Vasculature-Driven Biomechanical Deformable Image Registration of Longitudinal Liver Cholangiocarcinoma Computed Tomographic Scans

Abstract

Purpose: Deformable image registration (DIR) of longitudinal liver cancer computed tomographic (CT) images can be challenging owing to anatomic changes caused by radiation therapy (RT) or disease progression. We propose a workflow for the DIR of longitudinal contrast-enhanced CT scans of liver cancer based on a biomechanical model of the liver driven by boundary conditions on the liver surface and centerline of an autosegmentation of the vasculature. Methods and Materials: Pre- and post-RT CT scans acquired with a median gap of 112 (32-217) days for 28 patients who underwent RT for intrahepatic cholangiocarcinoma were retrospectively analyzed. For each patient, 5 corresponding anatomic landmarks in pre- and post-RT scans were identified in the liver by a clinical expert for evaluation of the accuracy of different DIR strategies. The first strategy corresponded to the use of a biomechanical model-based DIR method with boundary conditions specified on the liver surface (BM_DIR). The second strategy corresponded to the use of an expansion of BM_DIR consisting of the auto-segmentation of the liver vasculature to determine additional boundary conditions in the biomechanical model (BM_DIR_VBC). The 2 strategies were also compared with an intensity-based DIR strategy using a Demons algorithms. Results: The group mean target registration errors were 12.4 ± 7.5, 7.7 ± 3.7 and 4.4 ± 2.5 mm, for the Demons, BM_DIR and BM_DIR_VBC, respectively. Conclusions: In regard to the large and complex deformation observed in this study and the achieved accuracy of 4.4 mm, the proposed BM_DIR_VBC method might reveal itself as a valuable tool in future studies on the relationship between delivered dose and treatment outcome.