Prediction of functional outcome in patients with ischemic stroke using advanced diffusion-weighted MRI parameters at 3 Tesla

IF 11.1 2区医学 Q1 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING

Diagnostic and Interventional Imaging Pub Date : 2026-10-01 Epub Date: 2026-03-19 DOI:10.1016/j.diii.2026.03.001

Aurore Sajust de Bergues de Escalup, Loïc Duron, Pierre Seners, Candice Sabben, Michael Obadia, Amélie Yavchitz, Julien Savatovsky, Augustin Lecler

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Abstract

Purpose

The purpose of this study was to prospectively evaluate the contribution of intravoxel incoherent motion (IVIM) and diffusion kurtosis imaging (DKI) for predicting outcome after ischemic stroke.

Materials and methods

Patients with acute ischemic stroke who underwent brain MRI at 3 Tesla, including a multi-b diffusion-weighted imaging sequence were prospectively included. Mean, maximum (max) and minimum (min) of diffusion parameters, including apparent diffusion coefficient (ADC), D, D*, f, f·D* and K were extracted from the infarct core and normal-appearing parenchyma. The primary endpoint was 3-month modified Rankin scale (mRS). Associations were tested by univariable ordinal logistic regression with false discovery rate correction. Model performance was assessed using area under the receiver operating characteristic curve (AUC) analysis and the ranked probability score.

Results

A total of 157 patients were included. There were 83 men and 74 women with a mean age of 70 ± 16 (standard deviation) years (range: 23–100 years). In univariable analyses, ADCmin in the infarct core was the strongest predictor of worse functional outcome at 3 months (OR, 0.37; P < 0.001). Within the infarct core, nine other parameters were significantly associated with mRS (one ADC, six IVIM and two DKI metrics). In the normal-appearing parenchyma, eight parameters (two ADC, four IVIM and two DKI metrics) were significantly associated with outcome. In multivariable analysis, the model combining ADCmin and Kmin in the core with ADCmax in the normal-appearing parenchyma provided the highest prognostic performance, with an AUC of 0.81 (95 % confidence interval [CI]: 0.77–0.86) compared to ADCmin alone (AUC, 0.75; 95 % CI: 0.67–0.82) (P < 0.0001).

Conclusion

A combination of advanced diffusion MRI parameters could predict functional outcome in patients with ischemic stroke with higher precision than standard ADC alone.

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利用3特斯拉高级弥散加权MRI参数预测缺血性脑卒中患者的功能结局。

目的：本研究的目的是前瞻性评估体素内非相干运动（IVIM）和弥散峰度成像（DKI）对预测缺血性脑卒中预后的贡献。材料和方法：前瞻性纳入接受3特斯拉脑MRI检查的急性缺血性卒中患者，包括多b弥散加权成像序列。提取梗死核心及外观正常的实质弥散参数的平均值、最大值（max）和最小值（min），包括表观弥散系数（ADC）、D、D*、f、f·D*和K。主要终点为3个月改良Rankin量表（mRS）。关联检验采用单变量有序逻辑回归并校正错误发现率。使用受试者工作特征曲线下面积（AUC）分析和排序概率评分来评估模型的性能。结果：共纳入157例患者。男性83例，女性74例，平均年龄70±16（标准差）岁（范围：23-100岁）。在单变量分析中，梗死核心的ADCmin是3个月时功能预后恶化的最强预测因子（OR, 0.37; P < 0.001）。在梗死核心内，其他9个参数与mRS显著相关（1个ADC， 6个IVIM和2个DKI指标）。在外观正常的实质中，8个参数（2个ADC、4个IVIM和2个DKI指标）与预后显著相关。在多变量分析中，与单独使用ADCmin （AUC为0.75,95% CI为0.67-0.82）相比，将核心ADCmin和Kmin与正常实质ADCmax相结合的模型具有最高的预后性能，AUC为0.81(95%可信区间[CI]: 0.77-0.86) （P < 0.0001）。结论：联合先进的弥散MRI参数预测缺血性脑卒中患者的功能预后比单独使用标准ADC具有更高的准确性。

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

Diagnostic and Interventional Imaging Medicine-Radiology, Nuclear Medicine and Imaging

CiteScore

8.50

自引率

29.10%

发文量

126

审稿时长

11 days

期刊介绍： Diagnostic and Interventional Imaging accepts publications originating from any part of the world based only on their scientific merit. The Journal focuses on illustrated articles with great iconographic topics and aims at aiding sharpening clinical decision-making skills as well as following high research topics. All articles are published in English. Diagnostic and Interventional Imaging publishes editorials, technical notes, letters, original and review articles on abdominal, breast, cancer, cardiac, emergency, forensic medicine, head and neck, musculoskeletal, gastrointestinal, genitourinary, interventional, obstetric, pediatric, thoracic and vascular imaging, neuroradiology, nuclear medicine, as well as contrast material, computer developments, health policies and practice, and medical physics relevant to imaging.