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 registra
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University College London, Centre for Medical Image Computing, London, UK University College London, Translational Imaging Group, CMIC, London, UK 3 University Dept Surgery, Royal Free Campus, UCL, London UK 4 University of Sheffield, CISTIB, Insigneo, Sheffield, UK
Abstract. 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 2.9611.31mm 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.
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Introduction
Many of the algorithms currently being proposed for the registration of the preoperative segmentation to intra-operative surface reconstructions [10] in imageguided laparoscopic liver surgery (e.g. Iterative Closest Points method) suffer from a tendency to converge to local cost-function minima when not well initialised. The main application for our pneumoperitoneum-deformation estimates is the initialisation of such registrations and thus avoid a manual initialisation c Springer International Publishing Switzerland 2015 N. Navab et al. (Eds.): MICCAI 2015, Part II, LNCS 9350, pp. 450–458, 2015. DOI: 10.1007/978-3-319-24571-3_54
Database-Based Estimation of Liver Deformation under Pneumoperitoneum
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step, which is desirable for both workflow and accuracy reasons. They could also help produce better patient-specific surgical simulations for the planning of a laparoscopic procedure. Few algorithms have been proposed for this particular purpose: Work conducted by Bano et al. [1], investigated the possibility of simulating pneumoperitoneum to guide port placement. Their method was based on a finite element simulation of the patient abdomen which modelled the effects of the gas pressure and gravity. While it was not their primary objective, they also evaluated their method’s ability to predict the position of the abdominal viscera in a pig model, and found errors in terms of mesh vertex dist
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