Computed tomography-based deep-learning prediction of neoadjuvant chemoradiotherapy treatment response in esophageal squamous cell carcinoma

Deep learning provides efficient and accurate prediction of treatment response. Transfer learning can be used in radiological task with insufficient image datasets. Tumor microenvironment and signaling pathways are linked with radiological prediction. Deep learning is promising to predict treatment response. We aimed to evaluate and validate the predictive performance of the CT-based model using deep learning features for predicting pathologic complete response to neoadjuvant chemoradiotherapy (nCRT) in esophageal squamous cell carcinoma (ESCC).