1
|
Ferreira R, Bastos-Leite AJ. Arterial spin labelling magnetic resonance imaging and perfusion patterns in neurocognitive and other mental disorders: a systematic review. Neuroradiology 2024:10.1007/s00234-024-03323-0. [PMID: 38536448 DOI: 10.1007/s00234-024-03323-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2023] [Accepted: 02/24/2024] [Indexed: 04/18/2024]
Abstract
We reviewed 33 original research studies assessing brain perfusion, using consensus guidelines from a "white paper" issued by the International Society for Magnetic Resonance in Medicine Perfusion Study Group and the European Cooperation in Science and Technology Action BM1103 ("Arterial Spin Labelling Initiative in Dementia"; https://www.cost.eu/actions/BM1103/ ). The studies were published between 2011 and 2023 and included participants with subjective cognitive decline plus; neurocognitive disorders, including mild cognitive impairment (MCI), Alzheimer's disease (AD), frontotemporal lobar degeneration (FTLD), dementia with Lewy bodies (DLB) and vascular cognitive impairment (VCI); as well as schizophrenia spectrum disorders, bipolar and major depressive disorders, autism spectrum disorder, attention-deficit/hyperactivity disorder, panic disorder and alcohol use disorder. Hypoperfusion associated with cognitive impairment was the major finding across the spectrum of cognitive decline. Regional hyperperfusion also was reported in MCI, AD, frontotemporal dementia phenocopy syndrome and VCI. Hypoperfused structures found to aid in diagnosing AD included the precunei and adjacent posterior cingulate cortices. Hypoperfused structures found to better diagnose patients with FTLD were the anterior cingulate cortices and frontal regions. Hypoperfusion in patients with DLB was found to relatively spare the temporal lobes, even after correction for partial volume effects. Hyperperfusion in the temporal cortices and hypoperfusion in the prefrontal and anterior cingulate cortices were found in patients with schizophrenia, most of whom were on medication and at the chronic stage of illness. Infratentorial structures were found to be abnormally perfused in patients with bipolar or major depressive disorders. Brain perfusion abnormalities were helpful in diagnosing most neurocognitive disorders. Abnormalities reported in VCI and the remaining mental disorders were heterogeneous and not generalisable.
Collapse
Affiliation(s)
- Rita Ferreira
- Faculty of Medicine, University of Porto, Porto, Portugal
| | | |
Collapse
|
2
|
Sollmann N, Hoffmann G, Schramm S, Reichert M, Hernandez Petzsche M, Strobel J, Nigris L, Kloth C, Rosskopf J, Börner C, Bonfert M, Berndt M, Grön G, Müller HP, Kassubek J, Kreiser K, Koerte IK, Liebl H, Beer A, Zimmer C, Beer M, Kaczmarz S. Arterial Spin Labeling (ASL) in Neuroradiological Diagnostics - Methodological Overview and Use Cases. ROFO-FORTSCHR RONTG 2024; 196:36-51. [PMID: 37467779 DOI: 10.1055/a-2119-5574] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/21/2023]
Abstract
BACKGROUND Arterial spin labeling (ASL) is a magnetic resonance imaging (MRI)-based technique using labeled blood-water of the brain-feeding arteries as an endogenous tracer to derive information about brain perfusion. It enables the assessment of cerebral blood flow (CBF). METHOD This review aims to provide a methodological and technical overview of ASL techniques, and to give examples of clinical use cases for various diseases affecting the central nervous system (CNS). There is a special focus on recent developments including super-selective ASL (ssASL) and time-resolved ASL-based magnetic resonance angiography (MRA) and on diseases commonly not leading to characteristic alterations on conventional structural MRI (e. g., concussion or migraine). RESULTS ASL-derived CBF may represent a clinically relevant parameter in various pathologies such as cerebrovascular diseases, neoplasms, or neurodegenerative diseases. Furthermore, ASL has also been used to investigate CBF in mild traumatic brain injury or migraine, potentially leading to the establishment of imaging-based biomarkers. Recent advances made possible the acquisition of ssASL by selective labeling of single brain-feeding arteries, enabling spatial perfusion territory mapping dependent on blood flow of a specific preselected artery. Furthermore, ASL-based MRA has been introduced, providing time-resolved delineation of single intracranial vessels. CONCLUSION Perfusion imaging by ASL has shown promise in various diseases of the CNS. Given that ASL does not require intravenous administration of a gadolinium-based contrast agent, it may be of particular interest for investigations in pediatric cohorts, patients with impaired kidney function, patients with relevant allergies, or patients that undergo serial MRI for clinical indications such as disease monitoring. KEY POINTS · ASL is an MRI technique that uses labeled blood-water as an endogenous tracer for brain perfusion imaging.. · It allows the assessment of CBF without the need for administration of a gadolinium-based contrast agent.. · CBF quantification by ASL has been used in several pathologies including brain tumors or neurodegenerative diseases.. · Vessel-selective ASL methods can provide brain perfusion territory mapping in cerebrovascular diseases.. · ASL may be of particular interest in patient cohorts with caveats concerning gadolinium administration..
Collapse
Affiliation(s)
- Nico Sollmann
- Department of Diagnostic and Interventional Radiology, University Hospital Ulm, Ulm, Germany
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- TUM-Neuroimaging Center, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- cBrain, Department of Child and Adolescent Psychiatry, Psychosomatics, and Psychotherapy, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Gabriel Hoffmann
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- TUM-Neuroimaging Center, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Severin Schramm
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Miriam Reichert
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Moritz Hernandez Petzsche
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Joachim Strobel
- Department of Nuclear Medicine, University Hospital Ulm, Ulm, Germany
| | - Lorenzo Nigris
- cBrain, Department of Child and Adolescent Psychiatry, Psychosomatics, and Psychotherapy, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Christopher Kloth
- Department of Diagnostic and Interventional Radiology, University Hospital Ulm, Ulm, Germany
| | - Johannes Rosskopf
- Department of Diagnostic and Interventional Radiology, University Hospital Ulm, Ulm, Germany
- Section of Neuroradiology, Bezirkskrankenhaus Günzburg, Günzburg, Germany
| | - Corinna Börner
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- LMU Hospital, Department of Pediatrics - Dr. von Hauner Children's Hospital, Division of Pediatric Neurology and Developmental Medicine, Ludwig-Maximilians-Universität München, Munich, Germany
- LMU Center for Children with Medical Complexity - iSPZ Hauner, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Michaela Bonfert
- LMU Hospital, Department of Pediatrics - Dr. von Hauner Children's Hospital, Division of Pediatric Neurology and Developmental Medicine, Ludwig-Maximilians-Universität München, Munich, Germany
- LMU Center for Children with Medical Complexity - iSPZ Hauner, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Maria Berndt
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Georg Grön
- Department of Psychiatry and Psychotherapy III, University Hospital Ulm, Ulm, Germany
| | | | - Jan Kassubek
- Department of Neurology, University Hospital Ulm, Ulm, Germany
- German Center for Neurodegenerative Diseases (DZNE), Ulm University, Ulm, Germany
| | - Kornelia Kreiser
- Department of Diagnostic and Interventional Radiology, University Hospital Ulm, Ulm, Germany
- Department of Radiology and Neuroradiology, Universitäts- und Rehabilitationskliniken Ulm, Ulm, Germany
| | - Inga K Koerte
- cBrain, Department of Child and Adolescent Psychiatry, Psychosomatics, and Psychotherapy, Ludwig-Maximilians-Universität München, Munich, Germany
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women's Hospital, Boston, United States
- Department of Psychiatry, Harvard Medical School, Massachusetts General Hospital, Boston, United States
| | - Hans Liebl
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- Department of Radiology, Berufsgenossenschaftliche Unfallklinik Murnau, Murnau, Germany
| | - Ambros Beer
- Department of Nuclear Medicine, University Hospital Ulm, Ulm, Germany
- MoMan - Center for Translational Imaging, University Hospital Ulm, Ulm, Germany
- i2SouI - Innovative Imaging in Surgical Oncology, University Hospital Ulm, Ulm, Germany
| | - Claus Zimmer
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- TUM-Neuroimaging Center, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Meinrad Beer
- Department of Diagnostic and Interventional Radiology, University Hospital Ulm, Ulm, Germany
- MoMan - Center for Translational Imaging, University Hospital Ulm, Ulm, Germany
- i2SouI - Innovative Imaging in Surgical Oncology, University Hospital Ulm, Ulm, Germany
| | - Stephan Kaczmarz
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- TUM-Neuroimaging Center, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- Market DACH, Philips GmbH, Hamburg, Germany
| |
Collapse
|
4
|
Xu F, Liu D, Zhu D, Hillis AE, Bakker A, Soldan A, Albert MS, Lin DDM, Qin Q. Test-retest reliability of 3D velocity-selective arterial spin labeling for detecting normal variations of cerebral blood flow. Neuroimage 2023; 271:120039. [PMID: 36931331 PMCID: PMC10150252 DOI: 10.1016/j.neuroimage.2023.120039] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2022] [Revised: 02/23/2023] [Accepted: 03/14/2023] [Indexed: 03/18/2023] Open
Abstract
Velocity-selective inversion (VSI) based velocity-selective arterial spin labeling (VSASL) has been developed to measure cerebral blood flow (CBF) with low susceptibility to the prolonged arterial transit time and high sensitivity to brain perfusion signal. The purpose of this magnetic resonance imaging study is to evaluate the test-retest reliability of a VSI-prepared 3D VSASL protocol with whole-brain coverage to detect baseline CBF variations among cognitively normal participants in different brain regions. Coefficients of variation (CoV) of both absolute and relative CBF across scans or sessions, subjects, and gray matter regions were calculated, and corresponding intraclass correlation coefficients (ICC) were computed. The higher between-subject CoV of absolute CBF (13.4 ± 2.0%) over within-subject CoV (within-session: 3.8 ± 1.1%; between-session: 4.9 ± 0.9%) yielded moderate to excellent ICC (within-session: 0.88±0.08; between-session: 0.77±0.14) to detect normal variations of individual CBF. The higher between-region CoV of relative CBF (11.4 ± 3.0%) over within-region CoV (within-session: 2.3 ± 0.9%; between-session: 3.3 ± 1.0%) yielded excellent ICC (within-session: 0.92±0.06; between-session: 0.85±0.12) to detect normal variations of regional CBF. Age, blood pressure, end-tidal CO2, and hematocrit partially explained the variability of CBF across subjects. Together these results show excellent test-retest reliability of VSASL to detect both between-subject and between-region variations supporting its clinical utility.
Collapse
Affiliation(s)
- Feng Xu
- The Russell H. Morgan Department of Radiology and Radiological Science, Division of MR Research, Johns Hopkins University, Baltimore, MD 21205, USA; F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD 21205, USA.
| | - Dapeng Liu
- The Russell H. Morgan Department of Radiology and Radiological Science, Division of MR Research, Johns Hopkins University, Baltimore, MD 21205, USA; F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD 21205, USA
| | - Dan Zhu
- The Russell H. Morgan Department of Radiology and Radiological Science, Division of MR Research, Johns Hopkins University, Baltimore, MD 21205, USA; F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD 21205, USA
| | - Argye E Hillis
- Department of Neurology, Johns Hopkins University, Baltimore, MD 21205, USA
| | - Arnold Bakker
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University, Baltimore, MD 21287, USA
| | - Anja Soldan
- Department of Neurology, Johns Hopkins University, Baltimore, MD 21205, USA
| | - Marilyn S Albert
- Department of Neurology, Johns Hopkins University, Baltimore, MD 21205, USA
| | - Doris D M Lin
- The Russell H. Morgan Department of Radiology and Radiological Science, Division of MR Research, Johns Hopkins University, Baltimore, MD 21205, USA
| | - Qin Qin
- The Russell H. Morgan Department of Radiology and Radiological Science, Division of MR Research, Johns Hopkins University, Baltimore, MD 21205, USA; F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD 21205, USA
| |
Collapse
|
5
|
Narciso L, Ssali T, Liu L, Jesso S, Hicks JW, Anazodo U, Finger E, St Lawrence K. Noninvasive Quantification of Cerebral Blood Flow Using Hybrid PET/MR Imaging to Extract the [ 15 O]H 2 O Image-Derived Input Function Free of Partial Volume Errors. J Magn Reson Imaging 2022; 56:1243-1255. [PMID: 35226390 DOI: 10.1002/jmri.28134] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2021] [Revised: 02/16/2022] [Accepted: 02/16/2022] [Indexed: 11/06/2022] Open
Abstract
BACKGROUND Quantification of cerebral blood flow (CBF) with [15 O]H2 O-positron emission tomography (PET) requires arterial sampling to measure the input function. This invasive procedure can be avoided by extracting an image-derived input function (IDIF); however, IDIFs are sensitive to partial volume errors due to the limited spatial resolution of PET. PURPOSE To present an alternative hybrid PET/MR imaging of CBF (PMRFlowIDIF ) that uses phase-contrast (PC) MRI measurements of whole-brain (WB) CBF to calibrate an IDIF extracted from a WB [15 O]H2 O time-activity curve. STUDY TYPE Technical development and validation. ANIMAL MODEL Twelve juvenile Duroc pigs (83% female). POPULATION Thirteen healthy individuals (38% female). FIELD STRENGTH/SEQUENCES 3 T; gradient-echo PC-MRI. ASSESSMENT PMRFlowIDIF was validated against PET-only in a porcine model that included arterial sampling. CBF maps were generated by applying PMRFlowIDIF and two previous PMRFlow methods (PC-PET and double integration method [DIM]) to [15 O]H2 O-PET data acquired from healthy individuals. STATISTICAL TESTS PMRFlow and PET CBF measurements were compared with regression and correlation analyses. Paired t-tests were performed to evaluate differences. Potential biases were assessed using one-sample t-tests. Reliability was assessed by intraclass correlation coefficients. Statistical significance: α = 0.05. RESULTS In the animal study, strong agreement was observed between PMRFlowIDIF (average voxel-wise CBF, 58.0 ± 16.9 mL/100 g/min) and PET (63.0 ± 18.9 mL/100 g/min). In the human study, PMRFlowDIM (y = 1.11x - 5.16, R2 = 0.99 ± 0.01) and PMRFlowPC-PET (y = 0.87x + 3.82, R2 = 0.97 ± 0.02) performed similarly to PMRFlowIDIF, and CBF was within the expected range (eg, 49.7 ± 7.2 mL/100 g/min for gray matter). DATA CONCLUSION Accuracy of PMRFlowIDIF was confirmed in the animal study with the primary source of error attributed to differences in WB CBF measured by PC MRI and PET. In the human study, differences in CBF from PMRFlowIDIF , PMRFlowDIM , and PMRFlowPC-PET were due to the latter two not accounting for blood-borne activity. LEVEL OF EVIDENCE 2 TECHNICAL EFFICACY STAGE: 1.
Collapse
Affiliation(s)
- Lucas Narciso
- Medical Imaging, Lawson Health Research Institute, London, Ontario, Canada.,Department of Medical Biophysics, Western University, London, Ontario, Canada
| | - Tracy Ssali
- Medical Imaging, Lawson Health Research Institute, London, Ontario, Canada.,Department of Medical Biophysics, Western University, London, Ontario, Canada
| | - Linshan Liu
- Medical Imaging, Lawson Health Research Institute, London, Ontario, Canada
| | - Sarah Jesso
- Medical Imaging, Lawson Health Research Institute, London, Ontario, Canada.,Department of Clinical Neurological Sciences, Western University, London, Ontario, Canada
| | - Justin W Hicks
- Medical Imaging, Lawson Health Research Institute, London, Ontario, Canada.,Department of Medical Biophysics, Western University, London, Ontario, Canada
| | - Udunna Anazodo
- Medical Imaging, Lawson Health Research Institute, London, Ontario, Canada.,Department of Medical Biophysics, Western University, London, Ontario, Canada.,Department of Clinical Neurological Sciences, Western University, London, Ontario, Canada
| | - Elizabeth Finger
- Medical Imaging, Lawson Health Research Institute, London, Ontario, Canada.,Department of Clinical Neurological Sciences, Western University, London, Ontario, Canada
| | - Keith St Lawrence
- Medical Imaging, Lawson Health Research Institute, London, Ontario, Canada.,Department of Medical Biophysics, Western University, London, Ontario, Canada
| |
Collapse
|