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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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Ibaraki M, Nakamura K, Matsubara K, Shinohara Y, Kinoshita T. Effect of hematocrit on cerebral blood flow measured by pseudo-continuous arterial spin labeling MRI: A comparative study with 15O-water positron emission tomography. Magn Reson Imaging 2021; 84:58-68. [PMID: 34562565 DOI: 10.1016/j.mri.2021.09.012] [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: 03/30/2021] [Revised: 09/16/2021] [Accepted: 09/18/2021] [Indexed: 11/30/2022]
Abstract
INTRODUCTION In cerebral blood flow (CBF) quantification with pseudo-continuous arterial spin labeling (pCASL) MRI, arterial blood T1 (T1a) is usually fixed to a typical value (e.g., 1650 ms). However, individual T1a depends strongly on hematocrit (Hct) level. To investigate the utility of Hct-based T1a as an alternative to the fixed T1a method, we performed a comparative study with 15O-water positron emission tomography (PET). METHODS For patients with unilateral occlusion or stenosis of major arteries, hemispheric CBF on the healthy side was measured using pCASL and 15O-water PET. The pCASL CBFs were calculated with both (a) fixed T1a (1650 ms) and (b) individual T1a estimated from blood-sampled Hct (Hct-based T1a). Correlation coefficients of Hct-CBF were calculated and compared between pCASL and PET. RESULTS In pCASL, CBF with fixed T1a showed a strong negative correlation with Hct (r = -0.568), which was reduced with individual Hct-based T1a (r = -0.341 to -0.190), consistent with the Hct-CBF relation measured with PET (r = -0.349). DISCUSSION AND CONCLUSION We demonstrated that Hct-based T1a resulted in smaller inter-individual variations in pCASL CBF and an inverse Hct-CBF relationship more similar to that of PET. Care must be taken in the interpretation of pCASL CBF imaging in relation to Hct level even in subjects without anemia. Further comparative studies are needed to investigate whether advanced techniques improve pCASL CBF quantification at the individual level.
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Affiliation(s)
- Masanobu Ibaraki
- Department of Radiology and Nuclear Medicine, Akita Research Institute of Brain and Blood Vessels, Akita, Japan.
| | - Kazuhiro Nakamura
- Department of Radiology and Nuclear Medicine, Akita Research Institute of Brain and Blood Vessels, Akita, Japan.
| | - Keisuke Matsubara
- Department of Radiology and Nuclear Medicine, Akita Research Institute of Brain and Blood Vessels, Akita, Japan.
| | - Yuki Shinohara
- Department of Radiology and Nuclear Medicine, Akita Research Institute of Brain and Blood Vessels, Akita, Japan.
| | - Toshibumi Kinoshita
- Department of Radiology and Nuclear Medicine, Akita Research Institute of Brain and Blood Vessels, Akita, Japan.
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Stoeter P, Roa-Sanchez P, Gonzalez CF, Speckter H, Oviedo J, Bido P. Cerebral blood flow in dystonia due to pantothenate kinase-associated neurodegeneration. Neuroradiol J 2020; 33:479-485. [PMID: 32851917 DOI: 10.1177/1971400920943967] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
BACKGROUND AND PURPOSE The aim of this study was to look for deviations of cerebral perfusion in patients suffering from pantothenate kinase-associated neurodegeneration, where the globus pallidus is affected by severe accumulation of iron. MATERIAL AND METHODS Under resting conditions, cerebral blood flow was measured by the magnetic resonance imaging technique of arterial spin labelling in cortical areas and basal ganglia in eight pantothenate kinase-associated neurodegeneration patients and 14 healthy age-matched control subjects and correlated to T2* time of these areas and - in patients - to clinical parameters. RESULTS Despite highly significant differences of T2* time of the globus pallidus (20 vs 39 ms, p < 0.001), perfusion values of this nucleus were nearly identical in both groups (32 ± 3.3 vs 31 ± 4.0 ml/min/100 g) as well as in total brain gray matter (both 62 ± 6.7 resp. ±10.3 ml/min/100 g), putamen (41 ± 5.4 vs 40 ± 6.1 ml/min/100 g), in selected cortical regions, and the cerebellum. Correlations between perfusion and T2* time to clinical data did not reach significance (p > 0.05). CONCLUSION The absence of any obvious deviations of perfusion in the group of patients during a resting condition does not support the view that (non-functional) vascular pathology is a major pathogenic factor in pantothenate kinase-associated neurodegeneration in the younger age group. The findings underline the value of the arterial spin technique to measure cerebral blood flow in areas of disturbed susceptibility.
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Affiliation(s)
- Peter Stoeter
- Department of Radiology, Centros de Diagnóstico y Medicina Avanzada y de Conferencias Médicas y Telemedicina, Dominican Republic
| | - Pedro Roa-Sanchez
- Department of Neurology, Centros de Diagnóstico y Medicina Avanzada y de Conferencias Médicas y Telemedicina, Dominican Republic
| | - Cesar F Gonzalez
- Department of Radiology, Centros de Diagnóstico y Medicina Avanzada y de Conferencias Médicas y Telemedicina, Dominican Republic
| | - Herwin Speckter
- Department of Radiology, Centros de Diagnóstico y Medicina Avanzada y de Conferencias Médicas y Telemedicina, Dominican Republic
| | - Jairo Oviedo
- Department of Radiology, Centros de Diagnóstico y Medicina Avanzada y de Conferencias Médicas y Telemedicina, Dominican Republic
| | - Pamela Bido
- Department of Neurology, Centros de Diagnóstico y Medicina Avanzada y de Conferencias Médicas y Telemedicina, Dominican Republic
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Bladt P, van Osch MJP, Clement P, Achten E, Sijbers J, den Dekker AJ. Supporting measurements or more averages? How to quantify cerebral blood flow most reliably in 5 minutes by arterial spin labeling. Magn Reson Med 2020; 84:2523-2536. [PMID: 32424947 PMCID: PMC7402018 DOI: 10.1002/mrm.28314] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2019] [Revised: 03/19/2020] [Accepted: 04/17/2020] [Indexed: 11/29/2022]
Abstract
Purpose To determine whether sacrificing part of the scan time of pseudo‐continuous arterial spin labeling (PCASL) for measurement of the labeling efficiency and blood
T1 is beneficial in terms of CBF quantification reliability. Methods In a simulation framework, 5‐minute scan protocols with different scan time divisions between PCASL data acquisition and supporting measurements were evaluated in terms of CBF estimation variability across both noise and ground truth parameter realizations taken from the general population distribution. The entire simulation experiment was repeated for a single‐post‐labeling delay (PLD), multi‐PLD, and free‐lunch time‐encoded (te‐FL) PCASL acquisition strategy. Furthermore, a real data study was designed for preliminary validation. Results For the considered population statistics, measuring the labeling efficiency and the blood
T1 proved beneficial in terms of CBF estimation variability for any distribution of the 5‐minute scan time compared to only acquiring ASL data. Compared to single‐PLD PCASL without support measurements as recommended in the consensus statement, a 26%, 33%, and 42% reduction in relative CBF estimation variability was found for optimal combinations of supporting measurements with single‐PLD, free‐lunch, and multi‐PLD PCASL data acquisition, respectively. The benefit of taking the individual variation of blood
T1 into account was also demonstrated in the real data experiment. Conclusions Spending time to measure the labeling efficiency and the blood
T1 instead of acquiring more averages of the PCASL data proves to be advisable for robust CBF quantification in the general population.
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Affiliation(s)
- Piet Bladt
- imec - Vision Lab, Department of Physics, University of Antwerp, Antwerp, Belgium
| | - Matthias J P van Osch
- Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands.,Leiden Institute of Brain and Cognition, Leiden University, Leiden, The Netherlands
| | - Patricia Clement
- Department of Radiology and Nuclear Medicine, Ghent University, Ghent, Belgium
| | - Eric Achten
- Department of Radiology and Nuclear Medicine, Ghent University, Ghent, Belgium
| | - Jan Sijbers
- imec - Vision Lab, Department of Physics, University of Antwerp, Antwerp, Belgium
| | - Arnold J den Dekker
- imec - Vision Lab, Department of Physics, University of Antwerp, Antwerp, Belgium
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