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Updated: Jul 21, 2025
Advanced Animal Model of Colorectal Metastasis in Liver: Imaging Techniques and Properties of Metastatic Clones
Published on: November 30, 2016
Development of an Algorithm to Predict Recurrences After Resection of Liver Metastases in Patients With Metastatic
Mitsuhiro Katagiri1, Tomoya Sudo2, Tatsuyuki Tounann3
1Department of Surgery, Kurume University, Kurume, Japan; m.katagiri507@gmail.com.
Background/Aim:
Hepatic recurrences after resection of metastatic lesions in advanced colorectal cancer (CRC) have an enormous impact on patient prognosis. Response evaluation criteria in solid tumor (RECIST) or morphologic response on computed tomography (CT) have been reported as surrogate prognostication markers. This study assessed a novel algorithm for the prognostication of liver metastasis treatment.
Patients And Methods:
Forty-seven patients with liver metastases from CRC who underwent liver resection after systemic chemotherapy were included. The CT values examined before and after chemotherapy were collected. The velocity of CT values (CTvΔ) was calculated, and the subjects were divided into CTvΔ_high and _low groups. Clinicopathological variables, recurrence-free survival (RFS), and overall survival (OS) were statistically compared between the two groups. In addition, the effect of the combined evaluation of CTvΔ and carcinoembryonic antigen (CEA) was evaluated.
Results:
In univariate analyses, the hazard ratio (HR) for a recurrence after liver resection was relatively higher in the RECIST_stable disease (SD) or _progressive disease (PD) and the CTvΔ_low groups. In multivariate analysis, the HR was significantly higher in the CEA_high, the RECIST_SD or PD, and the CTvΔ_low groups. The RFS was significantly longer in the CTvΔ_high group. Furthermore, the combination of CTvΔ and CEA predicted the RFS and OS.
Conclusion:
Our algorithm using CTvΔ could be a useful tool to select patients suitable for liver resection of hepatic CRC metastases.
