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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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Jiang YY, Zhong ZL, Zuo M. Three-dimensional arterial spin labeling and diffusion kurtosis imaging in evaluating perfusion and infarct area size in acute cerebral ischemia. World J Clin Cases 2022; 10:5586-5594. [PMID: 35979093 PMCID: PMC9258361 DOI: 10.12998/wjcc.v10.i17.5586] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/06/2022] [Revised: 03/01/2022] [Accepted: 04/09/2022] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND Early thrombolytic therapy is crucial to treat acute cerebral infarction, especially since the onset of thrombolytic therapy takes 1-6 h. Therefore, early diagnosis and evaluation of cerebral infarction is important.
AIM To investigate the diagnostic value of magnetic resonance multi-delay three-dimensional arterial spin labeling (3DASL) and diffusion kurtosis imaging (DKI) in evaluating the perfusion and infarct area size in patients with acute cerebral ischemia.
METHODS Eighty-four patients who experienced acute cerebral ischemia from March 2019 to February 2021 were included. All patients in the acute stage underwent magnetic resonance-based examination, and the data were processed by the system’s own software. The apparent diffusion coefficient (ADC), average diffusion coefficient (MD), axial diffusion (AD), radial diffusion (RD), average kurtosis (MK), radial kurtosis (fairly RK), axial kurtosis (AK), and perfusion parameters post-labeling delays (PLD) in the focal area and its corresponding area were compared. The correlation between the lesion area of cerebral infarction under MK and MD and T2-weighted imaging (T2WI) was analyzed.
RESULTS The DKI parameters of focal and control areas in the study subjects were compared. The ADC, MD, AD, and RD values in the lesion area were significantly lower than those in the control area. The MK, RK, and AK values in the lesion area were significantly higher than those in the control area. The MK/MD value in the infarct lesions was used to determine the matching situation. MK/MD < 5 mm was considered matching and MK/MD ≥ 5 mm was considered mismatching. PLD1.5s and PLD2.5s perfusion parameters in the central, peripheral, and control areas of the infarct lesions in MK/MD-matched and -unmatched patients were not significantly different. PLD1.5s and PLD2.5s perfusion parameter values in the central area of the infarct lesions in MK/MD-matched and -unmatched patients were significantly lower than those in peripheral and control areas. The MK and MD maps showed a lesion area of 20.08 ± 5.74 cm2 and 22.09 ± 5.58 cm2, respectively. T2WI showed a lesion area of 19.76 ± 5.02 cm2. There were no significant differences in the cerebral infarction lesion areas measured using the three methods. MK, MD, and T2WI showed a good correlation.
CONCLUSION DKI parameters showed significant difference between the focal and control areas in patients with acute ischemic cerebral infarction. 3DASL can effectively determine the changes in perfusion levels in the lesion area. There was a high correlation between the area of the infarct lesions diagnosed by DKI and T2WI.
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Affiliation(s)
- Yan-Yan Jiang
- Department of Magnetic Resonance, Wuhan Asia General Hospital, Wuhan 430056, Hubei Province, China
| | - Zhi-Lin Zhong
- Department of Radiology, Wuhan Yaxin General Hospital, Wuhan 430056, Hubei Province, China
| | - Min Zuo
- Department of Radiology, Wuhan Hanyang Hospital, Wuhan University of Science and Technology, Wuhan 430050, Hubei Province, China
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Delmas J, Toupin S, Pfeuffer J, Chateil JF. A practical guide to optimize arterial spin labeling in neonates at 1.5 Tesla: what the radiologist needs to know. Pediatr Radiol 2022; 52:1370-1380. [PMID: 35249145 DOI: 10.1007/s00247-022-05288-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/26/2021] [Revised: 12/04/2021] [Accepted: 01/15/2022] [Indexed: 11/30/2022]
Abstract
Arterial spin labeling magnetic resonance imaging is highly suited to the exploration of brain perfusion in neonates and has the potential to provide relevant complementary information to neuroimaging studies, with insights into neurodevelopmental outcomes. Applying this technique within the first days of life is challenging and requires specific technical adaptations. The literature on this topic is scarce and heterogeneous, especially on 1.5-T scanners, limiting widespread clinical adoption. This paper aims to describe a simple approach for arterial spin labeling in neonates, with key considerations for radiologists.
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Affiliation(s)
- Jean Delmas
- Pediatric and Prenatal Imaging Department, Hôpital Pellegrin, CHU de Bordeaux, Place Amélie Raba Léon, F-33000, Bordeaux, France.
| | - Solenn Toupin
- Scientific Partnerships, Siemens Healthcare France, Saint-Denis, France
| | - Josef Pfeuffer
- Application Development, Siemens Healthcare, Erlangen, Germany
| | - Jean-François Chateil
- Pediatric and Prenatal Imaging Department, Hôpital Pellegrin, CHU de Bordeaux, Place Amélie Raba Léon, F-33000, Bordeaux, France
- University of Bordeaux, CNRS, CRMSB, UMR 5536, F-33076, Bordeaux, France
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Woods JG, Wong EC, Boyd EC, Bolar DS. VESPA ASL: VElocity and SPAtially Selective Arterial Spin Labeling. Magn Reson Med 2022; 87:2667-2684. [PMID: 35061920 DOI: 10.1002/mrm.29159] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2021] [Revised: 11/25/2021] [Accepted: 12/22/2021] [Indexed: 01/22/2023]
Abstract
PURPOSE Spatially selective arterial spin labeling (ASL) perfusion MRI is sensitive to arterial transit times (ATT) that can result in inaccurate perfusion quantification when ATTs are long. Velocity-selective ASL is robust to this effect because blood is labeled within the imaging region, allowing immediate label delivery. However, velocity-selective ASL cannot characterize ATTs, which can provide important clinical information. Here, we introduce a novel pulse sequence, called VESPA ASL, that combines velocity-selective and pseudo-continuous ASL to simultaneously label different pools of arterial blood for robust cerebral blood flow (CBF) and ATT measurement. METHODS The VESPA ASL sequence is similar to velocity-selective ASL, but the velocity-selective labeling is made spatially selective, and pseudo-continuous ASL is added to fill the inflow time. The choice of inflow time and other sequence settings were explored. VESPA ASL was compared to multi-delay pseudo-continuous ASL and velocity-selective ASL through simulations and test-retest experiments in healthy volunteers. RESULTS VESPA ASL is shown to accurately measure CBF in the presence of long ATTs, and ATTs < TI can also be measured. Measurements were similar to established ASL techniques when ATT was short. When ATT was long, VESPA ASL measured CBF more accurately than multi-delay pseudo-continuous ASL, which tended to underestimate CBF. CONCLUSION VESPA ASL is a novel and robust approach to simultaneously measure CBF and ATT and offers important advantages over existing methods. It fills an important clinical need for noninvasive perfusion and transit time imaging in vascular diseases with delayed arterial transit.
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Affiliation(s)
- Joseph G Woods
- Center for Functional Magnetic Resonance Imaging, Department of Radiology, University of California San Diego, La Jolla, California, USA
| | - Eric C Wong
- Center for Functional Magnetic Resonance Imaging, Department of Radiology, University of California San Diego, La Jolla, California, USA.,Department of Psychiatry, University of California San Diego, La Jolla, California, USA
| | - Emma C Boyd
- Center for Functional Magnetic Resonance Imaging, Department of Radiology, University of California San Diego, La Jolla, California, USA.,Department of Neurosciences, University of California San Diego, La Jolla, California, USA
| | - Divya S Bolar
- Center for Functional Magnetic Resonance Imaging, Department of Radiology, University of California San Diego, La Jolla, California, USA
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