A proposed radiological model for preoperative chemotherapy response prediction in patients with skeletal Ewing sarcoma.

Abstract

Objective: To develop a predictive model for estimating the histological response to preoperative chemotherapy based on imaging data in patients with Ewing sarcoma.

Materials and methods: We included 133 patients with Enneking stage IIB or IIIB Ewing sarcoma who underwent chemotherapy and definitive surgery between 2003 and 2020. We analyzed various radiological parameters before and after preoperative chemotherapy. The necrotic area was evaluated using gadolinium-contrasted magnetic resonance imaging (radiological necrotic grade). Patients were classified as good histological responders if > 95% of their resected specimens showed necrosis; otherwise, they were classified as poor responders. Radiological parameters were assessed using the least absolute shrinkage and selection operator (LASSO) with cross-validation. Optimal regularization parameters were identified as those minimizing cross-validation error. The area under the curve (AUC) was calculated based on the predictive model with the selected parameters for training and test data using receiver operating characteristic (ROC) curve.

Results: LASSO models identified key parameters including volume change, radiological necrotic grade, complete regression of the extraskeletal component, and the disappearance of peritumoral gadolinium-enhancement after preoperative chemotherapy. ROC curve analysis showed that the predictive model achieved measurable discrimination ability on both training and test datasets (AUC = 0.89 [95% confidence interval (95%CI); 0.83-0.95] on training data, 0.77 [95%CI; 0.58-0.95] on test data).

Conclusion: The developed model may facilitate accurate monitoring of the efficacy of preoperative chemotherapy in patients with Ewing sarcoma. Identifying patients with a poor histological response to preoperative chemotherapy can aid in the planning of secure surgical margins and effective treatment strategies.