Prediction model for hypertrophied liver volume followed by hemihepatectomy: a retrospective cohort study.

PURPOSE: This study aimed to develop a statistical model for predicting hypertrophied future liver remnant volume (HFLRV) in patients with right hemihepatectomy (RHH). METHODS: Patients who underwent RHH at Samsung Medical Center between January 2022 and March 2024 were included in this study. Liver volume was calculated from abdomen CT by using a deep learning-based volumetric tool. RESULTS: A total of 98 patients were included. There were 58 and 40 patients whose liver regeneration index was less than 0.8 and 0.8 or more, respectively. The prediction model, which focused on identifying variables associated with HFLRV, included age at diagnosis (P = 0.14), sex (P = 0.01), both preoperative hemi-liver volumes (P < 0.001), and international normalized ratio (P < 0.05). This model demonstrated adjusted R2 of 0.60, correlation coefficient (r) of 0.78, and P-value of <0.001. CONCLUSION: This study developed a linear prediction model for HFLRV and determined which factors can be used to predict HFLRV before RHH.