1
|
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] [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.
Collapse
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
| |
Collapse
|
2
|
Davison CM, O'Brien JT. A comparison of FDG-PET and blood flow SPECT in the diagnosis of neurodegenerative dementias: a systematic review. Int J Geriatr Psychiatry 2014; 29:551-61. [PMID: 24123413 DOI: 10.1002/gps.4036] [Citation(s) in RCA: 51] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/15/2013] [Accepted: 09/16/2013] [Indexed: 11/08/2022]
Abstract
OBJECTIVE Perfusion single photon emission computed tomography (SPECT) and 18F fluorodeoxyglucose positron emission tomography (FDG-PET) both have clinical utility for the differential diagnosis of dementia. Although PET is often viewed by some as more accurate and therefore preferential, the extent to which published evidence supports this is not clear. The aim of this review was to address the question by reviewing studies of SPECT and PET imaging in dementia diagnosis, with a particular focus on all published head-to-head studies. DESIGN A MEDLINE search was carried out using the following keywords: "PET" and "SPECT" and "dementia" or "Mild Cognitive Impairment," together with "alzheimers" or "DLB" or "lewy body" or "frontotemporal" or "FTD" or "Picks." Articles were included up to February 2013, limited to human studies and in English language. RESULTS Published studies of SPECT accuracy show that it is a useful tool for differential diagnosis, with sensitivities of 65-85% for diagnosing Alzheimer's disease (AD) and specificities (for other neurodegenerative dementias) of 72-87%. PET studies generally report higher accuracy, with sensitivities of 75-99% for AD and specificities of 71-93%. However, there have been few direct head-to-head comparisons, with some indicating SPECT and PET to be equally useful in dementia diagnosis and others favouring PET. Many of these studies are limited with respect to numbers and methodically with poorly matched control groups. CONCLUSIONS Overall, although studies suggest superiority of PET over SPECT, the evidence base for this is actually quite limited. We suggest that further direct comparative studies, including health economic and patient preference evaluations, are needed to help direct future service provision.
Collapse
|
3
|
Chen W, Song X, Beyea S, D'Arcy R, Zhang Y, Rockwood K. Advances in perfusion magnetic resonance imaging in Alzheimer's disease. Alzheimers Dement 2010; 7:185-96. [DOI: 10.1016/j.jalz.2010.04.004] [Citation(s) in RCA: 36] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2009] [Revised: 03/31/2010] [Accepted: 04/21/2010] [Indexed: 01/01/2023]
Affiliation(s)
- Wei Chen
- National Research Council CanadaInstitute for Biodiagnostics (Atlantic)HalifaxCanada
- Department of RadiologyGeneral Hospital of Tianjin Medical UniversityTianjinChina
| | - Xiaowei Song
- National Research Council CanadaInstitute for Biodiagnostics (Atlantic)HalifaxCanada
- Division of Geriatric MedicineDepartment of Medicine, Dalhousie UniversityHalifaxCanada
| | - Steven Beyea
- National Research Council CanadaInstitute for Biodiagnostics (Atlantic)HalifaxCanada
- Department of PhysicsDalhousie UniversityHalifaxCanada
| | - Ryan D'Arcy
- National Research Council CanadaInstitute for Biodiagnostics (Atlantic)HalifaxCanada
- Department of PsychologyDalhousie UniversityHalifaxCanada
- Neuroscience Institute, Dalhousie UniversityHalifaxCanada
| | - Yunting Zhang
- Department of RadiologyGeneral Hospital of Tianjin Medical UniversityTianjinChina
| | - Kenneth Rockwood
- Division of Geriatric MedicineDepartment of Medicine, Dalhousie UniversityHalifaxCanada
- Centre for Health Care of the Elderly, Queen Elizabeth II Health Sciences CentreHalifaxCanada
| |
Collapse
|
4
|
Borghesani PR, DeMers SM, Manchanda V, Pruthi S, Lewis DH, Borson S. Neuroimaging in the clinical diagnosis of dementia: observations from a memory disorders clinic. J Am Geriatr Soc 2010; 58:1453-8. [PMID: 20670380 DOI: 10.1111/j.1532-5415.2010.02975.x] [Citation(s) in RCA: 27] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
OBJECTIVES To determine how often neuroimaging confirms, clarifies, or contradicts initial diagnoses of late-life cognitive disorders. DESIGN Retrospective case review. SETTING Outpatient clinic specializing in memory disorders. PARTICIPANTS One hundred ninety-three consecutively referred cognitively impaired patients. MEASUREMENTS Diagnoses using research criteria were developed for each patient at the first visit and ranged from cognitive impairment without dementia to dementias of single, complex, or indeterminate etiology. Structural (noncontrast magnetic resonance imaging) and perfusion (technetium-99m ethyl cysteine dimer single photon emission computed tomography) images were categorized together as normal, suggestive of specific diseases, or abnormal/not diagnostic. RESULTS When a single neurodegenerative disease was suspected clinically (n=94), imaging confirmed the diagnosis in 50, contradicted the diagnosis in 32, and was abnormal/not diagnostic in 12. When more than one neurodegenerative etiology was clinically suspected (n=21), imaging assigned a single diagnosis in 13 and only cerebrovascular disease in one and was abnormal/not diagnostic in seven. In dementia not otherwise specified (NOS) (n=33), imaging suggested a specific etiology in 23 and was abnormal/not diagnostic in 10. Abnormal/not diagnostic images were more common in cognitive disorder NOS (n=25, 68%) than in other clinical groups (22%, chi-square=22.8 P<.001). Neuroimaging indicators of cerebrovascular disease were common (60% prevalence) but not predicted by the presence of vascular risk factors alone. CONCLUSION Overall, neuroimaging confirmed, clarified, or contradicted the initial clinical diagnosis in more than 80% of patients, whereas fewer than 20% had abnormal/not diagnostic patterns. Imaging suggested a complex dementia etiology in 21% of cases clinically thought to be caused by a single process, whereas 46% of complex clinical differential diagnoses appeared to reflect a single causal pattern. Further work is needed to determine whether refinement of clinical diagnoses using specialized neuroimaging improves clinical decision-making and patient outcomes.
Collapse
Affiliation(s)
- Paul R Borghesani
- Department of Psychiatry and Behavioral Sciences, University of Washington Medical Center, Seattle, Washington, USA.
| | | | | | | | | | | |
Collapse
|