Prediction of Local Tumor Progression After Thermal Ablation of Colorectal Cancer Liver Metastases Based on Magnetic Resonance Imaging Δ-Radiomics.

Purpose: This study aimed to enhance the predictability of local tumor progression (LTP) postthermal ablation in patients with colorectal cancer liver metastases (CRLMs). A sophisticated approach integrating magnetic resonance imaging (MRI) Δ-radiomics and clinical feature-based modeling was employed.

Materials and methods: In this retrospective study, 37 patients with CRLM were included, encompassing a total of 57 tumors. Radiomics features were derived by delineating the images of lesions pretreatment and images of the ablation zones posttreatment. The change in these features, termed Δ-radiomics, was calculated by subtracting preprocedure values from postprocedure values. Three models were developed using the least absolute shrinkage and selection operators (LASSO) and logistic regression: the preoperative lesion model, the postoperative ablation area model, and the Δ model. Additionally, a composite model incorporating identified clinical features predictive of early treatment success was created to assess its prognostic utility for LTP.

Results: LTP was observed in 20 out of the 57 lesions (35%). The clinical model identified, tumor size (P = 0.010), and ΔCEA (P = 0.044) as factors significantly associated with increased LTP risk postsurgery. Among the three models, the Δ model demonstrated the highest AUC value (T2WI AUC in training, 0.856; Delay AUC, 0.909; T2WI AUC in testing, 0.812; Delay AUC, 0.875), whereas the combined model yielded optimal performance (T2WI AUC in training, 0.911; Delay AUC, 0.954; T2WI AUC in testing, 0.847; Delay AUC, 0.917). Despite its superior AUC values, no significant difference was noted when comparing the performance of the combined model across the two sequences (P = 0.6087).

Conclusions: Combined models incorporating clinical data and Δ-radiomics features serve as valuable indicators for predicting LTP following thermal ablation in patients with CRLM.