Dual-Time-Point Radiomics for Prognosis Prediction in Colorectal Liver Metastasis Treated with Neoadjuvant Therapy Before Radical Resection: A Two-Center Study

Abstract

Background: Optimal prognostic stratification for colorectal liver metastases (CRLM) patients undergoing surgery with neoadjuvant therapy (NAT) remains elusive. This study aimed to develop and validate dual-time-point radiomic models for CRLM prognosis prediction using pre- and post-NAT imaging features.

Methods: Radiomic features were extracted from four MRI sequences in 100 cases of CRLM patients who underwent NAT and radical resection. RAD scores were generated, and clinical/pathologic variables were incorporated into uni- and multivariate Cox regression analyses to construct prognosis models. Time-ROC, time-C index, decision curve analysis (DCA), and calibration curves assessed the predictive performance of Fong score and pre- and post-NAT models for overall survival (OS) and disease-free survival (DFS) in a testing set.

Results: The final models included four variables for OS and three variables for DFS. The post-NAT models outperformed the pre-NAT models in time-ROC, time-C index, calibration, and DCA analysis, except for the 1-year DFS area under the curve (AUC). The Fong score models underperformed. The post-NAT OS RAD score effectively stratified patients into prognostic subgroups.

Conclusions: The radiomic models incorporating pre- and post-NAT MRI features and clinical/pathologic variables effectively stratified CRLM patients prognositically. The post-NAT models demonstrated superior performance.

Keywords: Colorectal liver metastasis; MRI; Neoadjuvant treatment; Prognosis; Radiomics.