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Jellema PEJ, Mannsdörfer LM, Visser F, De Luca A, Smit CLE, Hoving EW, van Baarsen KM, Lindner T, Mutsaerts HJMM, Dankbaar JW, Lequin MH, Wijnen JP. Improving advanced intraoperative MRI methods during pediatric neurosurgery. NMR IN BIOMEDICINE 2024; 37:e5124. [PMID: 38403798 DOI: 10.1002/nbm.5124] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/27/2023] [Revised: 01/24/2024] [Accepted: 01/25/2024] [Indexed: 02/27/2024]
Abstract
Advanced intraoperative MR images (ioMRI) acquired during the resection of pediatric brain tumors could offer additional physiological information to preserve healthy tissue. With this work, we aimed to develop a protocol for ioMRI with increased sensitivity for arterial spin labeling (ASL) and diffusion MRI (dMRI), optimized for patient positioning regularly used in the pediatric neurosurgery setting. For ethical reasons, ASL images were acquired in healthy adult subjects that were imaged in the prone and supine position. After this, the ASL cerebral blood flow (CBF) was quantified and compared between both positions. To evaluate the impact of the RF coils setups on image quality, we compared different setups (two vs. four RF coils) by looking at T1-weighted (T1w) signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR), as well as undertaking a qualitative evaluation of T1w, T2w, ASL, and dMR images. Mean ASL CBF did not differ between the surgical prone and supine positions in any of the investigated regions of interest or the whole brain. T1w SNR (gray matter: p = 0.016, 34% increase; white matter: p = 0.016, 32% increase) and CNR were higher (p = 0.016) in the four versus two RF coils setups (18.0 ± 1.8 vs. 13.9 ± 1.8). Qualitative evaluation of T1w, T2w, ASL, and dMR images resulted in acceptable to good image quality and did not differ statistically significantly between setups. Only the nonweighted diffusion image maps and corticospinal tract reconstructions yielded higher image quality and reduced susceptibility artifacts with four RF coils. Advanced ioMRI metrics were more precise with four RF coils as the standard deviation decreased. Taken together, we have investigated the practical use of advanced ioMRI during pediatric neurosurgery. We conclude that ASL CBF quantification in the surgical prone position is valid and that ASL and dMRI acquisition with two RF coils can be performed adequately for clinical use. With four versus two RF coils, the SNR of the images increases, and the sensitivity to artifacts reduces.
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Affiliation(s)
- Pien E J Jellema
- Department of Pediatric Neuro-Oncology, Princess Máxima Centre for Pediatric Oncology, Utrecht, The Netherlands
- Centre for Image Sciences, University Medical Centre Utrecht, Utrecht, The Netherlands
| | - Lilli M Mannsdörfer
- Department of Pediatric Neuro-Oncology, Princess Máxima Centre for Pediatric Oncology, Utrecht, The Netherlands
| | - Fredy Visser
- Centre for Image Sciences, University Medical Centre Utrecht, Utrecht, The Netherlands
- Philips HealthCare, Best, The Netherlands
| | - Alberto De Luca
- Centre for Image Sciences, University Medical Centre Utrecht, Utrecht, The Netherlands
- Department of Neurology, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Cynthia L E Smit
- Department of Pediatric Neuro-Oncology, Princess Máxima Centre for Pediatric Oncology, Utrecht, The Netherlands
| | - Eelco W Hoving
- Department of Pediatric Neuro-Oncology, Princess Máxima Centre for Pediatric Oncology, Utrecht, The Netherlands
- Department of Neurosurgery, University Medical Centre Utrecht, Utrecht, The Netherlands
| | - Kirsten M van Baarsen
- Department of Pediatric Neuro-Oncology, Princess Máxima Centre for Pediatric Oncology, Utrecht, The Netherlands
- Department of Neurosurgery, University Medical Centre Utrecht, Utrecht, The Netherlands
| | - Thomas Lindner
- Department of Diagnostic and Interventional Neuroradiology, University Hospital Hamburg-Eppendorf, Hamburg, Germany
| | - Henk-Jan M M Mutsaerts
- Department of Radiology and Nuclear Medicine, Amsterdam UMC Location Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, The Netherlands
| | - Jan Willem Dankbaar
- Department of Radiology, University Medical Centre Utrecht, Utrecht, The Netherlands
| | - Maarten H Lequin
- Department of Pediatric Neuro-Oncology, Princess Máxima Centre for Pediatric Oncology, Utrecht, The Netherlands
- Department of Radiology, University Medical Centre Utrecht, Utrecht, The Netherlands
| | - Jannie P Wijnen
- Centre for Image Sciences, University Medical Centre Utrecht, Utrecht, The Netherlands
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Park KY, Shimony JS, Chakrabarty S, Tanenbaum AB, Hacker CD, Donovan KM, Luckett PH, Milchenko M, Sotiras A, Marcus DS, Leuthardt EC, Snyder AZ. Optimal approaches to analyzing functional MRI data in glioma patients. J Neurosci Methods 2024; 402:110011. [PMID: 37981126 PMCID: PMC10926951 DOI: 10.1016/j.jneumeth.2023.110011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2023] [Revised: 09/18/2023] [Accepted: 11/09/2023] [Indexed: 11/21/2023]
Abstract
BACKGROUND Resting-state fMRI is increasingly used to study the effects of gliomas on the functional organization of the brain. A variety of preprocessing techniques and functional connectivity analyses are represented in the literature. However, there so far has been no systematic comparison of how alternative methods impact observed results. NEW METHOD We first surveyed current literature and identified alternative analytical approaches commonly used in the field. Following, we systematically compared alternative approaches to atlas registration, parcellation scheme, and choice of graph-theoretical measure as regards differentiating glioma patients (N = 59) from age-matched reference subjects (N = 163). RESULTS Our results suggest that non-linear, as opposed to affine registration, improves structural match to an atlas, as well as measures of functional connectivity. Functionally- as opposed to anatomically-derived parcellation schemes maximized the contrast between glioma patients and reference subjects. We also demonstrate that graph-theoretic measures strongly depend on parcellation granularity, parcellation scheme, and graph density. COMPARISON WITH EXISTING METHODS AND CONCLUSIONS Our current work primarily focuses on technical optimization of rs-fMRI analysis in glioma patients and, therefore, is fundamentally different from the bulk of papers discussing glioma-induced functional network changes. We report that the evaluation of glioma-induced alterations in the functional connectome strongly depends on analytical approaches including atlas registration, choice of parcellation scheme, and graph-theoretical measures.
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Affiliation(s)
- Ki Yun Park
- Department of Neurological Surgery, Washington University School of Medicine, St. Louis, MO 63110, USA; Medical Scientist Training Program, Washington University School of Medicine, St. Louis, MO, USA; Division of Neurotechnology, Washington University School of Medicine, St. Louis, MO 63110, USA.
| | - Joshua S Shimony
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Satrajit Chakrabarty
- Department of Electrical and Systems Engineering, Washington University, St. Louis, MO 63130, USA
| | - Aaron B Tanenbaum
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Carl D Hacker
- Department of Neurological Surgery, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Kara M Donovan
- Department of Biomedical Engineering, Washington University, St. Louis, MO 63130, USA; Division of Neurotechnology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Patrick H Luckett
- Department of Neurological Surgery, Washington University School of Medicine, St. Louis, MO 63110, USA; Division of Neurotechnology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Mikhail Milchenko
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Aristeidis Sotiras
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110, USA; Institute for Informatics, Data Science & Biostatistics, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Daniel S Marcus
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Eric C Leuthardt
- Department of Neurological Surgery, Washington University School of Medicine, St. Louis, MO 63110, USA; Department of Biomedical Engineering, Washington University, St. Louis, MO 63130, USA; Department of Mechanical Engineering and Materials Science, Washington University, St. Louis, MO 63130, USA; Center for Innovation in Neuroscience and Technology, Washington University School of Medicine, St. Louis, MO 63110, USA; Brain Laser Center, Washington University School of Medicine, St. Louis, MO 63110, USA; Division of Neurotechnology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Abraham Z Snyder
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110, USA; Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA
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Jellema PEJ, Wijnen JP, De Luca A, Mutsaerts HJMM, Obdeijn IV, van Baarsen KM, Lequin MH, Hoving EW. Advanced intraoperative MRI in pediatric brain tumor surgery. Front Physiol 2023; 14:1098959. [PMID: 37123260 PMCID: PMC10134397 DOI: 10.3389/fphys.2023.1098959] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Accepted: 03/29/2023] [Indexed: 05/02/2023] Open
Abstract
Introduction: In the pediatric brain tumor surgery setting, intraoperative MRI (ioMRI) provides "real-time" imaging, allowing for evaluation of the extent of resection and detection of complications. The use of advanced MRI sequences could potentially provide additional physiological information that may aid in the preservation of healthy brain regions. This review aims to determine the added value of advanced imaging in ioMRI for pediatric brain tumor surgery compared to conventional imaging. Methods: Our systematic literature search identified relevant articles on PubMed using keywords associated with pediatrics, ioMRI, and brain tumors. The literature search was extended using the snowball technique to gather more information on advanced MRI techniques, their technical background, their use in adult ioMRI, and their use in routine pediatric brain tumor care. Results: The available literature was sparse and demonstrated that advanced sequences were used to reconstruct fibers to prevent damage to important structures, provide information on relative cerebral blood flow or abnormal metabolites, or to indicate the onset of hemorrhage or ischemic infarcts. The explorative literature search revealed developments within each advanced MRI field, such as multi-shell diffusion MRI, arterial spin labeling, and amide-proton transfer-weighted imaging, that have been studied in adult ioMRI but have not yet been applied in pediatrics. These techniques could have the potential to provide more accurate fiber tractography, information on intraoperative cerebral perfusion, and to match gadolinium-based T1w images without using a contrast agent. Conclusion: The potential added value of advanced MRI in the intraoperative setting for pediatric brain tumors is to prevent damage to important structures, to provide additional physiological or metabolic information, or to indicate the onset of postoperative changes. Current developments within various advanced ioMRI sequences are promising with regard to providing in-depth tissue information.
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Affiliation(s)
- Pien E. J. Jellema
- Department of Pediatric Neuro-Oncology, Princess Máxima Centre for Pediatric Oncology, Utrecht, Netherlands
- Centre for Image Sciences, University Medical Centre Utrecht, Utrecht, Netherlands
- *Correspondence: Pien E. J. Jellema,
| | - Jannie P. Wijnen
- Centre for Image Sciences, University Medical Centre Utrecht, Utrecht, Netherlands
| | - Alberto De Luca
- Centre for Image Sciences, University Medical Centre Utrecht, Utrecht, Netherlands
- Department of Neurology, University Medical Center Utrecht, Utrecht, Netherlands
| | - Henk J. M. M. Mutsaerts
- Department of Radiology and Nuclear Medicine, Amsterdam UMC Location Vrije Universiteit Amsterdam, Amsterdam, Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, Netherlands
| | - Iris V. Obdeijn
- Centre for Image Sciences, University Medical Centre Utrecht, Utrecht, Netherlands
| | - Kirsten M. van Baarsen
- Department of Pediatric Neuro-Oncology, Princess Máxima Centre for Pediatric Oncology, Utrecht, Netherlands
- Department of Neurosurgery, University Medical Centre Utrecht, Utrecht, Netherlands
| | - Maarten H. Lequin
- Department of Pediatric Neuro-Oncology, Princess Máxima Centre for Pediatric Oncology, Utrecht, Netherlands
- Department of Radiology, University Medical Centre Utrecht, Utrecht, Netherlands
| | - Eelco W. Hoving
- Department of Pediatric Neuro-Oncology, Princess Máxima Centre for Pediatric Oncology, Utrecht, Netherlands
- Department of Neurosurgery, University Medical Centre Utrecht, Utrecht, Netherlands
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