1
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Fan H, Mutsaerts HJ, Anazodo U, Arteaga D, Baas KP, Buchanan C, Camargo A, Keil VC, Lin Z, Lindner T, Hirschler L, Hu J, Padrela BE, Taghvaei M, Thomas DL, Dolui S, Petr J. ISMRM Open Science Initiative for Perfusion Imaging (OSIPI): ASL pipeline inventory. Magn Reson Med 2024; 91:1787-1802. [PMID: 37811778 PMCID: PMC10950546 DOI: 10.1002/mrm.29869] [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: 03/03/2023] [Revised: 08/21/2023] [Accepted: 08/30/2023] [Indexed: 10/10/2023]
Abstract
PURPOSE To create an inventory of image processing pipelines of arterial spin labeling (ASL) and list their main features, and to evaluate the capability, flexibility, and ease of use of publicly available pipelines to guide novice ASL users in selecting their optimal pipeline. METHODS Developers self-assessed their pipelines using a questionnaire developed by the Task Force 1.1 of the ISMRM Open Science Initiative for Perfusion Imaging. Additionally, each publicly available pipeline was evaluated by two independent testers with basic ASL experience using a scoring system created for this purpose. RESULTS The developers of 21 pipelines filled the questionnaire. Most pipelines are free for noncommercial use (n = 18) and work with the standard NIfTI (Neuroimaging Informatics Technology Initiative) data format (n = 15). All pipelines can process standard 3D single postlabeling delay pseudo-continuous ASL images and primarily differ in their support of advanced sequences and features. The publicly available pipelines (n = 9) were included in the independent testing, all of them being free for noncommercial use. The pipelines, in general, provided a trade-off between ease of use and flexibility for configuring advanced processing options. CONCLUSION Although most ASL pipelines can process the common ASL data types, only some (namely, ASLPrep, ASLtbx, BASIL/Quantiphyse, ExploreASL, and MRICloud) are well-documented, publicly available, support multiple ASL types, have a user-friendly interface, and can provide a useful starting point for ASL processing. The choice of an optimal pipeline should be driven by specific data to be processed and user experience, and can be guided by the information provided in this ASL inventory.
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Affiliation(s)
- Hongli Fan
- The Johns Hopkins School of Medicine, Department of Biomedical Engineering, Baltimore, Maryland, USA
- MR Research and Development, Siemens Medical Solutions USA, Inc., Dallas, Texas, USA
| | - Henk J.M.M. Mutsaerts
- Amsterdam UMC, location Vrije Universiteit Amsterdam, Department of Radiology and Nuclear Medicine, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, The Netherlands
| | - Udunna Anazodo
- Montreal Neurological Institute, McGill University, Montreal, Canada
| | - Daniel Arteaga
- Ascension Saint Thomas Hospital, Nashville, Tennessee, USA
| | - Koen P.A. Baas
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, The Netherlands
- Amsterdam UMC, Location AMC, Department of Radiology and Nuclear Medicine, Amsterdam, The Netherlands
| | - Charlotte Buchanan
- Sir Peter Mansfield Imaging Centre, School of Medicine, University of Nottingham, United Kingdom
| | - Aldo Camargo
- School of Medicine, Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland of Baltimore
| | - Vera C. Keil
- Amsterdam UMC, location Vrije Universiteit Amsterdam, Department of Radiology and Nuclear Medicine, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, The Netherlands
- Cancer Center Amsterdam, Imaging and Biomarkers, Amsterdam, The Netherlands
| | - Zixuan Lin
- The Johns Hopkins School of Medicine, Department of Biomedical Engineering, Baltimore, Maryland, USA
| | - Thomas Lindner
- Department of Diagnostic and Interventional Neuroradiology, University Hospital Hamburg-Eppendorf, Hamburg, Germany
| | - Lydiane Hirschler
- C.J. Gorter MRI Center, Department of Radiology, Leiden University Medical Center, the Netherlands
| | - Jian Hu
- Sir Peter Mansfield Imaging Centre, School of Medicine, University of Nottingham, United Kingdom
- Mental Health & Clinical Neurosciences, School of Medicine, University of Nottingham, United Kingdom
| | - Beatriz E. Padrela
- Amsterdam UMC, location Vrije Universiteit Amsterdam, Department of Radiology and Nuclear Medicine, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, The Netherlands
| | - Mohammad Taghvaei
- Department of Radiology, University of Pennsylvania, Philadelphia, USA
| | - David L. Thomas
- Department of Brain Repair and Rehabilitation, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Sudipto Dolui
- Department of Radiology, University of Pennsylvania, Philadelphia, USA
| | - Jan Petr
- Amsterdam UMC, location Vrije Universiteit Amsterdam, Department of Radiology and Nuclear Medicine, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, The Netherlands
- Helmholtz-Zentrum Dresden-Rossendorf, Institute of Radiopharmaceutical Cancer Research, Dresden, Germany
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2
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Paschoal AM, Woods JG, Pinto J, Bron EE, Petr J, Kennedy McConnell FA, Bell L, Dounavi ME, van Praag CG, Mutsaerts HJMM, Taylor AO, Zhao MY, Brumer I, Chan WSM, Toner J, Hu J, Zhang LX, Domingos C, Monteiro SP, Figueiredo P, Harms AGJ, Padrela BE, Tham C, Abdalle A, Croal PL, Anazodo U. Reproducibility of arterial spin labeling cerebral blood flow image processing: A report of the ISMRM open science initiative for perfusion imaging (OSIPI)_and the ASL MRI challenge. Magn Reson Med 2024. [PMID: 38502108 DOI: 10.1002/mrm.30081] [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: 04/28/2023] [Revised: 02/20/2024] [Accepted: 02/21/2024] [Indexed: 03/20/2024]
Abstract
PURPOSE Arterial spin labeling (ASL) is a widely used contrast-free MRI method for assessing cerebral blood flow (CBF). Despite the generally adopted ASL acquisition guidelines, there is still wide variability in ASL analysis. We explored this variability through the ISMRM-OSIPI ASL-MRI Challenge, aiming to establish best practices for more reproducible ASL analysis. METHODS Eight teams analyzed the challenge data, which included a high-resolution T1-weighted anatomical image and 10 pseudo-continuous ASL datasets simulated using a digital reference object to generate ground-truth CBF values in normal and pathological states. We compared the accuracy of CBF quantification from each team's analysis to the ground truth across all voxels and within predefined brain regions. Reproducibility of CBF across analysis pipelines was assessed using the intra-class correlation coefficient (ICC), limits of agreement (LOA), and replicability of generating similar CBF estimates from different processing approaches. RESULTS Absolute errors in CBF estimates compared to ground-truth synthetic data ranged from 18.36 to 48.12 mL/100 g/min. Realistic motion incorporated into three datasets produced the largest absolute error and variability between teams, with the least agreement (ICC and LOA) with ground-truth results. Fifty percent of the submissions were replicated, and one produced three times larger CBF errors (46.59 mL/100 g/min) compared to submitted results. CONCLUSIONS Variability in CBF measurements, influenced by differences in image processing, especially to compensate for motion, highlights the significance of standardizing ASL analysis workflows. We provide a recommendation for ASL processing based on top-performing approaches as a step toward ASL standardization.
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Affiliation(s)
- Andre M Paschoal
- Institute of Physics, University of Campinas, Campinas, Brazil
- LIM44, Institute of Radiology, Department of Radiology and Oncology of Clinical Hospital, University of Sao Paulo, Sao Paulo, Brazil
| | - Joseph G Woods
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK
- Department of Radiology, Center for Functional Magnetic Resonance Imaging, University of California, San Diego, La Jolla, California, USA
| | - Joana Pinto
- Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, UK
| | - Esther E Bron
- Department of Radiology & Nuclear Medicine, Erasmus MC-University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Jan Petr
- Helmholtz-Zentrum Dresden-Rossendorf, Institute of Radiopharmaceutical Cancer Research, Dresden, Germany
| | - Flora A Kennedy McConnell
- Radiological Sciences, Division of Clinical Neuroscience, School of Medicine, University of Nottingham, Nottingham, UK
- Sir Peter Mansfield Imaging Centre, School of Medicine, University of Nottingham, Nottingham, UK
- Nottingham Biomedical Research Centre, Queens Medical Centre, Nottingham, UK
| | - Laura Bell
- Clinical Imaging Group, Genentech, Inc., South San Francisco, California, USA
| | | | - Cassandra Gould van Praag
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK
- Department of Psychiatry, University of Oxford, Oxford, UK
| | - Henk J M M Mutsaerts
- Department of Radiology and Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, Amsterdam, the Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, the Netherlands
| | | | - Moss Y Zhao
- Department of Radiology, Stanford University, Stanford, California, USA
| | - Irène Brumer
- Computer Assisted Clinical Medicine, Mannheim Institute for Intelligent Systems in Medicine, Medical Faculty Mannheim, Heidelberg University, Heidelberg, Germany
| | - Wei Siang Marcus Chan
- Computer Assisted Clinical Medicine, Mannheim Institute for Intelligent Systems in Medicine, Medical Faculty Mannheim, Heidelberg University, Heidelberg, Germany
| | - Jack Toner
- Sir Peter Mansfield Imaging Centre, School of Medicine, University of Nottingham, Nottingham, UK
- Mental Health & Clinical Neurosciences, School of Medicine, University of Nottingham, Nottingham, UK
| | - Jian Hu
- Sir Peter Mansfield Imaging Centre, School of Medicine, University of Nottingham, Nottingham, UK
- Mental Health & Clinical Neurosciences, School of Medicine, University of Nottingham, Nottingham, UK
| | - Logan X Zhang
- Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, UK
| | - Catarina Domingos
- Institute for Systems and Robotics-Lisboa and Department of Bioengineering, Instituto Superior Técnico-Universidade de Lisboa, Lisbon, Portugal
| | - Sara P Monteiro
- Institute for Systems and Robotics-Lisboa and Department of Bioengineering, Instituto Superior Técnico-Universidade de Lisboa, Lisbon, Portugal
| | - Patrícia Figueiredo
- Institute for Systems and Robotics-Lisboa and Department of Bioengineering, Instituto Superior Técnico-Universidade de Lisboa, Lisbon, Portugal
| | - Alexander G J Harms
- Department of Radiology & Nuclear Medicine, Erasmus MC-University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Beatriz E Padrela
- Department of Radiology and Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, Amsterdam, the Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, the Netherlands
| | - Channelle Tham
- Department of Cognitive Neuroscience, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Ahmed Abdalle
- Schulich School of Medicine and Dentistry, Western University, London, Ontario, Canada
| | - Paula L Croal
- Radiological Sciences, Division of Clinical Neuroscience, School of Medicine, University of Nottingham, Nottingham, UK
- Sir Peter Mansfield Imaging Centre, School of Medicine, University of Nottingham, Nottingham, UK
| | - Udunna Anazodo
- Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, Montreal, Québec, Canada
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3
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Padrela BE, Lorenzini L, Collij LE, García DV, Coomans E, Ingala S, Tomassen J, Deckers Q, Shekari M, de Geus EJC, van de Giessen E, Kate MT, Visser PJ, Barkhof F, Petr J, den Braber A, Mutsaerts HJMM. Genetic, vascular and amyloid components of cerebral blood flow in a preclinical population. J Cereb Blood Flow Metab 2023; 43:1726-1736. [PMID: 37231665 PMCID: PMC10581242 DOI: 10.1177/0271678x231178993] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/25/2022] [Revised: 04/05/2023] [Accepted: 04/09/2023] [Indexed: 05/27/2023]
Abstract
Aging-related cognitive decline can be accelerated by a combination of genetic factors, cardiovascular and cerebrovascular dysfunction, and amyloid-β burden. Whereas cerebral blood flow (CBF) has been studied as a potential early biomarker of cognitive decline, its normal variability in healthy elderly is less known. In this study, we investigated the contribution of genetic, vascular, and amyloid-β components of CBF in a cognitively unimpaired (CU) population of monozygotic older twins. We included 134 participants who underwent arterial spin labeling (ASL) MRI and [18F]flutemetamol amyloid-PET imaging at baseline and after a four-year follow-up. Generalized estimating equations were used to investigate the associations of amyloid burden and white matter hyperintensities with CBF. We showed that, in CU individuals, CBF: 1) has a genetic component, as within-pair similarities in CBF values were moderate and significant (ICC > 0.40); 2) is negatively associated with cerebrovascular damage; and 3) is positively associated with the interaction between cardiovascular risk scores and early amyloid-β burden, which may reflect a vascular compensatory response of CBF to early amyloid-β accumulation. These findings encourage future studies to account for multiple interactions with CBF in disease trajectory analyses.
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Affiliation(s)
- Beatriz E Padrela
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam University Medical Center, Location VUmc, Amsterdam, the Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, the Netherlands
| | - Luigi Lorenzini
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam University Medical Center, Location VUmc, Amsterdam, the Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, the Netherlands
| | - Lyduine E Collij
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam University Medical Center, Location VUmc, Amsterdam, the Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, the Netherlands
| | - David Vállez García
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam University Medical Center, Location VUmc, Amsterdam, the Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, the Netherlands
| | - Emma Coomans
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam University Medical Center, Location VUmc, Amsterdam, the Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, the Netherlands
| | - Silvia Ingala
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam University Medical Center, Location VUmc, Amsterdam, the Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, the Netherlands
| | - Jori Tomassen
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, the Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, the Netherlands
| | - Quinten Deckers
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam University Medical Center, Location VUmc, Amsterdam, the Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, the Netherlands
| | - Mahnaz Shekari
- BBRC: Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- Pompeu Fabra University, Barcelona, Spain
- IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain
| | - Eco JC de Geus
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Elsmarieke van de Giessen
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam University Medical Center, Location VUmc, Amsterdam, the Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, the Netherlands
| | - Mara ten Kate
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam University Medical Center, Location VUmc, Amsterdam, the Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, the Netherlands
| | - Pieter Jelle Visser
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, the Netherlands
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
- Alzheimer Center Limburg, School for Mental Health and Neuroscience, Maastricht University, Maastricht, the Netherlands
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam University Medical Center, Location VUmc, Amsterdam, the Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, the Netherlands
- Queen Square Institute of Neurology and Centre for Medical Image Computing (CMIC), University College London, London, UK
| | - Jan Petr
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam University Medical Center, Location VUmc, Amsterdam, the Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, the Netherlands
- Helmholtz-Zentrum Dresden-Rossendorf, Institute of Radiopharmaceutical Cancer Research, Dresden, Germany
| | - Anouk den Braber
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, the Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, the Netherlands
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Henk JMM Mutsaerts
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam University Medical Center, Location VUmc, Amsterdam, the Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, the Netherlands
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4
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Wamelink IJHG, Kuijer JPA, Padrela BE, Zhang Y, Barkhof F, Mutsaerts HJMM, Petr J, van de Giessen E, Keil VC. Reproducibility of 3 T APT-CEST in Healthy Volunteers and Patients With Brain Glioma. J Magn Reson Imaging 2023; 57:206-215. [PMID: 35633282 PMCID: PMC10084114 DOI: 10.1002/jmri.28239] [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: 02/23/2022] [Revised: 04/28/2022] [Accepted: 04/29/2022] [Indexed: 02/03/2023] Open
Abstract
BACKGROUND Amide proton transfer (APT) imaging is a chemical exchange saturation transfer (CEST) technique offering potential clinical applications such as diagnosis, characterization, and treatment planning and monitoring in glioma patients. While APT-CEST has demonstrated high potential, reproducibility remains underexplored. PURPOSE To investigate whether cerebral APT-CEST with clinically feasible scan time is reproducible in healthy tissue and glioma for clinical use at 3 T. STUDY TYPE Prospective, longitudinal. SUBJECTS Twenty-one healthy volunteers (11 females; mean age ± SD: 39 ± 11 years) and 6 glioma patients (3 females; 50 ± 17 years: 4 glioblastomas, 1 oligodendroglioma, 1 radiologically suspected low-grade glioma). FIELD STRENGTH/SEQUENCE 3 T, Turbo Spin Echo - ampling perfection with application optimized contrasts using different flip angle evolution - chemical exchange saturation transfer (TSE SPACE-CEST). ASSESSMENT APT-CEST measurement reproducibility was assessed within-session (glioma patients, scan session 1; healthy volunteers scan sessions 1, 2, and 3), between-sessions (healthy volunteers scan sessions 1 and 2), and between-days (healthy volunteers, scan sessions 1 and 3). The mean APTCEST values and standard deviation of the within-subject difference (SDdiff ) were calculated in whole tumor enclosed by regions of interest (ROIs) in patients, and eight ROIs in healthy volunteers-whole-brain, cortical gray matter, putamen, thalami, orbitofrontal gyri, occipital lobes, central brain-and compared. STATISTICAL TESTS Brown-Forsythe tests and variance component analysis (VCA) were used to assess the reproducibility of ROIs for the three time intervals. Significance was set at P < 0.003 after Bonferroni correction. RESULTS Intratumoral mean APTCEST was significantly higher than APTCEST in healthy-appearing tissue in patients (0.5 ± 0.46%). The average within-session, between-sessions, and between-days SDdiff of healthy control brains was 0.2% and did not differ significantly with each other (0.76 > P > 0.22). The within-session SDdiff of whole-brain was 0.2% in both healthy volunteers and patients, and 0.21% in the segmented tumor. VCA showed that within-session factors were the most important (60%) for scanning variance. DATA CONCLUSION Cerebral APT-CEST imaging may show good scan-rescan reproducibility in healthy tissue and tumors with clinically feasible scan times at 3 T. Short-term measurement effects may be the dominant components for reproducibility. LEVEL OF EVIDENCE 2 TECHNICAL EFFICACY: Stage 2.
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Affiliation(s)
- Ivar J H G Wamelink
- Department of Radiology and Nuclear Medicine, Cancer Center Amsterdam, Amsterdam University Medical Center, Amsterdam, The Netherlands
| | - Joost P A Kuijer
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam University Medical Center, Amsterdam, The Netherlands
| | - Beatriz E Padrela
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam University Medical Center, Amsterdam, The Netherlands
| | - Yi Zhang
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam University Medical Center, Amsterdam, The Netherlands.,Queen Square Institute of Neurology and Centre for Medical Image Computing, University College London, London, UK
| | - Henk J M M Mutsaerts
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam University Medical Center, Amsterdam, The Netherlands
| | - Jan Petr
- Department of Radiology and Nuclear Medicine, Cancer Center Amsterdam, Amsterdam University Medical Center, Amsterdam, The Netherlands.,Helmholtz-Zentrum Dresden-Rossendorf, Institute of Radiopharmaceutical Cancer Research, Dresden, Germany
| | - Elsmarieke van de Giessen
- Department of Radiology and Nuclear Medicine, Cancer Center Amsterdam, Amsterdam University Medical Center, Amsterdam, The Netherlands.,Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam University Medical Center, Amsterdam, The Netherlands
| | - Vera C Keil
- Department of Radiology and Nuclear Medicine, Cancer Center Amsterdam, Amsterdam University Medical Center, Amsterdam, The Netherlands
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5
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Moyaert P, Padrela BE, Morgan CA, Petr J, Versijpt J, Barkhof F, Jurkiewicz MT, Shao X, Oyeniran O, Manson T, Wang DJJ, Günther M, Achten E, Mutsaerts HJMM, Anazodo UC. Imaging blood-brain barrier dysfunction: A state-of-the-art review from a clinical perspective. Front Aging Neurosci 2023; 15:1132077. [PMID: 37139088 PMCID: PMC10150073 DOI: 10.3389/fnagi.2023.1132077] [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: 12/26/2022] [Accepted: 03/15/2023] [Indexed: 05/05/2023] Open
Abstract
The blood-brain barrier (BBB) consists of specialized cells that tightly regulate the in- and outflow of molecules from the blood to brain parenchyma, protecting the brain's microenvironment. If one of the BBB components starts to fail, its dysfunction can lead to a cascade of neuroinflammatory events leading to neuronal dysfunction and degeneration. Preliminary imaging findings suggest that BBB dysfunction could serve as an early diagnostic and prognostic biomarker for a number of neurological diseases. This review aims to provide clinicians with an overview of the emerging field of BBB imaging in humans by answering three key questions: (1. Disease) In which diseases could BBB imaging be useful? (2. Device) What are currently available imaging methods for evaluating BBB integrity? And (3. Distribution) what is the potential of BBB imaging in different environments, particularly in resource limited settings? We conclude that further advances are needed, such as the validation, standardization and implementation of readily available, low-cost and non-contrast BBB imaging techniques, for BBB imaging to be a useful clinical biomarker in both resource-limited and well-resourced settings.
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Affiliation(s)
- Paulien Moyaert
- Department of Medical Imaging, Ghent University Hospital, Ghent, Belgium
- Lawson Health Research Institute, London, ON, Canada
- Department of Neurology, Vrije Universiteit Brussel (VUB), Universitair Ziekenhuis Brussel (UZ Brussel), Brussels, Belgium
- *Correspondence: Paulien Moyaert,
| | - Beatriz E. Padrela
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Center, Amsterdam Neuroscience, Amsterdam, Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, Netherlands
| | - Catherine A. Morgan
- School of Psychology and Centre for Brain Research, The University of Auckland, Auckland, New Zealand
- Centre for Advanced MRI, Auckland UniServices Limited, Auckland, New Zealand
| | - Jan Petr
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Center, Amsterdam Neuroscience, Amsterdam, Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, Netherlands
- Helmholtz-Zentrum Dresden-Rossendorf, Institute of Radiopharmaceutical Cancer Research, Dresden, Germany
| | - Jan Versijpt
- Department of Neurology, Vrije Universiteit Brussel (VUB), Universitair Ziekenhuis Brussel (UZ Brussel), Brussels, Belgium
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Center, Amsterdam Neuroscience, Amsterdam, Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, Netherlands
- Queen Square Institute of Neurology and Centre for Medical Image Computing, University College London, London, United Kingdom
| | | | - Xingfeng Shao
- Laboratory of FMRI Technology (LOFT), USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States
| | - Olujide Oyeniran
- Lawson Health Research Institute, London, ON, Canada
- Department of Medical Biophysics, Western University, London, ON, Canada
| | - Tabitha Manson
- Centre for Advanced MRI, Auckland UniServices Limited, Auckland, New Zealand
- Auckland Bioengineering Institute, The University of Auckland, Auckland, New Zealand
| | - Danny J. J. Wang
- Laboratory of FMRI Technology (LOFT), USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States
| | - Matthias Günther
- Fraunhofer Institute for Digital Medicine, University of Bremen, Bremen, Germany
| | - Eric Achten
- Department of Medical Imaging, Ghent University Hospital, Ghent, Belgium
| | - Henk J. M. M. Mutsaerts
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Center, Amsterdam Neuroscience, Amsterdam, Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, Netherlands
| | - Udunna C. Anazodo
- Lawson Health Research Institute, London, ON, Canada
- Montreal Neurological Institute, McGill University, Montreal, QC, Canada
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