A multimodal synergistic model for personalized neoadjuvant immunochemotherapy in esophageal cancer.

ABSTRACT: Neoadjuvant immunochemotherapy (nICT) has significantly improved the treatment of locally advanced esophageal cancer (EC), yet accurately identifying patients' response remains a major challenge. In this study, we introduce eSPARK, a multimodal framework designed to integrate routinely available clinical data for informed decision-making in nICT treatment for EC. The model is developed using 344 patients from three independent regions, each with pre-treatment-paired computed tomography (CT) imaging and pathological slides, and postoperative pathological complete response (pCR) outcomes. By incorporating cytological semantic information, eSPARK demonstrates superior generalizability, outperforming single-modality models and achieving robust predictive accuracy across multicenter datasets. A

SUBMITTER: Zhao Z 

PROVIDER: S-EPMC12765826 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature