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

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.