Abstract #0079

Prognosis prediction based on penumbra and infarct core radiomics features in patients with acute ischemic stroke

Xiaoling Wu¹, Jing Zhang², Fei Wang¹, Xiao Zhang³, Mengzhou Sun⁴, Pinjia Cai⁵, Zihan Li⁵, Shuixing Zhang¹, and Xiaoyun Liang²

¹Department of Radiology, The First Affiliated Hospital of Jinan University, Guangzhou, Guangdong, China, ²Institute of Research and Clinical Innovations, Neusoft Medical Systems Co., Ltd, Shanghai, China, ³Institute of Research and Clinical Innovations, Neusoft Medical Systems Co., Ltd, Guangzhou, China, ⁴Institute of Research and Clinical Innovations, Neusoft Medical Systems Co., Ltd, Beijing, China, ⁵Neusoft Medical Systems Co. Ltd,, Shenyang, China

Synopsis

Keywords: Stroke, Radiomics

Motivation: The identification and assessment of the penumbra are crucial for making the right treatment decisions and improving clinical outcomes in acute ischemic stroke (AIS) patients.

Goal(s): To develop a radiomics model based ASL and DWI to predict outcomes of AIS patients with clinical factors.

Approach: Radiomics features were extracted from penumbra and infarct core in 151 patients with clinical parameters. Five-fold cross-validation was performed on 70% data sets, and the model performance was evaluated by an independent test cohort.

Results: The joint model with 4 radiomics features from infarct core and NHISS score yielded highest AUC of 0.802.

Impact: The combined model incorporating clinical factors and radiomics features based on infarct core and penumbra has achieved satisfactory performance in predicting the outcomes of AIS patients, which provides a non-invasive approach to optimize individualized treatment for AIS patients.

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