Automated DWI-FLAIR mismatch assessment in stroke using DWI only.

IF 4.5 3区医学 Q1 CLINICAL NEUROLOGY

European Stroke Journal Pub Date : 2025-08-28 DOI:10.1177/23969873251362712

Joseph Benzakoun, Lauranne Scheldeman, Anke Wouters, Bastian Cheng, Martin Ebinger, Matthias Endres, Jochen B Fiebach, Jens Fiehler, Ivana Galinovic, Keith W Muir, Norbert Nighoghossian, Salvador Pedraza, Josep Puig, Claus Z Simonsen, Vincent Thijs, Götz Thomalla, Emilien Micard, Bailiang Chen, Bertrand Lapergue, Grégoire Boulouis, Alice Le Berre, Jean-Claude Baron, Guillaume Turc, Wagih Ben Hassen, Olivier Naggara, Catherine Oppenheim, Robin Lemmens

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引用次数: 0

Abstract

Introduction: In Acute Ischemic Stroke (AIS), mismatch between Diffusion-Weighted Imaging (DWI) and Fluid-Attenuated Inversion-Recovery (FLAIR) helps identify patients who can benefit from thrombolysis when stroke onset time is unknown (15% of AIS). However, visual assessment has suboptimal observer agreement. Our study aims to develop and validate a Deep-Learning model for predicting DWI-FLAIR mismatch using solely DWI data.

Patients and methods: This retrospective study included AIS patients from ETIS registry (derivation cohort, 2018-2024) and WAKE-UP trial (validation cohort, 2012-2017). DWI-FLAIR mismatch was rated visually. We trained a model to predict manually-labeled FLAIR visible areas (FVA) matching the DWI lesion on baseline and early follow-up MRIs, using only DWI as input. FVA-index was defined as the volume of predicted regions. Area under the ROC curve (AUC) and optimal FVA-index cutoff to predict DWI-FLAIR mismatch in the derivation cohort were computed. Validation was performed using baseline MRIs of the validation cohort.

Results: The derivation cohort included 3605 MRIs in 2922 patients and the validation cohort 844 MRIs in 844 patients. FVA-index demonstrated strong predictive value for DWI-FLAIR mismatch in baseline MRIs from the derivation (n = 2453, AUC = 0.85, 95%CI: 0.84-0.87) and validation cohort (n = 844, AUC = 0.86, 95%CI: 0.84-0.89). With an optimal FVA-index cutoff at 0.5, we obtained a kappa of 0.54 (95%CI: 0.48-0.59), 70% sensitivity (378/537, 95%CI: 66-74%) and 88% specificity (269/307, 95%CI: 83-91%) in the validation cohort.

Discussion and conclusion: The model accurately predicts DWI-FLAIR mismatch in AIS patients with unknown stroke onset. It could aid readers when visual rating is challenging, or FLAIR unavailable.

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自动DWI- flair错配评估中风仅使用DWI。

简介：在急性缺血性卒中（AIS）中，弥散加权成像（DWI）和液体衰减反转恢复（FLAIR）之间的不匹配有助于识别在卒中发病时间未知（15%的AIS）时可以从溶栓治疗中获益的患者。然而，视觉评估具有次优的观察者一致性。我们的研究旨在开发和验证一个深度学习模型，用于仅使用DWI数据预测DWI- flair不匹配。患者和方法：本回顾性研究纳入了来自ETIS登记（衍生队列，2018-2024）和wake - wake试验（验证队列，2012-2017）的AIS患者。DWI-FLAIR失配目测评定。我们训练了一个模型来预测手工标记的FLAIR可见区域（FVA），该区域与基线和早期随访mri上的DWI病变相匹配，仅使用DWI作为输入。fva指数定义为预测区域的体积。计算ROC曲线下面积（AUC）和预测衍生队列DWI-FLAIR失配的最佳fva指数截止值。使用验证队列的基线mri进行验证。结果：衍生队列包括2922例患者的3605个mri，验证队列包括844例患者的844个mri。从推导（n = 2453, AUC = 0.85, 95%CI: 0.84-0.87）和验证队列（n = 844, AUC = 0.86, 95%CI: 0.84-0.89）的基线mri中，fva指数显示出对DWI-FLAIR不匹配的强大预测价值。在验证队列中，最佳fva指数截止值为0.5，kappa为0.54 (95%CI: 0.48-0.59)，敏感性为70% (378/537,95%CI: 66-74%)，特异性为88% （269/307,95%CI: 83-91%）。讨论与结论：该模型能准确预测脑卒中发病未知的AIS患者的DWI-FLAIR失配。它可以帮助读者，当视觉评级是具有挑战性的，或FLAIR不可用。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

European Stroke Journal Multiple-

CiteScore

7.50

自引率

6.60%

发文量

102

期刊介绍： Launched in 2016 the European Stroke Journal (ESJ) is the official journal of the European Stroke Organisation (ESO), a professional non-profit organization with over 1,400 individual members, and affiliations to numerous related national and international societies. ESJ covers clinical stroke research from all fields, including clinical trials, epidemiology, primary and secondary prevention, diagnosis, acute and post-acute management, guidelines, translation of experimental findings into clinical practice, rehabilitation, organisation of stroke care, and societal impact. It is open to authors from all relevant medical and health professions. Article types include review articles, original research, protocols, guidelines, editorials and letters to the Editor. Through ESJ, authors and researchers have gained a new platform for the rapid and professional publication of peer reviewed scientific material of the highest standards; publication in ESJ is highly competitive. The journal and its editorial team has developed excellent cooperation with sister organisations such as the World Stroke Organisation and the International Journal of Stroke, and the American Heart Organization/American Stroke Association and the journal Stroke. ESJ is fully peer-reviewed and is a member of the Committee on Publication Ethics (COPE). Issues are published 4 times a year (March, June, September and December) and articles are published OnlineFirst prior to issue publication.