CT-radiomics and pathological tumor response to systemic therapy: A predictive analysis for colorectal liver metastases. Development and internal validation of a clinical-radiomic model

Abstract

Introduction: The standard treatment of colorectal liver metastases (CRLM) is surgery with perioperative chemotherapy. A tumor response to systemic therapy confirmed at pathology examination is the strongest predictor of survival, but it cannot be adequately predicted in the preoperative setting. This bi-institutional retrospective study investigates whether CT-based radiomics of CRLM and peritumoral tissue provides a reliable non-invasive estimation of the pathological tumor response to chemotherapy.

Methods: All consecutive patients undergoing liver resection for CRLM at the two institutions were considered. Only patients with a radiological partial response or stable disease at chemotherapy and with a preoperative/post-chemotherapy CT performed <60 days before surgery were included. The pathological response was evaluated according to the tumor regression grade (TRG). The tumor (Tumor-VOI) was manually segmented on the portal phase of the CT and a 5-mm ring of peritumoral tissue was automatically generated (Margin-VOI). The predictive models underwent internal validation.

Results: Overall, 222 patients were included; 64 had a pathological response (29 %, TRG1-3). Two-third of patients displaying a radiological response (111/170) did not have a pathological one (TRG4-5). For TRG1-3 prediction, the clinical model performed fairly (Accuracy = 0.725, validation-AUC = 0.717 95%CI = 0.652-0.788). Radiomics improved the results: the model combining the clinical data and Tumor-VOI features had Accuracy = 0.743 and validation-AUC = 0.729 (95%CI = 0.665-0.798); the full model (clinical/Tumor-VOI/Margin-VOI) achieved Accuracy = 0.820 and validation-AUC = 0.768 (95%CI = 0.707-0.826).

Conclusion: CT-based radiomics of CRLM allows an insightful non-invasive assessment of TRG. The combined analysis of the tumor and peritumoral tissue improves the prediction. In association with clinical data, the radiomic indices outperform standard radiological and clinical evaluation.

Keywords: Colorectal liver metastases; Computed tomography; Neoadjuvant chemotherapy; Pathological response; Radiomics; Tumor regression grade.