Evidence map›Paper›PMID 40183965›Full record

ArticleNeuroradiology2025

Using generative adversarial deep learning networks to synthesize cerebrovascular reactivity imaging from pre-acetazolamide arterial spin labeling in moyamoya disease.

Guangming Zhu, Bin Jiang, Hui Chen, Jeremy J Heit, Micah Etter, G Alex Hishaw, Tobias D Faizy, Gary Steinberg, Max Wintermark

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Article in Neuroradiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

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1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

9 authors.

Guangming ZhuDepartment of Neurology, University of Arizona, Tucson, AZ, USA.
Bin JiangDepartment of Radiology, Neuroradiology Section, Stanford University, Stanford, CA, USA.
Hui ChenDepartment of Neuroradiology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Jeremy J HeitDepartment of Radiology, Neuroradiology Section, Stanford University, Stanford, CA, USA.
Micah EtterDepartment of Neurology, University of Arizona, Tucson, AZ, USA.
G Alex HishawDepartment of Neurology, University of Arizona, Tucson, AZ, USA.
Tobias D FaizyDepartment of Neuroradiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
Gary SteinbergDepartment of Neurosurgery, Stanford University, Stanford, CA, USA.
Max WintermarkDepartment of Neuroradiology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA. max.wintermark@gmail.com.ORCID http://orcid.org/0000-0002-6726-3951

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCerebrovascular reactivity (CVR) assesses vascular health in various brain conditions, but CVR measurement requires a challenge to cerebral perfusion such as the administration of acetazolamide(ACZ), thus limiting widespread use. We determined whether generative adversarial networks (GANs) can create CVR images from baseline pre-ACZ arterial spin labeling (ASL) MRI.

methodsThis study included 203 Moyamoya cases with a total of 3248 pre- and post-ACZ ASL Cerebral Blood Flow (CBF) images. Reference CVRs were generated from these CBF slices. From this set, 2640 slices were used to train a Pixel-to-Pixel GAN consisting of a generator and discriminator network, with the remaining 608 slices reserved as a testing set. Following training, the pre-ACZ CBF in the testing set was introduced to the trained model to generate synthesized CVR. The quality of the synthesized CVR was evaluated with structural similarity index(SSI), spatial correlation coefficient(SCC), and the root mean squared error(RMSE), compared with reference CVR. The segmentations of the low CVR regions were compared using the Dice similarity coefficient (DSC). Reference and synthesized CVRs in single-slice and individual-hemisphere settings were reviewed to assess CVR status, with Cohen's Kappa measuring consistency.

resultsThe mean SSIs of the CVR of training and testing sets were 0.943 ± 0.019 and 0.943 ± 0.020. The mean SCCs of the CVR of training and testing sets were 0.988 ± 0.009 and 0.987 ± 0.011. The mean RMSEs of the CVR are 0.077 ± 0.015 and 0.079 ± 0.018. Mean DSC of low CVR area of testing sets was 0.593 ± 0.128. Visual interpretation yielded Cohen's Kappa values of 0.896 and 0.813 for the training and testing sets in the single-slice setting, and 0.781 and 0.730 in the individual-hemisphere setting.

conclusionsSynthesized CVR by GANs from baseline ASL without challenge may be a useful alternative in detecting vascular deficits in clinical applications when ACZ challenge is not feasible.

Indexed as

AcetazolamideCerebrovascular CirculationDeep LearningMagnetic Resonance AngiographyMagnetic Resonance ImagingMoyamoya DiseaseAdolescentAdultChildFemaleHumansImage Interpretation, Computer-AssistedMaleMiddle AgedSpin LabelsAcetazolamideSpin LabelsArterial spin labelingCerebral blood flowCerebrovascular reactivityDeep learningGenerative adversarial networks

Identifiers

PMID40183965

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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.