ArticleRadiology2020
Predicting PET Cerebrovascular Reserve with Deep Learning by Using Baseline MRI: A Pilot Investigation of a Drug-Free Brain Stress Test.
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Article in Radiology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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11citing papers in PubMed
2.4field-weighted citation impact, top 9% of its field
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Who cites it
11 citing papers in PubMed, 28 citations in OpenAlex.
- Generating Synthetic MR Spectroscopic Imaging Data with Generative Adversarial Networks to Train Machine Learning Models.Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine · 2025Article
- Individualised evaluation based on pathophysiology for moyamoya vasculopathy: application in surgical revascularisation.Stroke and vascular neurology · 2024Article
- Turning brain MRI into diagnostic PET:Medical image analysis · 2024Article
- Evaluation of cerebrovascular reactivity in moyamoya disease using oxygen-dependent magnetic resonance imaging.iScience · 2024Article
- Added value of dynamic contrast-enhanced MR imaging in deep learning-based prediction of local recurrence in grade 4 adult-type diffuse gliomas patients.Scientific reports · 2024Article
- Revascularization improves vascular hemodynamics - a study assessing cerebrovascular reserve and transit time in Moyamoya patients using MRI.Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism · 2023Article
- Convolutional Neural Networks to Assess Steno-Occlusive Disease Using Cerebrovascular Reactivity.Healthcare (Basel, Switzerland) · 2023Article
- Deep-learning-enabled brain hemodynamic mapping using resting-state fMRI.NPJ digital medicine · 2023Article
- A review on AI in PET imaging.Annals of nuclear medicine · 2022Review
- Progression in Moyamoya Disease: Clinical Features, Neuroimaging Evaluation, and Treatment.Current neuropharmacology · 2022Review
- Prediction of an oxygen extraction fraction map by convolutional neural network: validation of input data among MR and PET images.International journal of computer assisted radiology and surgery · 2021Article
Corrections and comments
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Authors and funding
7 authors at 3 institutions in 3 countries.
David Y T ChenFrom the Department of Radiology, The Richard M. Lucas Center for Imaging, Stanford University, 1201 Welch Rd, Stanford, CA 94305 (D.Y.T.C., A.P.F., M.Y.Z., G.Z.); Department of Medical Imaging, Taipei Medical University-Shuan-Ho Hospital, New Taipei City, Taiwan (D.Y.T.C.); Department of Radiology, School of Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan (D.Y.T.C.); Department of Neurosurgery, Tokyo Medical and Dental University, Tokyo, Japan (Y.I.); Department of Bioengineering, University of California Riverside, Riverside, Calif (J.G.); and Department of Neurosurgery, Stanford University, Stanford, Calif (G.K.S.).ORCID 0000-0002-2587-2214
Yosuke IshiiFrom the Department of Radiology, The Richard M. Lucas Center for Imaging, Stanford University, 1201 Welch Rd, Stanford, CA 94305 (D.Y.T.C., A.P.F., M.Y.Z., G.Z.); Department of Medical Imaging, Taipei Medical University-Shuan-Ho Hospital, New Taipei City, Taiwan (D.Y.T.C.); Department of Radiology, School of Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan (D.Y.T.C.); Department of Neurosurgery, Tokyo Medical and Dental University, Tokyo, Japan (Y.I.); Department of Bioengineering, University of California Riverside, Riverside, Calif (J.G.); and Department of Neurosurgery, Stanford University, Stanford, Calif (G.K.S.).ORCID 0000-0001-8944-6241
Audrey P FanFrom the Department of Radiology, The Richard M. Lucas Center for Imaging, Stanford University, 1201 Welch Rd, Stanford, CA 94305 (D.Y.T.C., A.P.F., M.Y.Z., G.Z.); Department of Medical Imaging, Taipei Medical University-Shuan-Ho Hospital, New Taipei City, Taiwan (D.Y.T.C.); Department of Radiology, School of Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan (D.Y.T.C.); Department of Neurosurgery, Tokyo Medical and Dental University, Tokyo, Japan (Y.I.); Department of Bioengineering, University of California Riverside, Riverside, Calif (J.G.); and Department of Neurosurgery, Stanford University, Stanford, Calif (G.K.S.).ORCID 0000-0001-5850-6117
Jia GuoFrom the Department of Radiology, The Richard M. Lucas Center for Imaging, Stanford University, 1201 Welch Rd, Stanford, CA 94305 (D.Y.T.C., A.P.F., M.Y.Z., G.Z.); Department of Medical Imaging, Taipei Medical University-Shuan-Ho Hospital, New Taipei City, Taiwan (D.Y.T.C.); Department of Radiology, School of Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan (D.Y.T.C.); Department of Neurosurgery, Tokyo Medical and Dental University, Tokyo, Japan (Y.I.); Department of Bioengineering, University of California Riverside, Riverside, Calif (J.G.); and Department of Neurosurgery, Stanford University, Stanford, Calif (G.K.S.).ORCID 0000-0003-3371-5857
Moss Y ZhaoFrom the Department of Radiology, The Richard M. Lucas Center for Imaging, Stanford University, 1201 Welch Rd, Stanford, CA 94305 (D.Y.T.C., A.P.F., M.Y.Z., G.Z.); Department of Medical Imaging, Taipei Medical University-Shuan-Ho Hospital, New Taipei City, Taiwan (D.Y.T.C.); Department of Radiology, School of Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan (D.Y.T.C.); Department of Neurosurgery, Tokyo Medical and Dental University, Tokyo, Japan (Y.I.); Department of Bioengineering, University of California Riverside, Riverside, Calif (J.G.); and Department of Neurosurgery, Stanford University, Stanford, Calif (G.K.S.).
Gary K SteinbergFrom the Department of Radiology, The Richard M. Lucas Center for Imaging, Stanford University, 1201 Welch Rd, Stanford, CA 94305 (D.Y.T.C., A.P.F., M.Y.Z., G.Z.); Department of Medical Imaging, Taipei Medical University-Shuan-Ho Hospital, New Taipei City, Taiwan (D.Y.T.C.); Department of Radiology, School of Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan (D.Y.T.C.); Department of Neurosurgery, Tokyo Medical and Dental University, Tokyo, Japan (Y.I.); Department of Bioengineering, University of California Riverside, Riverside, Calif (J.G.); and Department of Neurosurgery, Stanford University, Stanford, Calif (G.K.S.).
Greg ZaharchukFrom the Department of Radiology, The Richard M. Lucas Center for Imaging, Stanford University, 1201 Welch Rd, Stanford, CA 94305 (D.Y.T.C., A.P.F., M.Y.Z., G.Z.); Department of Medical Imaging, Taipei Medical University-Shuan-Ho Hospital, New Taipei City, Taiwan (D.Y.T.C.); Department of Radiology, School of Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan (D.Y.T.C.); Department of Neurosurgery, Tokyo Medical and Dental University, Tokyo, Japan (Y.I.); Department of Bioengineering, University of California Riverside, Riverside, Calif (J.G.); and Department of Neurosurgery, Stanford University, Stanford, Calif (G.K.S.).ORCID 0000-0001-5781-8848
Taipei Medical University Hospital · TWTokyo Medical and Dental University · JPUniversity of California, Riverside · US
Funding
Cerebrovascular Reserve Imaging with Simultaneous PET/MRI Using Arterial Spin Labeling and Deep LearningR01EB025220 · NIBIB · STANFORD UNIVERSITY · PI ZAHARCHUK, GREGORY GEORGE · 2018 to 2021
$2.8MQuantitative PET/MRI of brain oxygenation in cerebrovascular diseaseK99NS102884 · NINDS · STANFORD UNIVERSITY · PI FAN, AUDREY PEIWEN · 2018 to 2019
$170kNIBIB NIH HHS R01 EB025220NINDS NIH HHS K99 NS102884
Abstract
Background Cerebrovascular reserve (CVR) may be measured by using an acetazolamide test to clinically evaluate patients with cerebrovascular disease. However, acetazolamide use may be contraindicated and/or undesirable in certain clinical settings. Purpose To predict CVR images generated from acetazolamide vasodilation with a deep learning network by using only images before acetazolamide administration. Materials and Methods Simultaneous oxygen 15 (
Indexed as
Deep LearningAdolescentAdultBrainCerebrovascular CirculationFemaleHumansMagnetic Resonance ImagingMaleMiddle AgedMoyamoya DiseasePilot ProjectsPositron-Emission TomographyYoung Adult
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.