CT-based radiomics analysis to predict local progression of recurrent colorectal liver metastases after microwave ablation.

ABSTRACT

The objective of this study is to establish and validate a radiomics nomogram for prediction of local tumor progression (LTP) after microwave ablation (MWA) for recurrent colorectal liver metastases (CRLM) after hepatic resection. We included 318 consecutive recurrent CRLM patients (216 of training while 102 of validation cohort) with contrast-enhanced computerized tomography images treated with MWA between January 2014 and October 2018. Support vector machine-generated radiomics signature was incorporated together with clinical information to establish a radiomics nomogram. Our constructed radiomics signature including 15 features (first-order intensity statistics features, shape and size-based features, gray level size zone/dependence matrix features) performed well in assessing LTP for both cohorts. With regard to its predictive performance, its C-index was 0.912, compared to the clinical or radiomics models only (c-statistic 0.89 and 0.75, respectively) in the training cohort. In the validation cohort, the radiomics nomogram had better performance (area under the curve = 0.89) compared to the radiomics and clinical models (0.85 and 0.69). According to decision curve analysis, our as-constructed radiomics nomogram showed high clinical utility. As revealed by survival analysis, LTP showed worse progression-free survival (3-year progression-free survival 42.6% vs 78.4%, P < .01). High-risk patients identified using this radiomics signature exhibited worse LTP compared with low-risk patients (3-year LTP 80.2% vs 48.6%, P < .01). A radiomics-based nomogram of pre-ablation computerized tomography imaging may be the precious biomarker model for predicting LTP and personalized risk stratification for recurrent CRLM after hepatic resection treated by MWA.