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Xu F, Xu C, Zhu D, Liu D, Lu H, Qin Q. Evaluating cerebrovascular reactivity measured by velocity selective inversion arterial spin labeling with different post-labeling delays: The effect of fast flow. Magn Reson Med 2024; 92:2065-2073. [PMID: 38852173 PMCID: PMC11341248 DOI: 10.1002/mrm.30166] [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: 02/03/2024] [Revised: 04/24/2024] [Accepted: 05/08/2024] [Indexed: 06/11/2024]
Abstract
PURPOSE Velocity selective arterial spin labeling (VSASL) quantification assumes that the labeled bolus continuously moves into the imaging voxel during the post-labeling delay (PLD). Faster blood flow could lead to a bolus duration shorter than the applied PLD of VSASL and cause underestimation of cerebral blood flow (CBF). This study aims to evaluate the performance of velocity-selective inversion (VSI) prepared arterial spin labeling (ASL) with different PLDs and pseudo-continuous ASL (PCASL) for quantification of hypercapnia-induced cerebrovascular reactivity (CVR), using phase-contrast (PC) MRI as a global reference. METHODS We compared CVR obtained by VSI-ASL with PLD of 1520 ms (VSASL-1520), 1000 ms (VSASL-1000), and 500 ms (VSASL-500), PCASL with PLD of 1800 ms (PCASL-1800), and PC MRI on eight healthy volunteers at two sessions. RESULTS Compared with PC MRI, VSASL-1520 produced significantly lower global CVR values, while PCASL-1800, VSASL-1000, and VSASL-500 yielded more consistent results. The reduced CVR in VSASL-1520 was more pronounced in carotid territories including frontal and temporal lobes than in vertebral territories such as the occipital lobe. This is largely caused by the underestimated perfusion during hypercapnia due to the reduced bolus duration being less than the PLD. CONCLUSION Although VSASL offers certain advantages over spatially selective ASL due to its reduced susceptibility to delayed ATT, this technique is prone to biases when the ATT is excessively short. Therefore, a short PLD should be employed for reliable perfusion and CVR quantification in populations or conditions with fast flow.
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Affiliation(s)
- Feng Xu
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University, Baltimore, MD, USA
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Cuimei Xu
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University, Baltimore, MD, USA
| | - Dan Zhu
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University, Baltimore, MD, USA
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Dapeng Liu
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University, Baltimore, MD, USA
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Hanzhang Lu
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University, Baltimore, MD, USA
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Qin Qin
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University, Baltimore, MD, USA
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
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Raghavan V, Sobczyk O, Sayin ES, Poublanc J, Skanda A, Duffin J, Venkatraghavan L, Fisher JA, Mikulis DJ. Assessment of Cerebrovascular Reactivity Using CO 2-BOLD MRI: A 15-Year, Single Center Experience. J Magn Reson Imaging 2024; 60:954-961. [PMID: 38135486 DOI: 10.1002/jmri.29176] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2023] [Revised: 11/21/2023] [Accepted: 11/22/2023] [Indexed: 12/24/2023] Open
Abstract
BACKGROUND Cerebrovascular reactivity (CVR) is a measure of the change in cerebral blood flow (CBF) in response to a vasoactive challenge. It is a useful indicator of the brain's vascular health. PURPOSE To evaluate the factors that influence successful and unsuccessful CVR examinations using precise arterial and end-tidal partial pressure of CO2 control during blood oxygen level-dependent (BOLD) MRI. STUDY TYPE Retrospective. SUBJECTS Patients that underwent a CVR between October 2005 and May 2021 were studied (total of 1162 CVR examinations). The mean (±SD) age was 46.1 (±18.8) years, and 352 patients (43%) were female. FIELD STRENGTH/SEQUENCE 3 T; T1-weighted images, T2*-weighed two-dimensional gradient-echo sequence with standard echo-planar readout. ASSESSMENT Measurements were obtained following precise hypercapnic stimuli using BOLD MRI as a surrogate of CBF. Successful CVR examinations were defined as those where: 1) patients were able to complete CVR testing, and 2) a clinically useful CVR map was generated. Unsuccessful examinations were defined as those where patients were not able to complete the CVR examination or the CVR maps were judged to be unreliable due to, for example, excessive head motion, and poor PETCO2 targeting. STATISTICAL ANALYSIS Successful and unsuccessful CVR examinations between hypercapnic stimuli, and between different patterns of stimulus were compared with Chi-Square tests. Interobserver variability was determined by using the intraclass correlation coefficient (P < 0.05 is significant). RESULTS In total 1115 CVR tests in 662 patients were included in the final analysis. The success rate of generating CVR maps was 90.8% (1012 of 1115). Among the different hypercapnic stimuli, those containing a step plus a ramp protocol was the most successful (95.18%). Among the unsuccessful examinations (9.23%), most were patient related (89.3%), the most common of which was difficulty breathing. DATA CONCLUSION CO2-BOLD MRI CVR studies are well tolerated with a high success rate. EVIDENCE LEVEL 4 TECHNICAL EFFICACY: Stage 3.
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Affiliation(s)
- Vishvak Raghavan
- School of Computer Science, McGill University, Montreal, Quebec, Canada
| | - Olivia Sobczyk
- Joint Department of Medical Imaging and the Functional Neuroimaging Laboratory, University Health Network, Toronto, Ontario, Canada
| | - Ece Su Sayin
- Joint Department of Medical Imaging and the Functional Neuroimaging Laboratory, University Health Network, Toronto, Ontario, Canada
- Department of Physiology, University of Toronto, Toronto, Ontario, Canada
| | - Julien Poublanc
- Joint Department of Medical Imaging and the Functional Neuroimaging Laboratory, University Health Network, Toronto, Ontario, Canada
| | - Abby Skanda
- Joint Department of Medical Imaging and the Functional Neuroimaging Laboratory, University Health Network, Toronto, Ontario, Canada
| | - James Duffin
- Department of Physiology, University of Toronto, Toronto, Ontario, Canada
| | - Lashmi Venkatraghavan
- Department of Physiology, University of Toronto, Toronto, Ontario, Canada
- Institute of Medical Sciences, University of Toronto, Toronto, Ontario, Canada
| | - Joseph A Fisher
- Joint Department of Medical Imaging and the Functional Neuroimaging Laboratory, University Health Network, Toronto, Ontario, Canada
- Department of Physiology, University of Toronto, Toronto, Ontario, Canada
- Institute of Medical Sciences, University of Toronto, Toronto, Ontario, Canada
| | - David J Mikulis
- Joint Department of Medical Imaging and the Functional Neuroimaging Laboratory, University Health Network, Toronto, Ontario, Canada
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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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4
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Engle J, Saberi P, Bain P, Ikram A, Selim M, Soman S. Oxygen extraction fraction (OEF) values and applications in neurological diseases. Neurol Sci 2024; 45:3007-3020. [PMID: 38367153 DOI: 10.1007/s10072-024-07362-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2023] [Accepted: 01/22/2024] [Indexed: 02/19/2024]
Abstract
One of the goals of this systematic review is to provide a meta-analysis-derived mean OEF of healthy volunteers. Another aim of this study is to indicate the OEF ranges of various neurological pathologies. Potential clinical applications of OEF metrics are presented. Peer-reviewed studies reporting OEF metrics derived from computed tomography (CT)/positron emission tomography (PET) and/or magnetic resonance imaging (MRI) were considered. Databases utilized included MEDLINE, PubMed, EMBASE, Web of Science, and Google Scholar. The Newcastle-Ottawa scoring system was used for evaluating studies. R Studio was utilized for the meta-analysis calculations when appropriate. The GRADE framework was utilized to assess additional findings. Of 2267 potential studies, 165 met the inclusion criteria. The healthy volunteer meta-analysis included 339 subjects and found a mean OEF value of 38.87 (37.38, 40.36), with a prediction interval of 32.40-45.34. There were no statistical differences in OEF values derived from PET versus MRI. We provided a GRADE A certainty rating for the use of OEF metrics to predict stroke occurrence in patients with symptomatic carotid or cerebral vessel disease. We provided a GRADE B certainty rating for monitoring treatment response in Moyamoya disease. Use of OEF metrics in diagnosing and/or monitoring other conditions had a GRADE C certainty rating or less. OEF might have a role in diagnosing and monitoring patients with symptomatic carotid or cerebral vessel disease and Moyamoya disease. While we found insufficient evidence to support measuring OEF metrics in other patient populations, in many cases, further studies are warranted.
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Affiliation(s)
- Joshua Engle
- Beth Israel Deaconess Medical Center (Radiology), Boston, MA, USA.
| | - Parastoo Saberi
- Beth Israel Deaconess Medical Center (Radiology), Boston, MA, USA
| | - Paul Bain
- Harvard Medical School, Boston, MA, USA
| | - Asad Ikram
- Beth Israel Deaconess Medical Center (Radiology), Boston, MA, USA
| | - Magdy Selim
- Beth Israel Deaconess Medical Center (Radiology), Boston, MA, USA
| | - Salil Soman
- Beth Israel Deaconess Medical Center (Radiology), Boston, MA, USA
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5
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Fahlström M, Sousa JM, Svedung Wettervik T, Berglund J, Enblad P, Lewén A, Wikström J. A mathematical model for temporal cerebral blood flow response to acetazolamide evaluated in patients with Moyamoya disease. Magn Reson Imaging 2024; 110:35-42. [PMID: 38574981 DOI: 10.1016/j.mri.2024.03.044] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2024] [Revised: 03/27/2024] [Accepted: 03/31/2024] [Indexed: 04/06/2024]
Abstract
BACKGROUND Paired cerebral blood flow (CBF) measurement is usually acquired before and after vasoactive stimulus to estimate cerebrovascular reserve (CVR). However, CVR may be confounded because of variations in time-to-maximum CBF response (tmax) following acetazolamide injection. With a mathematical model, CVR can be calculated insensitive to variations in tmax, and a model offers the possibility to calculate additional model-derived parameters. A model that describes the temporal CBF response following a vasodilating acetazolamide injection is proposed and evaluated. METHODS A bi-exponential model was adopted and fitted to four CBF measurements acquired using arterial spin labelling before and initialised at 5, 15 and 25 min after acetazolamide injection in a total of fifteen patients with Moyamoya disease. Curve fitting was performed using a non-linear least squares method with a priori constraints based on simulations. RESULTS Goodness of fit (mean absolute error) varied between 0.30 and 0.62 ml·100 g-1·min-1. Model-derived CVR was significantly higher compared to static CVR measures. Maximum CBF increase occurred earlier in healthy- compared to diseased vascular regions. CONCLUSIONS The proposed mathematical model offers the possibility to calculate CVR insensitive to variations in time to maximum CBF response which gives a more detailed characterisation of CVR compared to static CVR measures. Although the mathematical model adapts generally well to this dataset of patients with MMD it should be considered as experimental; hence, further studies in healthy populations and other patient cohorts are warranted.
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Affiliation(s)
- Markus Fahlström
- Molecular Imaging and Medical Physics, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden; Medical Physics, Uppsala University Hospital, Uppsala, Sweden.
| | - Joao M Sousa
- Molecular Imaging and Medical Physics, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden; Medical Physics, Uppsala University Hospital, Uppsala, Sweden.
| | | | - Johan Berglund
- Molecular Imaging and Medical Physics, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden; Medical Physics, Uppsala University Hospital, Uppsala, Sweden.
| | - Per Enblad
- Neurosurgery, Department of Medical Sciences, Uppsala University, Uppsala, Sweden.
| | - Anders Lewén
- Neurosurgery, Department of Medical Sciences, Uppsala University, Uppsala, Sweden.
| | - Johan Wikström
- Neuroradiology, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden.
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Hussein R, Shin D, Zhao MY, Guo J, Davidzon G, Steinberg G, Moseley M, Zaharchuk G. Turning brain MRI into diagnostic PET: 15O-water PET CBF synthesis from multi-contrast MRI via attention-based encoder-decoder networks. Med Image Anal 2024; 93:103072. [PMID: 38176356 PMCID: PMC10922206 DOI: 10.1016/j.media.2023.103072] [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: 08/15/2022] [Revised: 12/20/2023] [Accepted: 12/20/2023] [Indexed: 01/06/2024]
Abstract
Accurate quantification of cerebral blood flow (CBF) is essential for the diagnosis and assessment of a wide range of neurological diseases. Positron emission tomography (PET) with radiolabeled water (15O-water) is the gold-standard for the measurement of CBF in humans, however, it is not widely available due to its prohibitive costs and the use of short-lived radiopharmaceutical tracers that require onsite cyclotron production. Magnetic resonance imaging (MRI), in contrast, is more accessible and does not involve ionizing radiation. This study presents a convolutional encoder-decoder network with attention mechanisms to predict the gold-standard 15O-water PET CBF from multi-contrast MRI scans, thus eliminating the need for radioactive tracers. The model was trained and validated using 5-fold cross-validation in a group of 126 subjects consisting of healthy controls and cerebrovascular disease patients, all of whom underwent simultaneous 15O-water PET/MRI. The results demonstrate that the model can successfully synthesize high-quality PET CBF measurements (with an average SSIM of 0.924 and PSNR of 38.8 dB) and is more accurate compared to concurrent and previous PET synthesis methods. We also demonstrate the clinical significance of the proposed algorithm by evaluating the agreement for identifying the vascular territories with impaired CBF. Such methods may enable more widespread and accurate CBF evaluation in larger cohorts who cannot undergo PET imaging due to radiation concerns, lack of access, or logistic challenges.
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Affiliation(s)
- Ramy Hussein
- Radiological Sciences Laboratory, Department of Radiology, Stanford University, Stanford, CA 94305, USA.
| | - David Shin
- Global MR Applications & Workflow, GE Healthcare, Menlo Park, CA 94025, USA
| | - Moss Y Zhao
- Radiological Sciences Laboratory, Department of Radiology, Stanford University, Stanford, CA 94305, USA; Stanford Cardiovascular Institute, Stanford University, Stanford, CA 94305, USA
| | - Jia Guo
- Department of Bioengineering, University of California, Riverside, CA 92521, USA
| | - Guido Davidzon
- Division of Nuclear Medicine, Department of Radiology, Stanford University, Stanford, CA 94305, USA
| | - Gary Steinberg
- Department of Neurosurgery, Stanford University, Stanford, CA 94304, USA
| | - Michael Moseley
- Radiological Sciences Laboratory, Department of Radiology, Stanford University, Stanford, CA 94305, USA
| | - Greg Zaharchuk
- Radiological Sciences Laboratory, Department of Radiology, Stanford University, Stanford, CA 94305, USA
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7
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Zhao MY, Tong E, Duarte Armindo R, Fettahoglu A, Choi J, Bagley J, Yeom KW, Moseley M, Steinberg GK, Zaharchuk G. Short- and Long-Term MRI Assessed Hemodynamic Changes in Pediatric Moyamoya Patients After Revascularization. J Magn Reson Imaging 2024; 59:1349-1357. [PMID: 37515518 DOI: 10.1002/jmri.28902] [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: 06/04/2023] [Revised: 06/28/2023] [Accepted: 06/29/2023] [Indexed: 07/31/2023] Open
Abstract
BACKGROUND Cerebrovascular reserve (CVR) reflects the capacity of cerebral blood flow (CBF) to change following a vasodilation challenge. Decreased CVR is associated with a higher stroke risk in patients with cerebrovascular diseases. While revascularization can improve CVR and reduce this risk in adult patients with vasculopathy such as those with Moyamoya disease, its impact on hemodynamics in pediatric patients remains to be elucidated. Arterial spin labeling (ASL) is a quantitative MRI technique that can measure CBF, CVR, and arterial transit time (ATT) non-invasively. PURPOSE To investigate the short- and long-term changes in hemodynamics after bypass surgeries in patients with Moyamoya disease. STUDY TYPE Longitudinal. POPULATION Forty-six patients (11 months-18 years, 28 females) with Moyamoya disease. FIELD STRENGTH/SEQUENCE 3-T, single- and multi-delay ASL, T1-weighted, T2-FLAIR, 3D MRA. ASSESSMENT Imaging was performed 2 weeks before and 1 week and 6 months after surgical intervention. Acetazolamide was employed to induce vasodilation during the imaging procedure. CBF and ATT were measured by fitting the ASL data to the general kinetic model. CVR was computed as the percentage change in CBF. The mean CBF, ATT, and CVR values were measured in the regions affected by vasculopathy. STATISTICAL TESTS Pre- and post-revascularization CVR, CBF, and ATT were compared for different regions of the brain. P-values <0.05 were considered statistically significant. RESULTS ASL-derived CBF in flow territories affected by vasculopathy significantly increased after bypass by 41 ± 31% within a week. At 6 months, CBF significantly increased by 51 ± 34%, CVR increased by 68 ± 33%, and ATT was significantly reduced by 6.6 ± 2.9%. DATA CONCLUSION There may be short- and long-term improvement in the hemodynamic parameters of pediatric Moyamoya patients after bypass surgery. EVIDENCE LEVEL 4 TECHNICAL EFFICACY: Stage 2.
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Affiliation(s)
- Moss Y Zhao
- Department of Radiology, Stanford University, Stanford, California, USA
| | - Elizabeth Tong
- Department of Radiology, Stanford University, Stanford, California, USA
| | - Rui Duarte Armindo
- Department of Radiology, Stanford University, Stanford, California, USA
- Department of Neuroradiology, Hospital Beatriz Ângelo, Lisbon, Portugal
| | - Ates Fettahoglu
- Department of Radiology, Stanford University, Stanford, California, USA
| | - Jason Choi
- Department of Neurosurgery, Stanford University, Stanford, California, USA
| | - Jacob Bagley
- Department of Neurosurgery, Stanford University, Stanford, California, USA
| | - Kristen W Yeom
- Department of Radiology, Stanford University, Stanford, California, USA
| | - Michael Moseley
- Department of Radiology, Stanford University, Stanford, California, USA
| | - Gary K Steinberg
- Department of Neurosurgery, Stanford University, Stanford, California, USA
| | - Greg Zaharchuk
- Department of Radiology, Stanford University, Stanford, California, USA
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8
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Baron JC. Predicting Stroke Recurrence in Occlusive Disease Using Noninvasive Quantitative Mapping of Cerebrovascular Reserve. Stroke 2024; 55:622-624. [PMID: 38328925 DOI: 10.1161/strokeaha.124.046235] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/09/2024]
Affiliation(s)
- Jean-Claude Baron
- Department of Neurology, Hôpital Sainte-Anne, GHU Paris Psychiatrie et Neurosciences, FHU NeuroVasc, France. Université Paris Cité, Institut de Psychiatrie et Neurosciences de Paris, Inserm U1266, France
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9
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Zhao MY, Tong E, Armindo RD, Woodward A, Yeom KW, Moseley ME, Zaharchuk G. Measuring Quantitative Cerebral Blood Flow in Healthy Children: A Systematic Review of Neuroimaging Techniques. J Magn Reson Imaging 2024; 59:70-81. [PMID: 37170640 PMCID: PMC10638464 DOI: 10.1002/jmri.28758] [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: 02/03/2023] [Revised: 04/13/2023] [Accepted: 04/14/2023] [Indexed: 05/13/2023] Open
Abstract
Cerebral blood flow (CBF) is an important hemodynamic parameter to evaluate brain health. It can be obtained quantitatively using medical imaging modalities such as magnetic resonance imaging and positron emission tomography (PET). Although CBF in adults has been widely studied and linked with cerebrovascular and neurodegenerative diseases, CBF data in healthy children are sparse due to the challenges in pediatric neuroimaging. An understanding of the factors affecting pediatric CBF and its normal range is crucial to determine the optimal CBF measuring techniques in pediatric neuroradiology. This review focuses on pediatric CBF studies using neuroimaging techniques in 32 articles including 2668 normal subjects ranging from birth to 18 years old. A systematic literature search was conducted in PubMed, Embase, and Scopus and reported following the preferred reporting items for systematic reviews and meta-analyses (PRISMA). We identified factors (such as age, gender, mood, sedation, and fitness) that have significant effects on pediatric CBF quantification. We also investigated factors influencing the CBF measurements in infants. Based on this review, we recommend best practices to improve CBF measurements in pediatric neuroimaging. LEVEL OF EVIDENCE: 1 TECHNICAL EFFICACY: Stage 2.
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Affiliation(s)
- Moss Y Zhao
- Department of Radiology, Stanford University, Stanford, CA, USA
| | - Elizabeth Tong
- Department of Radiology, Stanford University, Stanford, CA, USA
| | - Rui Duarte Armindo
- Department of Radiology, Stanford University, Stanford, CA, USA
- Department of Neuroradiology, Hospital Beatriz Ângelo, Loures, Lisbon, Portugal
| | - Amanda Woodward
- Lane Medical Library, Stanford University, Stanford, CA, USA
| | - Kristen W. Yeom
- Department of Radiology, Stanford University, Stanford, CA, USA
| | | | - Greg Zaharchuk
- Department of Radiology, Stanford University, Stanford, CA, USA
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10
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Wang J, Li H, Jia J, Shao X, Li Y, Zhou Y, Wang H, Jin L. Progressive Cerebrovascular Reactivity Reduction Occurs in Parkinson's Disease: A Longitudinal Study. Mov Disord 2024; 39:94-104. [PMID: 38013597 DOI: 10.1002/mds.29671] [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: 09/07/2023] [Revised: 10/15/2023] [Accepted: 11/07/2023] [Indexed: 11/29/2023] Open
Abstract
BACKGROUND The change of microvascular function over the course of Parkinson's disease (PD) remains unclear. OBJECTIVE We aimed to ascertain regional cerebrovascular reactivity (CVR) changes in the patients with PD at baseline (V0) and during a 2-year follow-up period (V1). We further investigated whether alterations in CVR were linked to cognitive decline and brain functional connectivity (FC). METHODS We recruited 90 PD patients and 51 matched healthy controls (HCs). PD patients underwent clinical evaluations, neuropsychological assessments, and magnetic resonance (MR) scanning at V0 and V1, whereas HCs completed neuropsychological assessments and MR at baseline. The analysis included evaluating CVR and FC maps derived from resting-state functional magnetic resonance imaging and investigating CVR measurement reproducibility. RESULTS Compared with HCs, CVR reduction in left inferior occipital gyrus and right superior temporal cortex at V0 persisted at V1, with larger clusters. Longitudinal reduction in CVR of the left posterior cingulate cortex correlated with decline in Trail Making Test B performance within PD patients. Reproducibility validation further confirmed these findings. In addition, the results also showed that there was a tendency for FC to be weakened from posterior to anterior with the progression of the disease. CONCLUSIONS Microvascular dysfunction might be involved in disease progression, subsequently weaken brain FC, and partly contribute to executive function deficits in early PD. © 2023 International Parkinson and Movement Disorder Society.
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Affiliation(s)
- Jian Wang
- Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai, China
- Department of Radiology, Zhongshan Hospital, Fudan University (Xiamen Branch), China
| | - Hongwei Li
- Institute of Science and Technology for Brain-inspired Intelligence, Fudan University, Shanghai, China
| | - Jia Jia
- Department of Neurology, Zhongshan Hospital, Fudan University, Shanghai, China
- Department of Neurology, Shanghai Xuhui Central Hospital, Shanghai, China
| | - Xiali Shao
- Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Yuanfang Li
- Department of Neurology, Zhongshan Hospital, Fudan University (Xiamen Branch), Xiamen, China
| | - Ying Zhou
- Department of Neurology, Zhongshan Hospital, Fudan University (Xiamen Branch), Xiamen, China
| | - He Wang
- Institute of Science and Technology for Brain-inspired Intelligence, Fudan University, Shanghai, China
- Human Phenome Institute, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China
| | - Lirong Jin
- Department of Neurology, Zhongshan Hospital, Fudan University, Shanghai, China
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11
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Biondetti E, Chiarelli AM, Germuska M, Lipp I, Villani A, Caporale AS, Patitucci E, Murphy K, Tomassini V, Wise RG. Breath-hold BOLD fMRI without CO 2 sampling enables estimation of venous cerebral blood volume: potential use in normalization of stimulus-evoked BOLD fMRI data. Neuroimage 2024; 285:120492. [PMID: 38070840 DOI: 10.1016/j.neuroimage.2023.120492] [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: 02/22/2023] [Revised: 10/30/2023] [Accepted: 12/06/2023] [Indexed: 01/13/2024] Open
Abstract
BOLD fMRI signal has been used in conjunction with vasodilatory stimulation as a marker of cerebrovascular reactivity (CVR): the relative change in cerebral blood flow (CBF) arising from a unit change in the vasodilatory stimulus. Using numerical simulations, we demonstrate that the variability in the relative BOLD signal change induced by vasodilation is strongly influenced by the variability in deoxyhemoglobin-containing cerebral blood volume (CBV), as this source of variability is likely to be more prominent than that of CVR. It may, therefore, be more appropriate to describe the relative BOLD signal change induced by an isometabolic vasodilation as a proxy of deoxygenated CBV (CBVdHb) rather than CVR. With this in mind, a new method was implemented to map a marker of CBVdHb, termed BOLD-CBV, based on the normalization of voxel-wise BOLD signal variation by an estimate of the intravascular venous BOLD signal from voxels filled with venous blood. The intravascular venous BOLD signal variation, recorded during repeated breath-holding, was extracted from the superior sagittal sinus in a cohort of 27 healthy volunteers and used as a regressor across the whole brain, yielding maps of BOLD-CBV. In the same cohort, we demonstrated the potential use of BOLD-CBV for the normalization of stimulus-evoked BOLD fMRI by comparing group-level BOLD fMRI responses to a visuomotor learning task with and without the inclusion of voxel-wise vascular covariates of BOLD-CBV and the BOLD signal change per mmHg variation in end-tidal carbon dioxide (BOLD-CVR). The empirical measure of BOLD-CBV accounted for more between-subject variability in the motor task-induced BOLD responses than BOLD-CVR estimated from end-tidal carbon dioxide recordings. The new method can potentially increase the power of group fMRI studies by including a measure of vascular characteristics and has the strong practical advantage of not requiring experimental measurement of end-tidal carbon dioxide, unlike traditional methods to estimate BOLD-CVR. It also more closely represents a specific physiological characteristic of brain vasculature than BOLD-CVR, namely blood volume.
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Affiliation(s)
- Emma Biondetti
- Department of Neurosciences, Imaging, and Clinical Sciences, 'G. D'Annunzio' University of Chieti-Pescara, Chieti, Italy; Institute for Advanced Biomedical Technologies, 'G. D'Annunzio' University of Chieti-Pescara, Chieti, Italy.
| | - Antonio Maria Chiarelli
- Department of Neurosciences, Imaging, and Clinical Sciences, 'G. D'Annunzio' University of Chieti-Pescara, Chieti, Italy; Institute for Advanced Biomedical Technologies, 'G. D'Annunzio' University of Chieti-Pescara, Chieti, Italy
| | - Michael Germuska
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Physics and Astronomy, Cardiff University, Cardiff, United Kingdom
| | - Ilona Lipp
- Department of Neurophysics, Max Planck Institute for Human Cognitive & Brain Sciences, Leipzig, Germany; Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, UK
| | - Alessandro Villani
- Department of Neurosciences, Imaging, and Clinical Sciences, 'G. D'Annunzio' University of Chieti-Pescara, Chieti, Italy; Institute for Advanced Biomedical Technologies, 'G. D'Annunzio' University of Chieti-Pescara, Chieti, Italy
| | - Alessandra S Caporale
- Department of Neurosciences, Imaging, and Clinical Sciences, 'G. D'Annunzio' University of Chieti-Pescara, Chieti, Italy; Institute for Advanced Biomedical Technologies, 'G. D'Annunzio' University of Chieti-Pescara, Chieti, Italy
| | - Eleonora Patitucci
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, UK
| | - Kevin Murphy
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Physics and Astronomy, Cardiff University, Cardiff, United Kingdom
| | - Valentina Tomassini
- Department of Neurosciences, Imaging, and Clinical Sciences, 'G. D'Annunzio' University of Chieti-Pescara, Chieti, Italy; Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, UK; MS Centre, Neurology Unit, 'SS. Annunziata' University Hospital, Chieti, Italy; Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, UK; Helen Durham Centre for Neuroinflammation, University Hospital of Wales, Cardiff, UK
| | - Richard G Wise
- Department of Neurosciences, Imaging, and Clinical Sciences, 'G. D'Annunzio' University of Chieti-Pescara, Chieti, Italy; Institute for Advanced Biomedical Technologies, 'G. D'Annunzio' University of Chieti-Pescara, Chieti, Italy; Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, UK
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12
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Khaw AV, Thiessen JD, St. Lawrence K, Pandey SK. The Quest of Characterizing Hemodynamic Failure in Patients With Cerebrovascular Disease. J Am Heart Assoc 2023; 12:e032657. [PMID: 38084748 PMCID: PMC10863759 DOI: 10.1161/jaha.123.032657] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/20/2023] [Accepted: 10/24/2023] [Indexed: 12/20/2023]
Affiliation(s)
- Alexander V. Khaw
- Department of Clinical Neurosciences, Schulich School of Medicine and DentistryWestern UniversityLondonOntarioCanada
- Lawson Health Research InstituteLondonOntarioCanada
- Department of Medical Biophysics, Schulich School of Medicine and DentistryWestern UniversityLondonOntarioCanada
| | - Jonathan D. Thiessen
- Lawson Health Research InstituteLondonOntarioCanada
- Department of Medical Biophysics, Schulich School of Medicine and DentistryWestern UniversityLondonOntarioCanada
- Department of Medical Imaging, Schulich School of Medicine and DentistryWestern UniversityLondonOntarioCanada
| | - Keith St. Lawrence
- Lawson Health Research InstituteLondonOntarioCanada
- Department of Medical Biophysics, Schulich School of Medicine and DentistryWestern UniversityLondonOntarioCanada
- Department of Medical Imaging, Schulich School of Medicine and DentistryWestern UniversityLondonOntarioCanada
| | - Sachin K. Pandey
- Department of Medical Imaging, Schulich School of Medicine and DentistryWestern UniversityLondonOntarioCanada
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13
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Zhao MY, Armindo RD, Gauden AJ, Yim B, Tong E, Moseley M, Steinberg GK, Zaharchuk G. Revascularization improves vascular hemodynamics - a study assessing cerebrovascular reserve and transit time in Moyamoya patients using MRI. J Cereb Blood Flow Metab 2023; 43:138-151. [PMID: 36408536 PMCID: PMC10638998 DOI: 10.1177/0271678x221140343] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/28/2022] [Revised: 10/04/2022] [Accepted: 10/25/2022] [Indexed: 11/22/2022]
Abstract
Cerebrovascular reserve (CVR) reflects the capacity of cerebral blood flow (CBF) to change. Decreased CVR implies poor hemodynamics and is linked to a higher risk for stroke. Revascularization has been shown to improve CBF in patients with vasculopathy such as Moyamoya disease. Dynamic susceptibility contrast (DSC) can measure transit time to evaluate patients suspected of stroke. Arterial spin labeling (ASL) is a non-invasive technique for CBF, CVR, and arterial transit time (ATT) measurements. Here, we investigate the change in hemodynamics 4-12 months after extracranial-to-intracranial direct bypass in 52 Moyamoya patients using ASL with single and multiple post-labeling delays (PLD). Images were collected using ASL and DSC with acetazolamide. CVR, CBF, ATT, and time-to-maximum (Tmax) were measured in different flow territories. Results showed that hemodynamics improved significantly in regions affected by arterial occlusions after revascularization. CVR increased by 16 ± 11% (p < 0.01) and 25 ± 13% (p < 0.01) for single- and multi-PLD ASL, respectively. Transit time measured by multi-PLD ASL and post-vasodilation DSC reduced by 13 ± 7% (p < 0.01) and 9 ± 5% (p < 0.01), respectively. For all regions, ATT correlated significantly with Tmax (R2 = 0.59, p < 0.01). Thus, revascularization improved CVR and decreased transit times. Multi-PLD ASL can serve as an effective and non-invasive modality to examine vascular hemodynamics in Moyamoya patients.
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Affiliation(s)
- Moss Y Zhao
- Department of Radiology, Stanford University, Stanford, CA, USA
| | - Rui Duarte Armindo
- Department of Radiology, Stanford University, Stanford, CA, USA
- Department of Neuroradiology, Hospital Beatriz Ângelo, Loures, Lisbon, Portugal
| | - Andrew J Gauden
- Department of Neurosurgery, Stanford University, Stanford, CA, USA
| | - Benjamin Yim
- Department of Neurosurgery, Stanford University, Stanford, CA, USA
| | - Elizabeth Tong
- Department of Radiology, Stanford University, Stanford, CA, USA
| | - Michael Moseley
- Department of Radiology, Stanford University, Stanford, CA, USA
| | - Gary K Steinberg
- Department of Neurosurgery, Stanford University, Stanford, CA, USA
| | - Greg Zaharchuk
- Department of Radiology, Stanford University, Stanford, CA, USA
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14
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Cevik J, Seth I, Rozen WM. Transforming breast reconstruction: the pioneering role of artificial intelligence in preoperative planning. Gland Surg 2023; 12:1271-1275. [PMID: 37842522 PMCID: PMC10570966 DOI: 10.21037/gs-23-265] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2023] [Accepted: 09/02/2023] [Indexed: 10/17/2023]
Abstract
Autologous breast reconstruction surgery is a vital part of the recovery process for patients with breast cancer. While various reconstructive options exist, the deep inferior epigastric artery perforator (DIEP) flap is often favoured for its ability to closely mimic natural breast tissue. However, the complex vascular anatomy associated with the deep inferior epigastric artery (DIEA) presents challenges for surgeons during DIEP flap execution. Preoperative imaging, such as computed tomography angiography (CTA), is commonly used to understand vascular architecture and aid in selecting appropriate perforators. Conventional reporting of CTA scans is a labour-intensive process that can be challenging and requires specific expertise. The integration of artificial intelligence (AI) and machine learning (ML) algorithms in medical imaging has the potential to address these challenges. AI can enhance CTA through improved data acquisition, image post-processing, and potentially interpretation. By automating the perforator selection process, AI applications can significantly reduce the time spent on preoperative imaging analysis and potentially improve accuracy and reliability. While AI shows promise in optimizing efficiency, accuracy, and reliability in breast reconstruction planning, challenges and ethical considerations need to be addressed. This article explores the challenges, opportunities, and future directions of using AI in the preoperative planning of autologous breast reconstruction.
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Affiliation(s)
- Jevan Cevik
- Department of Plastic and Reconstructive Surgery, Peninsula Health, Frankston, Victoria, Australia
- Peninsula Clinical School, Central Clinical School, Faculty of Medicine, Monash University, Frankston, Victoria, Australia
| | - Ishith Seth
- Department of Plastic and Reconstructive Surgery, Peninsula Health, Frankston, Victoria, Australia
- Peninsula Clinical School, Central Clinical School, Faculty of Medicine, Monash University, Frankston, Victoria, Australia
| | - Warren M. Rozen
- Department of Plastic and Reconstructive Surgery, Peninsula Health, Frankston, Victoria, Australia
- Peninsula Clinical School, Central Clinical School, Faculty of Medicine, Monash University, Frankston, Victoria, Australia
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15
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Zhao MY, Dahlen A, Ramirez NJ, Moseley M, Van Haren K, Zaharchuk G. Effect of vitamin D supplementation on cerebral blood flow in male patients with adrenoleukodystrophy. J Neurosci Res 2023; 101:1086-1097. [PMID: 36967233 DOI: 10.1002/jnr.25187] [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: 03/22/2022] [Revised: 02/20/2023] [Accepted: 02/28/2023] [Indexed: 03/29/2023]
Abstract
One-third of boys with X-linked adrenoleukodystrophy (ALD) develop inflammatory demyelinating lesions, typically at the splenium. These lesions share similarities with multiple sclerosis, including cerebral hypoperfusion and links to vitamin D insufficiency. We hypothesized that increasing vitamin D levels would increase cerebral blood flow (CBF) in ALD boys. We conducted an exploratory analysis of vitamin D supplementation and CBF using all available data from participants enrolled in a recent single-arm interventional study of vitamin D supplementation in boys with ALD. We measured whole brain and splenium CBF using arterial spin labeling (ASL) from three study time points (baseline, 6 months, and 12 months). We used linear generalized estimating equations to evaluate CBF changes between time points and to test for an association between CBF and vitamin D. ASL data were available for 16 participants, aged 2-22 years. Mean vitamin D levels increased by 72.7% (p < .001) after 6 months and 88.6% (p < .01) after 12 months. Relative to baseline measures, mean CBF of the whole brain (6 months: +2.5%, p = .57; 12 months: +6.1%, p = .18) and splenium (6 months: +1.2%, p = .80; 12 months: +7.4%, p = .058) were not significantly changed. Vitamin D levels were positively correlated with CBF in the splenium (slope = .59, p < .001). In this exploratory analysis, we observed a correlation between vitamin D levels and splenial CBF in ALD boys. We confirm the feasibility of measuring CBF in this brain region and population, but further work is needed to establish a causal role for vitamin D in modulating CBF.
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Affiliation(s)
- Moss Y Zhao
- Department of Radiology, Stanford University, California, Stanford, USA
| | - Alex Dahlen
- Quantitative Sciences Unit, Stanford University School of Medicine, California, Stanford, USA
| | | | - Michael Moseley
- Department of Radiology, Stanford University, California, Stanford, USA
| | - Keith Van Haren
- Department of Neurology and Neurological Sciences, Stanford University, California, Stanford, USA
| | - Greg Zaharchuk
- Department of Radiology, Stanford University, California, Stanford, USA
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16
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Hou X, Guo P, Wang P, Liu P, Lin DDM, Fan H, Li Y, Wei Z, Lin Z, Jiang D, Jin J, Kelly C, Pillai JJ, Huang J, Pinho MC, Thomas BP, Welch BG, Park DC, Patel VM, Hillis AE, Lu H. Deep-learning-enabled brain hemodynamic mapping using resting-state fMRI. NPJ Digit Med 2023; 6:116. [PMID: 37344684 PMCID: PMC10284915 DOI: 10.1038/s41746-023-00859-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2022] [Accepted: 06/09/2023] [Indexed: 06/23/2023] Open
Abstract
Cerebrovascular disease is a leading cause of death globally. Prevention and early intervention are known to be the most effective forms of its management. Non-invasive imaging methods hold great promises for early stratification, but at present lack the sensitivity for personalized prognosis. Resting-state functional magnetic resonance imaging (rs-fMRI), a powerful tool previously used for mapping neural activity, is available in most hospitals. Here we show that rs-fMRI can be used to map cerebral hemodynamic function and delineate impairment. By exploiting time variations in breathing pattern during rs-fMRI, deep learning enables reproducible mapping of cerebrovascular reactivity (CVR) and bolus arrival time (BAT) of the human brain using resting-state CO2 fluctuations as a natural "contrast media". The deep-learning network is trained with CVR and BAT maps obtained with a reference method of CO2-inhalation MRI, which includes data from young and older healthy subjects and patients with Moyamoya disease and brain tumors. We demonstrate the performance of deep-learning cerebrovascular mapping in the detection of vascular abnormalities, evaluation of revascularization effects, and vascular alterations in normal aging. In addition, cerebrovascular maps obtained with the proposed method exhibit excellent reproducibility in both healthy volunteers and stroke patients. Deep-learning resting-state vascular imaging has the potential to become a useful tool in clinical cerebrovascular imaging.
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Affiliation(s)
- Xirui Hou
- Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Pengfei Guo
- Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA
| | - Puyang Wang
- Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Peiying Liu
- Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Doris D M Lin
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Hongli Fan
- Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Yang Li
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Zhiliang Wei
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Zixuan Lin
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Dengrong Jiang
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Jin Jin
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Catherine Kelly
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Jay J Pillai
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Neurosurgery, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Judy Huang
- Department of Neurosurgery, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Marco C Pinho
- Department of Radiology, UT Southwestern Medical Center, Dallas, TX, USA
| | - Binu P Thomas
- Department of Radiology, UT Southwestern Medical Center, Dallas, TX, USA
| | - Babu G Welch
- Department of Neurologic Surgery, UT Southwestern Medical Center, Dallas, TX, USA
- Center for Vital Longevity, School of Behavioral and Brain Sciences, University of Texas at Dallas, Dallas, TX, USA
| | - Denise C Park
- Center for Vital Longevity, School of Behavioral and Brain Sciences, University of Texas at Dallas, Dallas, TX, USA
| | - Vishal M Patel
- Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA
- Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Argye E Hillis
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Hanzhang Lu
- Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA.
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17
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Pinto J, Blockley NP, Harkin JW, Bulte DP. Modelling spatiotemporal dynamics of cerebral blood flow using multiple-timepoint arterial spin labelling MRI. Front Physiol 2023; 14:1142359. [PMID: 37304817 PMCID: PMC10250662 DOI: 10.3389/fphys.2023.1142359] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2023] [Accepted: 04/14/2023] [Indexed: 06/13/2023] Open
Abstract
Introduction: Cerebral blood flow (CBF) is an important physiological parameter that can be quantified non-invasively using arterial spin labelling (ASL) imaging. Although most ASL studies are based on single-timepoint strategies, multi-timepoint approaches (multiple-PLD) in combination with appropriate model fitting strategies may be beneficial not only to improve CBF quantification but also to retrieve other physiological information of interest. Methods: In this work, we tested several kinetic models for the fitting of multiple-PLD pCASL data in a group of 10 healthy subjects. In particular, we extended the standard kinetic model by incorporating dispersion effects and the macrovascular contribution and assessed their individual and combined effect on CBF quantification. These assessments were performed using two pseudo-continuous ASL (pCASL) datasets acquired in the same subjects but during two conditions mimicking different CBF dynamics: normocapnia and hypercapnia (achieved through a CO2 stimulus). Results: All kinetic models quantified and highlighted the different CBF spatiotemporal dynamics between the two conditions. Hypercapnia led to an increase in CBF whilst decreasing arterial transit time (ATT) and arterial blood volume (aBV). When comparing the different kinetic models, the incorporation of dispersion effects yielded a significant decrease in CBF (∼10-22%) and ATT (∼17-26%), whilst aBV (∼44-74%) increased, and this was observed in both conditions. The extended model that includes dispersion effects and the macrovascular component has been shown to provide the best fit to both datasets. Conclusion: Our results support the use of extended models that include the macrovascular component and dispersion effects when modelling multiple-PLD pCASL data.
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Affiliation(s)
- Joana Pinto
- Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, United Kingdom
| | - Nicholas P. Blockley
- David Greenfield Human Physiology Unit, School of Life Sciences, University of Nottingham, Nottingham, United Kingdom
| | | | - Daniel P. Bulte
- Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, United Kingdom
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18
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Iutaka T, de Freitas MB, Omar SS, Scortegagna FA, Nael K, Nunes RH, Pacheco FT, Maia Júnior ACM, do Amaral LLF, da Rocha AJ. Arterial Spin Labeling: Techniques, Clinical Applications, and Interpretation. Radiographics 2023; 43:e220088. [DOI: 10.1148/rg.220088] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
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19
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Shams S, Prokopiou P, Esmaelbeigi A, Mitsis GD, Chen JJ. Modeling the dynamics of cerebrovascular reactivity to carbon dioxide in fMRI under task and resting-state conditions. Neuroimage 2023; 265:119758. [PMID: 36442732 DOI: 10.1016/j.neuroimage.2022.119758] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2022] [Revised: 11/11/2022] [Accepted: 11/18/2022] [Indexed: 11/26/2022] Open
Abstract
Conventionally, cerebrovascular reactivity (CVR) is estimated as the amplitude of the hemodynamic response to vascular stimuli, most commonly carbon dioxide (CO2). While the CVR amplitude has established clinical utility, the temporal characteristics of CVR (dCVR) have been increasingly explored and may yield even more pathology-sensitive parameters. This work is motivated by the current need to evaluate the feasibility of dCVR modeling in various experimental conditions. In this work, we present a comparison of several recently published/utilized model-based deconvolution (response estimation) approaches for estimating the CO2 response function h(t), including maximum a posteriori likelihood (MAP), inverse logit (IL), canonical correlation analysis (CCA), and basis expansion (using Gamma and Laguerre basis sets). To aid the comparison, we devised a novel simulation framework that incorporates a wide range of SNRs, ranging from 10 to -7 dB, representative of both task and resting-state CO2 changes. In addition, we built ground-truth h(t) into our simulation framework, overcoming the conventional limitation that the true h(t) is unknown. Moreover, to best represent realistic noise found in fMRI scans, we extracted noise from in-vivo resting-state scans. Furthermore, we introduce a simple optimization of the CCA method (CCAopt) and compare its performance to these existing methods. Our findings suggest that model-based methods can accurately estimate dCVR even amidst high noise (i.e. resting-state), and in a manner that is largely independent of the underlying model assumptions for each method. We also provide a quantitative basis for making methodological choices, based on the desired dCVR parameters, the estimation accuracy and computation time. The BEL method provided the highest accuracy and robustness, followed by the CCAopt and IL methods. Of the three, the CCAopt method has the lowest computational requirements. These findings lay the foundation for wider adoption of dCVR estimation in CVR mapping.
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Affiliation(s)
- Seyedmohammad Shams
- Rotman Research Institute, Baycrest Health Sciences, Canada; Department of Neurology, Henry Ford Health, USA
| | - Prokopis Prokopiou
- Department of Radiology, Gordon Center for Medical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | | | | | - J Jean Chen
- Rotman Research Institute, Baycrest Health Sciences, Canada; Department of Bioengineering, McGill University, Canada; Department of Medical Biophysics, University of Toronto, Canada; Institute of Biomedical Engineering, University of Toronto, Canada.
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20
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Luijten SPR, Bos D, van Doormaal PJ, Goyal M, Dijkhuizen RM, Dippel DWJ, Roozenbeek B, van der Lugt A, Warnert EAH. Cerebral blood flow quantification with multi-delay arterial spin labeling in ischemic stroke and the association with early neurological outcome. Neuroimage Clin 2023; 37:103340. [PMID: 36739791 PMCID: PMC9932490 DOI: 10.1016/j.nicl.2023.103340] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2022] [Revised: 01/13/2023] [Accepted: 01/26/2023] [Indexed: 02/01/2023]
Abstract
Restoring blood flow to brain tissue at risk of infarction is essential for tissue survival and clinical outcome. We used cerebral blood flow (CBF) quantified with multiple post-labeling delay (PLD) pseudocontinuous arterial spin labeling (ASL) MRI after ischemic stroke and assessed the association between CBF and early neurological outcome. We acquired ASL with 7 PLDs at 3.0 T in large vessel occlusion stroke patients at 24 h. We quantified CBF relative to the contralateral hemisphere (rCBF) and defined hyperperfusion as a ≥30% increase and hypoperfusion as a ≥40% decrease in rCBF. We included 44 patients (median age: 70 years, median NIHSS: 13, 40 treated with endovascular thrombectomy) of whom 37 were recanalized. Hyperperfusion in ischemic core occurred in recanalized but not in non-recanalized patients (65.8% vs 0%, p = 0.006). Hypoperfusion occurred only in the latter group (0% vs 85.7%, p < 0.001). In recanalized patients, hyperperfusion was also seen in salvaged penumbra (38.9%). Higher rCBF in ischemic core (aβ, -2.75 [95% CI: -4.11 to -1.40]) and salvaged penumbra (aβ, -5.62 [95% CI: -9.57 to -1.68]) was associated with lower NIHSS scores at 24 h. In conclusion, hyperperfusion frequently occurs in infarcted and salvaged brain tissue following successful recanalization and early neurological outcome is positively associated with the level of reperfusion.
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Affiliation(s)
- Sven P R Luijten
- Department of Radiology & Nuclear Medicine, Erasmus MC University Medical Center, the Netherlands.
| | - Daniel Bos
- Department of Radiology & Nuclear Medicine, Erasmus MC University Medical Center, the Netherlands
| | - Pieter-Jan van Doormaal
- Department of Radiology & Nuclear Medicine, Erasmus MC University Medical Center, the Netherlands
| | - Mayank Goyal
- Department of Radiology, Foothills Medical Center, University of Calgary, Canada
| | - Rick M Dijkhuizen
- Biomedical MR Imaging and Spectroscopy Group, Center for Image Sciences, University Medical Center Utrecht & Utrecht University, the Netherlands
| | - Diederik W J Dippel
- Department of Neurology, Erasmus MC University Medical Center, the Netherlands
| | - Bob Roozenbeek
- Department of Neurology, Erasmus MC University Medical Center, the Netherlands
| | - Aad van der Lugt
- Department of Radiology & Nuclear Medicine, Erasmus MC University Medical Center, the Netherlands
| | - Esther A H Warnert
- Department of Radiology & Nuclear Medicine, Erasmus MC University Medical Center, the Netherlands
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21
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Qin Q, Alsop DC, Bolar DS, Hernandez‐Garcia L, Meakin J, Liu D, Nayak KS, Schmid S, van Osch MJP, Wong EC, Woods JG, Zaharchuk G, Zhao MY, Zun Z, Guo J. Velocity-selective arterial spin labeling perfusion MRI: A review of the state of the art and recommendations for clinical implementation. Magn Reson Med 2022; 88:1528-1547. [PMID: 35819184 PMCID: PMC9543181 DOI: 10.1002/mrm.29371] [Citation(s) in RCA: 30] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2022] [Revised: 05/16/2022] [Accepted: 06/08/2022] [Indexed: 12/11/2022]
Abstract
This review article provides an overview of the current status of velocity-selective arterial spin labeling (VSASL) perfusion MRI and is part of a wider effort arising from the International Society for Magnetic Resonance in Medicine (ISMRM) Perfusion Study Group. Since publication of the 2015 consensus paper on arterial spin labeling (ASL) for cerebral perfusion imaging, important advancements have been made in the field. The ASL community has, therefore, decided to provide an extended perspective on various aspects of technical development and application. Because VSASL has the potential to become a principal ASL method because of its unique advantages over traditional approaches, an in-depth discussion was warranted. VSASL labels blood based on its velocity and creates a magnetic bolus immediately proximal to the microvasculature within the imaging volume. VSASL is, therefore, insensitive to transit delay effects, in contrast to spatially selective pulsed and (pseudo-) continuous ASL approaches. Recent technical developments have improved the robustness and the labeling efficiency of VSASL, making it a potentially more favorable ASL approach in a wide range of applications where transit delay effects are of concern. In this review article, we (1) describe the concepts and theoretical basis of VSASL; (2) describe different variants of VSASL and their implementation; (3) provide recommended parameters and practices for clinical adoption; (4) describe challenges in developing and implementing VSASL; and (5) describe its current applications. As VSASL continues to undergo rapid development, the focus of this review is to summarize the fundamental concepts of VSASL, describe existing VSASL techniques and applications, and provide recommendations to help the clinical community adopt VSASL.
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Affiliation(s)
- Qin Qin
- The Russell H. Morgan Department of Radiology and Radiological ScienceJohns Hopkins University School of MedicineBaltimoreMarylandUSA
| | - David C. Alsop
- Department of RadiologyBeth Israel Deaconess Medical Center and Harvard Medical SchoolBostonMassachusettsUSA
| | - Divya S. Bolar
- Center for Functional Magnetic Resonance Imaging, Department of RadiologyUniversity of CaliforniaSan Diego La JollaCaliforniaUSA
| | | | - James Meakin
- Department of Radiology, Nuclear Medicine and AnatomyRadboud University Medical CenterNijmegenThe Netherlands
| | - Dapeng Liu
- The Russell H. Morgan Department of Radiology and Radiological ScienceJohns Hopkins University School of MedicineBaltimoreMarylandUSA
| | - Krishna S. Nayak
- Magnetic Resonance Engineering Laboratory, Ming Hsieh Department of Electrical EngineeringUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
| | - Sophie Schmid
- C.J. Gorter Center for high field MRI, Department of RadiologyLeiden University Medical CenterLeidenThe Netherlands
| | - Matthias J. P. van Osch
- C.J. Gorter Center for high field MRI, Department of RadiologyLeiden University Medical CenterLeidenThe Netherlands
| | - Eric C. Wong
- Center for Functional Magnetic Resonance Imaging, Department of RadiologyUniversity of CaliforniaSan Diego La JollaCaliforniaUSA
| | - Joseph G. Woods
- Center for Functional Magnetic Resonance Imaging, Department of RadiologyUniversity of CaliforniaSan Diego La JollaCaliforniaUSA
| | - Greg Zaharchuk
- Department of RadiologyStanford UniversityStanfordCaliforniaUSA
| | - Moss Y. Zhao
- Department of RadiologyStanford UniversityStanfordCaliforniaUSA
| | - Zungho Zun
- Department of RadiologyWeill Cornell MedicineNew YorkNew YorkUSA
| | - Jia Guo
- Department of BioengineeringUniversity of California RiversideRiversideCaliforniaUSA
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22
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Zhao MY, Fan AP, Chen DYT, Ishii Y, Khalighi MM, Moseley M, Steinberg GK, Zaharchuk G. Using arterial spin labeling to measure cerebrovascular reactivity in Moyamoya disease: Insights from simultaneous PET/MRI. J Cereb Blood Flow Metab 2022; 42:1493-1506. [PMID: 35236136 PMCID: PMC9274857 DOI: 10.1177/0271678x221083471] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Cerebrovascular reactivity (CVR) reflects the CBF change to meet different physiological demands. The reference CVR technique is PET imaging with vasodilators but is inaccessible to most patients. DSC can measure transit time to evaluate patients suspected of stroke, but the use of gadolinium may cause side-effects. Arterial spin labeling (ASL) is a non-invasive MRI technique for CBF measurements. Here, we investigate the effectiveness of ASL with single and multiple post labeling delays (PLD) to replace PET and DSC for CVR and transit time mapping in 26 Moyamoya patients. Images were collected using simultaneous PET/MRI with acetazolamide. CVR, CBF, arterial transit time (ATT), and time-to-maximum (Tmax) were measured in different flow territories. Results showed that CVR was lower in occluded regions than normal regions (by 68 ± 12%, 52 ± 5%, and 56 ± 9%, for PET, single- and multi-PLD PCASL, respectively, all p < 0.05). Multi-PLD PCASL correlated slightly higher with PET (CCC = 0.36 and 0.32 in affected and unaffected territories respectively). Vasodilation caused ATT to reduce by 4.5 ± 3.1% (p < 0.01) in occluded regions. ATT correlated significantly with Tmax (R2 > 0.35, p < 0.01). Therefore, multi-PLD ASL is recommended for CVR studies due to its high agreement with the reference PET technique and the capability of measuring transit time.
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Affiliation(s)
- Moss Y Zhao
- Department of Radiology, Stanford University, Stanford, CA, USA
| | - Audrey P Fan
- Department of Biomedical Engineering, University of California Davis, Davis, CA, USA.,Department of Neurology, University of California Davis, Davis, CA, USA
| | - David Yen-Ting Chen
- Department of Medical Imaging, Taipei Medical University - Shuan-Ho Hospital, New Taipei City.,Department of Radiology, School of Medicine, College of Medicine, Taipei Medical University, Taipei
| | - Yosuke Ishii
- Department of Neurosurgery, Tokyo Medical and Dental University, Tokyo, Japan
| | | | - Michael Moseley
- Department of Radiology, Stanford University, Stanford, CA, USA
| | - Gary K Steinberg
- Department of Neurosurgery, Stanford University, Stanford, CA, USA
| | - Greg Zaharchuk
- Department of Radiology, Stanford University, Stanford, CA, USA
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23
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Golay X, Ho ML. Multidelay ASL of the pediatric brain. Br J Radiol 2022; 95:20220034. [PMID: 35451851 PMCID: PMC10996417 DOI: 10.1259/bjr.20220034] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2022] [Accepted: 03/22/2022] [Indexed: 11/05/2022] Open
Abstract
Arterial spin labeling (ASL) is a powerful noncontrast MRI technique for evaluation of cerebral blood flow (CBF). A key parameter in single-delay ASL is the choice of postlabel delay (PLD), which refers to the timing between the labeling of arterial free water and measurement of flow into the brain. Multidelay ASL (MDASL) utilizes several PLDs to improve the accuracy of CBF calculations using arterial transit time (ATT) correction. This approach is particularly helpful in situations where ATT is unknown, including young subjects and slow-flow conditions. In this article, we discuss the technical considerations for MDASL, including labeling techniques, quantitative metrics, and technical artefacts. We then provide a practical summary of key clinical applications with real-life imaging examples in the pediatric brain, including stroke, vasculopathy, hypoxic-ischemic injury, epilepsy, migraine, tumor, infection, and metabolic disease.
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Affiliation(s)
- Xavier Golay
- MR Neurophysics and Translational Neuroscience, UCL Queen
Square Institute of Neurology London, London,
England, UK
| | - Mai-Lan Ho
- Radiology, Nationwide Children’s Hospital and The Ohio
State University, Columbus, OH,
USA
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24
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Late breaking abstracts. J Cereb Blood Flow Metab 2022; 42:285-324. [PMID: 35645158 PMCID: PMC9152585 DOI: 10.1177/0271678x221099127] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
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25
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Zhao MY, Woodward A, Fan AP, Chen KT, Yu Y, Chen DY, Moseley ME, Zaharchuk G. Reproducibility of cerebrovascular reactivity measurements: A systematic review of neuroimaging techniques . J Cereb Blood Flow Metab 2022; 42:700-717. [PMID: 34806918 PMCID: PMC9254040 DOI: 10.1177/0271678x211056702] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Cerebrovascular reactivity (CVR), the capacity of the brain to increase cerebral blood flow (CBF) to meet changes in physiological demand, is an important biomarker to evaluate brain health. Typically, this brain "stress test" is performed by using a medical imaging modality to measure the CBF change between two states: at baseline and after vasodilation. However, since there are many imaging modalities and many ways to augment CBF, a wide range of CVR values have been reported. An understanding of CVR reproducibility is critical to determine the most reliable methods to measure CVR as a clinical biomarker. This review focuses on CVR reproducibility studies using neuroimaging techniques in 32 articles comprising 427 total subjects. The literature search was performed in PubMed, Embase, and Scopus. The review was conducted using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). We identified 5 factors of the experimental subjects (such as sex, blood characteristics, and smoking) and 9 factors of the measuring technique (such as the imaging modality, the type of the vasodilator, and the quantification method) that have strong effects on CVR reproducibility. Based on this review, we recommend several best practices to improve the reproducibility of CVR quantification in neuroimaging studies.
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Affiliation(s)
- Moss Y Zhao
- Department of Radiology, Stanford University, Stanford, CA, USA
| | - Amanda Woodward
- Lane Medical Library, Stanford University, Stanford, CA, USA
| | - Audrey P Fan
- Department of Biomedical Engineering, University of California Davis, Davis, CA, USA.,Department of Neurology, University of California Davis, Davis, CA, USA
| | - Kevin T Chen
- Department of Radiology, Stanford University, Stanford, CA, USA
| | - Yannan Yu
- Department of Radiology, Stanford University, Stanford, CA, USA
| | - David Y Chen
- Department of Medical Imaging, Taipei Medical University - Shuan-Ho Hospital, New Taipei City.,Department of Radiology, School of Medicine, Taipei Medical University, Taipei *Research materials supporting this publication can be accessed at https://doi.org/10.25740/hd852bg4538
| | | | - Greg Zaharchuk
- Department of Radiology, Stanford University, Stanford, CA, USA
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26
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Mast IH, Baas KPA, Jørstad HT, Wood JC, Nederveen AJ, Bakermans AJ. Dynamic MR imaging of cerebral perfusion during bicycling exercise. Neuroimage 2022; 250:118961. [PMID: 35121183 DOI: 10.1016/j.neuroimage.2022.118961] [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: 12/14/2021] [Revised: 01/25/2022] [Accepted: 01/31/2022] [Indexed: 10/19/2022] Open
Abstract
Habitual physical activity is beneficial for cerebrovascular health and cognitive function. Physical exercise therefore constitutes a clinically relevant cerebrovascular stimulus. This study demonstrates the feasibility of quantitative cerebral blood flow (CBF) measurements during supine bicycling exercise with pseudo-continuous arterial spin labeling (pCASL) magnetic resonance imaging (MRI) at 3 Tesla. Twelve healthy volunteers performed a steady-state exercise-recovery protocol on an MR-compatible bicycle ergometer, while dynamic pCASL data were acquired at rest, during moderate (60% of the age-predicted supine maximal heart rate (HRmax)) and vigorous (80% of supine HRmax) exercise, and subsequent recovery. These CBF measurements were compared with 2D phase-contrast MRI measurements of blood flow through the carotid arteries. Procedures were repeated on a separate day for an assessment of measurement repeatability. Whole-brain (WB) CBF was 41.2 ± 6.9 mL/100 g/min at rest (heart rate 63 [57-71] beats/min), remained similar at moderate exercise (102 [97-107] beats/min), decreased by 10% to 37.1 ± 5.7 mL/100 g/min (p = 0.001) during vigorous exercise (139 [136-142] beats/min) and decreased further to 34.2 ± 6.0 mL/100 g/min (p < 0.001) during recovery. Hippocampus CBF decreased by 12% (p = 0.001) during moderate exercise, decreased further during vigorous exercise (-21%; p < 0.001) and was even lower during recovery (-31%; p < 0.001). In contrast, motor cortex CBF increased by 12% (p = 0.027) during moderate exercise, returned to resting-state values during vigorous exercise, and decreased by 17% (p = 0.006) during recovery. The inter-session repeatability coefficients for WB CBF were approximately 20% for all stages of the exercise-recovery protocol. Phase-contrast blood flow measurements through the common carotid arteries overestimated the WB CBF because of flow directed to the face and scalp. This bias increased with exercise. We have demonstrated the feasibility of dynamic pCASL-MRI of the human brain for a quantitative evaluation of cerebral perfusion during bicycling exercise. Our spatially resolved measurements revealed a differential response of CBF in the motor cortex as well as the hippocampus compared with the brain as a whole. Caution is warranted when using flow through the common carotid arteries as a surrogate measure for cerebral perfusion.
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Affiliation(s)
- Isa H Mast
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands; Department of Human Movement Sciences, Vrije Universiteit, Amsterdam Movement Sciences, Amsterdam, The Netherlands
| | - Koen P A Baas
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
| | - Harald T Jørstad
- Department of Cardiology, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
| | - John C Wood
- Division of Hematology, Children's Hospital Los Angeles, Los Angeles, California, USA
| | - Aart J Nederveen
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
| | - Adrianus J Bakermans
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands.
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27
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Troy AM, Cheng HM. Human microvascular reactivity: a review of vasomodulating stimuli and non-invasive imaging assessment. Physiol Meas 2021; 42. [PMID: 34325417 DOI: 10.1088/1361-6579/ac18fd] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2021] [Accepted: 07/29/2021] [Indexed: 11/11/2022]
Abstract
The microvasculature serves an imperative function in regulating perfusion and nutrient exchange throughout the body, adaptively altering blood flow to preserve hemodynamic and metabolic homeostasis. Its normal functioning is vital to tissue health, whereas its dysfunction is present in many chronic conditions, including diabetes, heart disease, and cognitive decline. As microvascular dysfunction often appears early in disease progression, its detection can offer early diagnostic information. To detect microvascular dysfunction, one uses imaging to probe the microvasculature's ability to react to a stimulus, also known as microvascular reactivity (MVR). An assessment of MVR requires an integrated understanding of vascular physiology, techniques for stimulating reactivity, and available imaging methods to capture the dynamic response. Practical considerations, including compatibility between the selected stimulus and imaging approach, likewise require attention. In this review, we provide a comprehensive foundation necessary for informed imaging of MVR, with a particular focus on the challenging endeavor of assessing microvascular function in deep tissues.
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Affiliation(s)
- Aaron M Troy
- Institute of Biomedical Engineering, University of Toronto, Toronto, CANADA
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