Abstract #0713

CVT Detection with Routine Brain MRI Sequences by Multi-Modal Multi-Task Deep Learning algorithm

Xiaoxu Yang¹, Pengxin Yu², Haoyue Zhang², Rongguo Zhang², Yuehong Liu¹, Xiuqin Jia¹, Penghui Sun¹, Xin Liu¹, Xunming Ji³, Qi Yang¹, and Chen Zhang⁴

¹Beijing Chaoyang Hospital, Beijing, China, ²Infervision Medical Technology Co., Ltd, Beijing, China, Beijing, China, ³Beijing Xuanwu Hospital, Beijing, China, ⁴MR Scientific Marketing, Siemens Healthineers, Beijing, China, Beijing, China

Synopsis

Keywords: Stroke, BrainA deep learning algorithm for detecting cerebral venous thrombosis using routine brain MRI achieved higher patient-level sensitivity than radiologists and reduced the number of overlooked thrombosed segments. The proposed deep learning (DL) algorithm achieved area under the receiver operating characteristic curve of 0.96 for detecting patient with cerebral venous thrombosis. The sensitivity of DL algorithm was higher than that of radiologists and obtained high specificity on patient-level.Compared to radiologists, DL algorithm found more thrombosed segments, indicating greater sensitivity and a sufficient specificity at the segment-level.

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