608 RADIOMICS MODEL FACILITATES ORGAN-SAVING STRATEGY IN PATIENTS WITH ESOPHAGEAL SQUAMOUS CELL CANCER RECEIVING NEOADJUVANT CHEMORADIOTHERAPY

After neoadjuvant chemoradiotherapy(NCRT) in locally advanced esophageal squamous cell cancer(ESCC), roughly 40% of the patients may achieve pathologic complete response (pCR) of the primary tumor. Those patients may benefit from organ-saving strategy if the probability of pCR could be correctly identified before esophagectomy. A reliable approach to predict pathological response allows future studies to investigate individualized treatment plans. We aim to establish a CT-based radiomics model to predict tumor response to NCRT. Methods 121 patients with ESCC who underwent NCRT followed by esophagectomy were retrospectively collected. Radiomics features extracted from pre−/post-NCRT CT images were selected by univariate logistic (p < 0.157) and LASSO regression. A radiomics signature(RS) developed with selected features was combined with 4 clinical variables, including percentage of tumor thickness reduction, tumor adventitia type, tumor minimum diameter on post-NCRT esophagogram and age, to construct RS + clinical model with multivariate logistic regression which was internally validated by bootstrapping. Performance and clinical usefulness of RS + clinical model were assessed by receiver operating characteristic(ROC) curves and decision curve analysis, respectively, comparing with the model of clinical variables alone. Results Among the 121 patients, 51 achieved pCR(42%) after NCRT. 16 radiomics features were selected and incorporated into RS. The RS + clinical model has improved prediction performance for pCR compared with the clinical model(corrected area under the ROC curve,0.843 vs. 0.700). At the 60% probability threshold cutoff(i.e., the patient would opt for observation if his probability of pCR was >60%), net 12% surgeries could be avoided by RS + clinical model without an increase in the number of missed residual diseases, equivalent to implementing organ-saving strategy in 29.4% of the 51 true-pCR cases. Conclusion The model built with CT radiomics features and clinical variables shows the potential of predicting pCR after NCRT; it provides significant clinical benefit in identifying qualified patients to receive individualized organ-saving treatment plans.