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Woods JG, Achten E, Asllani I, Bolar DS, Dai W, Detre JA, Fan AP, Fernández-Seara M, Golay X, Günther M, Guo J, Hernandez-Garcia L, Ho ML, Juttukonda MR, Lu H, MacIntosh BJ, Madhuranthakam AJ, Mutsaerts HJ, Okell TW, Parkes LM, Pinter N, Pinto J, Qin Q, Smits M, Suzuki Y, Thomas DL, Van Osch MJ, Wang DJJ, Warnert EA, Zaharchuk G, Zelaya F, Zhao M, Chappell MA. Recommendations for quantitative cerebral perfusion MRI using multi-timepoint arterial spin labeling: Acquisition, quantification, and clinical applications. Magn Reson Med 2024; 92:469-495. [PMID: 38594906 PMCID: PMC11142882 DOI: 10.1002/mrm.30091] [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: 08/31/2023] [Revised: 02/09/2024] [Accepted: 03/07/2024] [Indexed: 04/11/2024]
Abstract
Accurate assessment of cerebral perfusion is vital for understanding the hemodynamic processes involved in various neurological disorders and guiding clinical decision-making. This guidelines article provides a comprehensive overview of quantitative perfusion imaging of the brain using multi-timepoint arterial spin labeling (ASL), along with recommendations for its acquisition and quantification. A major benefit of acquiring ASL data with multiple label durations and/or post-labeling delays (PLDs) is being able to account for the effect of variable arterial transit time (ATT) on quantitative perfusion values and additionally visualize the spatial pattern of ATT itself, providing valuable clinical insights. Although multi-timepoint data can be acquired in the same scan time as single-PLD data with comparable perfusion measurement precision, its acquisition and postprocessing presents challenges beyond single-PLD ASL, impeding widespread adoption. Building upon the 2015 ASL consensus article, this work highlights the protocol distinctions specific to multi-timepoint ASL and provides robust recommendations for acquiring high-quality data. Additionally, we propose an extended quantification model based on the 2015 consensus model and discuss relevant postprocessing options to enhance the analysis of multi-timepoint ASL data. Furthermore, we review the potential clinical applications where multi-timepoint ASL is expected to offer significant benefits. This article is part of a series published by the International Society for Magnetic Resonance in Medicine (ISMRM) Perfusion Study Group, aiming to guide and inspire the advancement and utilization of ASL beyond the scope of the 2015 consensus article.
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Affiliation(s)
- Joseph G. Woods
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
- Center for Functional Magnetic Resonance Imaging, Department of Radiology, University of California San Diego, La Jolla, California, USA
| | - Eric Achten
- Ghent Institute for Functional and Metabolic Imaging (GIfMI), Ghent University, Ghent, Belgium
| | - Iris Asllani
- Department of Neuroscience, University of Sussex, UK and Department of Biomedical Engineering, Rochester Institute of Technology, USA
| | - Divya S. Bolar
- Center for Functional Magnetic Resonance Imaging, Department of Radiology, University of California San Diego, La Jolla, California, USA
| | - Weiying Dai
- Department of Computer Science, State University of New York at Binghamton, Binghamton, NY, USA, 13902
| | - John A. Detre
- Department of Neurology, University of Pennsylvania, 3 Dulles Building, 3400 Spruce Street, Philadelphia, PA 19104 USA
| | - Audrey P. Fan
- Department of Biomedical Engineering, Department of Neurology, University of California Davis, Davis, CA, USA
| | - Maria Fernández-Seara
- Department of Radiology, Clínica Universidad de Navarra, Pamplona, Spain; IdiSNA, Instituto de Investigación Sanitaria de Navarra, Pamplona, Spain
| | - Xavier Golay
- UCL Queen Square Institute of Neurology, University College London, London, UK; Gold Standard Phantoms, UK
| | - Matthias Günther
- Imaging Physics, Fraunhofer Institute for Digital Medicine MEVIS, Bremen, Germany
- Departments of Physics and Electrical Engineering, University of Bremen, Bremen, Germany
| | - Jia Guo
- Department of Bioengineering, University of California Riverside, Riverside, CA, USA
| | | | - Mai-Lan Ho
- Department of Radiology, University of Missouri, Columbia, MO, USA. ORCID: 0000-0002-9455-1350
| | - Meher R. Juttukonda
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA
- Department of Radiology, Harvard Medical School, Boston, Massachusetts, USA
| | - Hanzhang Lu
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Bradley J. MacIntosh
- Hurvitz Brain Sciences Program, Centre for Brain Resilience & Recovery, Sunnybrook Research Institute, Toronto, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, Canada
- Computational Radiology & Artificial Intelligence unit, Oslo University Hospital, Oslo, Norway
| | - Ananth J. Madhuranthakam
- Department of Radiology and Advanced Imaging Research Center, UT Southwestern Medical Center, Dallas, TX, USA
| | - Henk-Jan Mutsaerts
- Amsterdam UMC location Vrije Universiteit Amsterdam, Department of Radiology and Nuclear Medicine, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, The Netherlands
| | - Thomas W. Okell
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Laura M. Parkes
- School of Health Sciences, Faculty of Biology, Medicine and Health, University of Manchester, UK
- Geoffrey Jefferson Brain Research Centre, Manchester Academic Health Science Centre, UK
| | - Nandor Pinter
- Dent Neurologic Institute, Buffalo, New York, USA; University at Buffalo Neurosurgery, Buffalo, New York, USA
| | - Joana Pinto
- Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, UK
| | - Qin Qin
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Marion Smits
- Department of Radiology & Nuclear Medicine, Erasmus MC, Rotterdam, The Netherlands
- Medical Delta, Delft, The Netherlands
- Erasmus MC Cancer Institute, Erasmus MC, Rotterdam, NL
| | - Yuriko Suzuki
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - David L. Thomas
- Department of Brain Repair and Rehabilitation, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Matthias J.P. Van Osch
- C.J. Gorter MRI Center, Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Danny JJ Wang
- Laboratory of FMRI Technology (LOFT), Stevens Neuroimaging and Informatics Institute, University of Southern California, Los Angeles, CA, USA
| | - Esther A.H. Warnert
- Department of Radiology & Nuclear Medicine, Erasmus MC, Rotterdam, The Netherlands
- Erasmus MC Cancer Institute, Erasmus MC, Rotterdam, NL
| | - Greg Zaharchuk
- Department of Radiology, Stanford University, Stanford, CA, USA
| | - Fernando Zelaya
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, Kings College London, London, UK
| | - Moss Zhao
- Department of Radiology, Stanford University, Stanford, CA, USA
- Maternal & Child Health Research Institute, Stanford University, Stanford, CA, USA
| | - Michael A. Chappell
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
- Sir Peter Mansfield Imaging Centre, School of Medicine, University of Nottingham, Nottingham, UK
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Triantafyllou GA, Triantafyllou A, Zafeiridis AS, Koletsos N, Zafeiridis A, Gkaliagkousi E, Douma S, Dipla K. Association of Cerebral Oxygenation During Exercise With Target Organ Damage in Middle-Aged Hypertensive and Normotensive Individuals. Am J Hypertens 2022; 35:664-671. [PMID: 35325928 PMCID: PMC11024639 DOI: 10.1093/ajh/hpac040] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2022] [Revised: 03/20/2022] [Accepted: 03/23/2022] [Indexed: 01/27/2023] Open
Abstract
BACKGROUND The brain is one of the main target organs affected by hypertension. Impaired cerebral oxygenation during exercise is an indicator of cerebral dysfunction. We aimed to investigate whether cerebral oxygenation during exercise correlates with subclinical markers of early target organ damage in a population of middle-aged, newly diagnosed hypertensive and healthy individuals. METHODS Carotid intima-media thickness (cIMT) was measured using ultrasound, arterial stiffness was estimated measuring the augmentation index and pulse wave velocity, and retinal vessel diameter was assessed via the central retinal-arteriolar and vein equivalent and retinal-arteriovenous ratio. Participants (n = 93) performed a 3-minute isometric handgrip exercise. Cerebral prefrontal oxygenation was measured continuously using near infrared spectroscopy. The average exercise responses in oxygenated hemoglobin (O2Hb), deoxygenated hemoglobin (HHb), and total hemoglobin (tHb) were assessed. Univariate analyses were performed; partial correlation was used to account for traditional cardiovascular risk factors to identify independent associations between cerebral-oxygenation indices and early markers of target organ damage. RESULTS Mean cIMT was negatively correlated with the average exercise response in cerebral oxygenation (rhoO2Hb = -0.348, PO2Hb = 0.001; rhotHb = -0.253, Pthb = 0.02). Augmentation index was negatively correlated with cerebral oxygenation during exercise (rhoO2Hb = -0.374, P < 0.001; rhotHb = -0.332, P = 0.02), whereas no significant correlation was observed between pulse wave velocity and cerebral-oxygenation indices. In the adjusted analysis, cerebral oxygenation was correlated with central retinal arteriolar diameter (CRAE r = 0.233, P = 0.043). CONCLUSIONS Our novel findings suggest that indices of lower cerebral oxygenation during a submaximal physical task are associated with markers of early, subclinical target organ damage, namely increased cIMT, arterial stiffness, and arteriolar retinal narrowing in newly diagnosed, untreated, hypertensive individuals.
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Affiliation(s)
- Georgios A Triantafyllou
- 3rd Department of Internal Medicine, Papageorgiou General Hospital, Aristotle University of Thessaloniki, Thessaloniki, Greece
- Division of Pulmonary, Allergy and Critical Care Medicine, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania, USA
| | - Areti Triantafyllou
- 3rd Department of Internal Medicine, Papageorgiou General Hospital, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - Alexandros Savvas Zafeiridis
- 3rd Department of Internal Medicine, Papageorgiou General Hospital, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - Nikolaos Koletsos
- 3rd Department of Internal Medicine, Papageorgiou General Hospital, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - Andreas Zafeiridis
- Exercise Physiology and Biochemistry Laboratory, Department of Sports Science at Serres, Agios Ioannis 62110, Aristotle University of Thessaloniki, Serres, Greece
| | - Eugenia Gkaliagkousi
- 3rd Department of Internal Medicine, Papageorgiou General Hospital, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - Stella Douma
- 3rd Department of Internal Medicine, Papageorgiou General Hospital, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - Konstantina Dipla
- Exercise Physiology and Biochemistry Laboratory, Department of Sports Science at Serres, Agios Ioannis 62110, Aristotle University of Thessaloniki, Serres, Greece
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Triantafyllou GA, Dipla K, Triantafyllou A, Gkaliagkousi E, Douma S. Measurement and Changes in Cerebral Oxygenation and Blood Flow at Rest and During Exercise in Normotensive and Hypertensive Individuals. Curr Hypertens Rep 2020; 22:71. [PMID: 32852614 DOI: 10.1007/s11906-020-01075-9] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
Abstract
PURPOSE OF REVIEW Summarize the methods used for measurement of cerebral blood flow and oxygenation; describe the effects of hypertension on cerebral blood flow and oxygenation. RECENT FINDINGS Information regarding the effects of hypertension on cerebrovascular circulation during exercise is very limited, despite a plethora of methods to help with its assessment. In normotensive individuals performing incremental exercise testing, total blood flow to the brain increases. In contrast, the few studies performed in hypertensive patients suggest a smaller increase in cerebral blood flow, despite higher blood pressure levels. Endothelial dysfunction and increased vasoconstrictor concentration, as well as large vessel atherosclerosis and decreased small vessel number, have been proposed as the underlying mechanisms. Hypertension may adversely impact oxygen and blood delivery to the brain, both at rest and during exercise. Future studies should utilize the newer, noninvasive techniques to better characterize the interplay between the brain and exercise in hypertension.
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Affiliation(s)
- Georgios A Triantafyllou
- 3rd Department of Internal Medicine, Papageorgiou Hospital, Aristotle University of Thessaloniki, Ring Road Nea Eukarpia, 56403, Thessaloniki, Greece.,Division of Pulmonary, Allergy and Critical Care Medicine, University of Pittsburgh Medical Center, 3459 Fifth Avenue, Pittsburgh, PA, 15213, USA
| | - Konstantina Dipla
- Exercise Physiology and Biochemistry Laboratory, Department of Sports Science at Serres, Aristotle University of Thessaloniki, Agios Ioannis, 62122, Serres, Greece
| | - Areti Triantafyllou
- 3rd Department of Internal Medicine, Papageorgiou Hospital, Aristotle University of Thessaloniki, Ring Road Nea Eukarpia, 56403, Thessaloniki, Greece.
| | - Eugenia Gkaliagkousi
- 3rd Department of Internal Medicine, Papageorgiou Hospital, Aristotle University of Thessaloniki, Ring Road Nea Eukarpia, 56403, Thessaloniki, Greece
| | - Stella Douma
- 3rd Department of Internal Medicine, Papageorgiou Hospital, Aristotle University of Thessaloniki, Ring Road Nea Eukarpia, 56403, Thessaloniki, Greece
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van der Plas MCE, Teeuwisse WM, Schmid S, Chappell M, van Osch MJP. High temporal resolution arterial spin labeling MRI with whole-brain coverage by combining time-encoding with Look-Locker and simultaneous multi-slice imaging. Magn Reson Med 2019; 81:3734-3744. [PMID: 30828873 PMCID: PMC6593668 DOI: 10.1002/mrm.27692] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2018] [Revised: 01/23/2019] [Accepted: 01/24/2019] [Indexed: 11/07/2022]
Abstract
PURPOSE The goal of this study was to achieve high temporal resolution, multi-time point pseudo-continuous arterial spin labeling (pCASL) MRI in a time-efficient manner, while maintaining whole-brain coverage. METHODS A Hadamard 8-matrix was used to dynamically encode the pCASL labeling train, thereby providing the first source of temporal information. The second method for obtaining dynamic arterial spin labeling (ASL) signal consisted of a Look-Locker (LL) readout of 4 phases that are acquired with a flip-angle sweep to maintain constant sensitivity over the phases. To obtain whole-brain coverage in the short LL interval, 4 slices were excited simultaneously by multi-banded radiofrequency pulses. After subtraction according to the Hadamard scheme, the ASL signal was corrected for the use of the flip-angle sweep and background suppression pulses. The BASIL toolkit of the Oxford Centre for FMRIB was used to quantify the ASL signal. RESULTS By combining a time-encoded pCASL labeling scheme with an LL readout and simultaneous multi-slice acquisition, 28 time points of 16 slices with a 75- or 150-ms time resolution were acquired in a total scan time of 10 minutes 20 seconds, from which cerebral blood flow (CBF) maps, arterial transit time maps, and arterial blood volume could be determined. CONCLUSION Whole-brain ASL images were acquired with a 75-ms time resolution for the angiography and 150-ms resolution for the perfusion phase by combining the proposed techniques. Reducing the total scan time to 1 minute 18 seconds still resulted in reasonable CBF maps, which demonstrates the feasibility of this approach for practical studies on brain hemodynamics.
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Affiliation(s)
- Merlijn C E van der Plas
- C.J. Gorter Center for High Field MRI, Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Wouter M Teeuwisse
- C.J. Gorter Center for High Field MRI, Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Sophie Schmid
- C.J. Gorter Center for High Field MRI, Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Michael Chappell
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom.,Institute of Biomedical Engineering, Research Council UK (EP/P012361/1), University of Oxford, Oxford, United Kingdom
| | - Matthias J P van Osch
- C.J. Gorter Center for High Field MRI, Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
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Hua J, Liu P, Kim T, Donahue M, Rane S, Chen JJ, Qin Q, Kim SG. MRI techniques to measure arterial and venous cerebral blood volume. Neuroimage 2019; 187:17-31. [PMID: 29458187 PMCID: PMC6095829 DOI: 10.1016/j.neuroimage.2018.02.027] [Citation(s) in RCA: 63] [Impact Index Per Article: 12.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2017] [Revised: 02/12/2018] [Accepted: 02/14/2018] [Indexed: 12/14/2022] Open
Abstract
The measurement of cerebral blood volume (CBV) has been the topic of numerous neuroimaging studies. To date, however, most in vivo imaging approaches can only measure CBV summed over all types of blood vessels, including arterial, capillary and venous vessels in the microvasculature (i.e. total CBV or CBVtot). As different types of blood vessels have intrinsically different anatomy, function and physiology, the ability to quantify CBV in different segments of the microvascular tree may furnish information that is not obtainable from CBVtot, and may provide a more sensitive and specific measure for the underlying physiology. This review attempts to summarize major efforts in the development of MRI techniques to measure arterial (CBVa) and venous CBV (CBVv) separately. Advantages and disadvantages of each type of method are discussed. Applications of some of the methods in the investigation of flow-volume coupling in healthy brains, and in the detection of pathophysiological abnormalities in brain diseases such as arterial steno-occlusive disease, brain tumors, schizophrenia, Huntington's disease, Alzheimer's disease, and hypertension are demonstrated. We believe that the continual development of MRI approaches for the measurement of compartment-specific CBV will likely provide essential imaging tools for the advancement and refinement of our knowledge on the exquisite details of the microvasculature in healthy and diseased brains.
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Affiliation(s)
- Jun Hua
- Neurosection, Div. of MRI Research, Dept. of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, USA; F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA.
| | - Peiying Liu
- Neurosection, Div. of MRI Research, Dept. of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, USA; F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Tae Kim
- Department of Radiology, University of Pittsburgh, Pittsburgh, PA, USA; Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA
| | - Manus Donahue
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA; Department of Neurology, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Swati Rane
- Radiology, University of Washington Medical Center, Seattle, WA, USA
| | - J Jean Chen
- Rotman Research Institute, Baycrest Centre, Canada; Department of Medical Biophysics, University of Toronto, Canada
| | - Qin Qin
- Neurosection, Div. of MRI Research, Dept. of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, USA; F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Seong-Gi Kim
- Center for Neuroscience Imaging Research, Institute for Basic Science (IBS), Suwon, South Korea; Department of Biomedical Engineering, Sungkyunkwan University, Suwon, South Korea
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