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Sousa JM, Appel L, Engström M, Nyholm D, Ahlström H, Lubberink M. Comparison of quantitative [ 11C]PE2I brain PET studies between an integrated PET/MR and a stand-alone PET system. Phys Med 2024; 117:103185. [PMID: 38042064 DOI: 10.1016/j.ejmp.2023.103185] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/21/2023] [Revised: 11/03/2023] [Accepted: 11/20/2023] [Indexed: 12/04/2023] Open
Abstract
PET/MR systems demanded great efforts for accurate attenuation correction (AC) but differences in technology, geometry and hardware attenuation may also affect quantitative results. Dedicated PET systems using transmission-based AC are regarded as the gold standard for quantitative brain PET. The study aim was to investigate the agreement between quantitative PET outcomes from a PET/MR scanner against a stand-alone PET system. Nine patients with Parkinsonism underwent two 80-min dynamic PET scans with the dopamine transporter ligand [11C]PE2I. Images were reconstructed with resolution-matched settings using 68Ge-transmission (stand-alone PET), and zero-echo-time MR (PET/MR) scans for AC. Non-displaceable binding potential (BPND) and relative delivery (R1) were evaluated using volumes of interest and voxel-wise analysis. Correlations between systems were high (r ≥ 0.85) for both quantitative outcome parameters in all brain regions. Striatal BPND was significantly lower on PET/MR than on stand-alone PET (-7%). R1 was significantly overestimated in posterior cortical regions (9%) and underestimated in striatal (-9%) and limbic areas (-6%). The voxel-wise evaluation revealed that the MR-safe headphones caused a negative bias in both parametric BPND and R1 images. Additionally, a significant positive bias of R1 was found in the auditory cortex, most likely due to the acoustic background noise during MR imaging. The relative bias of the quantitative [11C]PE2I PET data acquired from a SIGNA PET/MR system was in the same order as the expected test-retest reproducibility of [11C]PE2I BPND and R1, compared to a stand-alone ECAT PET scanner. MR headphones and background noise are potential sources of error in functional PET/MR studies.
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Affiliation(s)
- João M Sousa
- Nuclear Medicine & PET, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden; Medical Physics, Uppsala University Hospital, Uppsala, Sweden.
| | - Lieuwe Appel
- Nuclear Medicine & PET, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden; Medical Imaging Centre, Uppsala University Hospital, Uppsala, Sweden
| | | | - Dag Nyholm
- Department of Neurology, Uppsala University Hospital, Uppsala, Sweden; Department of Medical Sciences, Neurology, Uppsala University, Uppsala, Sweden
| | - Håkan Ahlström
- Nuclear Medicine & PET, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden; Medical Imaging Centre, Uppsala University Hospital, Uppsala, Sweden; Antaros Medical AB, BioVenture Hub, Mölndal, Sweden
| | - Mark Lubberink
- Nuclear Medicine & PET, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden; Medical Physics, Uppsala University Hospital, Uppsala, Sweden
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Hamdi M, Ying C, An H, Laforest R. An automatic pipeline for PET/MRI attenuation correction validation in the brain. EJNMMI Phys 2023; 10:71. [PMID: 37962707 PMCID: PMC10645915 DOI: 10.1186/s40658-023-00590-3] [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: 04/23/2023] [Accepted: 11/06/2023] [Indexed: 11/15/2023] Open
Abstract
PURPOSE Challenges in PET/MRI quantitative accuracy for neurological uses arise from PET attenuation correction accuracy. We proposed and evaluated an automatic pipeline to assess the quantitative accuracy of four MRI-derived PET AC methods using analytically simulated PET brain lesions and ROIs as ground truth for PET activity. METHODS Our proposed pipeline, integrating a synthetic lesion insertion tool and the FreeSurfer neuroimaging framework, inserts simulated spherical and brain ROIs into PET projection space, reconstructing them via four PET MRAC techniques. Utilizing an 11-patient brain PET dataset, we compared the quantitative accuracy of four MRACs (DIXON, DIXONbone, UTE AC, and DL-DIXON) against the gold standard PET CTAC, evaluating MRAC to CTAC activity bias in spherical lesions and brain ROIs with and without background activity against original (lesion free) PET reconstructed images. RESULTS The proposed pipeline yielded accurate results for spherical lesions and brain ROIs, adhering to the MRAC to CTAC pattern of original brain PET images. Among the MRAC methods, DIXON AC exhibited the highest bias, followed by UTE, DIXONBone, and DL-DIXON showing the least. DIXON, DIXONbone, UTE, and DL-DIXON showed MRAC to CTAC biases of - 5.41%, - 1.85%, - 2.74%, and 0.08% respectively for ROIs inserted in background activity; - 7.02%, - 2.46%, - 3.56%, and - 0.05% for lesion ROIs without background; and - 6.82%, - 2.08%, - 2.29%, and 0.22% for the original brain PET images' 16 FreeSurfer brain ROIs. CONCLUSION The proposed pipeline delivers accurate results for synthetic spherical lesions and brain ROIs, with and without background activity consideration, enabling the evaluation of new attenuation correction approaches without utilizing measured PET emission data. Additionally, it offers a consistent method to generate realistic lesion ROIs, potentially applicable in assessing further PET correction techniques.
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Affiliation(s)
- Mahdjoub Hamdi
- Mallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, MO, USA.
| | - Chunwei Ying
- Mallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, MO, USA
| | - Hongyu An
- Mallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, MO, USA
- Neurology, Washington University in St. Louis, St. Louis, MO, USA
- Biomedical Engineering, Washington University in St. Louis, St. Louis, MO, USA
- Electrical and Systems Engineering, Washington University in St. Louis, St. Louis, MO, USA
| | - Richard Laforest
- Mallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, MO, USA
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Wall MB, Harding R, Zafar R, Rabiner EA, Nutt DJ, Erritzoe D. Neuroimaging in psychedelic drug development: past, present, and future. Mol Psychiatry 2023; 28:3573-3580. [PMID: 37759038 PMCID: PMC10730398 DOI: 10.1038/s41380-023-02271-0] [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] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/29/2022] [Accepted: 09/13/2023] [Indexed: 09/29/2023]
Abstract
Psychedelic therapy (PT) is an emerging paradigm with great transdiagnostic potential for treating psychiatric disorders, including depression, addiction, post-traumatic stress disorder, and potentially others. 'Classic' serotonergic psychedelics, such as psilocybin and lysergic acid diethylamide (LSD), which have a key locus of action at the 5-HT2A receptor, form the main focus of this movement, but substances including ketamine, 3,4-Methylenedioxymethamphetamine (MDMA) and ibogaine also hold promise. The modern phase of development of these treatment modalities in the early 21st century has occurred concurrently with the wider use of advanced human neuroscientific research methods; principally neuroimaging. This can potentially enable assessment of drug and therapy brain effects with greater precision and quantification than any previous novel development in psychiatric pharmacology. We outline the major trends in existing data and suggest the modern development of PT has benefitted greatly from the use of neuroimaging. Important gaps in existing knowledge are identified, namely: the relationship between acute drug effects and longer-term (clinically-relevant) effects, the precise characterisation of effects at the 5-HT2A receptor and relationships with functional/clinical effects, and the possible impact of these compounds on neuroplasticity. A road-map for future research is laid out, outlining clinical studies which will directly address these three questions, principally using combined Positron Emission Tomography (PET) and Magnetic Resonance Imaging (MRI) methods, plus other adjunct techniques. Multimodal (PET/MRI) studies using modern PET techniques such as the 5-HT2A-selective ligand [11 C]Cimbi-36 (and other ligands sensitive to neuroplasticity changes) alongside MRI measures of brain function would provide a 'molecular-functional-clinical bridge' in understanding. Such results would help to resolve some of these questions and provide a firmer foundation for the ongoing development of PT.
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Affiliation(s)
- Matthew B Wall
- Invicro, London, UK.
- Faculty of Medicine, Imperial College London, London, UK.
- Centre for Psychedelic research and Neuropsychopharmacology, Imperial College London, London, UK.
| | - Rebecca Harding
- Clinical Psychopharmacology Unit, Faculty of Brain Sciences, University College London, London, UK
| | - Rayyan Zafar
- Faculty of Medicine, Imperial College London, London, UK
- Centre for Psychedelic research and Neuropsychopharmacology, Imperial College London, London, UK
| | | | - David J Nutt
- Faculty of Medicine, Imperial College London, London, UK
- Centre for Psychedelic research and Neuropsychopharmacology, Imperial College London, London, UK
| | - David Erritzoe
- Faculty of Medicine, Imperial College London, London, UK
- Centre for Psychedelic research and Neuropsychopharmacology, Imperial College London, London, UK
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Hamdi M, Ying C, An H, Laforest R. An automatic pipeline for PET/MRI attenuation correction validation in the brain. Res Sq 2023:rs.3.rs-2842317. [PMID: 37292630 PMCID: PMC10246257 DOI: 10.21203/rs.3.rs-2842317/v1] [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] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
Purpose PET/MRI quantitative accuracy for neurological applications is challenging due to accuracy of the PET attenuation correction. In this work, we proposed and evaluated an automatic pipeline for assessing the quantitative accuracy of four different MRI = based attenuation correction (PET MRAC) approaches. Methods The proposed pipeline consists of a synthetic lesion insertion tool and the FreeSurfer neuroimaging analysis framework. The synthetic lesion insertion tool is used to insert simulated spherical, and brain regions of interest (ROI) into the PET projection space and reconstructed with four different PET MRAC techniques, while FreeSurfer is used to generate brain ROIs from T1 weighted MRI image. Using a cohort of 11 patients' brain PET dataset, the quantitative accuracy of four MRAC(s), which are: DIXON AC, DIXONbone AC, UTE AC, and Deep learning trained with DIXON AC, named DL-DIXON AC, were compared to the PET-based CT attenuation correction (PET CTAC). MRAC to CTAC activity bias in spherical lesions and brain ROIs were reconstructed with and without background activity and compared to the original PET images. Results The proposed pipeline provides accurate and consistent results for inserted spherical lesions and brain ROIs inserted with and without considering the background activity and following the same MRAC to CTAC pattern as the original brain PET images. As expected, the DIXON AC showed the highest bias; the second was for the UTE, then the DIXONBone, and the DL-DIXON with the lowest bias. For simulated ROIs inserted in the background activity, DIXON showed a -4.65% MRAC to CTAC bias, 0.06% for the DIXONbone, -1.70% for the UTE, and - 0.23% for the DL-DIXON. For lesion ROIs inserted without background activity, DIXON showed a -5.21%, -1% for the DIXONbone, -2.55% for the UTE, and - 0.52 for the DL-DIXON. For MRAC to CTAC bias calculated using the same 16 FreeSurfer brain ROIs in the original brain PET reconstructed images, a 6.87% was observed for the DIXON, -1.83% for DIXON bone, -3.01% for the UTE, and - 0.17% for the DL-DIXON. Conclusion The proposed pipeline provides accurate and consistent results for synthetic spherical lesions and brain ROIs inserted with and without considering the background activity; hence a new attenuation correction approach can be evaluated without using measured PET emission data.
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Affiliation(s)
- Mahdjoub Hamdi
- Washington University In St Louis: Washington University in St Louis
| | - Chunwei Ying
- Washington University in St Louis School of Medicine Mallinckrodt Institute of Radiology
| | - Hongyu An
- Washington University in St Louis School of Medicine Mallinckrodt Institute of Radiology
| | - Richard Laforest
- Washington University in St Louis School of Medicine Mallinckrodt Institute of Radiology
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Puig O, Henriksen OM, Andersen FL, Lindberg U, Højgaard L, Law I, Ladefoged CN. Deep-learning-based attenuation correction in dynamic [ 15O]H 2O studies using PET/MRI in healthy volunteers. J Cereb Blood Flow Metab 2021; 41:3314-3323. [PMID: 34250821 PMCID: PMC8669198 DOI: 10.1177/0271678x211029178] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Quantitative [15O]H2O positron emission tomography (PET) is the accepted reference method for regional cerebral blood flow (rCBF) quantification. To perform reliable quantitative [15O]H2O-PET studies in PET/MRI scanners, MRI-based attenuation-correction (MRAC) is required. Our aim was to compare two MRAC methods (RESOLUTE and DeepUTE) based on ultrashort echo-time with computed tomography-based reference standard AC (CTAC) in dynamic and static [15O]H2O-PET. We compared rCBF from quantitative perfusion maps and activity concentration distribution from static images between AC methods in 25 resting [15O]H2O-PET scans from 14 healthy men at whole-brain, regions of interest and voxel-wise levels. Average whole-brain CBF was 39.9 ± 6.0, 39.0 ± 5.8 and 40.0 ± 5.6 ml/100 g/min for CTAC, RESOLUTE and DeepUTE corrected studies respectively. RESOLUTE underestimated whole-brain CBF by 2.1 ± 1.50% and rCBF in all regions of interest (range -2.4%- -1%) compared to CTAC. DeepUTE showed significant rCBF overestimation only in the occipital lobe (0.6 ± 1.1%). Both MRAC methods showed excellent correlation on rCBF and activity concentration with CTAC, with slopes of linear regression lines between 0.97 and 1.01 and R2 over 0.99. In conclusion, RESOLUTE and DeepUTE provide AC information comparable to CTAC in dynamic [15O]H2O-PET but RESOLUTE is associated with a small but systematic underestimation.
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Affiliation(s)
- Oriol Puig
- Department of Clinical Physiology, Nuclear Medicine and PET, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
| | - Otto M Henriksen
- Department of Clinical Physiology, Nuclear Medicine and PET, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
| | - Flemming L Andersen
- Department of Clinical Physiology, Nuclear Medicine and PET, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
| | - Ulrich Lindberg
- Department of Clinical Physiology, Nuclear Medicine and PET, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
| | - Liselotte Højgaard
- Department of Clinical Physiology, Nuclear Medicine and PET, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
| | - Ian Law
- Department of Clinical Physiology, Nuclear Medicine and PET, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
| | - Claes N Ladefoged
- Department of Clinical Physiology, Nuclear Medicine and PET, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
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Gong K, Yang J, Larson PEZ, Behr SC, Hope TA, Seo Y, Li Q. MR-based Attenuation Correction for Brain PET Using 3D Cycle-Consistent Adversarial Network. IEEE Trans Radiat Plasma Med Sci 2021; 5:185-192. [PMID: 33778235 PMCID: PMC7993643 DOI: 10.1109/trpms.2020.3006844] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [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] [Indexed: 12/22/2022]
Abstract
Attenuation correction (AC) is important for the quantitative merits of positron emission tomography (PET). However, attenuation coefficients cannot be derived from magnetic resonance (MR) images directly for PET/MR systems. In this work, we aimed to derive continuous AC maps from Dixon MR images without the requirement of MR and computed tomography (CT) image registration. To achieve this, a 3D generative adversarial network with both discriminative and cycle-consistency loss (Cycle-GAN) was developed. The modified 3D U-net was employed as the structure of the generative networks to generate the pseudo CT/MR images. The 3D patch-based discriminative networks were used to distinguish the generated pseudo CT/MR images from the true CT/MR images. To evaluate its performance, datasets from 32 patients were used in the experiment. The Dixon segmentation and atlas methods provided by the vendor and the convolutional neural network (CNN) method which utilized registered MR and CT images were employed as the reference methods. Dice coefficients of the pseudo-CT image and the regional quantification in the reconstructed PET images were compared. Results show that the Cycle-GAN framework can generate better AC compared to the Dixon segmentation and atlas methods, and shows comparable performance compared to the CNN method.
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Affiliation(s)
- Kuang Gong
- Center for Advanced Medical Computing and Analysis, Gordon Center for Medical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114 USA
| | - Jaewon Yang
- Physics Research Laboratory, Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA 94143 USA
| | - Peder E Z Larson
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA 94143 USA
| | - Spencer C Behr
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA 94143 USA
| | - Thomas A Hope
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA 94143 USA
| | - Youngho Seo
- Physics Research Laboratory, Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA 94143 USA
| | - Quanzheng Li
- Center for Advanced Medical Computing and Analysis, Gordon Center for Medical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114 USA
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Sousa JM, Appel L, Merida I, Heckemann RA, Costes N, Engström M, Papadimitriou S, Nyholm D, Ahlström H, Hammers A, Lubberink M. Accuracy and precision of zero-echo-time, single- and multi-atlas attenuation correction for dynamic [ 11C]PE2I PET-MR brain imaging. EJNMMI Phys 2020; 7:77. [PMID: 33369700 PMCID: PMC7769756 DOI: 10.1186/s40658-020-00347-2] [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] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2020] [Accepted: 12/09/2020] [Indexed: 01/12/2023] Open
Abstract
BACKGROUND A valid photon attenuation correction (AC) method is instrumental for obtaining quantitatively correct PET images. Integrated PET/MR systems provide no direct information on attenuation, and novel methods for MR-based AC (MRAC) are still under investigation. Evaluations of various AC methods have mainly focused on static brain PET acquisitions. In this study, we determined the validity of three MRAC methods in a dynamic PET/MR study of the brain. METHODS Nine participants underwent dynamic brain PET/MR scanning using the dopamine transporter radioligand [11C]PE2I. Three MRAC methods were evaluated: single-atlas (Atlas), multi-atlas (MaxProb) and zero-echo-time (ZTE). The 68Ge-transmission data from a previous stand-alone PET scan was used as reference method. Parametric relative delivery (R1) images and binding potential (BPND) maps were generated using cerebellar grey matter as reference region. Evaluation was based on bias in MRAC maps, accuracy and precision of [11C]PE2I BPND and R1 estimates, and [11C]PE2I time-activity curves. BPND was examined for striatal regions and R1 in clusters of regions across the brain. RESULTS For BPND, ZTE-MRAC showed the highest accuracy (bias < 2%) in striatal regions. Atlas-MRAC exhibited a significant bias in caudate nucleus (- 12%) while MaxProb-MRAC revealed a substantial, non-significant bias in the putamen (9%). R1 estimates had a marginal bias for all MRAC methods (- 1.0-3.2%). MaxProb-MRAC showed the largest intersubject variability for both R1 and BPND. Standardized uptake values (SUV) of striatal regions displayed the strongest average bias for ZTE-MRAC (~ 10%), although constant over time and with the smallest intersubject variability. Atlas-MRAC had highest variation in bias over time (+10 to - 10%), followed by MaxProb-MRAC (+5 to - 5%), but MaxProb showed the lowest mean bias. For the cerebellum, MaxProb-MRAC showed the highest variability while bias was constant over time for Atlas- and ZTE-MRAC. CONCLUSIONS Both Maxprob- and ZTE-MRAC performed better than Atlas-MRAC when using a 68Ge transmission scan as reference method. Overall, ZTE-MRAC showed the highest precision and accuracy in outcome parameters of dynamic [11C]PE2I PET analysis with use of kinetic modelling.
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Affiliation(s)
- João M Sousa
- Department of Surgical Sciences, Uppsala University, Uppsala, Sweden.
| | - Lieuwe Appel
- Department of Surgical Sciences, Uppsala University, Uppsala, Sweden
- Medical Imaging Centre, Uppsala University Hospital, Uppsala, Sweden
| | | | - Rolf A Heckemann
- Department of Radiation Physics, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | | | | | | | - Dag Nyholm
- Department of Neurology, Uppsala University Hospital, Uppsala, Sweden
- Department of Neurosciences, Uppsala University, Uppsala, Sweden
| | - Håkan Ahlström
- Department of Surgical Sciences, Uppsala University, Uppsala, Sweden
- Medical Imaging Centre, Uppsala University Hospital, Uppsala, Sweden
| | - Alexander Hammers
- King's College London & Guy's and St Thomas' PET Centre, King's College, London, UK
| | - Mark Lubberink
- Department of Surgical Sciences, Uppsala University, Uppsala, Sweden
- Medical Physics, Uppsala University Hospital, Uppsala, Sweden
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Abstract
Attenuation correction has been one of the main methodological challenges in the integrated positron emission tomography and magnetic resonance imaging (PET/MRI) field. As standard transmission or computed tomography approaches are not available in integrated PET/MRI scanners, MR-based attenuation correction approaches had to be developed. Aspects that have to be considered for implementing accurate methods include the need to account for attenuation in bone tissue, normal and pathological lung and the MR hardware present in the PET field-of-view, to reduce the impact of subject motion, to minimize truncation and susceptibility artifacts, and to address issues related to the data acquisition and processing both on the PET and MRI sides. The standard MR-based attenuation correction techniques implemented by the PET/MRI equipment manufacturers and their impact on clinical and research PET data interpretation and quantification are first discussed. Next, the more advanced methods, including the latest generation deep learning-based approaches that have been proposed for further minimizing the attenuation correction related bias are described. Finally, a future perspective focused on the needed developments in the field is given.
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Affiliation(s)
- Ciprian Catana
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, United States of America
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Rischka L, Gryglewski G, Berroterán-Infante N, Rausch I, James GM, Klöbl M, Sigurdardottir H, Hartenbach M, Hahn A, Wadsak W, Mitterhauser M, Beyer T, Kasper S, Prayer D, Hacker M, Lanzenberger R. Attenuation Correction Approaches for Serotonin Transporter Quantification With PET/MRI. Front Physiol 2019; 10:1422. [PMID: 31824335 PMCID: PMC6883225 DOI: 10.3389/fphys.2019.01422] [Citation(s) in RCA: 5] [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] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2019] [Accepted: 11/04/2019] [Indexed: 12/26/2022] Open
Abstract
Background Several MR-based attenuation correction (AC) approaches were developed to conquer the challenging AC in hybrid PET/MR imaging. These AC methods are commonly evaluated on standardized uptake values or tissue concentration. However, in neurotransmitter system studies absolute quantification is more favorable due to its accuracy. Therefore, our aim was to investigate the accuracy of segmentation- and atlas-based MR AC approaches on serotonin transporter (SERT) distribution volumes and occupancy after a drug challenge. Methods 18 healthy subjects (7 male) underwent two [11C]DASB PET/MRI measurements in a double-blinded, placebo controlled, cross-over design. After 70 min the selective serotonin reuptake inhibitor (SSRI) citalopram or a placebo was infused. The parameters total and specific volume of distribution (VT, VS = BPP) and occupancy were quantified. All subjects underwent a low-dose CT scan as reference AC method. Besides the standard AC approaches DIXON and UTE, a T1-weighted structural image was recorded to estimate a pseudo-CT based on an MR/CT database (pseudoCT). Another evaluated AC approach superimposed a bone model on AC DIXON. Lastly, an approach optimizing the segmentation of UTE images was analyzed (RESOLUTE). PET emission data were reconstructed with all 6 AC methods. The accuracy of the AC approaches was evaluated on a region of interest-basis for the parameters VT, BPP, and occupancy with respect to the results of AC CT. Results Variations for VT and BPP were found with all AC methods with bias ranging from -15 to 17%. The smallest relative errors for all regions were found with AC pseudoCT (<|5%|). Although the bias between BPP SSRI and BPP placebo varied markedly with AC DIXON (<|12%|) and AC UTE (<|9%|), a high correlation to AC CT was obtained (r 2∼1). The relative difference of the occupancy for all tested AC methods was small for SERT high binding regions (<|4%|). Conclusion The high correlation might offer a rescaling from the biased parameters VT and BPP to the true values. Overall, the pseudoCT approach yielded smallest errors and the best agreement with AC CT. For SERT occupancy, all AC methods showed little bias in high binding regions, indicating that errors may cancel out in longitudinal assessments.
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Affiliation(s)
- Lucas Rischka
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - Gregor Gryglewski
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - Neydher Berroterán-Infante
- Division of Nuclear Medicine, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Ivo Rausch
- QIMP Group, Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Vienna, Austria
| | - Gregory Miles James
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - Manfred Klöbl
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - Helen Sigurdardottir
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - Markus Hartenbach
- Division of Nuclear Medicine, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Andreas Hahn
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - Wolfgang Wadsak
- Division of Nuclear Medicine, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria.,CBmed, Graz, Austria
| | - Markus Mitterhauser
- Division of Nuclear Medicine, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria.,Ludwig Boltzmann Institute Applied Diagnostics, Vienna, Austria
| | - Thomas Beyer
- QIMP Group, Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Vienna, Austria
| | - Siegfried Kasper
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - Daniela Prayer
- Division of Neuroradiology and Musculoskeletal Radiology, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Marcus Hacker
- Division of Nuclear Medicine, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Rupert Lanzenberger
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
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Cabello J, Avram M, Brandl F, Mustafa M, Scherr M, Leucht C, Leucht S, Sorg C, Ziegler SI. Impact of non-uniform attenuation correction in a dynamic [ 18F]-FDOPA brain PET/MRI study. EJNMMI Res 2019; 9:77. [PMID: 31428975 PMCID: PMC6702490 DOI: 10.1186/s13550-019-0547-0] [Citation(s) in RCA: 5] [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] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2019] [Accepted: 07/25/2019] [Indexed: 12/31/2022] Open
Abstract
Background PET (positron emission tomography) biokinetic modelling relies on accurate quantitative data. One of the main corrections required in PET imaging to obtain high quantitative accuracy is tissue attenuation correction (AC). Incorrect non-uniform PET-AC may result in local bias in the emission images, and thus in relative activity distributions and time activity curves for different regions. MRI (magnetic resonance imaging)-based AC is an active area of research in PET/MRI neuroimaging, where several groups developed in the last few years different methods to calculate accurate attenuation (μ-)maps. Some AC methods have been evaluated for different PET radioisotopes and pathologies. However, AC in PET/MRI has scantly been investigated in dynamic PET studies where the aim is to get quantitative kinetic parameters, rather than semi-quantitative parameters from static PET studies. In this work, we investigated the impact of AC accuracy in PET image absolute quantification and, more importantly, in the slope of the Patlak analysis based on the simplified reference tissue model, from a dynamic [18F]-fluorodopa (FDOPA) PET/MRI study. In the study, we considered the two AC methods provided by the vendor and an in-house AC method based on the dual ultrashort time echo MRI sequence, using as reference a multi-atlas-based AC method based on a T1-weighted MRI sequence. Results Non-uniform bias in absolute PET quantification across the brain, from − 20% near the skull to − 10% in the central region, was observed using the two vendor’s μ-maps. The AC method developed in-house showed a − 5% and 1% bias, respectively. Our study resulted in a 5–9% overestimation of the PET kinetic parameters with the vendor-provided μ-maps, while our in-house-developed AC method showed < 2% overestimation compared to the atlas-based AC method, using the cerebellar cortex as reference region. The overestimation obtained using the occipital pole as reference region resulted in a 7–10% with the vendor-provided μ-maps, while our in-house-developed AC method showed < 6% overestimation. Conclusions PET kinetic analyses based on a reference region are especially sensitive to the non-uniform bias in PET quantification from AC inaccuracies in brain PET/MRI. Depending on the position of the reference region and the bias with respect to the analysed region, kinetic analyses suffer different levels of bias. Considering bone in the μ-map can potentially result in larger errors, compared to the absence of bone, when non-uniformities in PET quantification are introduced.
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Affiliation(s)
- Jorge Cabello
- Nuklearmedizinische Klinik und Poliklinik, Klinikum rechts der Isar, Technische Universität München, Munich, Germany. .,Present Address: Siemens Healthineers Molecular Imaging, Knoxville, TN, USA.
| | - Mihai Avram
- Nuklearmedizinische Klinik und Poliklinik, Klinikum rechts der Isar, Technische Universität München, Munich, Germany.,Neuroradiology, Klinikum rechts der Isar, Technische Universität München, Munich, Germany.,Neuroimaging Center (TUM-NIC), Klinikum rechts der Isar, Technische Universität München, Munich, Germany
| | - Felix Brandl
- Neuroradiology, Klinikum rechts der Isar, Technische Universität München, Munich, Germany.,Neuroimaging Center (TUM-NIC), Klinikum rechts der Isar, Technische Universität München, Munich, Germany
| | - Mona Mustafa
- Nuklearmedizinische Klinik und Poliklinik, Klinikum rechts der Isar, Technische Universität München, Munich, Germany
| | - Martin Scherr
- Klinik und Poliklinik für Psychiatrie, Klinikum rechts der Isar, Technische Universität München, Munich, Germany.,Universitätsklinik für Psychiatrie und Psychotherapie, Paracelsus Medical University, Salzburg, Austria
| | - Claudia Leucht
- Klinik und Poliklinik für Psychiatrie, Klinikum rechts der Isar, Technische Universität München, Munich, Germany
| | - Stefan Leucht
- Klinik und Poliklinik für Psychiatrie, Klinikum rechts der Isar, Technische Universität München, Munich, Germany
| | - Christian Sorg
- Neuroradiology, Klinikum rechts der Isar, Technische Universität München, Munich, Germany.,Neuroimaging Center (TUM-NIC), Klinikum rechts der Isar, Technische Universität München, Munich, Germany.,Klinik und Poliklinik für Psychiatrie, Klinikum rechts der Isar, Technische Universität München, Munich, Germany
| | - Sibylle I Ziegler
- Nuklearmedizinische Klinik und Poliklinik, Klinikum rechts der Isar, Technische Universität München, Munich, Germany.,Klinik und Poliklinik für Nuklearmedizin, Klinikum der Universität München, Ludwig-Maximilians-Universität, Munich, Germany
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