Database-Based Estimation of Liver Deformation under Pneumoperitoneum for Surgical Image-Guidance and Simulation

The insufflation of the abdomen in laparoscopic liver surgery leads to significant deformation of the liver. The estimation of the shape and position of the liver after insufflation has many important applications, such as providing surface-based registration algorithms used in image guidance with an initial guess and realistic patient-specific surgical simulation.

Our proposed algorithm computes a deformation estimate for a patient subject from a database of known insufflation deformations, as a weighted average. The database is built from pre-operative and intra-operative 3D image segmentations. The estimation pipeline also comprises a biomechanical simulation to incorporate patient-specific boundary conditions (BCs) and eliminate any non-physical deformation arising from the computation of the deformation as a weighted average.

We have evaluated the accuracy of our intra-subject registration, used for the computation of the displacements stored in the database, and our liver deformation predictions based on segmented, in-vivo porcine CT image data from 5 animals and manually selected vascular landmarks. We found root mean squared (RMS) target registration errors (TREs) of 2.96-11.31mm after intra-subject registration. For our estimated deformation, we found an RMS TRE of 5.82-11.47mm for four of the subjects, on one outlier subject the method failed.