Baseline hepatobiliary MRI for predicting chemotherapeutic response and prognosis in initially unresectable colorectal cancer liver metastases

Author:

Chen Yazheng,Lu Tao,Zhang Yongchang,Li Hang,Xu Jingxu,Li Mou

Abstract

Abstract Purpose To evaluate the performance of hepatobiliary MRI parameters as predictors of clinical response to chemotherapy in patients with initially unresectable colorectal cancer liver metastases (CRLM). Methods Eighty-five patients with initially unresectable CRLM were retrospectively enrolled from two hospitals and scanned using gadobenate dimeglumine-enhanced MRI before treatment. Therapy response was evaluated based on the Response Evaluation Criteria in Solid Tumors (RECIST) version 1.1. Conventional parameters (i.e., signal intensity [SI]) and radiomics features of portal venous phase (PVP) and hepatobiliary phase (HBP) images were analyzed between the responders and non-responders. Next, the combined model was constructed, and the area under the receiver operating characteristic (ROC) curve (AUC) was calculated. The relationship between the combined model and progression-free survival (PFS) was analyzed using Cox regression. Results Of the 85 patients from two hospitals, 42 were in the response group, and 43 were in the non-response group. Upon conducting five-fold cross-validation, the normalized relative enhancement (NRE) of CRLM during the PVP yielded an AUC of 0.625. Additionally, a radiomics feature derived from the tumor area in the HBP achieved an AUC of 0.698, while a separate feature extracted from the peritumoral region in the HBP recorded an AUC of 0.709. The model that integrated these three features outperformed the individual features, achieving an AUC of 0.818. Furthermore, the combined model exhibited a significant correlation with PFS (P < 0.001). Conclusion The combined model, based on baseline hepatobiliary MRI, aids in predicting chemotherapeutic response and PFS in patients with initially unresectable CRLM.

Funder

the Natural Science Foundation of Sichuan Province from Science & Technology Department of Sichuan Province

Foundation of Sichuan Provincial People’s Hospital

Publisher

Springer Science and Business Media LLC

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