Evaluation of Computer-Assisted Quantitative Volumetric Analysis for Pre-Operative Resectability Assessment of Huge Hepatocellular Carcinoma

Purpose: Hepatic resection is arguably the preferred treatment for huge hepatocellular carcinoma (H-HCC). Estimating the remnant liver volume is therefore essential. This study aimed to evaluate the feasibility of using computer-assisted volumetric analysis for this purpose. Methods: The study involved 40 patients with H-HCC. Laboratory examinations were conducted, and a contrast CT-scan revealed that 30 cases out of the participating 40 had single-lesion tumors. The remaining 10 had less than three satellite tumors. With the consensus of the team, two physicians conducted computer-assisted 3D segmentation of the liver, tumor, and vessels in each case. Volume was automatically computed from each segmented/labeled anatomical field. To estimate the resection volume, virtual lobectomy was applied to the main tumor. A margin greater than 1 cm was applied to the satellite tumors. Resectability was predicted by computing a ratio of functional liver resection (R) as (Vresected-Vtumor)/(Vtotal-Vtumor) x 100%, applying a threshold of 50% and 60% for cirrhotic and non-cirrhotic cases, respectively. This estimation was then compared with surgical findings. Results: Out of the 22 patients who had undergone hepatectomies, only one had an R that exceeded the threshold. Among the remaining 18 patients with non-resectable H-HCC, 12 had Rs that exceeded the specified ratio and the remaining 6 had Rs that were < 50%. Four of the patients who had Rs less than 50% underwent incomplete surgery due to operative findings of more extensive satellite tumors, vascular invasion, or metastasis. The other two cases did not undergo surgery because of the high risk involved in removing the tumor. Overall, the ratio of functional liver resection for estimating resectability correlated well with the other surgical findings. Conclusion: Efficient pre-operative resectability assessment of H-HCC using computer-assisted volumetric analysis is feasible.