Validation of a Semiautomated Liver Segmentation Method Using CT for Accurate Volumetry

Rationale and Objectives To compare the repeatability and agreement of a semiautomated liver segmentation method with manual segmentation for assessment of total liver volume on CT (computed tomography). Materials and Methods This retrospective, institutional review board–approved study was conducted in 41 subjects who underwent liver CT for preoperative planning. The major pathologies encountered were colorectal cancer metastases, benign liver lesions and hepatocellular carcinoma. This semiautomated segmentation method is based on variational interpolation and 3D minimal path–surface segmentation. Total and subsegmental liver volumes were segmented from contrast-enhanced CT images in venous phase. Two image analysts independently performed semiautomated segmentations and two other image analysts performed manual segmentations. Repeatability and agreement of both methods were evaluated with intraclass correlation coefficients (ICC) and Bland–Altman analysis. Interaction time was recorded for both methods. Results Bland–Altman analysis revealed an intrareader agreement of −1 ± 27 mL (mean ± 1.96 standard deviation) with ICC of 0.999 ( P P P P P P Conclusions A semiautomated segmentation method can substantially shorten interaction time while preserving a high repeatability and agreement with manual segmentation.