Novel Semiautomatic Real-time CT Segmentation Tool and Preliminary Clinical Evaluation on Thermally Induced Lesions in the Liver

CT data were available from patients with unresectable, primary liver tumors that underwent CT-guided radiofrequency ablation at our institution (MX8000/Brilliance, Philips, NL; StarBurst, Angiodynamics, NY). Two radiological readers retrospectively segmented 12 lesions in CT images using a manual contouring tool under MeVisLab (Bremen, GER). One independent reader used a novel real-time segmentation tool derived from a previous batch application for the brain [1, 2, 3] and prostate [4]. The algorithm starts with a spherical template of 3D nodes and edges outside the lesion [5]. Nodes are continuously adapted by sending rays from a user-defined seed point inside the lesion through the surface of the polyhedron [6]. Key parameters like stiffness and number of nodes were defined on a training dataset. The user can visually explore and modify the 3D result on the fly. The Dice Similarity Coefficient (DSC) [7] was used to measure the agreement of two segmentations. Differences in manual processing times tP and measured lesion volumes VL were analyzed by two-sided paired t-tests (α=0.05) using SPSS 20 (IBM, NY).