A Mechanics-Based Nonrigid Registration Method for Liver Surgery Using Sparse Intraoperative Data.

Rucker DC, Wu Y, Clements LW, Ondrake JE, Pheiffer TS, Simpson AL, Jarnagin WR, Miga MI
IEEE Trans Med Imaging. 2014 33 (1): 147-58

PMID: 24107926 · PMCID: PMC4057359 · DOI:10.1109/TMI.2013.2283016

In open abdominal image-guided liver surgery, sparse measurements of the organ surface can be taken intraoperatively via a laser-range scanning device or a tracked stylus with relatively little impact on surgical workflow. We propose a novel nonrigid registration method which uses sparse surface data to reconstruct a mapping between the preoperative CT volume and the intraoperative patient space. The mapping is generated using a tissue mechanics model subject to boundary conditions consistent with surgical supportive packing during liver resection therapy. Our approach iteratively chooses parameters which define these boundary conditions such that the deformed tissue model best fits the intraoperative surface data. Using two liver phantoms, we gathered a total of five deformation datasets with conditions comparable to open surgery. The proposed nonrigid method achieved a mean target registration error (TRE) of 3.3 mm for targets dispersed throughout the phantom volume, using a limited region of surface data to drive the nonrigid registration algorithm, while rigid registration resulted in a mean TRE of 9.5 mm. In addition, we studied the effect of surface data extent, the inclusion of subsurface data, the trade-offs of using a nonlinear tissue model, robustness to rigid misalignments, and the feasibility in five clinical datasets.

MeSH Terms (10)

Computer Simulation Hepatectomy Humans Image Interpretation, Computer-Assisted Liver Models, Biological Reproducibility of Results Sensitivity and Specificity Surgery, Computer-Assisted Tomography, X-Ray Computed

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