1
|
van Dorth D, Jiang FY, Schmitz-Abecassis B, Croese RJI, Taphoorn MJB, Smits M, Koekkoek JAF, Dirven L, de Bresser J, van Osch MJP. Influence of arterial transit time delays on the differentiation between tumor progression and pseudoprogression in glioblastoma by arterial spin labeling magnetic resonance imaging. NMR Biomed 2024:e5166. [PMID: 38654579 DOI: 10.1002/nbm.5166] [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] [Received: 02/21/2023] [Revised: 03/26/2024] [Accepted: 03/28/2024] [Indexed: 04/26/2024]
Abstract
Arterial spin labeling (ASL) and dynamic susceptibility contrast (DSC) magnetic resonance imaging (MRI) have shown potential for differentiating tumor progression from pseudoprogression. For pseudocontinuous ASL with a single postlabeling delay, the presence of delayed arterial transit times (ATTs) could affect the evaluation of ASL-MRI perfusion data. In this study, the influence of ATT artifacts on the perfusion assessment and differentiation between tumor progression and pseudoprogression were studied. This study comprised 66 adult patients (mean age 60 ± 13 years; 40 males) with a histologically confirmed glioblastoma who received postoperative radio (chemo)therapy. ASL-MRI and DSC-MRI scans were acquired at 3 months postradiotherapy as part of the standard clinical routine. These scans were visually scored regarding (i) the severity of ATT artifacts (%) on the ASL-MRI scans only, scored by two neuroradiologists; (ii) perfusion of the enhancing tumor lesion; and (iii) radiological evaluation of tumor progression versus pseudoprogression by one neuroradiologist. The final outcome was based on combined clinical and radiological follow-up until 9 months postradiotherapy. ATT artifacts were identified in all patients based on the mean scores of two raters. A significant difference between the radiological evaluation of ASL-MRI and DSC-MRI was observed only for ASL images with moderate ATT severity (30%-65%). The perfusion assessment showed ASL-MRI tending more towards hyperperfusion than DSC-MRI in the case of moderate ATT artifacts. In addition, there was a significant difference between the prediction of tumor progression with ASL-MRI and the final outcome in the case of severe ATT artifacts (McNemar test, p = 0.041). Despite using ASL imaging parameters close to the recommended settings, ATT artifacts frequently occur in patients with treated brain tumors. Those artifacts could hinder the radiological evaluation of ASL-MRI data and the detection of true disease progression, potentially affecting treatment decisions for patients with glioblastoma.
Collapse
Affiliation(s)
- Daniëlle van Dorth
- C. J. Gorter MRI Center, Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Feng Yan Jiang
- Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
- Department of Radiology, HagaZiekenhuis, Den Haag, The Netherlands
| | - Bárbara Schmitz-Abecassis
- C. J. Gorter MRI Center, Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
- Medical Delta, Delft, The Netherlands
| | - Robert J I Croese
- Department of Neurology, Leiden University Medical Center, Leiden, The Netherlands
- Department of Neurology, Haaglanden Medical Center, Den Haag, The Netherlands
| | - Martin J B Taphoorn
- Department of Neurology, Leiden University Medical Center, Leiden, The Netherlands
- Department of Neurology, Haaglanden Medical Center, Den Haag, The Netherlands
| | - Marion Smits
- Medical Delta, Delft, The Netherlands
- Department of Radiology and Nuclear Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
- Brain Tumor Center, Erasmus MC Cancer Institute, Rotterdam, The Netherlands
| | - Johan A F Koekkoek
- Department of Neurology, Leiden University Medical Center, Leiden, The Netherlands
- Department of Neurology, Haaglanden Medical Center, Den Haag, The Netherlands
| | - Linda Dirven
- Department of Neurology, Leiden University Medical Center, Leiden, The Netherlands
- Department of Neurology, Haaglanden Medical Center, Den Haag, The Netherlands
| | - Jeroen de Bresser
- Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Matthias J P van Osch
- C. J. Gorter MRI Center, Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
- Medical Delta, Delft, The Netherlands
| |
Collapse
|
3
|
Hafdi M, Mutsaerts HJMM, Petr J, Richard E, van Dalen JW. Atherosclerotic risk is associated with cerebral perfusion - A cross-sectional study using arterial spin labeling MRI. Neuroimage Clin 2022; 36:103142. [PMID: 35970112 PMCID: PMC9400119 DOI: 10.1016/j.nicl.2022.103142] [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: 03/28/2022] [Revised: 07/11/2022] [Accepted: 08/01/2022] [Indexed: 12/14/2022]
Abstract
BACKGROUND Arterial spin labeling (ASL) magnetic resonance imaging (MRI) may be a promising technique to evaluate the presence of cerebral atherosclerosis. We tested whether the new and easily calculated ASL MRI parameter for vascular and tissue signal distribution - 'spatial coefficient of variation' (ASL-sCoV) - is a better radiological marker for atherosclerotic risk than the more conventional markers of white matter hyperintensity (WMH) volume and cerebral blood flow (ASL-CBF). METHODS Participants of the preDIVA trial (n = 195), aged 72-80 years with systolic hypertension (>140 mmHg) underwent two MRI scans two to three years apart. WMH volume was derived from 3D FLAIR-MRI; gray matter ASL-CBF and ASL-sCoV from ASL-MRI. Atherosclerotic risk was operationalized as 10-year cardiovascular risk by the Systematic COronary Risk Evaluation Older Persons (SCORE O.P) and calculated at baseline and follow-up. Data were analyzed using linear regression. RESULTS ASL-CBF was associated with atherosclerotic risk scores at baseline (standardized-beta = -0.26, 95 %CI = -0.40 to -0.13, p < 0.001) but not at follow-up (standardized-beta = -0.14, 95 %CI = -0.33 to 0.04, p = 0.12). ASL-sCoV was associated with atherosclerotic risk scores at both time points (baseline standardized-beta = 0.23, 95 %CI = 0.10 to 0.36, p < 0.0001, follow-up standardized beta = 0.20, 95 %CI = 0.03 to 0.36, p = 0.02). WMH volume was not associated with atherosclerotic risk scores at either time-point. There were no longitudinal associations between changes in MRI parameters and baseline atherosclerotic risk scores. CONCLUSIONS Our findings suggest that ASL-sCoV correlates better with atherosclerotic risk than the more conventional markers ASL-CBF and WMH volume. Our data reaffirm that non-invasive imaging with MRI is highly informative and could provide additional information about cerebrovascular damage.
Collapse
Affiliation(s)
- Melanie Hafdi
- Department of Neurology, Amsterdam University Medical Center, Amsterdam, The Netherlands,Corresponding author at: Amsterdam University Medical Centre, Department of Neurology Location AMC, Meibergdreef 9, 1105 AZ Amsterdam, The Netherlands.
| | - Henk JMM Mutsaerts
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Center, Amsterdam, The Netherlands
| | - Jan Petr
- Helmholtz-Zentrum Dresden-Rossendorf, Institute of Radiopharmaceutical Cancer Research, Dresden, Germany
| | - Edo Richard
- Department of Public and Occupational Health, Amsterdam University Medical Center, Amsterdam, The Netherlands,Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Jan Willem van Dalen
- Department of Neurology, Amsterdam University Medical Center, Amsterdam, The Netherlands,Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands
| |
Collapse
|
5
|
van Dalen JW, Mutsaerts HJ, Petr J, Caan MW, van Charante EPM, MacIntosh BJ, van Gool WA, Nederveen AJ, Richard E. Longitudinal relation between blood pressure, antihypertensive use and cerebral blood flow, using arterial spin labelling MRI. J Cereb Blood Flow Metab 2021; 41:1756-1766. [PMID: 33325767 PMCID: PMC8217888 DOI: 10.1177/0271678x20966975] [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] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Consistent cerebral blood flow (CBF) is fundamental to brain function. Cerebral autoregulation ensures CBF stability. Chronic hypertension can lead to disrupted cerebral autoregulation in older people, potentially leading to blood pressure levels interfering with CBF. This study tested whether low BP and AHD use are associated with contemporaneous low CBF, and whether longitudinal change in BP is associated with change in CBF, using arterial spin labelling (ASL) MRI, in a prospective longitudinal cohort of 186 community-dwelling older individuals with hypertension (77 ± 3 years, 53% female), 125 (67%) of whom with 3-year follow-up. Diastolic blood pressure, systolic blood pressure, mean arterial pressure, and pulse pressure were assessed as blood pressure parameters. As additional cerebrovascular marker, we evaluated the ASL signal spatial coefficient of variation (ASL SCoV), a measure of ASL signal heterogeneity that may reflect cerebrovascular health. We found no associations between any of the blood pressure measures and concurrent CBF nor between changes in blood pressure measures and CBF over three-year follow-up. Antihypertensive use was associated with lower grey matter CBF (-5.49 ml/100 g/min, 95%CI = -10.7|-0.27, p = 0.04) and higher ASL SCoV (0.32 SD, 95%CI = 0.12|0.52, p = 0.002). These results warrant future research on the potential relations between antihypertensive use and cerebral perfusion.
Collapse
Affiliation(s)
- Jan Willem van Dalen
- Department of Neurology, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands.,Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Henri Jmm Mutsaerts
- Department of Radiology, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
| | - Jan Petr
- Institute of Radiopharmaceutical Cancer Research, Helmholtz-Zentrum Dresden-Rossendorf, Dresden, Germany
| | - Matthan Wa Caan
- Department of Biomedical Engineering and Physics, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands
| | - Eric P Moll van Charante
- Department of General Practice, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
| | - Bradley J MacIntosh
- Department of Medical Biophysics, University of Toronto, Sunnybrook Research Institute, Toronto, ON, Canada
| | - Willem A van Gool
- Department of Neurology, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
| | - Aart J Nederveen
- Department of Radiology, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
| | - Edo Richard
- Department of Neurology, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands.,Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, the Netherlands
| |
Collapse
|
7
|
Baas KPA, Petr J, Kuijer JPA, Nederveen AJ, Mutsaerts HJMM, van de Ven KCC. Effects of Acquisition Parameter Modifications and Field Strength on the Reproducibility of Brain Perfusion Measurements Using Arterial Spin-Labeling. AJNR Am J Neuroradiol 2021; 42:109-115. [PMID: 33184068 DOI: 10.3174/ajnr.a6856] [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] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2020] [Accepted: 08/17/2020] [Indexed: 12/21/2022]
Abstract
BACKGROUND AND PURPOSE Although the added diagnostic value of arterial spin-labeling is shown in various cerebral pathologies, its use in clinical practice is limited. To encourage clinical adoption of ASL, we investigated the reproducibility of CBF measurements and the effects of variations in acquisition parameters compared to the recommended ASL implementation. MATERIALS AND METHODS Thirty-four volunteers (mean age, 57.8 ± 17.0 years; range, 22-80 years) underwent two separate sessions (1.5T and 3T scanners from a single vendor) using a 15-channel head coil. Both sessions contained repeated 3D and 2D pseudocontinuous arterial spin-labeling scans using vendor-recommended acquisition parameters (recommendation paper-based), followed by three 3D pseudocontinuous arterial spin-labeling scans, two with postlabeling delays of 1600 and 2000 ms and one with increased spatial resolution. All scans were single postlabeling delay. Intrasession (identical acquisitions, scanned five minutes apart) and intersession (first 2D and 3D acquisitions of two sessions) reproducibility was examined as well as the effect of parameter variations on CBF. RESULTS Intrasession CBF reproducibility was similar across image readouts and field strengths (within-subject coefficient of variation between 4.0% and 6.7%). Intersession within-subject coefficient of variation ranged from 6.6% to 14.8%. At 3T, the 3D acquisition with a higher spatial resolution resulted in less mixing of GM and WM signal, thus decreasing the bias in GM CBF between the 2D and 3D acquisitions (ΔCBF = 2.49 mL/100g/min [P < .001]). Postlabeling delay variations caused a modest bias (ΔCBF between -3.78 [P < .001] and 2.83 [P < .001] mL/100g/min). CONCLUSIONS Arterial spin-labeling imaging is reproducible at both field strengths, and the reproducibility is not significantly correlated with age. Furthermore, 3T tolerates more acquisition parameter variations and allows more extensive optimizations so that 3D and 2D acquisitions can be compared.
Collapse
Affiliation(s)
- K P A Baas
- From the Department of Radiology and Nuclear Medicine (K.P.A.B., A.J.N.), Amsterdam University Medical Center, Academic Medical Center, University of Amsterdam, Amsterdam, the Netherlands
| | - J Petr
- Institute of Radiopharmaceutical Cancer Research (J.P.), Helmholtz-Zentrum Dresden-Rossendorf, Dresden, Germany
- Department of Biomedical Engineering (J.P., H.J.M.M.M.), Institute Hall, Rochester Institute of Technology, Rochester, New York
| | - J P A Kuijer
- Department of Radiology and Nuclear Medicine (J.P.A.K., H.J.M.M.M.), Amsterdam University Medical Center, VU University Medical Center, Amsterdam, the Netherlands
| | - A J Nederveen
- From the Department of Radiology and Nuclear Medicine (K.P.A.B., A.J.N.), Amsterdam University Medical Center, Academic Medical Center, University of Amsterdam, Amsterdam, the Netherlands
| | - H J M M Mutsaerts
- Department of Biomedical Engineering (J.P., H.J.M.M.M.), Institute Hall, Rochester Institute of Technology, Rochester, New York
- Department of Radiology and Nuclear Medicine (J.P.A.K., H.J.M.M.M.), Amsterdam University Medical Center, VU University Medical Center, Amsterdam, the Netherlands
- Department of Radiology and Nuclear Medicine (H.J.M.M.M.), University Hospital Ghent, Ghent, Belgium
| | - K C C van de Ven
- BIU MR (K.C.C.v.d.V.), Philips Healthcare, Best, the Netherlands
| |
Collapse
|
8
|
Mutsaerts HJMM, Petr J, Groot P, Vandemaele P, Ingala S, Robertson AD, Václavů L, Groote I, Kuijf H, Zelaya F, O'Daly O, Hilal S, Wink AM, Kant I, Caan MWA, Morgan C, de Bresser J, Lysvik E, Schrantee A, Bjørnebekk A, Clement P, Shirzadi Z, Kuijer JPA, Wottschel V, Anazodo UC, Pajkrt D, Richard E, Bokkers RPH, Reneman L, Masellis M, Günther M, MacIntosh BJ, Achten E, Chappell MA, van Osch MJP, Golay X, Thomas DL, De Vita E, Bjørnerud A, Nederveen A, Hendrikse J, Asllani I, Barkhof F. ExploreASL: An image processing pipeline for multi-center ASL perfusion MRI studies. Neuroimage 2020; 219:117031. [PMID: 32526385 DOI: 10.1016/j.neuroimage.2020.117031] [Citation(s) in RCA: 57] [Impact Index Per Article: 14.3] [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: 12/20/2019] [Revised: 05/29/2020] [Accepted: 06/04/2020] [Indexed: 01/01/2023] Open
Abstract
Arterial spin labeling (ASL) has undergone significant development since its inception, with a focus on improving standardization and reproducibility of its acquisition and quantification. In a community-wide effort towards robust and reproducible clinical ASL image processing, we developed the software package ExploreASL, allowing standardized analyses across centers and scanners. The procedures used in ExploreASL capitalize on published image processing advancements and address the challenges of multi-center datasets with scanner-specific processing and artifact reduction to limit patient exclusion. ExploreASL is self-contained, written in MATLAB and based on Statistical Parameter Mapping (SPM) and runs on multiple operating systems. To facilitate collaboration and data-exchange, the toolbox follows several standards and recommendations for data structure, provenance, and best analysis practice. ExploreASL was iteratively refined and tested in the analysis of >10,000 ASL scans using different pulse-sequences in a variety of clinical populations, resulting in four processing modules: Import, Structural, ASL, and Population that perform tasks, respectively, for data curation, structural and ASL image processing and quality control, and finally preparing the results for statistical analyses on both single-subject and group level. We illustrate ExploreASL processing results from three cohorts: perinatally HIV-infected children, healthy adults, and elderly at risk for neurodegenerative disease. We show the reproducibility for each cohort when processed at different centers with different operating systems and MATLAB versions, and its effects on the quantification of gray matter cerebral blood flow. ExploreASL facilitates the standardization of image processing and quality control, allowing the pooling of cohorts which may increase statistical power and discover between-group perfusion differences. Ultimately, this workflow may advance ASL for wider adoption in clinical studies, trials, and practice.
Collapse
Affiliation(s)
- Henk J M M Mutsaerts
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam University Medical Center, Location VUmc, Amsterdam, the Netherlands; Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam University Medical Centers, Location Academic Medical Center, University of Amsterdam, Amsterdam, the Netherlands; Radiology, University Medical Center Utrecht, Utrecht, the Netherlands; Kate Gleason College of Engineering, Rochester Institute of Technology, NY, USA; Ghent Institute for Functional and Metabolic Imaging (GIfMI), Ghent University, Ghent, Belgium.
| | - Jan Petr
- Kate Gleason College of Engineering, Rochester Institute of Technology, NY, USA; Helmholtz-Zentrum Dresden-Rossendorf, Institute of Radiopharmaceutical Cancer Research, Dresden, Germany
| | - Paul Groot
- Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam University Medical Centers, Location Academic Medical Center, University of Amsterdam, Amsterdam, the Netherlands
| | - Pieter Vandemaele
- Ghent Institute for Functional and Metabolic Imaging (GIfMI), Ghent University, Ghent, Belgium
| | - Silvia Ingala
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam University Medical Center, Location VUmc, Amsterdam, the Netherlands
| | - Andrew D Robertson
- Schlegel-UW Research Institute for Aging, University of Waterloo, Waterloo, Ontario, Canada
| | - Lena Václavů
- C.J. Gorter Center for High Field MRI, Department of Radiology, Leiden University Medical Center, Leiden, the Netherlands
| | - Inge Groote
- Department of Diagnostic Physics, Oslo University Hospital, Oslo, Norway
| | - Hugo Kuijf
- Image Sciences Institute, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Fernando Zelaya
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Owen O'Daly
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Saima Hilal
- Department of Pharmacology, National University of Singapore, Singapore; Memory Aging and Cognition Center, National University Health System, Singapore; Saw Swee Hock School of Public Health, National University of Singapore, Singapore
| | - Alle Meije Wink
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam University Medical Center, Location VUmc, Amsterdam, the Netherlands
| | - Ilse Kant
- Radiology, University Medical Center Utrecht, Utrecht, the Netherlands; Department of Intensive Care, University Medical Centre, Utrecht, the Netherlands
| | - Matthan W A Caan
- Department of Biomedical Engineering and Physics, Amsterdam University Medical Center, Location Academic Medical Center, Amsterdam, the Netherlands
| | - Catherine Morgan
- School of Psychology and Centre for Brain Research, University of Auckland, Auckland, New Zealand
| | - Jeroen de Bresser
- Department of Radiology, Leiden University Medical Center, Leiden, the Netherlands
| | - Elisabeth Lysvik
- Department of Diagnostic Physics, Oslo University Hospital, Oslo, Norway
| | - Anouk Schrantee
- Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam University Medical Centers, Location Academic Medical Center, University of Amsterdam, Amsterdam, the Netherlands
| | - Astrid Bjørnebekk
- The Anabolic Androgenic Steroid Research Group, National Advisory Unit on Substance Use Disorder Treatment, Oslo University Hospital, Oslo, Norway
| | - Patricia Clement
- Ghent Institute for Functional and Metabolic Imaging (GIfMI), Ghent University, Ghent, Belgium
| | - Zahra Shirzadi
- Sunnybrook Research Institute, University of Toronto, Toronto, Canada
| | - Joost P A Kuijer
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam University Medical Center, Location VUmc, Amsterdam, the Netherlands
| | - Viktor Wottschel
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam University Medical Center, Location VUmc, Amsterdam, the Netherlands
| | - Udunna C Anazodo
- Department of Medical Biophysics, University of Western Ontario, London, Canada; Imaging Division, Lawson Health Research Institute, London, Canada
| | - Dasja Pajkrt
- Department of Pediatric Infectious Diseases, Emma Children's Hospital, Amsterdam University Medical Centre, Location Academic Medical Center, Amsterdam, the Netherlands
| | - Edo Richard
- Department of Neurology, Donders Institute for Brain, Behavior and Cognition, Radboud University Medical Centre, Nijmegen, the Netherlands; Neurology, Amsterdam University Medical Center, Location Academic Medical Center, University of Amsterdam, Amsterdam, the Netherlands
| | - Reinoud P H Bokkers
- Department of Radiology, Medical Imaging Center, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands
| | - Liesbeth Reneman
- Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam University Medical Centers, Location Academic Medical Center, University of Amsterdam, Amsterdam, the Netherlands
| | - Mario Masellis
- Sunnybrook Research Institute, University of Toronto, Toronto, Canada
| | - Matthias Günther
- Fraunhofer MEVIS, Bremen, Germany; University of Bremen, Bremen, Germany; Mediri GmbH, Heidelberg, Germany
| | | | - Eric Achten
- Ghent Institute for Functional and Metabolic Imaging (GIfMI), Ghent University, Ghent, Belgium
| | - Michael A Chappell
- Institute of Biomedical Engineering, Department of Engineering Science & Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neuroscience, University of Oxford, Oxford, UK
| | - Matthias J P van Osch
- C.J. Gorter Center for High Field MRI, Department of Radiology, Leiden University Medical Center, Leiden, the Netherlands
| | - Xavier Golay
- UCL Queen Square Institute of Neurology, University College London, London, UK
| | - David L Thomas
- UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Enrico De Vita
- Department of Biomedical Engineering, School of Biomedical Engineering & Imaging Sciences, King's College London, King's Health Partners, St Thomas' Hospital, London, SE1 7EH, UK
| | - Atle Bjørnerud
- Department of Diagnostic Physics, Oslo University Hospital, Oslo, Norway; Department of Psychology, University of Oslo, Norway
| | - Aart Nederveen
- Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam University Medical Centers, Location Academic Medical Center, University of Amsterdam, Amsterdam, the Netherlands
| | - Jeroen Hendrikse
- Radiology, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Iris Asllani
- Kate Gleason College of Engineering, Rochester Institute of Technology, NY, USA; Clinical Imaging Sciences Centre, Department of Neuroscience, Brighton and Sussex Medical School, Brighton, UK
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam University Medical Center, Location VUmc, Amsterdam, the Netherlands; UCL Queen Square Institute of Neurology, University College London, London, UK; Centre for Medical Image Computing (CMIC), Faculty of Engineering Science, University College London, London, UK
| |
Collapse
|