectivity in animal models provides an experimental framework to examine connectivity phenomena under controlled conditions and allows for comparisons with data modalities collected under invasive or terminal procedures. Currently, animal acquisitions are performed with varying protocols and analyses that hamper result comparison and integration. Here we introduce StandardRat, a consensus rat functional magnetic resonance imaging acquisition protocol tested across 20 centers. To develop this protocol with optimized acquisition and processing parameters, we initially aggregated 65 functional imaging datasets acquired from rats across 46 centers. We developed a reproducible pipeline for analyzing rat data acquired with diverse protocols and determined experimental and processing parameters associated with the robust detection of functional connectivity across centers. We show that the standardized protocol enhances biologically plausible functional connectivity patterns relative to previous acquisitions. The protocol and processing pipeline described here is openly shared with the neuroimaging community to promote interoperability and cooperation toward tackling the most important challenges in neuroscience.
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Affiliation(s)
- Joanes Grandjean
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands.
- Department for Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands.
| | - Gabriel Desrosiers-Gregoire
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Verdun, QC, Canada
- Integrated Program in Neuroscience, McGill University, Montreal, QC, Canada
| | - Cynthia Anckaerts
- Bio-imaging Lab, University of Antwerp, Antwerp, Belgium
- µNEURO Research Centre of Excellence, University of Antwerp, Antwerp, Belgium
| | - Diego Angeles-Valdez
- Instituto de Neurobiología, Universidad Nacional Autónoma de México, Campus Juriquilla, Querétaro, Mexico
| | - Fadi Ayad
- Biological and Biomedical Engineering, McGill University, Montreal, QC, Canada
- McConnell Brain Imaging Centre, McGill University, Montreal, QC, Canada
- Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - David A Barrière
- UMR INRAE/CNRS 7247 Physiologie des Comportements et de la Reproduction, Physiologie de la reproduction et des comportements, Centre de recherche INRAE de Nouzilly, Tours, France
| | - Ines Blockx
- Bio-imaging Lab, University of Antwerp, Antwerp, Belgium
- µNEURO Research Centre of Excellence, University of Antwerp, Antwerp, Belgium
| | - Aleksandra Bortel
- McConnell Brain Imaging Centre, McGill University, Montreal, QC, Canada
- Montreal Neurological Institute, McGill University, Montreal, QC, Canada
- Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
| | - Margaret Broadwater
- Center for Animal MRI, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Neurology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Beatriz M Cardoso
- Preclinical MRI, Champalimaud Research, Champalimaud Centre for the Unknown, Lisbon, Portugal
| | - Marina Célestine
- Laboratoire des Maladies Neurodégénératives, Molecular Imaging Research Center (MIRCen), Université Paris-Saclay, Commissariat à l'Énergie Atomique et aux Énergies Alternatives (CEA), CNRS, Fontenay-aux-Roses, France
| | - Jorge E Chavez-Negrete
- Departamento de Neurobiología Conductual y Cognitiva, Instituto de Neurobiología, Universidad Nacional Autónoma de México, Campus Juriquilla, Querétaro, México
| | - Sangcheon Choi
- Translational Neuroimaging and Neural Control Group, High-Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Tuebingen, Germany
- Graduate Training Centre of Neuroscience, International Max Planck Research School, University of Tuebingen, Tuebingen, Germany
| | - Emma Christiaen
- Institute Biomedical Technology (IBiTech), Electronics and Information Systems (ELIS), Ghent University, Gent, Belgium
| | - Perrin Clavijo
- Department of Biomedical Engineering, Emory University/Georgia Institute of Technology, Atlanta, GA, USA
| | - Luis Colon-Perez
- Department of Pharmacology & Neuroscience, University of North Texas Health Science Center, Fort Worth, TX, USA
| | - Samuel Cramer
- Translational Neuroimaging and Systems Neuroscience Lab, Biomedical Engineering, Pennsylvania State University, University Park, PA, USA
| | - Tolomeo Daniele
- Centre for Advanced Biomedical Imaging, University College London, London, UK
| | - Elaine Dempsey
- Neuropsychopharmacology Research Group, School of Pharmacy and Pharmaceutical Sciences, Trinity College Dublin, Dublin, Ireland
- Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
| | - Yujian Diao
- CIBM Center for Biomedical Imaging, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
- Laboratory for Functional and Metabolic Imaging, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Arno Doelemeyer
- Musculoskeletal Diseases Department, Novartis Institutes for BioMedical Research, Basel, Switzerland
| | - David Dopfel
- Translational Neuroimaging and Systems Neuroscience Lab, Biomedical Engineering, Pennsylvania State University, University Park, PA, USA
| | - Lenka Dvořáková
- Biomedical Imaging Unit, A.I.V. Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
| | - Claudia Falfán-Melgoza
- Translational Imaging, Department of Neuroimaging, Central Institute of Mental Health, Medical Faculty Mannheim, Mannheim, Germany
| | - Francisca F Fernandes
- Preclinical MRI, Champalimaud Research, Champalimaud Centre for the Unknown, Lisbon, Portugal
| | - Caitlin F Fowler
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Verdun, QC, Canada
- Biological and Biomedical Engineering, McGill University, Montreal, QC, Canada
| | - Antonio Fuentes-Ibañez
- Departamento de Neurobiología Conductual y Cognitiva, Instituto de Neurobiología, Universidad Nacional Autónoma de México, Campus Juriquilla, Querétaro, México
| | - Clément M Garin
- Laboratoire des Maladies Neurodégénératives, Molecular Imaging Research Center (MIRCen), Université Paris-Saclay, Commissariat à l'Énergie Atomique et aux Énergies Alternatives (CEA), CNRS, Fontenay-aux-Roses, France
| | - Eveline Gelderman
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
| | - Carla E M Golden
- Seaver Autism Center for Research & Treatment, Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York City, NY, USA
| | - Chao C G Guo
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
| | - Marloes J A G Henckens
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
- Department of Neuroscience and Pharmacology, Rudolf Magnus Institute of Neuroscience, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Lauren A Hennessy
- Experimental and Regenerative Neurosciences, School of Biological Sciences, University of Western Australia, Crawley, WA, Australia
- Brain Plasticity Group, Perron Institute for Neurological and Translational Science, Nedlands, WA, Australia
| | - Peter Herman
- Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, CT, USA
- Quantitative Neuroscience with Magnetic Resonance (QNMR) Core Center, Yale University School of Medicine, New Haven, CT, USA
| | - Nita Hofwijks
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
| | - Corey Horien
- Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, CT, USA
| | - Tudor M Ionescu
- Werner Siemens Imaging Center, Department of Preclinical Imaging and Radiopharmacy, University of Tuebingen, Tuebingen, Germany
| | - Jolyon Jones
- Department of Psychology, University of Cambridge, Cambridge, UK
| | - Johannes Kaesser
- Institute of Experimental and Clinical Pharmacology and Toxicology, FAU Erlangen-Nürnberg, Erlangen, Germany
| | - Eugene Kim
- Biomarker Research And Imaging in Neuroscience (BRAIN) Centre, Department of Neuroimaging King's College London, London, UK
| | - Henriette Lambers
- Experimental Magnetic Resonance Group, Clinic of Radiology, University of Münster, Münster, Germany
| | - Alberto Lazari
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging, FMRIB, University of Oxford, John Radcliffe Hospital, Headington, Oxford, UK
| | - Sung-Ho Lee
- Center for Animal MRI, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Neurology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Amanda Lillywhite
- School of Life Sciences, University of Nottingham, Nottingham, UK
- Pain Centre Versus Arthritis, University of Nottingham, Nottingham, UK
| | - Yikang Liu
- Translational Neuroimaging and Systems Neuroscience Lab, Biomedical Engineering, Pennsylvania State University, University Park, PA, USA
| | - Yanyan Y Liu
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing, China
| | - Alejandra López-Castro
- Instituto de Neurobiología, Universidad Nacional Autónoma de México, Campus Juriquilla, Querétaro, Mexico
| | - Xavier López-Gil
- Magnetic Imaging Resonance Core Facility, Institut d'Investigacions Biomèdiques August Pi I Sunyer (IDIBAPS), Barcelona, Spain
| | - Zilu Ma
- Translational Neuroimaging and Systems Neuroscience Lab, Biomedical Engineering, Pennsylvania State University, University Park, PA, USA
| | - Eilidh MacNicol
- Biomarker Research And Imaging in Neuroscience (BRAIN) Centre, Department of Neuroimaging King's College London, London, UK
| | - Dan Madularu
- Biological and Biomedical Engineering, McGill University, Montreal, QC, Canada
- Center for Translational Neuroimaging, Northeastern University, Boston, MA, USA
| | - Francesca Mandino
- Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, CT, USA
| | - Sabina Marciano
- Werner Siemens Imaging Center, Department of Preclinical Imaging and Radiopharmacy, University of Tuebingen, Tuebingen, Germany
| | - Matthew J McAuslan
- Neuropsychopharmacology Research Group, School of Pharmacy and Pharmaceutical Sciences, Trinity College Dublin, Dublin, Ireland
| | - Patrick McCunn
- Khokhar Lab, Department of Anatomy and Cell Biology, Western University, London, ON, Canada
| | - Alison McIntosh
- Neuropsychopharmacology Research Group, School of Pharmacy and Pharmaceutical Sciences, Trinity College Dublin, Dublin, Ireland
- Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
| | - Xianzong Meng
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
| | - Lisa Meyer-Baese
- Department of Biomedical Engineering, Emory University/Georgia Institute of Technology, Atlanta, GA, USA
| | - Stephan Missault
- Bio-imaging Lab, University of Antwerp, Antwerp, Belgium
- µNEURO Research Centre of Excellence, University of Antwerp, Antwerp, Belgium
| | - Federico Moro
- Laboratory of Acute Brain Injury and Therapeutic Strategies, Department of NeuroscienceIstituto di Ricerche Farmacologiche Mario Negri, IRCCS, Milan, Italy
| | - Daphne M P Naessens
- Biomedical Engineering and Physics, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Laura J Nava-Gomez
- Facultad de Medicina, Universidad Autónoma de Querétaro, Querétaro, México
- Escuela Nacional de Estudios Superiores, Juriquilla, Universidad Nacional Autónoma de México, Querétaro, México
| | - Hiroi Nonaka
- Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan
| | - Juan J Ortiz
- Departamento de Neurobiología Conductual y Cognitiva, Instituto de Neurobiología, Universidad Nacional Autónoma de México, Campus Juriquilla, Querétaro, México
| | - Jaakko Paasonen
- Biomedical Imaging Unit, A.I.V. Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
| | - Lore M Peeters
- Bio-imaging Lab, University of Antwerp, Antwerp, Belgium
- µNEURO Research Centre of Excellence, University of Antwerp, Antwerp, Belgium
| | - Mickaël Pereira
- Lyon Neuroscience Research Center, Université Claude Bernard Lyon 1, INSERM, CNRS, Lyon, France
| | - Pablo D Perez
- Translational Neuroimaging and Systems Neuroscience Lab, Biomedical Engineering, Pennsylvania State University, University Park, PA, USA
| | - Marjory Pompilus
- Febo Laboratory, Department of Psychiatry, University of Florida, Gainesville, FL, USA
| | - Malcolm Prior
- School of Medicine, University of Nottingham, Nottingham, UK
| | | | - Henning M Reimann
- Berlin Ultrahigh Field Facility (B.U.F.F.), Max-Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany
| | - Jonathan Reinwald
- Translational Imaging, Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Rodrigo Triana Del Rio
- Psychiatric neurosciences, Center for Psychiatric Neuroscience, Lausanne University and University Hospital Center, Unicentre, Lausanne, Switzerland
| | - Alejandro Rivera-Olvera
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
| | | | - Gabriele Russo
- Department of Neurophysiology, Medical Faculty, Ruhr University Bochum, Bochum, Germany
| | - Tobias J Rutten
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
| | - Rie Ryoke
- Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan
| | - Markus Sack
- Translational Imaging, Department of Neuroimaging, Central Institute of Mental Health, Medical Faculty Mannheim, Mannheim, Germany
| | - Piergiorgio Salvan
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging, FMRIB, University of Oxford, John Radcliffe Hospital, Headington, Oxford, UK
| | - Basavaraju G Sanganahalli
- Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, CT, USA
- Quantitative Neuroscience with Magnetic Resonance (QNMR) Core Center, Yale University School of Medicine, New Haven, CT, USA
| | - Aileen Schroeter
- Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland
| | - Bhedita J Seewoo
- Experimental and Regenerative Neurosciences, School of Biological Sciences, University of Western Australia, Crawley, WA, Australia
- Brain Plasticity Group, Perron Institute for Neurological and Translational Science, Nedlands, WA, Australia
- Centre for Microscopy, Characterisation & Analysis, Research Infrastructure Centres, University of Western Australia, Nedlands, WA, Australia
| | | | - Aline Seuwen
- Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland
| | - Bowen Shi
- iHuman Institute, ShanghaiTech University, Shanghai, China
| | - Nikoloz Sirmpilatze
- Functional Imaging Laboratory, German Primate Center - Leibniz Institute for Primate Research, Göttingen, Germany
- Faculty of Biology and Psychology, Georg-August University of Göttingen, Göttingen, Germany
- DFG Research Center for Nanoscale Microscopy and Molecular Physiology of the Brain (CNMPB), Göttingen, Germany
| | - Joanna A B Smith
- Simons Initiative for the Developing Brain, University of Edinburgh, Edinburgh, UK
- Patrick Wild Centre, University of Edinburgh, Edinburgh, UK
- Centre for Discovery Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Corrie Smith
- Department of Biomedical Engineering, Emory University/Georgia Institute of Technology, Atlanta, GA, USA
| | - Filip Sobczak
- Translational Neuroimaging and Neural Control Group, High-Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Tuebingen, Germany
- Graduate Training Centre of Neuroscience, International Max Planck Research School, University of Tuebingen, Tuebingen, Germany
| | - Petteri J Stenroos
- Univ. Grenoble Alpes, Inserm, U1216, Grenoble Institut Neurosciences, Grenoble, France
| | - Milou Straathof
- Biomedical MR Imaging and Spectroscopy Group, Center for Image Sciences, University Medical Center Utrecht & Utrecht University, Utrecht, The Netherlands
| | - Sandra Strobelt
- Institute of Experimental and Clinical Pharmacology and Toxicology, FAU Erlangen-Nürnberg, Erlangen, Germany
| | - Akira Sumiyoshi
- Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan
- National Institutes for Quantum Science and Technology, Chiba, Japan
| | - Kengo Takahashi
- Translational Neuroimaging and Neural Control Group, High-Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Tuebingen, Germany
- Graduate Training Centre of Neuroscience, International Max Planck Research School, University of Tuebingen, Tuebingen, Germany
| | - Maria E Torres-García
- Departamento de Neurobiología Conductual y Cognitiva, Instituto de Neurobiología, Universidad Nacional Autónoma de México, Campus Juriquilla, Querétaro, México
| | - Raul Tudela
- Group of Biomedical Imaging, Consorcio Centro de Investigación Biomédica en Red (CIBER) de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), University of Barcelona, Barcelona, Spain
| | - Monica van den Berg
- Bio-imaging Lab, University of Antwerp, Antwerp, Belgium
- µNEURO Research Centre of Excellence, University of Antwerp, Antwerp, Belgium
| | - Kajo van der Marel
- Biomedical MR Imaging and Spectroscopy Group, Center for Image Sciences, University Medical Center Utrecht & Utrecht University, Utrecht, The Netherlands
| | - Aran T B van Hout
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
| | - Roberta Vertullo
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
| | - Benjamin Vidal
- Lyon Neuroscience Research Center, Université Claude Bernard Lyon 1, INSERM, CNRS, Lyon, France
| | - Roël M Vrooman
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
| | - Victora X Wang
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York City, NY, USA
| | - Isabel Wank
- Institute of Experimental and Clinical Pharmacology and Toxicology, FAU Erlangen-Nürnberg, Erlangen, Germany
| | - David J G Watson
- School of Life Sciences, University of Nottingham, Nottingham, UK
| | - Ting Yin
- Animal Imaging and Technology Section, Center for Biomedical Imaging, École polytechnique fédérale de Lausanne, Lausanne, Switzerland
| | - Yongzhi Zhang
- Focused Ultrasound Laboratory, Department of Radiology Brigham and Women's Hospital, Boston, MA, USA
| | - Stefan Zurbruegg
- Neurosciences Department, Novartis Institutes for BioMedical Research, Basel, Switzerland
| | - Sophie Achard
- Inria, University Grenoble Alpes, CNRS, Grenoble, France
| | - Sarael Alcauter
- Departamento de Neurobiología Conductual y Cognitiva, Instituto de Neurobiología, Universidad Nacional Autónoma de México, Campus Juriquilla, Querétaro, México
| | - Dorothee P Auer
- School of Medicine, University of Nottingham, Nottingham, UK
- NIHR Biomedical Research Centre, University of Nottingham, Nottingham, UK
| | - Emmanuel L Barbier
- Univ. Grenoble Alpes, Inserm, U1216, Grenoble Institut Neurosciences, Grenoble, France
| | - Jürgen Baudewig
- Functional Imaging Laboratory, German Primate Center - Leibniz Institute for Primate Research, Göttingen, Germany
| | - Christian F Beckmann
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging, FMRIB, University of Oxford, John Radcliffe Hospital, Headington, Oxford, UK
| | - Nicolau Beckmann
- Musculoskeletal Diseases Department, Novartis Institutes for BioMedical Research, Basel, Switzerland
| | | | - Erwin L A Blezer
- Biomedical MR Imaging and Spectroscopy Group, Center for Image Sciences, University Medical Center Utrecht & Utrecht University, Utrecht, The Netherlands
| | | | - Susann Boretius
- Functional Imaging Laboratory, German Primate Center - Leibniz Institute for Primate Research, Göttingen, Germany
- Faculty of Biology and Psychology, Georg-August University of Göttingen, Göttingen, Germany
- DFG Research Center for Nanoscale Microscopy and Molecular Physiology of the Brain (CNMPB), Göttingen, Germany
| | - Sandrine Bouvard
- Lyon Neuroscience Research Center, Université Claude Bernard Lyon 1, INSERM, CNRS, Lyon, France
| | - Eike Budinger
- Combinatorial NeuroImaging Core Facility, Leibniz Institute for Neurobiology, Magdeburg, Germany
- Center for Behavioral Brain Sciences, Magdeburg, Germany
| | - Joseph D Buxbaum
- Seaver Autism Center for Research & Treatment, Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York City, NY, USA
| | - Diana Cash
- Biomarker Research And Imaging in Neuroscience (BRAIN) Centre, Department of Neuroimaging King's College London, London, UK
| | - Victoria Chapman
- School of Life Sciences, University of Nottingham, Nottingham, UK
- Pain Centre Versus Arthritis, University of Nottingham, Nottingham, UK
- NIHR Biomedical Research Centre, University of Nottingham, Nottingham, UK
| | - Kai-Hsiang Chuang
- Queensland Brain Institute and Centre for Advanced Imaging, University of Queensland, St. Lucia, QLD, Australia
| | | | - Bram F Coolen
- Biomedical Engineering and Physics, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Jeffrey W Dalley
- Department of Psychology, University of Cambridge, Cambridge, UK
| | - Marc Dhenain
- Laboratoire des Maladies Neurodégénératives, Molecular Imaging Research Center (MIRCen), Université Paris-Saclay, Commissariat à l'Énergie Atomique et aux Énergies Alternatives (CEA), CNRS, Fontenay-aux-Roses, France
| | - Rick M Dijkhuizen
- Biomedical MR Imaging and Spectroscopy Group, Center for Image Sciences, University Medical Center Utrecht & Utrecht University, Utrecht, The Netherlands
| | - Oscar Esteban
- Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Cornelius Faber
- Experimental Magnetic Resonance Group, Clinic of Radiology, University of Münster, Münster, Germany
| | - Marcelo Febo
- Febo Laboratory, Department of Psychiatry, University of Florida, Gainesville, FL, USA
| | - Kirk W Feindel
- Centre for Microscopy, Characterisation & Analysis, Research Infrastructure Centres, University of Western Australia, Nedlands, WA, Australia
| | - Gianluigi Forloni
- Biology of Neurodogenerative Disorders, Department of Neuroscience Istituto di Ricerche Farmacologiche Mario Negri, IRCCS, Milan, Italy
| | - Jérémie Fouquet
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Verdun, QC, Canada
| | - Eduardo A Garza-Villarreal
- Instituto de Neurobiología, Universidad Nacional Autónoma de México, Campus Juriquilla, Querétaro, Mexico
| | - Natalia Gass
- Translational Imaging, Department of Neuroimaging, Central Institute of Mental Health, Medical Faculty Mannheim, Mannheim, Germany
| | - Jeffrey C Glennon
- Conway Institute of Biomedical and Biomolecular Sciences, School of Medicine, University College Dublin, Dublin, Ireland
| | - Alessandro Gozzi
- Functional Neuroimaging Laboratory, Center for Neuroscience and Cognitive Systems, Istituto Italiano di Tecnologia, Rovereto, Italy
| | - Olli Gröhn
- Biomedical Imaging Unit, A.I.V. Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
| | - Andrew Harkin
- Neuropsychopharmacology Research Group, School of Pharmacy and Pharmaceutical Sciences, Trinity College Dublin, Dublin, Ireland
- Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
| | - Arend Heerschap
- Department for Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Xavier Helluy
- Department of Neurophysiology, Medical Faculty, Ruhr University Bochum, Bochum, Germany
- Department of Biopsychology, Institute of Cognitive Neuroscience, Ruhr University Bochum, Bochum, Germany
| | - Kristina Herfert
- Werner Siemens Imaging Center, Department of Preclinical Imaging and Radiopharmacy, University of Tuebingen, Tuebingen, Germany
| | - Arnd Heuser
- Max-Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany
| | - Judith R Homberg
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
| | - Danielle J Houwing
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
| | - Fahmeed Hyder
- Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, CT, USA
- Quantitative Neuroscience with Magnetic Resonance (QNMR) Core Center, Yale University School of Medicine, New Haven, CT, USA
| | | | - Ileana O Jelescu
- CIBM Center for Biomedical Imaging, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Heidi Johansen-Berg
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging, FMRIB, University of Oxford, John Radcliffe Hospital, Headington, Oxford, UK
| | - Gen Kaneko
- School of Arts & Sciences, University of Houston-Victoria, Victoria, TX, USA
| | - Ryuta Kawashima
- Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan
| | - Shella D Keilholz
- Department of Biomedical Engineering, Emory University/Georgia Institute of Technology, Atlanta, GA, USA
| | - Georgios A Keliris
- Bio-imaging Lab, University of Antwerp, Antwerp, Belgium
- µNEURO Research Centre of Excellence, University of Antwerp, Antwerp, Belgium
| | - Clare Kelly
- Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
- School of Psychology, Trinity College Dublin, Dublin, Ireland
- Department of Psychiatry, School of Medicine, Trinity College Dublin, Dublin, Ireland
| | - Christian Kerskens
- Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
- Trinity Centre for Biomedical Engineering, School of Medicine, Trinity College Dublin, Dublin, Ireland
| | - Jibran Y Khokhar
- Khokhar Lab, Department of Anatomy and Cell Biology, Western University, London, ON, Canada
| | - Peter C Kind
- Simons Initiative for the Developing Brain, University of Edinburgh, Edinburgh, UK
- Patrick Wild Centre, University of Edinburgh, Edinburgh, UK
- Centre for Discovery Brain Sciences, University of Edinburgh, Edinburgh, UK
- Centre for Brain Development and Repair, Institute for Stem Cell Biology and Regenerative Medicine, Bangalore, India
| | | | - Jason P Lerch
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging, FMRIB, University of Oxford, John Radcliffe Hospital, Headington, Oxford, UK
- Department of Medical Biophysics, University of Toronto, Toronto, QC, Canada
| | - Monica A López-Hidalgo
- Escuela Nacional de Estudios Superiores, Juriquilla, Universidad Nacional Autónoma de México, Querétaro, México
| | | | - Fabien Marchand
- Université Clermont Auvergne, Inserm U1107 Neuro-Dol, Pharmacologie Fondamentale et Clinique de la Douleur, Clermont-Ferrand, France
| | - Rogier B Mars
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging, FMRIB, University of Oxford, John Radcliffe Hospital, Headington, Oxford, UK
| | - Gerardo Marsella
- Animal Care Unit, Istituto di Ricerche Farmacologiche Mario Negri, IRCCS, Milan, Italy
| | - Edoardo Micotti
- Biology of Neurodogenerative Disorders, Department of Neuroscience Istituto di Ricerche Farmacologiche Mario Negri, IRCCS, Milan, Italy
| | - Emma Muñoz-Moreno
- Magnetic Imaging Resonance Core Facility, Institut d'Investigacions Biomèdiques August Pi I Sunyer (IDIBAPS), Barcelona, Spain
| | - Jamie Near
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Verdun, QC, Canada
- Physical Sciences Platform, Sunnybrook Research Institute, Toronto, QC, Canada
| | - Thoralf Niendorf
- Berlin Ultrahigh Field Facility (B.U.F.F.), Max-Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany
- Experimental and Clinical Research Center, A Joint Cooperation Between the Charité Medical Faculty and the Max-Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany
| | - Willem M Otte
- Biomedical MR Imaging and Spectroscopy Group, Center for Image Sciences, University Medical Center Utrecht & Utrecht University, Utrecht, The Netherlands
- Department of Pediatric Neurology, UMC Utrecht Brain Center, University Medical Center Utrecht & Utrecht University, Utrecht, The Netherlands
| | - Patricia Pais-Roldán
- Translational Neuroimaging and Neural Control Group, High-Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Tuebingen, Germany
- Medical Imaging Physics (INM-4), Institute of Neuroscience and Medicine, Forschungszentrum Juelich, Juelich, Germany
| | - Wen-Ju Pan
- Department of Biomedical Engineering, Emory University/Georgia Institute of Technology, Atlanta, GA, USA
| | - Roberto A Prado-Alcalá
- Departamento de Neurobiología Conductual y Cognitiva, Instituto de Neurobiología, Universidad Nacional Autónoma de México, Campus Juriquilla, Querétaro, México
| | - Gina L Quirarte
- Departamento de Neurobiología Conductual y Cognitiva, Instituto de Neurobiología, Universidad Nacional Autónoma de México, Campus Juriquilla, Querétaro, México
| | - Jennifer Rodger
- Experimental and Regenerative Neurosciences, School of Biological Sciences, University of Western Australia, Crawley, WA, Australia
- Brain Plasticity Group, Perron Institute for Neurological and Translational Science, Nedlands, WA, Australia
| | - Tim Rosenow
- Centre for Microscopy, Characterisation and Analysis, University of Western Australia, Crawley, WA, Australia
| | - Cassandra Sampaio-Baptista
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging, FMRIB, University of Oxford, John Radcliffe Hospital, Headington, Oxford, UK
- School of Psychology and Neuroscience, University of Glasgow, Glasgow, UK
| | - Alexander Sartorius
- Translational Imaging, Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Stephen J Sawiak
- Translational Neuroimaging Laboratory, Physiology, Development and Neuroscience, University of Cambridge, Cambridge, UK
| | - Tom W J Scheenen
- Department for Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands
- Erwin L. Hahn Institute for MR Imaging, University of Duisburg-Essen, Essen, Germany
| | - Noam Shemesh
- Preclinical MRI, Champalimaud Research, Champalimaud Centre for the Unknown, Lisbon, Portugal
| | - Yen-Yu Ian Shih
- Center for Animal MRI, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Neurology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Biomedical Engineering, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Amir Shmuel
- Biological and Biomedical Engineering, McGill University, Montreal, QC, Canada
- McConnell Brain Imaging Centre, McGill University, Montreal, QC, Canada
- Montreal Neurological Institute, McGill University, Montreal, QC, Canada
- Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
- Department of Physiology, McGill University, Montreal, QC, Canada
| | - Guadalupe Soria
- Laboratory of Surgical Neuroanatomy, Institute of Neuroscience, University of Barcelona, Barcelona, Spain
| | - Ron Stoop
- Psychiatric neurosciences, Center for Psychiatric Neuroscience, Lausanne University and University Hospital Center, Unicentre, Lausanne, Switzerland
| | | | - Sally M Till
- Simons Initiative for the Developing Brain, University of Edinburgh, Edinburgh, UK
- Patrick Wild Centre, University of Edinburgh, Edinburgh, UK
- Centre for Discovery Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Nick Todd
- Focused Ultrasound Laboratory, Department of Radiology Brigham and Women's Hospital, Boston, MA, USA
| | - Annemie Van Der Linden
- Bio-imaging Lab, University of Antwerp, Antwerp, Belgium
- µNEURO Research Centre of Excellence, University of Antwerp, Antwerp, Belgium
| | - Annette van der Toorn
- Biomedical MR Imaging and Spectroscopy Group, Center for Image Sciences, University Medical Center Utrecht & Utrecht University, Utrecht, The Netherlands
| | - Geralda A F van Tilborg
- Biomedical MR Imaging and Spectroscopy Group, Center for Image Sciences, University Medical Center Utrecht & Utrecht University, Utrecht, The Netherlands
| | - Christian Vanhove
- Institute Biomedical Technology (IBiTech), Electronics and Information Systems (ELIS), Ghent University, Gent, Belgium
| | - Andor Veltien
- Department for Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Marleen Verhoye
- Bio-imaging Lab, University of Antwerp, Antwerp, Belgium
- µNEURO Research Centre of Excellence, University of Antwerp, Antwerp, Belgium
| | - Lydia Wachsmuth
- Experimental Magnetic Resonance Group, Clinic of Radiology, University of Münster, Münster, Germany
| | - Wolfgang Weber-Fahr
- Translational Imaging, Department of Neuroimaging, Central Institute of Mental Health, Medical Faculty Mannheim, Mannheim, Germany
| | - Patricia Wenk
- Combinatorial NeuroImaging Core Facility, Leibniz Institute for Neurobiology, Magdeburg, Germany
| | - Xin Yu
- Translational Neuroimaging and Neural Control Group, High-Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Tuebingen, Germany
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA
| | - Valerio Zerbi
- Neuro-X Institute, School of Engineering (STI), EPFL, Lausanne, Switzerland
- Centre for Biomedical Imaging (CIBM), Lausanne, Switzerland
| | - Nanyin Zhang
- Translational Neuroimaging and Systems Neuroscience Lab, Biomedical Engineering, Pennsylvania State University, University Park, PA, USA
| | - Baogui B Zhang
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing, China
| | - Luc Zimmer
- Lyon Neuroscience Research Center, Université Claude Bernard Lyon 1, INSERM, CNRS, Lyon, France
- CERMEP - Imagerie du vivant, Lyon, France
- Hospices Civils de Lyon, Lyon, France
| | - Gabriel A Devenyi
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Verdun, QC, Canada
- Department of Psychiatry, McGill University, Montreal, QC, Canada
| | - M Mallar Chakravarty
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Verdun, QC, Canada
- Biological and Biomedical Engineering, McGill University, Montreal, QC, Canada
- Department of Psychiatry, McGill University, Montreal, QC, Canada
| | - Andreas Hess
- Institute of Experimental and Clinical Pharmacology and Toxicology, FAU Erlangen-Nürnberg, Erlangen, Germany
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Maris L, De Man K, Gryspeerdt F, Hoorens A, Keereman V, Kiekens A, Van den Broeck B, Van de Sande L, Vanhove C, Berrevoet F. 18F-FDG-PET-CT specimen imaging for perioperative visualization of pancreatic adenocarcinoma: a proof-of-concept study. European Journal of Surgical Oncology 2023. [DOI: 10.1016/j.ejso.2022.11.445] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/25/2023]
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16
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Vedunova M, Turubanova V, Vershinina O, Savyuk M, Efimova I, Mishchenko T, Raedt R, Vral A, Vanhove C, Korsakova D, Bachert C, Coppieters F, Agostinis P, Garg AD, Ivanchenko M, Krysko O, Krysko DV. DC vaccines loaded with glioma cells killed by photodynamic therapy induce Th17 anti-tumor immunity and provide a four-gene signature for glioma prognosis. Cell Death Dis 2022; 13:1062. [PMID: 36539408 PMCID: PMC9767932 DOI: 10.1038/s41419-022-05514-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2022] [Revised: 12/12/2022] [Accepted: 12/12/2022] [Indexed: 12/24/2022]
Abstract
Gliomas, the most frequent type of primary tumor of the central nervous system in adults, results in significant morbidity and mortality. Despite the development of novel, complex, multidisciplinary, and targeted therapies, glioma therapy has not progressed much over the last decades. Therefore, there is an urgent need to develop novel patient-adjusted immunotherapies that actively stimulate antitumor T cells, generate long-term memory, and result in significant clinical benefits. This work aimed to investigate the efficacy and molecular mechanism of dendritic cell (DC) vaccines loaded with glioma cells undergoing immunogenic cell death (ICD) induced by photosens-based photodynamic therapy (PS-PDT) and to identify reliable prognostic gene signatures for predicting the overall survival of patients. Analysis of the transcriptional program of the ICD-based DC vaccine led to the identification of robust induction of Th17 signature when used as a vaccine. These DCs demonstrate retinoic acid receptor-related orphan receptor-γt dependent efficacy in an orthotopic mouse model. Moreover, comparative analysis of the transcriptome program of the ICD-based DC vaccine with transcriptome data from the TCGA-LGG dataset identified a four-gene signature (CFH, GALNT3, SMC4, VAV3) associated with overall survival of glioma patients. This model was validated on overall survival of CGGA-LGG, TCGA-GBM, and CGGA-GBM datasets to determine whether it has a similar prognostic value. To that end, the sensitivity and specificity of the prognostic model for predicting overall survival were evaluated by calculating the area under the curve of the time-dependent receiver operating characteristic curve. The values of area under the curve for TCGA-LGG, CGGA-LGG, TCGA-GBM, and CGGA-GBM for predicting five-year survival rates were, respectively, 0.75, 0.73, 0.9, and 0.69. These data open attractive prospects for improving glioma therapy by employing ICD and PS-PDT-based DC vaccines to induce Th17 immunity and to use this prognostic model to predict the overall survival of glioma patients.
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Affiliation(s)
- Maria Vedunova
- grid.28171.3d0000 0001 0344 908XInstitute of Biology and Biomedicine, National Research Lobachevsky State University of Nizhny Novgorod, Nizhny Novgorod, Russia
| | - Victoria Turubanova
- grid.28171.3d0000 0001 0344 908XInstitute of Biology and Biomedicine, National Research Lobachevsky State University of Nizhny Novgorod, Nizhny Novgorod, Russia ,grid.5342.00000 0001 2069 7798Cell Death Investigation and Therapy (CDIT) Laboratory, Department of Human Structure and Repair, Ghent University, Ghent, Belgium
| | - Olga Vershinina
- grid.28171.3d0000 0001 0344 908XInstitute of Information Technology, Mathematics and Mechanics, National Research Lobachevsky State University of Nizhny Novgorod, Nizhny Novgorod, Russia
| | - Maria Savyuk
- grid.28171.3d0000 0001 0344 908XInstitute of Biology and Biomedicine, National Research Lobachevsky State University of Nizhny Novgorod, Nizhny Novgorod, Russia ,grid.5342.00000 0001 2069 7798Cell Death Investigation and Therapy (CDIT) Laboratory, Department of Human Structure and Repair, Ghent University, Ghent, Belgium
| | - Iuliia Efimova
- grid.5342.00000 0001 2069 7798Cell Death Investigation and Therapy (CDIT) Laboratory, Department of Human Structure and Repair, Ghent University, Ghent, Belgium ,grid.510942.bCancer Research Institute Ghent, Ghent, Belgium
| | - Tatiana Mishchenko
- grid.28171.3d0000 0001 0344 908XInstitute of Biology and Biomedicine, National Research Lobachevsky State University of Nizhny Novgorod, Nizhny Novgorod, Russia
| | - Robrecht Raedt
- grid.5342.00000 0001 2069 77984Brain Team, Department of Head and Skin, Ghent University, Ghent, Belgium
| | - Anne Vral
- grid.5342.00000 0001 2069 7798Radiobiology Research Group, Department of Human Structure and Repair, Ghent University, Ghent, Belgium
| | - Christian Vanhove
- grid.5342.00000 0001 2069 7798IBiTech-MEDISIP-Infinity Laboratory, Department of Electronics and Information Systems, Ghent University, Ghent, Belgium
| | - Daria Korsakova
- grid.28171.3d0000 0001 0344 908XInstitute of Biology and Biomedicine, National Research Lobachevsky State University of Nizhny Novgorod, Nizhny Novgorod, Russia
| | - Claus Bachert
- grid.5342.00000 0001 2069 7798Upper Airways Research Laboratory, Department of Head and Skin, Ghent University, Ghent, Belgium
| | - Frauke Coppieters
- grid.5342.00000 0001 2069 7798Center for Medical Genetics Ghent (CMGG), Department of Biomolecular Medicine, Ghent University, Ghent, Belgium
| | - Patrizia Agostinis
- grid.5596.f0000 0001 0668 7884Laboratory of Cell Death Research & Therapy, Department of Cellular and Molecular Medicine, KU Leuven, Leuven, Belgium ,grid.511459.dVIB Center for Cancer Biology Research, Leuven, Belgium
| | - Abhishek D. Garg
- grid.5596.f0000 0001 0668 7884Laboratory of Cell Stress & Immunity (CSI), Department of Cellular & Molecular Medicine, KU Leuven, Leuven, Belgium
| | - Mikhail Ivanchenko
- grid.28171.3d0000 0001 0344 908XInstitute of Information Technology, Mathematics and Mechanics, National Research Lobachevsky State University of Nizhny Novgorod, Nizhny Novgorod, Russia
| | - Olga Krysko
- grid.5342.00000 0001 2069 7798Cell Death Investigation and Therapy (CDIT) Laboratory, Department of Human Structure and Repair, Ghent University, Ghent, Belgium
| | - Dmitri V. Krysko
- grid.28171.3d0000 0001 0344 908XInstitute of Biology and Biomedicine, National Research Lobachevsky State University of Nizhny Novgorod, Nizhny Novgorod, Russia ,grid.5342.00000 0001 2069 7798Cell Death Investigation and Therapy (CDIT) Laboratory, Department of Human Structure and Repair, Ghent University, Ghent, Belgium ,grid.510942.bCancer Research Institute Ghent, Ghent, Belgium
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Donche S, Verhoeven J, Descamps B, Bouckaert C, Raedt R, Vanhove C, Goethals I. Positron Emission Tomography-based Dose Painting Radiation Therapy in a Glioblastoma Rat Model using the Small Animal Radiation Research Platform. J Vis Exp 2022. [DOI: 10.3791/62560] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/31/2022] Open
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Muller FM, Vanhove C, Vandeghinste B, Vandenberghe S. Performance evaluation of a micro-CT system for laboratory animal imaging with iterative reconstruction capabilities. Med Phys 2022; 49:3121-3133. [PMID: 35170057 DOI: 10.1002/mp.15538] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2021] [Revised: 01/22/2022] [Accepted: 02/07/2022] [Indexed: 11/06/2022] Open
Abstract
BACKGROUND In recent years, there has been a rapid proliferation in micro-computed tomography (micro-CT) systems becoming more available for routine preclinical research, with applications in many areas including bone, lung, cancer and cardiac imaging. Micro-CT provides the means to non-invasively acquire detailed anatomical information, but high-resolution imaging comes at the cost of longer scan times and higher doses, which is not desirable given the potential risks related to x-ray radiation. To achieve dose reduction and higher throughputs without compromising image quality (noise management), fewer projections can be acquired. This is where iterative reconstruction methods can have the potential to reduce noise since these algorithms can better handle sparse projection data, compared to filtered backprojection PURPOSE: We evaluate the performance characteristics of a compact benchtop micro-CT scanner that provides iterative reconstruction capabilities with GPU-based acceleration. More specifically, we thereby investigate the potential benefit of iterative reconstruction methods for dose reduction. METHODS Based on a series of phantom experiments, the benchtop micro-CT system was characterized in terms of image uniformity, noise, low contrast detectability, linearity and spatial resolution. Whole-body images of a plasticized ex vivo mouse phantom were also acquired. Different acquisition protocols (general-purpose versus high-resolution, including low dose scans) and different reconstruction strategies (analytic versus iterative algorithms: FDK, ISRA, ISRA-TV) were compared. RESULTS Signal uniformity was maintained across the radial and axial field-of-view (no cupping effect) with an average difference in Hounsfield units (HU) between peripheral and central regions below 50. For low contrast detectability, regions with at least ∆HU of 40 to surrounding material could be discriminated (for rods of 2.5 mm diameter). A high linear correlation (R2 = 0.997) was found between measured CT values and iodine concentrations (0-40 mg/ml). Modulation transfer function (MTF) calculations on a wire phantom evaluated a resolution of 10.2 lp/mm at 10% MTF that was consistent with the 8.3% MTF measured on the 50 μm bars (10 lp/mm) of a bar-pattern phantom. Noteworthy changes in signal-to-noise and contrast-to-noise values were found for different acquisition and reconstruction protocols. Our results further showed the potential of iterative reconstruction methods to deliver images with less noise and artefacts. CONCLUSIONS In summary, the micro-CT system for laboratory animal imaging that was evaluated in the present work was shown to provide a good combination of performance characteristics between image uniformity, low contrast detectability and resolution in short scan times. With the iterative reconstruction capabilities of this micro-CT system in mind (ISRA and ISRA-TV), the adoption of such algorithms by GPU-based acceleration enables the integration of noise reduction methods which here demonstrated potential for high quality imaging at reduced doses. This article is protected by copyright. All rights reserved.
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Affiliation(s)
- Florence M Muller
- MEDISIP-INFINITY, Department of Electronics and Information Systems, Faculty of Engineering and Architecture, Ghent University, Ghent, 9000, Belgium
| | - Christian Vanhove
- MEDISIP-INFINITY, Department of Electronics and Information Systems, Faculty of Engineering and Architecture, Ghent University, Ghent, 9000, Belgium
| | | | - Stefaan Vandenberghe
- MEDISIP-INFINITY, Department of Electronics and Information Systems, Faculty of Engineering and Architecture, Ghent University, Ghent, 9000, Belgium
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Piron S, Verhoeven J, Vanhove C, De Vos F. Recent advancements in 18F-labeled PSMA targeting PET radiopharmaceuticals. Nucl Med Biol 2021; 106-107:29-51. [PMID: 34998217 DOI: 10.1016/j.nucmedbio.2021.12.005] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2021] [Revised: 12/08/2021] [Accepted: 12/23/2021] [Indexed: 12/13/2022]
Abstract
Prostate specific membrane antigen (PSMA) is an attractive target for molecular imaging of prostate cancer and several other solid tumors because of its overexpression in prostate carcinoma and tumor neovasculature, respectively. While currently most commonly used PSMA PET radioligands are 68Ga-labeled compounds, the short half-life and relatively low available radioactivity of gallium-68 have led to a steep increase in the development of 18F-labeled PSMA ligands. Several 18F-PSMA tracers such as [18F]DCFPyL and [18F]PSMA-1007 are already established in clinical practice, but there are still several drawbacks to be considered. Radiofluorination is often a multistep and time-consuming process requiring harsh labeling conditions. The limited sensitivity in the lower PSA ranges raises the need for improving the binding affinity of the ligands. Due to the metallic character of therapeutic radionuclides, there is very limited experience with 18F-PSMA tracers that can be applied for a theranostic approach. However, developments in the past few years have brought forward several improvements in these fields. These include the application of new radiosynthesis pathways for radiofluorination that reduces the process complexity, new approaches for the design of the pharmacophore, improving target interaction and the introduction of radiohybrid ligands, allowing labeling of the ligand with both diagnostic and therapeutic radionuclides. In this review, we will give an overview of these recent advancements of 18F-labeled PSMA PET radioligands.
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Affiliation(s)
- Sarah Piron
- Laboratory for Radiopharmacy, Ghent University, Ghent, Belgium.
| | | | - Christian Vanhove
- IBiTech-MEDISIP, Dept of Electronics and Information Systems, Ghent University, Ghent, Belgium
| | - Filip De Vos
- Laboratory for Radiopharmacy, Ghent University, Ghent, Belgium
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Proesmans S, Raedt R, Germonpré C, Christiaen E, Descamps B, Boon P, De Herdt V, Vanhove C. Voxel-Based Analysis of [18F]-FDG Brain PET in Rats Using Data-Driven Normalization. Front Med (Lausanne) 2021; 8:744157. [PMID: 34746179 PMCID: PMC8565796 DOI: 10.3389/fmed.2021.744157] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2021] [Accepted: 09/24/2021] [Indexed: 11/13/2022] Open
Abstract
Introduction: [18F]-FDG PET is a widely used imaging modality that visualizes cellular glucose uptake and provides functional information on the metabolic state of different tissues in vivo. Various quantification methods can be used to evaluate glucose metabolism in the brain, including the cerebral metabolic rate of glucose (CMRglc) and standard uptake values (SUVs). Especially in the brain, these (semi-)quantitative measures can be affected by several physiological factors, such as blood glucose level, age, gender, and stress. Next to this inter- and intra-subject variability, the use of different PET acquisition protocols across studies has created a need for the standardization and harmonization of brain PET evaluation. In this study we present a framework for statistical voxel-based analysis of glucose uptake in the rat brain using histogram-based intensity normalization. Methods: [18F]-FDG PET images of 28 normal rat brains were coregistered and voxel-wisely averaged. Ratio images were generated by voxel-wisely dividing each of these images with the group average. The most prevalent value in the ratio image was used as normalization factor. The normalized PET images were voxel-wisely averaged to generate a normal rat brain atlas. The variability of voxel intensities across the normalized PET images was compared to images that were either normalized by whole brain normalization, or not normalized. To illustrate the added value of this normal rat brain atlas, 9 animals with a striatal hemorrhagic lesion and 9 control animals were intravenously injected with [18F]-FDG and the PET images of these animals were voxel-wisely compared to the normal atlas by group- and individual analyses. Results: The average coefficient of variation of the voxel intensities in the brain across normal [18F]-FDG PET images was 6.7% for the histogram-based normalized images, 11.6% for whole brain normalized images, and 31.2% when no normalization was applied. Statistical voxel-based analysis, using the normal template, indicated regions of significantly decreased glucose uptake at the site of the ICH lesion in the ICH animals, but not in control animals. Conclusion: In summary, histogram-based intensity normalization of [18F]-FDG uptake in the brain is a suitable data-driven approach for standardized voxel-based comparison of brain PET images.
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Affiliation(s)
- Silke Proesmans
- 4Brain Lab, Department of Head and Skin, Ghent University, Ghent, Belgium
| | - Robrecht Raedt
- 4Brain Lab, Department of Head and Skin, Ghent University, Ghent, Belgium
| | | | - Emma Christiaen
- IbiTech-MEDISIP-Infinity Lab, Department of Electronics and Information Systems, Ghent University, Ghent, Belgium
| | - Benedicte Descamps
- IbiTech-MEDISIP-Infinity Lab, Department of Electronics and Information Systems, Ghent University, Ghent, Belgium
| | - Paul Boon
- 4Brain Lab, Department of Head and Skin, Ghent University, Ghent, Belgium
| | - Veerle De Herdt
- 4Brain Lab, Department of Head and Skin, Ghent University, Ghent, Belgium
| | - Christian Vanhove
- IbiTech-MEDISIP-Infinity Lab, Department of Electronics and Information Systems, Ghent University, Ghent, Belgium
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Van Hoeck J, Vanhove C, De Smedt SC, Raemdonck K. Non-invasive cell-tracking methods for adoptive T cell therapies. Drug Discov Today 2021; 27:793-807. [PMID: 34718210 DOI: 10.1016/j.drudis.2021.10.012] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2021] [Revised: 07/26/2021] [Accepted: 10/20/2021] [Indexed: 12/12/2022]
Abstract
Adoptive T cell therapies (ACT) have demonstrated groundbreaking results in blood cancers and melanoma. Nevertheless, their significant cost, the occurrence of severe adverse events, and their poor performance in solid tumors are important hurdles hampering more widespread applicability. In vivo cell tracking allows instantaneous and non-invasive monitoring of the distribution, tumor homing, persistence, and redistribution to other organs of infused T cells in patients. Furthermore, cell tracking could aid in the clinical management of patients, allowing the detection of non-responders or severe adverse events at an early stage. This review provides a concise overview of the main principles and potential of cell tracking, followed by a discussion of the clinically relevant labeling strategies and their application in ACT.
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Affiliation(s)
- Jelter Van Hoeck
- Ghent Research Group on Nanomedicines, Laboratory of General Biochemistry and Physical Pharmacy, Faculty of Pharmaceutical Sciences, Department of Pharmaceutics, Ghent University, Ottergemsesteenweg 460, 9000 Ghent, Belgium
| | - Christian Vanhove
- Infinity Lab, Medical Imaging and Signal Processing Group-IBiTech, Faculty of Engineering and Architecture, Ghent University, Corneel Heymanslaan 10, 9000 Ghent, Belgium
| | - Stefaan C De Smedt
- Ghent Research Group on Nanomedicines, Laboratory of General Biochemistry and Physical Pharmacy, Faculty of Pharmaceutical Sciences, Department of Pharmaceutics, Ghent University, Ottergemsesteenweg 460, 9000 Ghent, Belgium
| | - Koen Raemdonck
- Ghent Research Group on Nanomedicines, Laboratory of General Biochemistry and Physical Pharmacy, Faculty of Pharmaceutical Sciences, Department of Pharmaceutics, Ghent University, Ottergemsesteenweg 460, 9000 Ghent, Belgium.
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22
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Donche S, Verhoeven J, Bouckaert C, Descamps B, Raedt R, Vanhove C, Goethals I. P13.21 PET-based dose painting radiation therapy strategy in a glioblastoma rat model using the small animal radiation research platform. Neuro Oncol 2021. [DOI: 10.1093/neuonc/noab180.127] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Abstract
BACKGROUND
Previously, a rat glioblastoma model to mimic chemo-radiation treatment of human glioblastoma in the clinic was established. Similarly to the clinic, CT and MRI were combined during the treatment planning process. PET imaging was subsequently added which allowed us to implement sub-volume boosting using a micro-irradiation system. However, combining three imaging modalities (CT, MRI and PET) using a micro-irradiation system, proved to be labour intensive because multimodal imaging, treatment planning and dose delivery have to be completed sequentially in the preclinical setting.
MATERIAL AND METHODS
Two different methodologies were compared in silico for performing preclinical [18F]FET PET based radiation therapy (20 Gy based on MRI, 8 Gy boost based on PET) based on three different cases. Method 1 is based on the previously published methods1,2. However, the process is automated using an in-house developed MATLAB code. Method 2 consists of a more sophisticated method where a series of isocenters and jaw dimensions for the motorised variable collimator were determined based on the [18F]FET PET uptake. Both methods were evaluated by means of the dose volume histograms (DVH) and Q-volume histograms.
RESULTS
The setup parameters for both methods were calculated. The DVHs for method 2 are systematically closer to the ideal dose distribution compared to method 1. These findings are confirmed by the D90 and D50 values which are considerably lower for method 1. When observing the Q-factor, method 2 always results in dose distributions that are closer to the dose objectives (method 1: 0.141±0.046; method 2: 0.064±0.011).
CONCLUSION
The described novel method to optimize the preclinical treatment planning process has many advantages in terms of dose delivery, time efficiency and variability, when compared to the previously used methods1,2. These improvements are important to narrow the gap between clinical and preclinical radiation research and for the development of new therapeutics and/or radiation therapy procedures for glioblastoma.
1. Bolcaen, J., Descamps, B., Boterberg, T., Vanhove, C. & Goethals, I. PET and MRI Guided Irradiation of a Glioblastoma Rat Model Using a Micro-irradiator. J. Vis. Exp. 1–10 (2017) doi:10.3791/56601.
2. Verhoeven, J. et al. Technical feasibility of [18F]FET and [18F]FAZA PET guided radiotherapy in a F98 glioblastoma rat model. Radiat. Oncol. 14, (2019).
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Affiliation(s)
| | | | | | | | - R Raedt
- Ghent university, Gent, Belgium
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23
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Christiaen E, Goossens MG, Descamps B, Delbeke J, Wadman W, Vonck K, Boon P, Raedt R, Vanhove C. White Matter Integrity in a Rat Model of Epileptogenesis: Structural Connectomics and Fixel-Based Analysis. Brain Connect 2021; 12:320-333. [PMID: 34155915 DOI: 10.1089/brain.2021.0026] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Introduction: Electrophysiological and neuroimaging studies have demonstrated that large-scale brain networks are affected during the development of epilepsy. These networks can be investigated by using diffusion magnetic resonance imaging (dMRI). The most commonly used model to analyze dMRI is diffusion tensor imaging (DTI). However, DTI metrics are not specific to microstructure or pathology and the DTI model does not take into account crossing fibers, which may lead to erroneous results. To overcome these limitations, a more advanced model based on multi-shell multi-tissue constrained spherical deconvolution was used in this study to perform tractography with more precise fiber orientation estimates and to assess changes in intra-axonal volume by using fixel-based analysis. Methods: dMRI images were acquired before and at several time points after induction of status epilepticus in the intraperitoneal kainic acid (IPKA) rat model of temporal lobe epilepsy. Tractography was performed, and fixel metrics were calculated in several white matter tracts. The tractogram was analyzed by using the graph theory. Results: Global degree, global and local efficiency were decreased in IPKA animals compared with controls during epileptogenesis. Nodal degree was decreased in the limbic system and default-mode network, mainly during early epileptogenesis. Further, fiber density (FD) and fiber-density-and-cross-section (FDC) were decreased in several white matter tracts. Discussion: These results indicate a decrease in overall structural connectivity, integration, and segregation and decreased structural connectivity in the limbic system and default-mode network. Decreased FD and FDC point to a decrease in intra-axonal volume fraction during epileptogenesis, which may be related to neuronal degeneration and gliosis. Impact statement To the best of our knowledge, this is the first longitudinal multi-shell diffusion magnetic resonance imaging study that combines whole-brain tractography and fixel-based analysis to investigate changes in structural brain connectivity and white matter integrity during epileptogenesis in a rat model of temporal lobe epilepsy. Our findings present better insights into how the topology of the structural brain network changes during epileptogenesis and how these changes are related to white matter integrity. This could improve the understanding of the basic mechanisms of epilepsy and aid the rational development of imaging biomarkers and epilepsy therapies.
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Affiliation(s)
- Emma Christiaen
- MEDISIP, Department of Electronics and Information Systems, Ghent University, Ghent, Belgium
| | | | - Benedicte Descamps
- MEDISIP, Department of Electronics and Information Systems, Ghent University, Ghent, Belgium
| | - Jean Delbeke
- 4Brain, Department of Head and Skin, Ghent University, Ghent, Belgium
| | - Wytse Wadman
- 4Brain, Department of Head and Skin, Ghent University, Ghent, Belgium
| | - Kristl Vonck
- 4Brain, Department of Head and Skin, Ghent University, Ghent, Belgium
| | - Paul Boon
- 4Brain, Department of Head and Skin, Ghent University, Ghent, Belgium
| | - Robrecht Raedt
- 4Brain, Department of Head and Skin, Ghent University, Ghent, Belgium
| | - Christian Vanhove
- MEDISIP, Department of Electronics and Information Systems, Ghent University, Ghent, Belgium
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24
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Debacker JM, Schelfhout V, Brochez L, Creytens D, D’Asseler Y, Deron P, Keereman V, Van de Vijver K, Vanhove C, Huvenne W. High-Resolution 18F-FDG PET/CT for Assessing Three-Dimensional Intraoperative Margins Status in Malignancies of the Head and Neck, a Proof-of-Concept. J Clin Med 2021; 10:jcm10163737. [PMID: 34442033 PMCID: PMC8397229 DOI: 10.3390/jcm10163737] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2021] [Revised: 08/20/2021] [Accepted: 08/20/2021] [Indexed: 01/27/2023] Open
Abstract
The surgical treatment of head and neck malignancies relies on the complete removal of tumoral tissue, while inadequate margins necessitate the use of adjuvant therapy. However, most positive margins are identified postoperatively as deep margins, and intraoperative identification of the deep positive margins could help achieve adequate surgical margins and decrease adjuvant therapies. To improve deep-margin identification, we investigated whether the use of high-resolution preclinical PET and CT could increase certainty about the surgical margins in three dimensions. Patients with a malignancy of the head and neck planned for surgical resection were administered a clinical activity of 4MBq/kg 18F-FDG approximately one hour prior to surgical initiation. Subsequently, the resected specimen was scanned with a micro-PET-CT imaging device, followed by histopathological assessment. Eight patients were included in the study and intraoperative PET/CT-imaging of 11 tumoral specimens and lymph nodes of three patients was performed. As a result of the increased resolution, differentiation between inflamed and dysplastic tissue versus malignant tissue was complicated in malignancies with increased peritumoral inflammation. The current technique allowed the three-dimensional delineation of 18F-FDG using submillimetric PET/CT imaging. While further optimization and patient stratification is required, clinical implementation could enable deep margin assessment in head and neck resection specimens.
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Affiliation(s)
- Jens M. Debacker
- Department of Head and Skin, Ghent University, 9000 Ghent, Belgium; (L.B.); (P.D.); (W.H.)
- Department of Head and Neck Surgery, Ghent University Hospital, 9000 Ghent, Belgium
- Department of Nuclear Medicine, University Hospital Brussels, 1090 Brussels, Belgium
- Cancer Research Institute Ghent, 9000 Ghent, Belgium; (V.S.); (D.C.); (Y.D.); (K.V.d.V.); (C.V.)
- Correspondence: ; Tel.: +32-9-332-39-90
| | - Vanessa Schelfhout
- Cancer Research Institute Ghent, 9000 Ghent, Belgium; (V.S.); (D.C.); (Y.D.); (K.V.d.V.); (C.V.)
- Department of Medical Imaging, Nuclear Medicine, Ghent University Hospital, 9000 Ghent, Belgium
- Department of Diagnostic Sciences, Ghent University, 9000 Ghent, Belgium
| | - Lieve Brochez
- Department of Head and Skin, Ghent University, 9000 Ghent, Belgium; (L.B.); (P.D.); (W.H.)
- Cancer Research Institute Ghent, 9000 Ghent, Belgium; (V.S.); (D.C.); (Y.D.); (K.V.d.V.); (C.V.)
- Department of Dermatology, Ghent University Hospital, 9000 Ghent, Belgium
| | - David Creytens
- Cancer Research Institute Ghent, 9000 Ghent, Belgium; (V.S.); (D.C.); (Y.D.); (K.V.d.V.); (C.V.)
- Department of Diagnostic Sciences, Ghent University, 9000 Ghent, Belgium
- Department of Pathology, Ghent University Hospital, 9000 Ghent, Belgium
| | - Yves D’Asseler
- Cancer Research Institute Ghent, 9000 Ghent, Belgium; (V.S.); (D.C.); (Y.D.); (K.V.d.V.); (C.V.)
- Department of Medical Imaging, Nuclear Medicine, Ghent University Hospital, 9000 Ghent, Belgium
- Department of Diagnostic Sciences, Ghent University, 9000 Ghent, Belgium
| | - Philippe Deron
- Department of Head and Skin, Ghent University, 9000 Ghent, Belgium; (L.B.); (P.D.); (W.H.)
- Department of Head and Neck Surgery, Ghent University Hospital, 9000 Ghent, Belgium
- Cancer Research Institute Ghent, 9000 Ghent, Belgium; (V.S.); (D.C.); (Y.D.); (K.V.d.V.); (C.V.)
| | - Vincent Keereman
- Department of Electronics and Information Systems, Ghent University, 9000 Ghent, Belgium;
- XEOS Medical NV, 9000 Ghent, Belgium
| | - Koen Van de Vijver
- Cancer Research Institute Ghent, 9000 Ghent, Belgium; (V.S.); (D.C.); (Y.D.); (K.V.d.V.); (C.V.)
- Department of Diagnostic Sciences, Ghent University, 9000 Ghent, Belgium
- Department of Pathology, Ghent University Hospital, 9000 Ghent, Belgium
| | - Christian Vanhove
- Cancer Research Institute Ghent, 9000 Ghent, Belgium; (V.S.); (D.C.); (Y.D.); (K.V.d.V.); (C.V.)
- Department of Electronics and Information Systems, Ghent University, 9000 Ghent, Belgium;
- INFINITY Lab, Ghent University, 9000 Ghent, Belgium
| | - Wouter Huvenne
- Department of Head and Skin, Ghent University, 9000 Ghent, Belgium; (L.B.); (P.D.); (W.H.)
- Department of Head and Neck Surgery, Ghent University Hospital, 9000 Ghent, Belgium
- Cancer Research Institute Ghent, 9000 Ghent, Belgium; (V.S.); (D.C.); (Y.D.); (K.V.d.V.); (C.V.)
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25
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Boel A, Burger J, Vanhomwegen M, Beyens A, Renard M, Barnhoorn S, Casteleyn C, Reinhardt DP, Descamps B, Vanhove C, van der Pluijm I, Coucke P, Willaert A, Essers J, Callewaert B. Slc2a10 knock-out mice deficient in ascorbic acid synthesis recapitulate aspects of arterial tortuosity syndrome and display mitochondrial respiration defects. Hum Mol Genet 2021; 29:1476-1488. [PMID: 32307537 DOI: 10.1093/hmg/ddaa071] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2020] [Revised: 04/08/2020] [Accepted: 04/15/2020] [Indexed: 12/19/2022] Open
Abstract
Arterial tortuosity syndrome (ATS) is a recessively inherited connective tissue disorder, mainly characterized by tortuosity and aneurysm formation of the major arteries. ATS is caused by loss-of-function mutations in SLC2A10, encoding the facilitative glucose transporter GLUT10. Former studies implicated GLUT10 in the transport of dehydroascorbic acid, the oxidized form of ascorbic acid (AA). Mouse models carrying homozygous Slc2a10 missense mutations did not recapitulate the human phenotype. Since mice, in contrast to humans, are able to intracellularly synthesize AA, we generated a novel ATS mouse model, deficient for Slc2a10 as well as Gulo, which encodes for L-gulonolactone oxidase, an enzyme catalyzing the final step in AA biosynthesis in mouse. Gulo;Slc2a10 double knock-out mice showed mild phenotypic anomalies, which were absent in single knock-out controls. While Gulo;Slc2a10 double knock-out mice did not fully phenocopy human ATS, histological and immunocytochemical analysis revealed compromised extracellular matrix formation. Transforming growth factor beta signaling remained unaltered, while mitochondrial function was compromised in smooth muscle cells derived from Gulo;Slc2a10 double knock-out mice. Altogether, our data add evidence that ATS is an ascorbate compartmentalization disorder, but additional factors underlying the observed phenotype in humans remain to be determined.
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Affiliation(s)
- Annekatrien Boel
- Center for Medical Genetics Ghent, Department of Biomolecular Medicine, Ghent University, 9000 Ghent, Belgium.,Ghent-Fertility and Stem cell Team, Department for Reproductive Medicine, Ghent University Hospital, 9000 Ghent, Belgium
| | - Joyce Burger
- Department of Molecular Genetics, Erasmus University Medical Center, 3015 GD Rotterdam, The Netherlands.,Department of Clinical Genetics, Erasmus University Medical Center, 3015 GD Rotterdam, The Netherlands
| | - Marine Vanhomwegen
- Center for Medical Genetics Ghent, Department of Biomolecular Medicine, Ghent University, 9000 Ghent, Belgium
| | - Aude Beyens
- Center for Medical Genetics Ghent, Department of Biomolecular Medicine, Ghent University, 9000 Ghent, Belgium.,Department of Dermatology, Ghent University Hospital, 9000 Ghent, Belgium
| | - Marjolijn Renard
- Center for Medical Genetics Ghent, Department of Biomolecular Medicine, Ghent University, 9000 Ghent, Belgium
| | - Sander Barnhoorn
- Department of Molecular Genetics, Erasmus University Medical Center, 3015 GD Rotterdam, The Netherlands.,Department of Clinical Genetics, Erasmus University Medical Center, 3015 GD Rotterdam, The Netherlands
| | - Christophe Casteleyn
- Department of Morphology, Faculty of Veterinary Medicine, Ghent University, 9820 Merelbeke, Belgium
| | - Dieter P Reinhardt
- Department of Anatomy and Cell Biology, Faculty of Medicine, Faculty of Dentistry, McGill University, H3A 0C7 Montreal, Quebec, Canada
| | - Benedicte Descamps
- Infinity (IBiTech-MEDISIP), Department of Electronics and Information Systems, Ghent University, 9000 Ghent, Belgium
| | - Christian Vanhove
- Infinity (IBiTech-MEDISIP), Department of Electronics and Information Systems, Ghent University, 9000 Ghent, Belgium
| | - Ingrid van der Pluijm
- Department of Molecular Genetics, Erasmus University Medical Center, 3015 GD Rotterdam, The Netherlands.,Department of Clinical Genetics, Erasmus University Medical Center, 3015 GD Rotterdam, The Netherlands.,Department of Vascular Surgery, Erasmus University Medical Center, 3015 GD Rotterdam, The Netherlands
| | - Paul Coucke
- Center for Medical Genetics Ghent, Department of Biomolecular Medicine, Ghent University, 9000 Ghent, Belgium
| | - Andy Willaert
- Center for Medical Genetics Ghent, Department of Biomolecular Medicine, Ghent University, 9000 Ghent, Belgium
| | - Jeroen Essers
- Department of Molecular Genetics, Erasmus University Medical Center, 3015 GD Rotterdam, The Netherlands.,Department of Clinical Genetics, Erasmus University Medical Center, 3015 GD Rotterdam, The Netherlands.,Department of Vascular Surgery, Erasmus University Medical Center, 3015 GD Rotterdam, The Netherlands.,Department of Radiation Oncology, Erasmus University Medical Center, 3015 GD Rotterdam, The Netherlands
| | - Bert Callewaert
- Center for Medical Genetics Ghent, Department of Biomolecular Medicine, Ghent University, 9000 Ghent, Belgium
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26
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Van Hoeck J, Van de Vyver T, Harizaj A, Goetgeluk G, Merckx P, Liu J, Wels M, Sauvage F, De Keersmaecker H, Vanhove C, de Jong OG, Vader P, Dewitte H, Vandekerckhove B, Braeckmans K, De Smedt SC, Raemdonck K. Hydrogel-Induced Cell Membrane Disruptions Enable Direct Cytosolic Delivery of Membrane-Impermeable Cargo. Adv Mater 2021; 33:e2008054. [PMID: 34106486 DOI: 10.1002/adma.202008054] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/29/2020] [Revised: 03/30/2021] [Indexed: 06/12/2023]
Abstract
Intracellular delivery of membrane-impermeable cargo offers unique opportunities for biological research and the development of cell-based therapies. Despite the breadth of available intracellular delivery tools, existing protocols are often suboptimal and alternative approaches that merge delivery efficiency with both biocompatibility, as well as applicability, remain highly sought after. Here, a comprehensive platform is presented that exploits the unique property of cationic hydrogel nanoparticles to transiently disrupt the plasma membrane of cells, allowing direct cytosolic delivery of uncomplexed membrane-impermeable cargo. Using this platform, which is termed Hydrogel-enabled nanoPoration or HyPore, the delivery of fluorescein isothiocyanate (FITC)-dextran macromolecules in various cancer cell lines and primary bovine corneal epithelial cells is convincingly demonstrated. Of note, HyPore demonstrates efficient FITC-dextran delivery in primary human T cells, outperforming state-of-the-art electroporation-mediated delivery. Moreover, the HyPore platform enables cytosolic delivery of functional proteins, including a histone-binding nanobody as well as the enzymes granzyme A and Cre-recombinase. Finally, HyPore-mediated delivery of the MRI contrast agent gadobutrol in primary human T cells significantly improves their T1 -weighted MRI signal intensities compared to electroporation. Taken together, HyPore is proposed as a straightforward, highly versatile, and cost-effective technique for high-throughput, ex vivo manipulation of primary cells and cell lines.
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Affiliation(s)
- Jelter Van Hoeck
- Ghent Research Group on Nanomedicines, Laboratory of General Biochemistry and Physical Pharmacy, Faculty of Pharmaceutical Sciences, Ghent University, Ottergemsesteenweg 460, Ghent, 9000, Belgium
| | - Thijs Van de Vyver
- Ghent Research Group on Nanomedicines, Laboratory of General Biochemistry and Physical Pharmacy, Faculty of Pharmaceutical Sciences, Ghent University, Ottergemsesteenweg 460, Ghent, 9000, Belgium
| | - Aranit Harizaj
- Ghent Research Group on Nanomedicines, Laboratory of General Biochemistry and Physical Pharmacy, Faculty of Pharmaceutical Sciences, Ghent University, Ottergemsesteenweg 460, Ghent, 9000, Belgium
| | - Glenn Goetgeluk
- Department of Diagnostic Sciences, Ghent University, Corneel Heymanslaan 10, Ghent, 9000, Belgium
| | - Pieterjan Merckx
- Ghent Research Group on Nanomedicines, Laboratory of General Biochemistry and Physical Pharmacy, Faculty of Pharmaceutical Sciences, Ghent University, Ottergemsesteenweg 460, Ghent, 9000, Belgium
| | - Jing Liu
- Ghent Research Group on Nanomedicines, Laboratory of General Biochemistry and Physical Pharmacy, Faculty of Pharmaceutical Sciences, Ghent University, Ottergemsesteenweg 460, Ghent, 9000, Belgium
| | - Mike Wels
- Ghent Research Group on Nanomedicines, Laboratory of General Biochemistry and Physical Pharmacy, Faculty of Pharmaceutical Sciences, Ghent University, Ottergemsesteenweg 460, Ghent, 9000, Belgium
| | - Félix Sauvage
- Ghent Research Group on Nanomedicines, Laboratory of General Biochemistry and Physical Pharmacy, Faculty of Pharmaceutical Sciences, Ghent University, Ottergemsesteenweg 460, Ghent, 9000, Belgium
| | - Herlinde De Keersmaecker
- Ghent Research Group on Nanomedicines, Laboratory of General Biochemistry and Physical Pharmacy, Faculty of Pharmaceutical Sciences, Ghent University, Ottergemsesteenweg 460, Ghent, 9000, Belgium
- Centre for Advanced Light Microscopy, Ghent University, Ottergemsesteenweg 460, Ghent, 9000, Belgium
| | - Christian Vanhove
- Infinity Lab, Medical Imaging and Signal Processing Group-IBiTech, Faculty of Engineering and Architecture, Ghent University, Corneel Heymanslaan 10, Ghent, 9000, Belgium
| | - Olivier G de Jong
- CDL Research, Division LAB, UMC Utrecht, Faculty of Medicine, Utrecht University, Heidelberglaan 100, Utrecht, 3584 CX, The Netherlands
- Department of Pharmaceutics, Utrecht Institute for Pharmaceutical Sciences (UIPS), Faculty of Science, Utrecht University, Universiteitsweg 99, Utrecht, 3584 CG, The Netherlands
| | - Pieter Vader
- CDL Research, Division LAB, UMC Utrecht, Faculty of Medicine, Utrecht University, Heidelberglaan 100, Utrecht, 3584 CX, The Netherlands
| | - Heleen Dewitte
- Ghent Research Group on Nanomedicines, Laboratory of General Biochemistry and Physical Pharmacy, Faculty of Pharmaceutical Sciences, Ghent University, Ottergemsesteenweg 460, Ghent, 9000, Belgium
| | - Bart Vandekerckhove
- Department of Diagnostic Sciences, Ghent University, Corneel Heymanslaan 10, Ghent, 9000, Belgium
| | - Kevin Braeckmans
- Ghent Research Group on Nanomedicines, Laboratory of General Biochemistry and Physical Pharmacy, Faculty of Pharmaceutical Sciences, Ghent University, Ottergemsesteenweg 460, Ghent, 9000, Belgium
- Centre for Advanced Light Microscopy, Ghent University, Ottergemsesteenweg 460, Ghent, 9000, Belgium
| | - Stefaan C De Smedt
- Ghent Research Group on Nanomedicines, Laboratory of General Biochemistry and Physical Pharmacy, Faculty of Pharmaceutical Sciences, Ghent University, Ottergemsesteenweg 460, Ghent, 9000, Belgium
- Centre for Advanced Light Microscopy, Ghent University, Ottergemsesteenweg 460, Ghent, 9000, Belgium
| | - Koen Raemdonck
- Ghent Research Group on Nanomedicines, Laboratory of General Biochemistry and Physical Pharmacy, Faculty of Pharmaceutical Sciences, Ghent University, Ottergemsesteenweg 460, Ghent, 9000, Belgium
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27
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Debacker J, Creytens D, Brochez L, Dasseler Y, Deron P, Dhooghe N, Dochy F, Keereman V, Schelfhout V, Tomassen P, van Holen R, Vanhove C, Huvenne W. Three-dimensional margin assessment in head and neck malignancies using a submillimetric 18F-FDG PET/CT, results of an ongoing clinical trial. Oral Oncol 2021. [DOI: 10.1016/s1368-8375(21)00270-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
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Mincke J, Courtyn J, Vanhove C, Vandenberghe S, Steppe K. Guide to Plant-PET Imaging Using 11CO 2. Front Plant Sci 2021; 12:602550. [PMID: 34149742 PMCID: PMC8206809 DOI: 10.3389/fpls.2021.602550] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/03/2020] [Accepted: 05/03/2021] [Indexed: 05/12/2023]
Abstract
Due to its high sensitivity and specificity for tumor detection, positron emission tomography (PET) has become a standard and widely used molecular imaging technique. Given the popularity of PET, both clinically and preclinically, its use has been extended to study plants. However, only a limited number of research groups worldwide report PET-based studies, while we believe that this technique has much more potential and could contribute extensively to plant science. The limited application of PET may be related to the complexity of putting together methodological developments from multiple disciplines, such as radio-pharmacology, physics, mathematics and engineering, which may form an obstacle for some research groups. By means of this manuscript, we want to encourage researchers to study plants using PET. The main goal is to provide a clear description on how to design and execute PET scans, process the resulting data and fully explore its potential by quantification via compartmental modeling. The different steps that need to be taken will be discussed as well as the related challenges. Hereby, the main focus will be on, although not limited to, tracing 11CO2 to study plant carbon dynamics.
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Affiliation(s)
- Jens Mincke
- Laboratory of Plant Ecology, Department of Plants and Crops, Faculty of Bioscience Engineering, Ghent University, Ghent, Belgium
- MEDISIP - INFINITY - IBiTech, Department of Electronics and Information Systems, Faculty of Engineering and Architecture, Ghent University, Ghent, Belgium
| | - Jan Courtyn
- Medical Molecular Imaging and Therapy, Department of Radiology and Nuclear Medicine, Ghent University Hospital, Ghent, Belgium
| | - Christian Vanhove
- MEDISIP - INFINITY - IBiTech, Department of Electronics and Information Systems, Faculty of Engineering and Architecture, Ghent University, Ghent, Belgium
| | - Stefaan Vandenberghe
- MEDISIP - INFINITY - IBiTech, Department of Electronics and Information Systems, Faculty of Engineering and Architecture, Ghent University, Ghent, Belgium
| | - Kathy Steppe
- Laboratory of Plant Ecology, Department of Plants and Crops, Faculty of Bioscience Engineering, Ghent University, Ghent, Belgium
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29
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Harizaj A, Descamps B, Mangodt C, Stremersch S, Stoppa A, Balcaen L, Brans T, De Rooster H, Devriendt N, Fraire JC, Bolea-Fernandez E, De Wever O, Willaert W, Vanhaecke F, Stevens CV, De Smedt SC, Roman B, Vanhove C, Lentacker I, Braeckmans K. Cytosolic delivery of gadolinium via photoporation enables improved in vivo magnetic resonance imaging of cancer cells. Biomater Sci 2021; 9:4005-4018. [PMID: 33899850 DOI: 10.1039/d1bm00479d] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/15/2023]
Abstract
Longitudinal in vivo monitoring of transplanted cells is crucial to perform cancer research or to assess the treatment outcome of cell-based therapies. While several bio-imaging techniques can be used, magnetic resonance imaging (MRI) clearly stands out in terms of high spatial resolution and excellent soft-tissue contrast. However, MRI suffers from low sensitivity, requiring cells to be labeled with high concentrations of contrast agents. An interesting option is to label cells with clinically approved gadolinium chelates which generate a hyperintense MR signal. However, spontaneous uptake of the label via pinocytosis results in its endosomal sequestration, leading to quenching of the T1-weighted relaxation. To avoid this quenching effect, delivery of gadolinium chelates directly into the cytosol via electroporation or hypotonic cell swelling have been proposed. However, these methods are also accompanied by several drawbacks such as a high cytotoxicity, and changes in gene expression and phenotype. Here, we demonstrate that nanoparticle-sensitized laser induced photoporation forms an attractive alternative to efficiently deliver the contrast agent gadobutrol into the cytosol of both HeLa and SK-OV-3 IP1 cells. After intracellular delivery by photoporation the quenching effect is clearly avoided, leading to a strong increase in the hyperintense T1-weighted MR signal. Moreover, when compared to nucleofection as a state-of-the-art electroporation platform, photoporation has much less impact on cell viability, which is extremely important for reliable cell tracking studies. Additional experiments confirm that photoporation does not induce any change in the long-term viability or the migratory capacity of the cells. Finally, we show that gadolinium 'labeled' SK-OV-3 IP1 cells can be imaged in vivo by MRI with high soft-tissue contrast and spatial resolution, revealing indications of potential tumor invasion or angiogenesis.
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Affiliation(s)
- Aranit Harizaj
- Laboratory of General Biochemistry and Physical Pharmacy, Faculty of Pharmaceutical Science, Ghent University, Ottergemsesteenweg 460, 9000 Ghent, Belgium.
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Bolcaen J, Descamps B, Deblaere K, De Vos F, Boterberg T, Hallaert G, Van den Broecke C, Vanhove C, Goethals I. Assessment of the effect of therapy in a rat model of glioblastoma using [18F]FDG and [18F]FCho PET compared to contrast-enhanced MRI. PLoS One 2021; 16:e0248193. [PMID: 33667282 PMCID: PMC7935304 DOI: 10.1371/journal.pone.0248193] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2020] [Accepted: 02/19/2021] [Indexed: 12/31/2022] Open
Abstract
Objective We investigated the potential of [18F]fluorodeoxyglucose ([18F]FDG) and [18F]Fluoromethylcholine ([18F]FCho) PET, compared to contrast-enhanced MRI, for the early detection of treatment response in F98 glioblastoma (GB) rats. Methods When GB was confirmed on T2- and contrast-enhanced T1-weighted MRI, animals were randomized into a treatment group (n = 5) receiving MRI-guided 3D conformal arc micro-irradiation (20 Gy) with concomitant temozolomide, and a sham group (n = 5). Effect of treatment was evaluated by MRI and [18F]FDG PET on day 2, 5, 9 and 12 post-treatment and [18F]FCho PET on day 1, 6, 8 and 13 post-treatment. The metabolic tumor volume (MTV) was calculated using a semi-automatic thresholding method and the average tracer uptake within the MTV was converted to a standard uptake value (SUV). Results To detect treatment response, we found that for [18F]FDG PET (SUVmean x MTV) is superior to MTV only. Using (SUVmean x MTV), [18F]FDG PET detects treatment effect starting as soon as day 5 post-therapy, comparable to contrast-enhanced MRI. Importantly, [18F]FDG PET at delayed time intervals (240 min p.i.) was able to detect the treatment effect earlier, starting at day 2 post-irradiation. No significant differences were found at any time point for both the MTV and (SUVmean x MTV) of [18F]FCho PET. Conclusions Both MRI and particularly delayed [18F]FDG PET were able to detect early treatment responses in GB rats, whereas, in this study this was not possible using [18F]FCho PET. Further comparative studies should corroborate these results and should also include (different) amino acid PET tracers.
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Affiliation(s)
- Julie Bolcaen
- Radiation Biophysics Division, Department of Nuclear Medicine, National Research Foundation iThemba LABS, Faure, South Africa
- * E-mail:
| | - Benedicte Descamps
- Department of Electronics and Information Systems, IBiTech-MEDISIP, Ghent University, Ghent, Belgium
| | - Karel Deblaere
- Department of Radiology, Ghent University Hospital, Ghent, Belgium
| | - Filip De Vos
- Department of Radiopharmacy, Ghent University, Ghent, Belgium
| | - Tom Boterberg
- Department of Radiation Oncology, Ghent University Hospital, Ghent, Belgium
| | - Giorgio Hallaert
- Department of Neurosurgery, Ghent University Hospital, Ghent, Belgium
| | | | - Christian Vanhove
- Department of Electronics and Information Systems, IBiTech-MEDISIP, Ghent University, Ghent, Belgium
| | - Ingeborg Goethals
- Department of Nuclear Medicine, Ghent University Hospital, Ghent, Belgium
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Goossens MG, Boon P, Wadman W, Van den Haute C, Baekelandt V, Verstraete AG, Vonck K, Larsen LE, Sprengers M, Carrette E, Desloovere J, Meurs A, Delbeke J, Vanhove C, Raedt R. Long-term chemogenetic suppression of seizures in a multifocal rat model of temporal lobe epilepsy. Epilepsia 2021; 62:659-670. [PMID: 33570167 DOI: 10.1111/epi.16840] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2020] [Revised: 01/21/2021] [Accepted: 01/21/2021] [Indexed: 01/14/2023]
Abstract
OBJECTIVE One third of epilepsy patients do not become seizure-free using conventional medication. Therefore, there is a need for alternative treatments. Preclinical research using designer receptors exclusively activated by designer drugs (DREADDs) has demonstrated initial success in suppressing epileptic activity. Here, we evaluated whether long-term chemogenetic seizure suppression could be obtained in the intraperitoneal kainic acid rat model of temporal lobe epilepsy, when DREADDs were selectively expressed in excitatory hippocampal neurons. METHODS Epileptic male Sprague Dawley rats received unilateral hippocampal injections of adeno-associated viral vector encoding the inhibitory DREADD hM4D(Gi), preceded by a cell-specific promotor targeting excitatory neurons. The effect of clozapine-mediated DREADD activation on dentate gyrus evoked potentials and spontaneous electrographic seizures was evaluated. Animals were systemically treated with single (.1 mg/kg/24 h) or repeated (.1 mg/kg/6 h) injections of clozapine. In addition, long-term continuous release of clozapine and olanzapine (2.8 mg/kg/7 days) using implantable minipumps was evaluated. All treatments were administered during the chronic epileptic phase and between 1.5 and 13.5 months after viral transduction. RESULTS In the DREADD group, dentate gyrus evoked potentials were inhibited after clozapine treatment. Only in DREADD-expressing animals, clozapine reduced seizure frequency during the first 6 h postinjection. When administered repeatedly, seizures were suppressed during the entire day. Long-term treatment with clozapine and olanzapine both resulted in significant seizure-suppressing effects for multiple days. Histological analysis revealed DREADD expression in both hippocampi and some cortical regions. However, lesions were also detected at the site of vector injection. SIGNIFICANCE This study shows that inhibition of the hippocampus using chemogenetics results in potent seizure-suppressing effects in the intraperitoneal kainic acid rat model, even 1 year after viral transduction. Despite a need for further optimization, chemogenetic neuromodulation represents a promising treatment prospect for temporal lobe epilepsy.
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Affiliation(s)
| | - Paul Boon
- 4BRAIN, Department of Head and Skin, Ghent University, Ghent, Belgium
| | - Wytse Wadman
- 4BRAIN, Department of Head and Skin, Ghent University, Ghent, Belgium
| | - Chris Van den Haute
- Laboratory for Neurobiology and Gene Therapy, Center for Molecular Medicine and Leuven Brain Institute, KU Leuven, Leuven, Belgium.,Leuven Viral Vector Core, Center for Molecular Medicine, KU Leuven, Leuven, Belgium
| | - Veerle Baekelandt
- Laboratory for Neurobiology and Gene Therapy, Center for Molecular Medicine and Leuven Brain Institute, KU Leuven, Leuven, Belgium
| | - Alain G Verstraete
- Department of Diagnostic Sciences, Ghent University, Ghent, Belgium.,Department of Laboratory Medicine, Ghent University Hospital, Ghent, Belgium
| | - Kristl Vonck
- 4BRAIN, Department of Head and Skin, Ghent University, Ghent, Belgium
| | - Lars E Larsen
- 4BRAIN, Department of Head and Skin, Ghent University, Ghent, Belgium
| | - Mathieu Sprengers
- 4BRAIN, Department of Head and Skin, Ghent University, Ghent, Belgium
| | - Evelien Carrette
- 4BRAIN, Department of Head and Skin, Ghent University, Ghent, Belgium
| | - Jana Desloovere
- 4BRAIN, Department of Head and Skin, Ghent University, Ghent, Belgium
| | - Alfred Meurs
- 4BRAIN, Department of Head and Skin, Ghent University, Ghent, Belgium
| | - Jean Delbeke
- 4BRAIN, Department of Head and Skin, Ghent University, Ghent, Belgium
| | - Christian Vanhove
- IBiTech, Department of Electronics and Information Systems, Ghent University, Ghent, Belgium
| | - Robrecht Raedt
- 4BRAIN, Department of Head and Skin, Ghent University, Ghent, Belgium
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Bridoux J, Broos K, Lecocq Q, Debie P, Martin C, Ballet S, Raes G, Neyt S, Vanhove C, Breckpot K, Devoogdt N, Caveliers V, Keyaerts M, Xavier C. Anti-human PD-L1 Nanobody for Immuno-PET Imaging: Validation of a Conjugation Strategy for Clinical Translation. Biomolecules 2020; 10:biom10101388. [PMID: 33003481 PMCID: PMC7599876 DOI: 10.3390/biom10101388] [Citation(s) in RCA: 37] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2020] [Revised: 09/25/2020] [Accepted: 09/26/2020] [Indexed: 01/01/2023] Open
Abstract
Immune checkpoints, such as programmed death-ligand 1 (PD-L1), limit T-cell function and tumor cells use this ligand to escape the anti-tumor immune response. Treatments with monoclonal antibodies blocking these checkpoints have shown long-lasting responses, but only in a subset of patients. This study aims to develop a Nanobody (Nb)-based probe in order to assess human PD-L1 (hPD-L1) expression using positron emission tomography imaging, and to compare the influence of two different radiolabeling strategies, since the Nb has a lysine in its complementarity determining region (CDR), which may impact its affinity upon functionalization. The Nb has been conjugated with the NOTA chelator site-specifically via the Sortase-A enzyme or randomly on its lysines. [68Ga]Ga-NOTA-(hPD-L1) Nbs were obtained in >95% radiochemical purity. In vivo tumor targeting studies at 1 h 20 post-injection revealed specific tumor uptake of 1.89 ± 0.40%IA/g for the site-specific conjugate, 1.77 ± 0.29%IA/g for the random conjugate, no nonspecific organ targeting, and excretion via the kidneys and bladder. Both strategies allowed for easily obtaining 68Ga-labeled hPD-L1 Nbs in high yields. The two conjugates were stable and showed excellent in vivo targeting. Moreover, we proved that the random lysine-conjugation is a valid strategy for clinical translation of the hPD-L1 Nb, despite the lysine present in the CDR.
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Affiliation(s)
- Jessica Bridoux
- Medical Imaging Department (MIMA), In Vivo Cellular and Molecular Imaging Laboratory (ICMI), Vrije Universiteit Brussel, Laarbeeklaan 103, Building K, 1090 Brussels, Belgium; (P.D.); (N.D.); (V.C.); (M.K.); (C.X.)
- Correspondence: ; Tel.: +32-2-4774991
| | - Katrijn Broos
- Department of Biomedical Sciences, Laboratory for Molecular and Cellular Therapy (LCMT), Vrije Universiteit Brussel, Laarbeeklaan 103, Building D, 1090 Brussels, Belgium; (K.B.); (Q.L.); (K.B.)
| | - Quentin Lecocq
- Department of Biomedical Sciences, Laboratory for Molecular and Cellular Therapy (LCMT), Vrije Universiteit Brussel, Laarbeeklaan 103, Building D, 1090 Brussels, Belgium; (K.B.); (Q.L.); (K.B.)
| | - Pieterjan Debie
- Medical Imaging Department (MIMA), In Vivo Cellular and Molecular Imaging Laboratory (ICMI), Vrije Universiteit Brussel, Laarbeeklaan 103, Building K, 1090 Brussels, Belgium; (P.D.); (N.D.); (V.C.); (M.K.); (C.X.)
| | - Charlotte Martin
- Research Group of Organic Chemistry (ORGC), Vrije Universiteit Brussel, Pleinlaan 2, 1050 Brussels, Belgium; (C.M.); (S.B.)
| | - Steven Ballet
- Research Group of Organic Chemistry (ORGC), Vrije Universiteit Brussel, Pleinlaan 2, 1050 Brussels, Belgium; (C.M.); (S.B.)
| | - Geert Raes
- Sciences and Bioengineering Sciences, Cellular and Molecular Immunology laboratory (CMIM), Vrije Universiteit Brussel, Pleinlaan 2, Building F, 1050 Brussels, Belgium;
- Myeloid Cell Immunology Laboratory (MCI), VIB Inflammation Research Center, Technologiepark-Zwijnaarde 71, 9052 Ghent, Belgium
| | - Sara Neyt
- MOLECUBES NV, Ottergemsesteenweg Zuid 325, 9000 Ghent, Belgium;
| | - Christian Vanhove
- IBiTech-MEDISIP, Ghent University Hospital Site, Block B, Corneel Heymanslaan 10, 9000 Ghent, Belgium;
| | - Karine Breckpot
- Department of Biomedical Sciences, Laboratory for Molecular and Cellular Therapy (LCMT), Vrije Universiteit Brussel, Laarbeeklaan 103, Building D, 1090 Brussels, Belgium; (K.B.); (Q.L.); (K.B.)
| | - Nick Devoogdt
- Medical Imaging Department (MIMA), In Vivo Cellular and Molecular Imaging Laboratory (ICMI), Vrije Universiteit Brussel, Laarbeeklaan 103, Building K, 1090 Brussels, Belgium; (P.D.); (N.D.); (V.C.); (M.K.); (C.X.)
| | - Vicky Caveliers
- Medical Imaging Department (MIMA), In Vivo Cellular and Molecular Imaging Laboratory (ICMI), Vrije Universiteit Brussel, Laarbeeklaan 103, Building K, 1090 Brussels, Belgium; (P.D.); (N.D.); (V.C.); (M.K.); (C.X.)
- Nuclear Medicine Department, UZ Brussel, Laarbeeklaan 101, 1090 Brussels, Belgium
| | - Marleen Keyaerts
- Medical Imaging Department (MIMA), In Vivo Cellular and Molecular Imaging Laboratory (ICMI), Vrije Universiteit Brussel, Laarbeeklaan 103, Building K, 1090 Brussels, Belgium; (P.D.); (N.D.); (V.C.); (M.K.); (C.X.)
- Nuclear Medicine Department, UZ Brussel, Laarbeeklaan 101, 1090 Brussels, Belgium
| | - Catarina Xavier
- Medical Imaging Department (MIMA), In Vivo Cellular and Molecular Imaging Laboratory (ICMI), Vrije Universiteit Brussel, Laarbeeklaan 103, Building K, 1090 Brussels, Belgium; (P.D.); (N.D.); (V.C.); (M.K.); (C.X.)
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Mincke J, Courtyn J, Vanhove C, Vandenberghe S, Steppe K. Studying in vivo dynamics of xylem-transported 11CO2 using positron emission tomography. Tree Physiol 2020; 40:1058-1070. [PMID: 32333788 DOI: 10.1093/treephys/tpaa048] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/10/2019] [Accepted: 04/20/2020] [Indexed: 05/26/2023]
Abstract
Respired CO2 in woody tissues can build up in the xylem and dissolve in the sap solution to be transported through the plant. From the sap, a fraction of the CO2 can either be radially diffuse to the atmosphere or be assimilated in chloroplasts present in woody tissues. These processes occur simultaneously in stems and branches, making it difficult to study their specific dynamics. Therefore, an 11C-enriched aqueous solution was administered to young branches of Populus tremula L., which were subsequently imaged by positron emission tomography (PET). This approach allows in vivo visualization of the internal movement of CO2 inside branches at high spatial and temporal resolution, and enables direct measurement of the transport speed of xylem-transported CO2 (vCO2). Through compartmental modeling of the dynamic data obtained from the PET images, we (i) quantified vCO2 and (ii) proposed a new method to assess the fate of xylem-transported 11CO2 within the branches. It was found that a fraction of 0.49 min-1 of CO2 present in the xylem was transported upwards. A fraction of 0.38 min-1 diffused radially from the sap to the surrounding parenchyma and apoplastic spaces (CO2,PA) to be assimilated by woody tissue photosynthesis. Another 0.12 min-1 of the xylem-transported CO2 diffused to the atmosphere via efflux. The remaining CO2 (i.e., 0.01 min-1) was stored as CO2,PA, representing the build-up within parenchyma and apoplastic spaces to be assimilated or directed to the atmosphere. Here, we demonstrate the outstanding potential of 11CO2-based plant-PET in combination with compartmental modeling to advance our understanding of internal CO2 movement and the respiratory physiology within woody tissues.
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Affiliation(s)
- Jens Mincke
- Laboratory of Plant Ecology, Department of Plants and Crops, Faculty of Bioscience Engineering, Ghent University, Coupure Links 653, 9000 Ghent, Belgium
- MEDISIP-INFINITY, Department of Electronics and Information Systems, Faculty of Engineering and Architecture, Ghent University, Corneel Heymanslaan 10, 9000 Ghent, Belgium
| | - Jan Courtyn
- Medical Molecular Imaging and Therapy, Department of Radiology and Nuclear Medicine, Ghent University Hospital, Corneel Heymanslaan 10, 9000 Ghent, Belgium
| | - Christian Vanhove
- MEDISIP-INFINITY, Department of Electronics and Information Systems, Faculty of Engineering and Architecture, Ghent University, Corneel Heymanslaan 10, 9000 Ghent, Belgium
| | - Stefaan Vandenberghe
- MEDISIP-INFINITY, Department of Electronics and Information Systems, Faculty of Engineering and Architecture, Ghent University, Corneel Heymanslaan 10, 9000 Ghent, Belgium
| | - Kathy Steppe
- Laboratory of Plant Ecology, Department of Plants and Crops, Faculty of Bioscience Engineering, Ghent University, Coupure Links 653, 9000 Ghent, Belgium
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Shariati M, Lollo G, Matha K, Descamps B, Vanhove C, Van de Sande L, Willaert W, Balcaen L, Vanhaecke F, Benoit JP, Ceelen W, De Smedt SC, Remaut K. Synergy between Intraperitoneal Aerosolization (PIPAC) and Cancer Nanomedicine: Cisplatin-Loaded Polyarginine-Hyaluronic Acid Nanocarriers Efficiently Eradicate Peritoneal Metastasis of Advanced Human Ovarian Cancer. ACS Appl Mater Interfaces 2020; 12:29024-29036. [PMID: 32506916 DOI: 10.1021/acsami.0c05554] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
Intra-abdominal dissemination of peritoneal nodules, a condition known as peritoneal carcinomatosis (PC), is typically diagnosed in ovarian cancer patients at the advanced stages. The current treatment of PC consists of perioperative systemic chemotherapy and cytoreductive surgery, followed by intra-abdominal flushing with solutions of chemotherapeutics such as cisplatin and oxaliplatin. In this study, we developed cisplatin-loaded polyarginine-hyaluronic acid nanoscale particles (Cis-pARG-HA NPs) with high colloidal stability, marked drug loading efficiency, unimpaired biological activity, and tumor-targeting ability. Injected Cis-pARG-HA NPs showed enhanced antitumor activity in a rat model of PC, compared to injection of the free cisplatin drug. The activity of Cis-pARG-HA NPs could even be further improved when administered by an intra-abdominal aerosol therapy, referred to as pressurized intraperitoneal aerosol chemotherapy (PIPAC). PIPAC is hypothesized to ensure a more homogeneous drug distribution together with a deeper drug penetration into peritoneal tumor nodules within the abdominal cavity. Using fluorescent pARG-HA NPs, this enhanced nanoparticle deposit on tumors could indeed be observed in regions opposite the aerosolization nozzle. Therefore, this study demonstrates that nanoparticles carrying chemotherapeutics can be synergistically combined with the PIPAC technique for IP therapy of disseminated advanced ovarian tumors, while this synergistic effect was not observed for the administration of free cisplatin.
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Affiliation(s)
- Molood Shariati
- Laboratory of General Biochemistry and Physical Pharmacy, Faculty of Pharmaceutical Sciences, Ghent University, 9000 Ghent, Belgium
- Cancer Research Institute Ghent (CRIG), 9000 Ghent, Belgium
| | - Giovanna Lollo
- Laboratoire d'Automatique, de Génie des Procédés et de Génie Pharmaceutique (LAGEPP), Univ Lyon, Université Lyon 1, CNRS, UMR5007, 43 bd du 11 Novembre 1918, F-69622 Lyon, France
| | - Kevin Matha
- Micro et Nanomédecines Translationnelles, MINT, UNIV Angers, UMR INSERM 1066, UMR CNRS 6021, Angers, France
- Département Pharmacie, CHU Angers, 4 rue Larrey, 49933 Angers cedex 9, France
| | - Benedicte Descamps
- Department of Electronics and Information Systems, Faculty of Engineering and Architecture, Ghent University, 9000 Ghent, Belgium
| | - Christian Vanhove
- Cancer Research Institute Ghent (CRIG), 9000 Ghent, Belgium
- Department of Electronics and Information Systems, Faculty of Engineering and Architecture, Ghent University, 9000 Ghent, Belgium
| | - Leen Van de Sande
- Cancer Research Institute Ghent (CRIG), 9000 Ghent, Belgium
- Department of GI Surgery, Ghent University Hospital and Laboratory for Experimental Surgery, Ghent University, Corneel Heymanslaan 10, 9000 Ghent, Belgium
| | - Wouter Willaert
- Cancer Research Institute Ghent (CRIG), 9000 Ghent, Belgium
- Department of GI Surgery, Ghent University Hospital and Laboratory for Experimental Surgery, Ghent University, Corneel Heymanslaan 10, 9000 Ghent, Belgium
| | - Lieve Balcaen
- Department of Analytical Chemistry, Atomic & Mass Spectrometry-A&MS Research Unit, Campus Sterre, Ghent University, Krijgslaan 281-S12, 9000 Ghent, Belgium
| | - Frank Vanhaecke
- Department of Analytical Chemistry, Atomic & Mass Spectrometry-A&MS Research Unit, Campus Sterre, Ghent University, Krijgslaan 281-S12, 9000 Ghent, Belgium
| | - Jean-Pierre Benoit
- Micro et Nanomédecines Translationnelles, MINT, UNIV Angers, UMR INSERM 1066, UMR CNRS 6021, Angers, France
- Département Pharmacie, CHU Angers, 4 rue Larrey, 49933 Angers cedex 9, France
| | - Wim Ceelen
- Cancer Research Institute Ghent (CRIG), 9000 Ghent, Belgium
- Department of GI Surgery, Ghent University Hospital and Laboratory for Experimental Surgery, Ghent University, Corneel Heymanslaan 10, 9000 Ghent, Belgium
| | - Stefaan C De Smedt
- Laboratory of General Biochemistry and Physical Pharmacy, Faculty of Pharmaceutical Sciences, Ghent University, 9000 Ghent, Belgium
- Cancer Research Institute Ghent (CRIG), 9000 Ghent, Belgium
| | - Katrien Remaut
- Laboratory of General Biochemistry and Physical Pharmacy, Faculty of Pharmaceutical Sciences, Ghent University, 9000 Ghent, Belgium
- Cancer Research Institute Ghent (CRIG), 9000 Ghent, Belgium
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Baguet T, Bouton J, Janssens J, Pauwelyn G, Verhoeven J, Descamps B, Van Calenbergh S, Vanhove C, De Vos F. Radiosynthesis, in vitro and preliminary biological evaluation of [ 18 F]2-amino-4-((2-((3-fluorobenzyl)oxy)benzyl)(2-((3-(fluoromethyl)benzyl)oxy)benzyl)amino)butanoic acid, a novel alanine serine cysteine transporter 2 inhibitor-based positron emission tomography tracer. J Labelled Comp Radiopharm 2020; 63:442-455. [PMID: 32472945 DOI: 10.1002/jlcr.3863] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2019] [Revised: 04/29/2020] [Accepted: 05/27/2020] [Indexed: 01/04/2023]
Abstract
The metabolic alterations in tumors make it possible to visualize the latter by means of positron emission tomography, enabling diagnosis and providing metabolic information. The alanine serine cysteine transporter-2 (ASCT-2) is the main transporter of glutamine and is upregulated in several tumors. Therefore, a good positron emission tracer targeting this transport protein would have substantial value. Hence, the aim of this study is to develop a fluorine-18-labeled version of a V-9302 analogue, one of the most potent inhibitors of ASCT-2. The precursor was labeled with fluorine-18 via a nucleophilic substitution of the corresponding benzylic bromide. The cold reference product was subjected to in vitro assays with [3 H]glutamine in a PC-3 and F98 cell line to determine the affinity for both the human and rat ASCT-2. To evaluate the tracer potential dynamic μPET, images were acquired in a mouse xenograft model for prostate cancer. The tracer could be synthesized with an overall nondecay corrected yield of 3.66 ± 1.90%. in vitro experiments show inhibitor constants Ki of 90 and 125 μM for the PC-3 and F98 cells, respectively. The experiments in the PC-3 xenograft demonstrate a low uptake in the tumor tissue. We have successfully synthesized the radiotracer [18 F]2-amino-4-((2-((3-fluorobenzyl)oxy)benzyl)(2-((3-(fluoromethyl)benzyl)oxy)benzyl)amino)butanoic acid. in vitro experiments show a good affinity for both the human and rat ASCT-2. However, the tracer suffers from poor in vivo tumor uptake in the PC-3 model. Briefly, we present the first fluorine-18-labeled derivative of compound V-9302, a promising novel ASCT-2 blocker used for inhibition of tumor growth.
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Affiliation(s)
- Tristan Baguet
- Laboratory of Radiopharmacy, Ghent University, Ghent, Belgium
| | - Jakob Bouton
- Laboratory for Medicinal Chemistry, Ghent University, Ghent, Belgium
| | - Jonas Janssens
- Laboratory for Medicinal Chemistry, Ghent University, Ghent, Belgium
| | - Glenn Pauwelyn
- Laboratory of Radiopharmacy, Ghent University, Ghent, Belgium
| | | | - Benedicte Descamps
- IBiTech-MEDISIP, Department of Electronics and Information Systems, Ghent University, Ghent, Belgium
| | | | - Christian Vanhove
- IBiTech-MEDISIP, Department of Electronics and Information Systems, Ghent University, Ghent, Belgium
| | - Filip De Vos
- Laboratory of Radiopharmacy, Ghent University, Ghent, Belgium
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Bridoux J, Neyt S, Debie P, Descamps B, Devoogdt N, Cleeren F, Bormans G, Broisat A, Caveliers V, Xavier C, Vanhove C, Hernot S. Improved Detection of Molecular Markers of Atherosclerotic Plaques Using Sub-Millimeter PET Imaging. Molecules 2020; 25:molecules25081838. [PMID: 32316285 PMCID: PMC7221983 DOI: 10.3390/molecules25081838] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2020] [Revised: 04/13/2020] [Accepted: 04/13/2020] [Indexed: 12/14/2022] Open
Abstract
Since atherosclerotic plaques are small and sparse, their non-invasive detection via PET imaging requires both highly specific radiotracers as well as imaging systems with high sensitivity and resolution. This study aimed to assess the targeting and biodistribution of a novel fluorine-18 anti-VCAM-1 Nanobody (Nb), and to investigate whether sub-millimetre resolution PET imaging could improve detectability of plaques in mice. The anti-VCAM-1 Nb functionalised with the novel restrained complexing agent (RESCA) chelator was labelled with [18F]AlF with a high radiochemical yield (>75%) and radiochemical purity (>99%). Subsequently, [18F]AlF(RESCA)-cAbVCAM1-5 was injected in ApoE-/- mice, or co-injected with excess of unlabelled Nb (control group). Mice were imaged sequentially using a cross-over design on two different commercially available PET/CT systems and finally sacrificed for ex vivo analysis. Both the PET/CT images and ex vivo data showed specific uptake of [18F]AlF(RESCA)-cAbVCAM1-5 in atherosclerotic lesions. Non-specific bone uptake was also noticeable, most probably due to in vivo defluorination. Image analysis yielded higher target-to-heart and target-to-brain ratios with the β-CUBE (MOLECUBES) PET scanner, demonstrating that preclinical detection of atherosclerotic lesions could be improved using the latest PET technology.
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Affiliation(s)
- Jessica Bridoux
- Laboratory of In Vivo Cellular and Molecular Imaging (ICMI, BEFY-MIMA), Vrije Universiteit Brussel, Laarbeeklaan 103, 1090 Brussels, Belgium; (J.B.); (P.D.); (N.D.); (V.C.); (C.X.)
| | - Sara Neyt
- Preclinical imaging, MOLECUBES NV, 9000 Ghent, Belgium;
| | - Pieterjan Debie
- Laboratory of In Vivo Cellular and Molecular Imaging (ICMI, BEFY-MIMA), Vrije Universiteit Brussel, Laarbeeklaan 103, 1090 Brussels, Belgium; (J.B.); (P.D.); (N.D.); (V.C.); (C.X.)
| | | | - Nick Devoogdt
- Laboratory of In Vivo Cellular and Molecular Imaging (ICMI, BEFY-MIMA), Vrije Universiteit Brussel, Laarbeeklaan 103, 1090 Brussels, Belgium; (J.B.); (P.D.); (N.D.); (V.C.); (C.X.)
| | - Frederik Cleeren
- Radiopharmaceutical Research, KU Leuven, 3000 Leuven, Belgium; (F.C.); (G.B.)
| | - Guy Bormans
- Radiopharmaceutical Research, KU Leuven, 3000 Leuven, Belgium; (F.C.); (G.B.)
| | - Alexis Broisat
- Radiopharmaceutiques Biocliniques, INSERM 1039, Université de Grenoble, 38400 Grenoble, France;
| | - Vicky Caveliers
- Laboratory of In Vivo Cellular and Molecular Imaging (ICMI, BEFY-MIMA), Vrije Universiteit Brussel, Laarbeeklaan 103, 1090 Brussels, Belgium; (J.B.); (P.D.); (N.D.); (V.C.); (C.X.)
- Nuclear Medicine department, UZ Brussel, 1090 Brussels, Belgium
| | - Catarina Xavier
- Laboratory of In Vivo Cellular and Molecular Imaging (ICMI, BEFY-MIMA), Vrije Universiteit Brussel, Laarbeeklaan 103, 1090 Brussels, Belgium; (J.B.); (P.D.); (N.D.); (V.C.); (C.X.)
| | - Christian Vanhove
- IBiTech-MEDISIP, Ghent University, 9000 Ghent, Belgium; (B.D.); (C.V.)
| | - Sophie Hernot
- Laboratory of In Vivo Cellular and Molecular Imaging (ICMI, BEFY-MIMA), Vrije Universiteit Brussel, Laarbeeklaan 103, 1090 Brussels, Belgium; (J.B.); (P.D.); (N.D.); (V.C.); (C.X.)
- Correspondence: ; Tel.: +32-2-477-49-91
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D'haenen H, Lezaire P, Vanhove C, Mertens J, Chavatte K, Terriere D, Bossuyt A. FC06.04 Spect imaging of 5-HT2A receptors during SSRI treatment. Eur Psychiatry 2020. [DOI: 10.1016/s0924-9338(00)94133-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/25/2022] Open
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Baguet T, Verhoeven J, Pauwelyn G, Hu J, Lambe P, De Lombaerde S, Piron S, Donche S, Descamps B, Goethals I, Vanhove C, De Vos F, Beyzavi MH. Radiosynthesis, in vitro and preliminary in vivo evaluation of the novel glutamine derived PET tracers [ 18F]fluorophenylglutamine and [ 18F]fluorobiphenylglutamine. Nucl Med Biol 2020; 86-87:20-29. [PMID: 32447069 DOI: 10.1016/j.nucmedbio.2020.03.006] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2019] [Revised: 03/13/2020] [Accepted: 03/31/2020] [Indexed: 12/13/2022]
Abstract
INTRODUCTION Glucose has been deemed the driving force of tumor growth for decades. However, research has shown that several tumors metabolically shift towards glutaminolysis. The development of radiolabeled glutamine derivatives could be a useful molecular imaging tool for visualizing these tumors. We elaborated on the glutamine-derived PET tracers by developing two novel probes, namely [18F]fluorophenylglutamine and [18F]fluorobiphenylglutamine. MATERIALS AND METHODS Both tracers were labelled with fluorine-18 using our recently reported ruthenium-based direct aromatic fluorination method. Their affinity was evaluated with a [3H]glutamine inhibition experiment in a human PC-3 and a rat F98 cell line. The imaging potential of [18F]fluorophenylglutamine and [18F]fluorobiphenylglutamine was tested using a mouse PC-3 and a rat F98 tumor model. RESULTS The radiosynthesis of both tracers was successful with overall non-decay corrected yields of 18.46 ± 4.18% (n = 10) ([18F]fluorophenylglutamine) and 8.05 ± 3.25% (n = 5) ([18F]fluorobiphenylglutamine). In vitro inhibition experiments showed a moderate and low affinity of fluorophenylglutamine and fluorobiphenylglutamine, respectively, towards the human ASCT-2 transporter. Both compounds had a low affinity towards the rat ASCT-2 transporter. These results were endorsed by the in vivo experiments with low uptake of both tracers in the F98 rat xenograft, low uptake of [18F]FBPG in the mice PC-3 xenograft and a moderate uptake of [18F]FPG in the PC-3 tumors. CONCLUSION We investigated the imaging potential of two novel PET radiotracers [18F]FPG and [18F]FBPG. [18F]FPG is the first example of a glutamine radiotracer derivatized with a phenyl group which enables the exploration of further derivatization of the phenyl group to increase the affinity and imaging qualities. We hypothesize that increasing the affinity of [18F]FPG by optimizing the substituents of the arene ring can result in a high-quality glutamine-based PET radiotracer. Advances in Knowledge and Implications for patient care: We hereby report novel glutamine-based PET-tracers. These tracers are tagged on the arene group with fluorine-18, hereby preventing in vivo defluorination, which can occur with alkyl labelled tracers (e.g. (2S,4R)4-[18F]fluoroglutamine). [18F]FPG shows clear tumor uptake in vivo, has no in vivo defluorination and has a straightforward production. We believe this tracer is a good starting point for the development of a high-quality tracer which is useful for the clinical visualization of the glutamine transport.
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Affiliation(s)
- Tristan Baguet
- Laboratory of Radiopharmacy, Ghent University, Ghent, Belgium.
| | | | - Glenn Pauwelyn
- Laboratory of Radiopharmacy, Ghent University, Ghent, Belgium
| | - Jiyun Hu
- Department of Chemistry and Biochemistry, University of Arkansas, AR, USA
| | - Patricia Lambe
- Department of Chemistry and Biochemistry, University of Arkansas, AR, USA
| | | | - Sarah Piron
- Laboratory of Radiopharmacy, Ghent University, Ghent, Belgium
| | - Sam Donche
- Ghent University Hospital, Department of Nuclear Medicine, Ghent, Belgium
| | - Benedicte Descamps
- IBiTech-MEDISIP Ghent University, Department of Electronics and Information Systems, Ghent, Belgium
| | - Ingeborg Goethals
- Ghent University Hospital, Department of Nuclear Medicine, Ghent, Belgium
| | - Christian Vanhove
- IBiTech-MEDISIP Ghent University, Department of Electronics and Information Systems, Ghent, Belgium
| | - Filip De Vos
- Laboratory of Radiopharmacy, Ghent University, Ghent, Belgium
| | - M Hassan Beyzavi
- Department of Chemistry and Biochemistry, University of Arkansas, AR, USA.
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Hoorelbeke D, Decrock E, De Smet M, De Bock M, Descamps B, Van Haver V, Delvaeye T, Krysko DV, Vanhove C, Bultynck G, Leybaert L. Cx43 channels and signaling via IP 3/Ca 2+, ATP, and ROS/NO propagate radiation-induced DNA damage to non-irradiated brain microvascular endothelial cells. Cell Death Dis 2020; 11:194. [PMID: 32188841 PMCID: PMC7080808 DOI: 10.1038/s41419-020-2392-5] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2019] [Revised: 02/17/2020] [Accepted: 02/18/2020] [Indexed: 02/06/2023]
Abstract
Radiotherapeutic treatment consists of targeted application of radiation beams to a tumor but exposure of surrounding healthy tissue is inevitable. In the brain, ionizing radiation induces breakdown of the blood-brain barrier by effects on brain microvascular endothelial cells. Damage from directly irradiated cells can be transferred to surrounding non-exposed bystander cells, known as the radiation-induced bystander effect. We investigated involvement of connexin channels and paracrine signaling in radiation-induced bystander DNA damage in brain microvascular endothelial cells exposed to focused X-rays. Irradiation caused DNA damage in the directly exposed area, which propagated over several millimeters in the bystander area. DNA damage was significantly reduced by the connexin channel-targeting peptide Gap26 and the Cx43 hemichannel blocker TAT-Gap19. ATP release, dye uptake, and patch clamp experiments showed that hemichannels opened within 5 min post irradiation in both irradiated and bystander areas. Bystander signaling involved cellular Ca2+ dynamics and IP3, ATP, ROS, and NO signaling, with Ca2+, IP3, and ROS as crucial propagators of DNA damage. We conclude that bystander effects are communicated by a concerted cascade involving connexin channels, and IP3/Ca2+, ATP, ROS, and NO as major contributors of regenerative signal expansion.
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Affiliation(s)
- Delphine Hoorelbeke
- Physiology group, Department of Basic and Applied Medical Sciences, Ghent University, Ghent, Belgium
| | - Elke Decrock
- Physiology group, Department of Basic and Applied Medical Sciences, Ghent University, Ghent, Belgium
| | - Maarten De Smet
- Physiology group, Department of Basic and Applied Medical Sciences, Ghent University, Ghent, Belgium
| | - Marijke De Bock
- Physiology group, Department of Basic and Applied Medical Sciences, Ghent University, Ghent, Belgium
| | - Benedicte Descamps
- Infinity Lab, IBiTech-MEDISIP, Department of Electronics and Information Systems, Ghent University, Ghent, Belgium
| | - Valérie Van Haver
- Physiology group, Department of Basic and Applied Medical Sciences, Ghent University, Ghent, Belgium
| | - Tinneke Delvaeye
- Physiology group, Department of Basic and Applied Medical Sciences, Ghent University, Ghent, Belgium
| | - Dmitri V Krysko
- Cell Death Investigation and Therapy Laboratory, Department of Human Structure and Repair, Ghent University, Ghent, Belgium.,Department of Physiology, Sechenov First Moscow State Medical University, Moskow, Russia
| | - Christian Vanhove
- Infinity Lab, IBiTech-MEDISIP, Department of Electronics and Information Systems, Ghent University, Ghent, Belgium
| | - Geert Bultynck
- Department of Cellular and Molecular Medicine, KU Leuven, Leuven, Belgium
| | - Luc Leybaert
- Physiology group, Department of Basic and Applied Medical Sciences, Ghent University, Ghent, Belgium.
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Stouthandel MEJ, Vanhove C, Devriendt W, De Bock S, Debbaut C, Vangestel C, Van Hoof T. Biomechanical comparison of Thiel embalmed and fresh frozen nerve tissue. Anat Sci Int 2020; 95:399-407. [PMID: 32144646 DOI: 10.1007/s12565-020-00535-1] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2019] [Accepted: 02/24/2020] [Indexed: 12/13/2022]
Abstract
The aim of this study was to determine the effect of Thiel embalming on the biomechanical properties of nerve tissue, to validate the use of Thiel embalmed bodies as a reliable model system for obtaining biomechanical data to supplement neurodynamic models, for anesthesiological and neurosurgical training and for future preclinical test set-ups involving nerve tissue. Upon the arrival of a body at the anatomy department, a fresh median nerve was harvested, the harvest site was sutured and following the Thiel embalming procedure the Thiel embalmed median nerve of the opposing wrist was harvested. Micro CT was performed to establish the cross-sectional area and biomechanical tensile testing was performed to compare the Young's modulus/elasticity of fresh frozen and Thiel embalmed nerves. Thiel embalming did not cause a significant difference in elasticity when comparing Thiel embalmed and fresh frozen specimens. A correlation was found between the cross-sectional area of Thiel embalmed nerve specimens and their Young's modulus. Thiel embalming does not significantly alter the elasticity of nerve tissue compared to fresh frozen nerve tissue. Similar shapes were observed when comparing the stress/strain curves of both specimen types. This indicates that Thiel embalmed nerve tissue is a viable alternative for using fresh frozen specimens when investigating biomechanical principles/mechanisms. Some specimens showed a reversed trend in Young's modulus that could be related to slight differences in embalming outcome, so caution is advised when Thiel embalmed specimens are used to obtain raw numerical data for direct application in the clinic.
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Affiliation(s)
- Michael E J Stouthandel
- Department of Human Structure and Repair, Ghent University, Radiotherapy Park, Entrance 98, C. Heymanslaan 10, 9000, Ghent, Belgium.
| | - Christian Vanhove
- Infinity Lab, Ghent University, Building P8, C. Heymanslaan 10, 9000, Ghent, Belgium
| | - Wouter Devriendt
- Agfa Healthcare, 150 Royall Street (Second Floor), Canton, Massachusetts, 02021, USA
| | - Sander De Bock
- IBiTech-bioMMeda, Ghent University, Block B, Entrance 36, C. Heymanslaan 10, 9000, Ghent, Belgium
| | - Charlotte Debbaut
- Infinity Lab, Ghent University, Building P8, C. Heymanslaan 10, 9000, Ghent, Belgium
| | - Carl Vangestel
- Directorate Taxonomy and Phylogeny, Royal Belgian Institute of Natural Sciences, 1000, Brussels, Belgium.,Terrestrial Ecology Unit, Biology Department, Ghent University, 9000, Ghent, Belgium
| | - Tom Van Hoof
- Department of Human Structure and Repair, Ghent University, Radiotherapy Park, Entrance 98, C. Heymanslaan 10, 9000, Ghent, Belgium
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Naert T, Dimitrakopoulou D, Tulkens D, Demuynck S, Carron M, Noelanders R, Eeckhout L, Van Isterdael G, Deforce D, Vanhove C, Van Dorpe J, Creytens D, Vleminckx K. RBL1 (p107) functions as tumor suppressor in glioblastoma and small-cell pancreatic neuroendocrine carcinoma in Xenopus tropicalis. Oncogene 2020; 39:2692-2706. [PMID: 32001819 DOI: 10.1038/s41388-020-1173-z] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2019] [Revised: 01/13/2020] [Accepted: 01/20/2020] [Indexed: 11/09/2022]
Abstract
Alterations of the retinoblastoma and/or the p53 signaling network are associated with specific cancers such as high-grade astrocytoma/glioblastoma, small-cell lung cancer (SCLC), choroid plexus tumors, and small-cell pancreatic neuroendocrine carcinoma (SC-PaNEC). However, the intricate functional redundancy between RB1 and the related pocket proteins RBL1/p107 and RBL2/p130 in suppressing tumorigenesis remains poorly understood. Here we performed lineage-restricted parallel inactivation of rb1 and rbl1 by multiplex CRISPR/Cas9 genome editing in the true diploid Xenopus tropicalis to gain insight into this in vivo redundancy. We show that while rb1 inactivation is sufficient to induce choroid plexus papilloma, combined rb1 and rbl1 inactivation is required and sufficient to drive SC-PaNEC, retinoblastoma and astrocytoma. Further, using a novel Li-Fraumeni syndrome-mimicking tp53 mutant X. tropicalis line, we demonstrate increased malignancy of rb1/rbl1-mutant glioma towards glioblastoma upon concomitant inactivation of tp53. Interestingly, although clinical SC-PaNEC samples are characterized by abnormal p53 expression or localization, in the current experimental models, the tp53 status had little effect on the establishment and growth of SC-PaNEC, but may rather be essential for maintaining chromosomal stability. SCLC was only rarely observed in our experimental setup, indicating requirement of additional or alternative oncogenic insults. In conclusion, we used CRISPR/Cas9 to delineate the tumor suppressor properties of Rbl1, generating new insights in the functional redundancy within the retinoblastoma protein family in suppressing neuroendocrine pancreatic cancer and glioma/glioblastoma.
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Affiliation(s)
- Thomas Naert
- Department of Biomedical Molecular Biology, Ghent University, Ghent, Belgium
- Cancer Research Institute Ghent, Ghent, Belgium
| | - Dionysia Dimitrakopoulou
- Department of Biomedical Molecular Biology, Ghent University, Ghent, Belgium
- Cancer Research Institute Ghent, Ghent, Belgium
| | - Dieter Tulkens
- Department of Biomedical Molecular Biology, Ghent University, Ghent, Belgium
- Cancer Research Institute Ghent, Ghent, Belgium
| | - Suzan Demuynck
- Department of Biomedical Molecular Biology, Ghent University, Ghent, Belgium
| | - Marjolein Carron
- Department of Biomedical Molecular Biology, Ghent University, Ghent, Belgium
- Center for Medical Genetics, Ghent University, Ghent, Belgium
| | - Rivka Noelanders
- Department of Biomedical Molecular Biology, Ghent University, Ghent, Belgium
| | - Liza Eeckhout
- Department of Biomedical Molecular Biology, Ghent University, Ghent, Belgium
| | | | - Dieter Deforce
- Laboratory for Pharmaceutical Biotechnology, Ghent University, Ghent, Belgium
| | - Christian Vanhove
- Cancer Research Institute Ghent, Ghent, Belgium
- Infinity lab, Ghent University Hospital, Ghent, Belgium
| | - Jo Van Dorpe
- Cancer Research Institute Ghent, Ghent, Belgium
- Department of Pathology, Ghent University and Ghent University Hospital, Ghent, Belgium
| | - David Creytens
- Cancer Research Institute Ghent, Ghent, Belgium
- Department of Pathology, Ghent University and Ghent University Hospital, Ghent, Belgium
| | - Kris Vleminckx
- Department of Biomedical Molecular Biology, Ghent University, Ghent, Belgium.
- Cancer Research Institute Ghent, Ghent, Belgium.
- Center for Medical Genetics, Ghent University, Ghent, Belgium.
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Christiaen E, Goossens MG, Descamps B, Larsen LE, Boon P, Raedt R, Vanhove C. Dynamic functional connectivity and graph theory metrics in a rat model of temporal lobe epilepsy reveal a preference for brain states with a lower functional connectivity, segregation and integration. Neurobiol Dis 2020; 139:104808. [PMID: 32087287 DOI: 10.1016/j.nbd.2020.104808] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2019] [Revised: 01/21/2020] [Accepted: 02/18/2020] [Indexed: 12/14/2022] Open
Abstract
Epilepsy is a neurological disorder characterized by recurrent epileptic seizures. The involvement of abnormal functional brain networks in the development of epilepsy and its comorbidities has been demonstrated by electrophysiological and neuroimaging studies in patients with epilepsy. This longitudinal study investigated changes in dynamic functional connectivity (dFC) and network topology during the development of epilepsy using the intraperitoneal kainic acid (IPKA) rat model of temporal lobe epilepsy (TLE). Resting state functional magnetic resonance images (rsfMRI) of 20 IPKA animals and 7 healthy control animals were acquired before and 1, 3, 6, 10 and 16 weeks after status epilepticus (SE) under medetomidine anaesthesia using a 7 T MRI system. Starting from 17 weeks post-SE, hippocampal EEG was recorded to determine the mean daily seizure frequency of each animal. Dynamic FC was assessed by calculating the correlation matrices between fMRI time series of predefined regions of interest within a sliding window of 50 s using a step length of 2 s. The matrices were classified into 6 FC states, each characterized by a correlation matrix, using k-means clustering. In addition, several time-variable graph theoretical network metrics were calculated from the time-varying correlation matrices and classified into 6 states of functional network topology, each characterized by a combination of network metrics. Our results showed that FC states with a lower mean functional connectivity, lower segregation and integration occurred more often in IPKA animals compared to control animals. Functional connectivity also became less variable during epileptogenesis. In addition, average daily seizure frequency was positively correlated with percentage dwell time (i.e. how often a state occurs) in states with high mean functional connectivity, high segregation and integration, and with the number of transitions between states, while negatively correlated with percentage dwell time in states with a low mean functional connectivity, low segregation and low integration. This indicates that animals that dwell in states of higher functional connectivity, higher segregation and higher integration, and that switch more often between states, have more seizures.
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Affiliation(s)
- Emma Christiaen
- MEDISIP, Department of Electronics and Information Systems, Ghent University, Ghent, Belgium.
| | | | - Benedicte Descamps
- MEDISIP, Department of Electronics and Information Systems, Ghent University, Ghent, Belgium
| | - Lars E Larsen
- MEDISIP, Department of Electronics and Information Systems, Ghent University, Ghent, Belgium; 4Brain Team, Department of Head and Skin, Ghent University, Ghent, Belgium
| | - Paul Boon
- 4Brain Team, Department of Head and Skin, Ghent University, Ghent, Belgium
| | - Robrecht Raedt
- 4Brain Team, Department of Head and Skin, Ghent University, Ghent, Belgium
| | - Christian Vanhove
- MEDISIP, Department of Electronics and Information Systems, Ghent University, Ghent, Belgium
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Verhoeven J, Baguet T, Piron S, Pauwelyn G, Bouckaert C, Descamps B, Raedt R, Vanhove C, De Vos F, Goethals I. 2-[ 18F]FELP, a novel LAT1-specific PET tracer, for the discrimination between glioblastoma, radiation necrosis and inflammation. Nucl Med Biol 2019; 82-83:9-16. [PMID: 31841816 DOI: 10.1016/j.nucmedbio.2019.12.002] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2019] [Revised: 12/04/2019] [Accepted: 12/04/2019] [Indexed: 01/02/2023]
Abstract
INTRODUCTION Considering the need for rapid change of treatment in recurrent glioblastoma (GB), it is of utmost importance to characterize PET radiopharmaceuticals that allow early discrimination of tumor from therapy-related effects. In this study, we examined the value of 2-[18F]FELP as a LAT1 tumor-specific PET tracer in comparison with [18F]FDG and [18F]FET in a combined orthotopic rat radiation necrosis and glioblastoma model. A second experiment compared 2-[18F]FELP to [18F]FDG in a mouse glioblastoma - inflammation model. METHODS Using the small animal radiation research platform (SARRP), radiation necrosis (RN) was induced in the left frontal lobe of the rat brain. When radiation-induced changes were visible on MRI, F98 rat glioblastoma cells were stereotactically inoculated in the contralateral right frontal lobe. When tumor growth was confirmed on MRI, 2-[18F]FELP, [18F]FET and [18F]FDG PET scans were acquired on three consecutive days. In an inflammation experiment, mice were inoculated in the left thigh with U87 human glioblastoma cells. After heterotopic tumor growth was confirmed macroscopically, inflammation was induced by injection of turpentine subcutaneously in the right thigh. Subsequently, 2-[18F]FELP and [18F]FDG scans were acquired on two consecutive days. RESULTS The in vivo PET images demonstrated that 2-[18F]FELP could differentiate glioblastoma and radiation necrosis using SUVmean (p = 0.0016) and LNRmean (p = 0.009), while [18F]FET was only able to differentiate both lesions by means of the SUVmean. (p = 0.047) Delayed [18F]FDGlate PET (4 h postinjection) was also able to distinguish glioblastoma from radiation necrosis, but smaller lesion-to-normal brain ratios were observed (SUVmean: p = 0.009; LNRmean: p = 0.028). In the inflammation study, 2-[18F]FELP showed no significant uptake in the inflammation lesion when compared to the control group (SUVmean: p = 0.149; LNRmean: p = 0.083). In contrast, both conventional and delayed [18F]FDG displayed significant uptake in the turpentine-invoked lesion (SUVmean: p = 0.021; LNRmean: p = 0.021). CONCLUSION This study suggests that the 2-[18F]FELP PET is able to differentiate glioblastoma from radiation necrosis and that the 2-[18F]FELP uptake is less likely to be contaminated by the presence of inflammation than the [18F]FDG signal. ADVANCES IN KNOWLEDGE These results are clinically relevant for the differential diagnosis between tumor and radiation necrosis because radiation necrosis always contains a certain amount of inflammatory cells. Hence, 2-[18F]FELP is preferred to discriminate tumor from radiation necrosis.
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Affiliation(s)
| | - Tristan Baguet
- Laboratory for Radiopharmacy, Ghent University, Ghent, Belgium
| | - Sarah Piron
- Laboratory for Radiopharmacy, Ghent University, Ghent, Belgium
| | - Glenn Pauwelyn
- Laboratory for Radiopharmacy, Ghent University, Ghent, Belgium
| | - Charlotte Bouckaert
- Laboratory for Clinical and Experimental Neurophysiology, Neurobiology and Neuropsychology (LCEN3), Ghent University Hospital, Ghent, Belgium
| | - Benedicte Descamps
- IBiTech-MEDISIP, Department of Electronics and Information Systems, Ghent University, Ghent, Belgium
| | - Robrecht Raedt
- Laboratory for Clinical and Experimental Neurophysiology, Neurobiology and Neuropsychology (LCEN3), Ghent University Hospital, Ghent, Belgium
| | - Christian Vanhove
- IBiTech-MEDISIP, Department of Electronics and Information Systems, Ghent University, Ghent, Belgium
| | - Filip De Vos
- Laboratory for Radiopharmacy, Ghent University, Ghent, Belgium
| | - Ingeborg Goethals
- Department of Nuclear Medicine, Ghent University Hospital, Ghent, Belgium
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Pauwelyn G, Vlerick L, Dockx R, Verhoeven J, Dobbeleir A, Bosmans T, Peremans K, Vanhove C, Polis I, De Vos F. Kinetic analysis of [ 18F] altanserin bolus injection in the canine brain using PET imaging. BMC Vet Res 2019; 15:415. [PMID: 31752848 PMCID: PMC6873736 DOI: 10.1186/s12917-019-2165-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2019] [Accepted: 11/06/2019] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Currently, [18F] altanserin is the most frequently used PET-radioligand for serotonin2A (5-HT2A) receptor imaging in the human brain but has never been validated in dogs. In vivo imaging of this receptor in the canine brain could improve diagnosis and therapy of several behavioural disorders in dogs. Furthermore, since dogs are considered as a valuable animal model for human psychiatric disorders, the ability to image this receptor in dogs could help to increase our understanding of the pathophysiology of these diseases. Therefore, five healthy laboratory beagles underwent a 90-min dynamic PET scan with arterial blood sampling after [18F] altanserin bolus injection. Compartmental modelling using metabolite corrected arterial input functions was compared with reference tissue modelling with the cerebellum as reference region. RESULTS The distribution of [18F] altanserin in the canine brain corresponded well to the distribution of 5-HT2A receptors in human and rodent studies. The kinetics could be best described by a 2-Tissue compartment (2-TC) model. All reference tissue models were highly correlated with the 2-TC model, indicating compartmental modelling can be replaced by reference tissue models to avoid arterial blood sampling. CONCLUSIONS This study demonstrates that [18F] altanserin PET is a reliable tool to visualize and quantify the 5-HT2A receptor in the canine brain.
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Affiliation(s)
- Glenn Pauwelyn
- Laboratory of Radiopharmacy, Ghent University, Ottergemsesteenweg 460, 9000, Ghent, Belgium.
| | - Lise Vlerick
- Small animal Departments, Faculty of Veterinary Medicine, Ghent University, Merelbeke, Belgium
| | - Robrecht Dockx
- Small animal Departments, Faculty of Veterinary Medicine, Ghent University, Merelbeke, Belgium.,Department of Psychiatry and Medical Psychology, Ghent University, Ghent, Belgium
| | - Jeroen Verhoeven
- Laboratory of Radiopharmacy, Ghent University, Ottergemsesteenweg 460, 9000, Ghent, Belgium
| | - Andre Dobbeleir
- Small animal Departments, Faculty of Veterinary Medicine, Ghent University, Merelbeke, Belgium.,Department of Nuclear Medicine, Ghent University Hospital, Ghent, Belgium
| | - Tim Bosmans
- Small animal Departments, Faculty of Veterinary Medicine, Ghent University, Merelbeke, Belgium
| | - Kathelijne Peremans
- Small animal Departments, Faculty of Veterinary Medicine, Ghent University, Merelbeke, Belgium
| | - Christian Vanhove
- Institute Biomedical Technology - Medisip - Infinity, Ghent University, Ghent, Belgium
| | - Ingeborgh Polis
- Small animal Departments, Faculty of Veterinary Medicine, Ghent University, Merelbeke, Belgium
| | - Filip De Vos
- Laboratory of Radiopharmacy, Ghent University, Ottergemsesteenweg 460, 9000, Ghent, Belgium
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De Meulenaere V, Bonte E, Verhoeven J, Kalala Okito JP, Pieters L, Vral A, De Wever O, Leybaert L, Goethals I, Vanhove C, Descamps B, Deblaere K. Adjuvant therapeutic potential of tonabersat in the standard treatment of glioblastoma: A preclinical F98 glioblastoma rat model study. PLoS One 2019; 14:e0224130. [PMID: 31634381 PMCID: PMC6802836 DOI: 10.1371/journal.pone.0224130] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2019] [Accepted: 10/07/2019] [Indexed: 12/21/2022] Open
Abstract
Purpose Even with an optimal treatment protocol, the median survival of glioblastoma (GB) patients is only 12–15 months. Hence, there is need for novel effective therapies that improve survival outcomes. Recent evidence suggests an important role for connexin (Cx) proteins (especially Cx43) in the microenvironment of malignant glioma. Cx43-mediated gap junctional communication has been observed between tumor cells, between astrocytes and between tumor cells and astrocytes. Therefore, gap junction directed therapy using a pharmacological suppressor or modulator, such as tonabersat, could be a promising target in the treatment of GB. In this preclinical study, we evaluated the possible therapeutic potential of tonabersat in the F98 model. Procedures Female Fischer rats were inoculated with ± 25.000 F98 tumor cells in the right frontal lobe. Eight days post-inoculation contrast-enhanced T1-weighted (CE-T1w) magnetic resonance (MR) images were acquired to confirm tumor growth in the brain. After tumor confirmation, rats were randomized into a Control Group, a Connexin Modulation Group (CM), a Standard Medical Treatment Group (ST), and a Standard Medical Treatment with adjuvant Connexin Modulation Group (STCM). To evaluate therapy response, T2-weighted (T2w) and CE-T1w sequences were acquired at several time points. Tumor volume analysis was performed on CE-T1w images and statistical analysis was performed using a linear mixed model. Results Significant differences in estimated geometric mean tumor volumes were found between the ST Group and the Control Group and also between the STCM Group and the Control Group. In addition, significant differences in estimated geometric mean tumor volumes between the ST Group and the STCM Group were demonstrated. No significant differences in estimated geometric mean tumor volumes were found between the Control Group and the CM Group. Conclusion Our results demonstrate a therapeutic potential of tonabersat for the treatment of GB when used in combination with radiotherapy and temozolomide chemotherapy.
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Affiliation(s)
| | - Ellen Bonte
- Department of Radiology, Ghent University Hospital, Ghent, Belgium
| | - Jeroen Verhoeven
- Department of Pharmaceutical analysis, Ghent University, Ghent, Belgium
| | | | - Leen Pieters
- Department of Human Structure and Repair, Ghent University, Ghent, Belgium
| | - Anne Vral
- Department of Human Structure and Repair, Ghent University, Ghent, Belgium
| | - Olivier De Wever
- Department of Experimental Cancer Research, Ghent University, Ghent, Belgium
| | - Luc Leybaert
- Department of Basic Medical Sciences, Ghent University, Ghent, Belgium
| | - Ingeborg Goethals
- Department of Nuclear Medicine, Ghent University Hospital, Ghent, Belgium
| | | | | | - Karel Deblaere
- Department of Radiology, Ghent University Hospital, Ghent, Belgium
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McDougald W, Vanhove C, Lehnert A, Lewellen B, Wright J, Mingarelli M, Corral CA, Schneider JE, Plein S, Newby DE, Welch A, Miyaoka R, Vandenberghe S, Tavares AAS. Standardization of Preclinical PET/CT Imaging to Improve Quantitative Accuracy, Precision, and Reproducibility: A Multicenter Study. J Nucl Med 2019; 61:461-468. [PMID: 31562220 PMCID: PMC7067528 DOI: 10.2967/jnumed.119.231308] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2019] [Accepted: 08/19/2019] [Indexed: 12/12/2022] Open
Abstract
Preclinical PET/CT is a well-established noninvasive imaging tool for studying disease development/progression and the development of novel radiotracers and pharmaceuticals for clinical applications. Despite this pivotal role, standardization of preclinical PET/CT protocols, including CT absorbed dose guidelines, is essentially nonexistent. This study (1) quantitatively assesses the variability of current preclinical PET/CT acquisition and reconstruction protocols routinely used across multiple centers and scanners; and (2) proposes acquisition and reconstruction PET/CT protocols for standardization of multicenter data, optimized for routine scanning in the preclinical PET/CT laboratory. Methods: Five different commercial preclinical PET/CT scanners in Europe and the United States were enrolled. Seven different PET/CT phantoms were used for evaluating biases on default/general scanner protocols, followed by developing standardized protocols. PET, CT, and absorbed dose biases were assessed. Results: Site default CT protocols were the following: greatest extracted Hounsfield units (HU) were 133 HU for water and −967 HU for air; significant differences in all tissue equivalent material (TEM) groups were measured. The average CT absorbed doses for mouse and rat were 72 mGy and 40 mGy, respectively. Standardized CT protocol were the following: greatest extracted HU were −77 HU for water and −990 HU for air; TEM precision improved with a reduction in variability for each tissue group. The average CT absorbed dose for mouse and rat decreased to 37 mGy and 24 mGy, respectively. Site default PET protocols were the following: uniformity was substandard in one scanner, recovery coefficients (RCs) were either over- or underestimated (maximum of 43%), standard uptake values (SUVs) were biased by a maximum of 44%. Standardized PET protocols were the following: scanner with substandard uniformity improved by 36%, RC variability decreased by 13% points, and SUV accuracy improved to 10%. Conclusion: Data revealed important quantitative biases in preclinical PET/CT and absorbed doses with default protocols. Standardized protocols showed improvements in measured PET/CT accuracy and precision with reduced CT absorbed dose across sites. Adhering to standardized protocols generates reproducible and consistent preclinical imaging datasets, thus augmenting translation of research findings to the clinic.
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Affiliation(s)
- Wendy McDougald
- BHF-Centre for Cardiovascular Science, College of Medicine & Veterinary Medicine, Queen's Medical Research Institute, University of Edinburgh, United Kingdom .,Edinburgh Preclinical Imaging (EPI), Edinburgh Imaging, University of Edinburgh, Edinburgh, United Kingdom
| | - Christian Vanhove
- Department of Electronics and Information Systems, MEDISIP, Ghent University, Ghent, Belgium
| | - Adrienne Lehnert
- Department of Radiology, Imaging Research Laboratory, University of Washington, Seattle, Washington
| | - Barbara Lewellen
- Department of Radiology, Imaging Research Laboratory, University of Washington, Seattle, Washington
| | - John Wright
- Leeds Institute of Cardiovascular and Metabolic Medicine, Department of Biomedical Imaging Science, LIGHT Laboratories, University of Leeds, Leeds, United Kingdom; and
| | - Marco Mingarelli
- Aberdeen Biomedical Imaging Centre, School of Medicine, Medical Sciences & Nutrition, University of Aberdeen, Aberdeen, United Kingdom
| | - Carlos Alcaide Corral
- BHF-Centre for Cardiovascular Science, College of Medicine & Veterinary Medicine, Queen's Medical Research Institute, University of Edinburgh, United Kingdom.,Edinburgh Preclinical Imaging (EPI), Edinburgh Imaging, University of Edinburgh, Edinburgh, United Kingdom
| | - Jurgen E Schneider
- Leeds Institute of Cardiovascular and Metabolic Medicine, Department of Biomedical Imaging Science, LIGHT Laboratories, University of Leeds, Leeds, United Kingdom; and
| | - Sven Plein
- Leeds Institute of Cardiovascular and Metabolic Medicine, Department of Biomedical Imaging Science, LIGHT Laboratories, University of Leeds, Leeds, United Kingdom; and
| | - David E Newby
- BHF-Centre for Cardiovascular Science, College of Medicine & Veterinary Medicine, Queen's Medical Research Institute, University of Edinburgh, United Kingdom
| | - Andy Welch
- Aberdeen Biomedical Imaging Centre, School of Medicine, Medical Sciences & Nutrition, University of Aberdeen, Aberdeen, United Kingdom
| | - Robert Miyaoka
- Department of Radiology, Imaging Research Laboratory, University of Washington, Seattle, Washington
| | - Stefaan Vandenberghe
- Department of Electronics and Information Systems, MEDISIP, Ghent University, Ghent, Belgium
| | - Adriana Alexandre S Tavares
- BHF-Centre for Cardiovascular Science, College of Medicine & Veterinary Medicine, Queen's Medical Research Institute, University of Edinburgh, United Kingdom.,Edinburgh Preclinical Imaging (EPI), Edinburgh Imaging, University of Edinburgh, Edinburgh, United Kingdom
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Braeckman K, Descamps B, Vanhove C, Caeyenberghs K. Exploratory relationships between cognitive improvements and training induced plasticity in hippocampus and cingulum in a rat model of mild traumatic brain injury: a diffusion MRI study. Brain Imaging Behav 2019; 14:2281-2294. [PMID: 31407153 DOI: 10.1007/s11682-019-00179-4] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
Abstract
Traumatic brain injury (TBI) is a major cause of long-term cognitive deficits, even in mild TBI patients. Computerized cognitive training can help alleviate complaints and improve daily life functioning of TBI patients. However, the underlying biological mechanisms of cognitive training in TBI are not fully understood. In the present study, we utilised for the first time a touchscreen cognitive training system in a rat model of mild TBI. Moreover, we wanted to examine whether the beneficial effects of a cognitive training are task-dependent and selective in their target. Specifically, we examined the effect of two training tasks, i.e. the Paired Associate Learning (PAL) task targeting spatial memory functioning and 5-Choice Continuous Performance (5-CCP) task loading on attention and inhibition control, on the microstructural organization of the hippocampus and cingulum, respectively, using diffusion tensor imaging (DTI). Our findings revealed that the two training protocols induced similar effects on the diffusion MRI metrics. Further, in the TBI groups who received training microstructural organization in the hippocampus and cingulum improved (as denoted by increases in fractional anisotropy), while a worsening (i.e., increases in mean diffusivity and radial diffusivity) was found in the TBI control group. In addition, these alterations in diffusion MRI metrics coincided with improved performance on the training tasks in the TBI groups who received training. Our findings show the potential of DTI metrics as reliable measure to evaluate cognitive training in TBI patients and to facilitate future research investigating further improvement of cognitive training targeting deficits in spatial memory and attention.
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Affiliation(s)
- Kim Braeckman
- Infinity Lab, Medical Imaging and Signal Processing Group-IBiTech, UGent, Blok B-5 (Ingang 36), Campus UZ Gent, Corneel Heymanslaan 10, 9000, Ghent, Belgium.
| | - Benedicte Descamps
- Infinity Lab, Medical Imaging and Signal Processing Group-IBiTech, UGent, Blok B-5 (Ingang 36), Campus UZ Gent, Corneel Heymanslaan 10, 9000, Ghent, Belgium
| | - Christian Vanhove
- Infinity Lab, Medical Imaging and Signal Processing Group-IBiTech, UGent, Blok B-5 (Ingang 36), Campus UZ Gent, Corneel Heymanslaan 10, 9000, Ghent, Belgium
| | - Karen Caeyenberghs
- Mary MacKillop Institute for Health Research, Australian Catholic University, 470.5.02, Level 5, Building 470, 215 Spring Street, Melbourne, VIC, 3000, Australia
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Abstract
Mild traumatic brain injury (mTBI) is the most common type of acquired brain injury. Since patients with traumatic brain injury show a tremendous variability and heterogeneity (age, gender, type of trauma, other possible pathologies, etc.), animal models play a key role in unraveling factors that are limitations in clinical research. They provide a standardized and controlled setting to investigate the biological mechanisms of injury and repair following TBI. However, not all animal models mimic the diffuse and subtle nature of mTBI effectively. For example, the commonly used controlled cortical impact (CCI) and lateral fluid percussion injury (LFPI) models make use of a craniotomy to expose the brain and induce widespread focal trauma, which are not commonly seen in mTBI. Therefore, these experimental models are not valid to mimic mTBI. Thus, an appropriate model should be used to investigate mTBI. The Marmarou weight drop model for rats induces similar microstructural alterations and cognitive impairments as seen in patients who sustain mild trauma; therefore, this model was selected for this protocol. Conventional computed tomography and magnetic resonance imaging (MRI) scans commonly show no damage following a mild injury, because mTBI induces often only subtle and diffuse injuries. With diffusion weighted MRI, it is possible to investigate microstructural properties of brain tissue, which can provide more insight into the microscopic alterations following mild trauma. Therefore, the goal of this study is to obtain quantitative information of a selected region-of-interest (i.e., hippocampus) to follow up disease progression after obtaining a mild and diffuse brain injury.
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Affiliation(s)
- Kim Braeckman
- Infinity lab, Medical Imaging and Signal Processing Group, Ghent University;
| | - Benedicte Descamps
- Infinity lab, Medical Imaging and Signal Processing Group, Ghent University
| | - Christian Vanhove
- Infinity lab, Medical Imaging and Signal Processing Group, Ghent University
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Steuperaert M, Debbaut C, Carlier C, De Wever O, Descamps B, Vanhove C, Ceelen W, Segers P. A 3D CFD model of the interstitial fluid pressure and drug distribution in heterogeneous tumor nodules during intraperitoneal chemotherapy. Drug Deliv 2019; 26:404-415. [PMID: 30929523 PMCID: PMC6450529 DOI: 10.1080/10717544.2019.1588423] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022] Open
Abstract
Although intraperitoneal chemotherapy (IPC) has evolved into an established treatment modality for patients with peritoneal metastasis (PM), drug penetration into tumor nodules remains limited. Drug transport during IPC is a complex process that depends on a large number of different parameters (e.g. drug, dose, tumor size, tumor pressure, tumor vascularization). Mathematical modeling allows for a better understanding of the processes that underlie drug transport and the relative importance of the parameters influencing it. In this work, we expanded our previously developed 3D Computational Fluid Dynamics (CFD) model of the drug mass transport in idealized tumor nodules during IP chemotherapy to include realistic tumor geometries and spatially varying vascular properties. DCE-MRI imaging made it possible to distinguish between tumorous tissues, healthy surrounding tissues and necrotic zones based on differences in the vascular properties. We found that the resulting interstitial pressure profiles within tumors were highly dependent on the irregular geometries and different zones. The tumor-specific cisplatin penetration depths ranged from 0.32 mm to 0.50 mm. In this work, we found that the positive relationship between tumor size and IFP does not longer hold in the presence of zones with different vascular properties, while we did observe a positive relationship between the percentage of viable tumor tissue and the maximal IFP. Our findings highlight the importance of incorporating both the irregular tumor geometries and different vascular zones in CFD models of IPC.
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Affiliation(s)
- Margo Steuperaert
- a Biofluid, Tissue and Solid Mechanics for Medical Applications (bioMMeda), Department of Electronics and Information Systems , Ghent University , Ghent , Belgium
| | - Charlotte Debbaut
- a Biofluid, Tissue and Solid Mechanics for Medical Applications (bioMMeda), Department of Electronics and Information Systems , Ghent University , Ghent , Belgium
| | - Charlotte Carlier
- b Departement of GI Surgery and Cancer Research Institute Ghent (CRIG) , Ghent University , Ghent , Belgium
| | - Olivier De Wever
- c Department of Human Structure and Repair , Ghent University , Ghent , Belgium
| | - Benedicte Descamps
- d Infinity (iMinds-IBiTech-MEDISIP), Department of Electronics and Information Systems , Ghent University , Ghent , Belgium
| | - Christian Vanhove
- d Infinity (iMinds-IBiTech-MEDISIP), Department of Electronics and Information Systems , Ghent University , Ghent , Belgium
| | - Wim Ceelen
- b Departement of GI Surgery and Cancer Research Institute Ghent (CRIG) , Ghent University , Ghent , Belgium
| | - Patrick Segers
- a Biofluid, Tissue and Solid Mechanics for Medical Applications (bioMMeda), Department of Electronics and Information Systems , Ghent University , Ghent , Belgium
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50
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Devoldere J, Peynshaert K, Dewitte H, Vanhove C, De Groef L, Moons L, Özcan SY, Dalkara D, De Smedt SC, Remaut K. Non-viral delivery of chemically modified mRNA to the retina: Subretinal versus intravitreal administration. J Control Release 2019; 307:315-330. [PMID: 31265881 DOI: 10.1016/j.jconrel.2019.06.042] [Citation(s) in RCA: 27] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2019] [Revised: 05/20/2019] [Accepted: 06/29/2019] [Indexed: 12/20/2022]
Abstract
mRNA therapeutics have recently experienced a new wave of interest, mainly due to the discovery that chemical modifications to mRNA's molecular structure could drastically reduce its inherent immunogenicity and perceived instability. On this basis, we aimed to explore the potential of chemically stabilized mRNA for ocular applications. More specifically, we investigated the behavior of mRNA-loaded lipid-based carriers in human retinal cells (in vitro), in bovine retinal explants (ex vivo) and in mouse retinas (in vivo). We demonstrate a clear superiority of mRNA over pDNA to induce protein expression in different retinal cell types, which was further enhanced by chemical modification of the mRNA, providing up to ~1800-fold higher reporter gene expression compared to pDNA. Moreover, transgene expression could be detected for at least 20 days after a single administration of chemically modified mRNA in vitro. We furthermore determined the localization and extent of mRNA expression depending on the administration route. After subretinal (SR) administration, mRNA expression was observed in vivo and ex vivo. By contrast, intravitreal (IVT) administration resulted in limited expression in vivo. Using ex vivo bovine explants with an intact vitreoretinal (VR) interface we could attribute this to the inner limiting membrane (ILM), which presents a large barrier for non-viral delivery of mRNA, trapping mRNA complexes at the vitreal side. When the vitreous was removed, which compromises the ILM, mRNA expression was apparent and seemed to colocalize with Müller cells or photoreceptors after respectively IVT or SR administration. Taken together, this study represents a first step towards mRNA-mediated therapy for retinal diseases.
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Affiliation(s)
- Joke Devoldere
- Ghent Research Group on Nanomedicines, Laboratory of General Biochemistry and Physical Pharmacy, Ghent University, Ottergemsesteenweg 460, 9000 Ghent, Belgium
| | - Karen Peynshaert
- Ghent Research Group on Nanomedicines, Laboratory of General Biochemistry and Physical Pharmacy, Ghent University, Ottergemsesteenweg 460, 9000 Ghent, Belgium
| | - Heleen Dewitte
- Ghent Research Group on Nanomedicines, Laboratory of General Biochemistry and Physical Pharmacy, Ghent University, Ottergemsesteenweg 460, 9000 Ghent, Belgium; Laboratory for Molecular and Cellular Therapy, Department of Biomedical Sciences, Medical School of the Vrije Universiteit Brussel (VUB), Laarbeeklaan 103, 1050 Jette, Belgium; Cancer Research Institute Ghent (CRIG), Ghent University Hospital, De Pintelaan 185, 9000 Ghent, Belgium
| | - Christian Vanhove
- Department of Respiratory Medicine, Ghent University, 9000 Ghent, Belgium
| | - Lies De Groef
- Neural Circuit Development and Regeneration Research Group, Animal Physiology and Neurobiology Section, Department of Biology, KU Leuven, Leuven, Belgium
| | - Lieve Moons
- Neural Circuit Development and Regeneration Research Group, Animal Physiology and Neurobiology Section, Department of Biology, KU Leuven, Leuven, Belgium
| | - Sinem Yilmaz Özcan
- Neurological Sciences and Psychiatry Institute; Hacettepe University, Ankara, Turkey
| | - Deniz Dalkara
- Sorbonne Université, INSERM, CNRS, Institut de la Vision, 17 rue Moreau, F-75012 Paris, France
| | - Stefaan C De Smedt
- Ghent Research Group on Nanomedicines, Laboratory of General Biochemistry and Physical Pharmacy, Ghent University, Ottergemsesteenweg 460, 9000 Ghent, Belgium; Cancer Research Institute Ghent (CRIG), Ghent University Hospital, De Pintelaan 185, 9000 Ghent, Belgium
| | - Katrien Remaut
- Ghent Research Group on Nanomedicines, Laboratory of General Biochemistry and Physical Pharmacy, Ghent University, Ottergemsesteenweg 460, 9000 Ghent, Belgium; Cancer Research Institute Ghent (CRIG), Ghent University Hospital, De Pintelaan 185, 9000 Ghent, Belgium.
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