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CT 灌注卒中成像:一种与传统缺血阈值相比可预测梗死体积的无阈值概率方法。

CT-perfusion stroke imaging: a threshold free probabilistic approach to predict infarct volume compared to traditional ischemic thresholds.

机构信息

Department of Diagnostic and Interventional Neuroradiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.

Department of Radiology and Hotchkiss Brain Institute, University of Calgary, Calgary, Canada.

出版信息

Sci Rep. 2017 Jul 27;7(1):6679. doi: 10.1038/s41598-017-06882-w.

Abstract

The aim was to evaluate a novel method of threshold-free prediction of brain infarct from computed tomography perfusion (CTP) imaging in comparison to conventional ischemic thresholds. In a multicenter cohort of 161 patients with acute large vessel occlusion who received endovascular therapy, brain infarction was predicted by CTP using (1) optimized parameter cut-off values determined by ROC curve analysis and (2) probabilistic logistic regression threshold-free analysis. Predicted infarct volumes and prediction errors based on four perfusion parameter maps were compared against observed infarcts. In 93 patients with successful recanalization, the mean observed infarct volume was 35.7 ± 61.9 ml (the reference for core infarct not savable by reperfusion). Optimal parameter thresholds predicted mean infarct volumes between 53.2 ± 44.4 and 125.0 ± 95.4 ml whereas threshold-free analysis predicted mean volumes between 35.9 ± 28.5 and 36.1 ± 29.0 ml. In 68 patients with persistent occlusion, the mean observed infarct volume was 113.4 ± 138.3 ml (the reference to define penumbral infarct savable by reperfusion). Predicted mean infarct volumes by parameter thresholds ranged from 91.4 ± 81.5 to 163.8 ± 135.7 ml, by threshold-free analysis from 113.2 ± 89.9 to 113.5 ± 89.0 ml. Threshold-free prediction of infarct volumes had a higher precision and lower patient-specific prediction error than conventional thresholding. Penumbra to core lesion mismatch estimate may therefore benefit from threshold-free CTP analysis.

摘要

目的是评估一种新的方法,即通过计算机断层灌注(CTP)成像对脑梗死进行无阈值预测,并与传统的缺血性阈值进行比较。在一项多中心队列研究中,对 161 例接受血管内治疗的急性大血管闭塞患者进行了 CTP 预测,其中包括(1)通过 ROC 曲线分析确定的优化参数截断值和(2)无阈值概率逻辑回归分析。将基于四个灌注参数图的预测梗死体积和预测误差与观察到的梗死进行了比较。在 93 例成功再通的患者中,观察到的平均梗死体积为 35.7 ± 61.9 ml(即不能通过再灌注挽救的核心梗死的参考值)。最佳参数阈值预测的平均梗死体积在 53.2 ± 44.4 和 125.0 ± 95.4 ml 之间,而无阈值分析预测的平均体积在 35.9 ± 28.5 和 36.1 ± 29.0 ml 之间。在 68 例持续闭塞的患者中,观察到的平均梗死体积为 113.4 ± 138.3 ml(即定义可通过再灌注挽救的缺血半暗带梗死的参考值)。通过参数阈值预测的平均梗死体积范围为 91.4 ± 81.5 至 163.8 ± 135.7 ml,通过无阈值分析为 113.2 ± 89.9 至 113.5 ± 89.0 ml。与传统阈值法相比,无阈值预测梗死体积的精度更高,患者特异性预测误差更小。因此,无阈值 CTP 分析可能会受益于半暗带-核心病变不匹配的估计。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9909/5532266/5c97121fc13d/41598_2017_6882_Fig1_HTML.jpg

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