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Histotripsy is an emerging focal tumor therapy that utilizes focused ultrasound (US) to mechanically destroy tissue. Cone beam CT (CBCT) guidance has been developed to overcome limitations of diagnostic US for visualizing and targeting tumors. Existing workflow for CBCT-guided histotripsy utilizes targeting based on CBCT images acquired with the patient in position for treatment; therefore, treatment planning is currently performed intraprocedurally right before delivering therapy. To provide a framework for planning liver tumor treatments in advance, a biomechanical, nonrigid model is proposed to predict volumetric liver deformations between a pre-procedural diagnostic scan and the intraprocedural CBCT. In the proposed registration approach, the liver, gallbladder (GB), and hepatic blood vessels were segmented from CBCT images acquired at two different points of motion. Segmented structural surfaces were registered using a rigid iterative closest point algorithm followed by deformable registration (demons algorithm). These internal and external hepatic structural surface registrations were used as boundary conditions for a finite element model (FEM) to determine internal liver deformations. Four FEM models were constructed: the liver alone (L-FEM), liver and GB (LG-FEM), liver and vessels (LV-FEM), and liver, GB, and vessels (LGV-FEM). Registration accuracy was measured as the Euclidean distance between manually annotated vessel bifurcations. Bifurcation error was 3.5±3.5mm for LGV-FEM, a 52% improvement from L-FEM (7.4±6.1mm). Including vessels and GB in the model both individually reduced bifurcation error compared to corresponding models excluding those structures. FEM-based liver registration guided by internal and external hepatic structures is a feasible method to facilitate CBCT-guided histotripsy treatment planning.
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