Deep learning model based on automated CT image segmentation for predicting the optimal radiotherapy protocol in limited-stage small cell lung cancer patients: a multicenter study

Radiotherapy combined with chemotherapy is the standard treatment regimen for patients with limited-stage small cell lung cancer (LS-SCLC), but the optimal radiotherapy regimen for these patients remains unclear. This study aims to construct an integrated, two-stage “image segmentation-response prediction” deep learning (DL) framework. By leveraging automated tumor segmentation to accurately define tumor habitats, this framework extracts deep imaging features to predict the optimal radiotherapy regimen for LS-SCLC patients.