Intraoperative Biomechanical Registration of the Liver: Does the Heterogeneity of the Liver Matter?

Abstract Background: Preoperative images such as computed tomography scans or magnetic resonance imaging contain lots of valuable information that are not easily available for surgeons during an operation. To help the clinicians better target the structures of interest during an intervention, many registration methods that align preoperative images onto the intraoperative view of the organs have been developed. For important organ deformation, biomechanically-based registration has proven to be a method of choice. Method: Using an existing biomechanically-based registration algorithm for laparoscopic liver surgery we investigate in this paper the influence of the heterogeneity of the liver on the registration result. Results: No statistical difference in the results was found between the registration performed with the homogeneous model and the one carried out with the heterogeneous model. Conclusion: As the use of an heterogeneous model does not improve significantly the registration result and increase the computation time we recommend to perform the type of registration task described in the paper with a simplified homogeneous model.

[1]  Lena Maier-Hein,et al.  Physics-based shape matching for intraoperative image guidance. , 2014, Medical physics.

[2]  Logan W. Clements,et al.  Concepts and Preliminary Data Toward the Realization of Image-guided Liver Surgery , 2007, Journal of Gastrointestinal Surgery.

[3]  D. Caleb Rucker,et al.  Nonrigid liver registration for image-guided surgery using partial surface data: a novel iterative approach , 2013, Medical Imaging.

[4]  K. Miller,et al.  On the unimportance of constitutive models in computing brain deformation for image-guided surgery , 2009, Biomechanics and modeling in mechanobiology.

[5]  Robert L. Galloway,et al.  Compensating for intraoperative soft-tissue deformations using incomplete surface data and finite elements , 2005, IEEE Transactions on Medical Imaging.

[6]  Luc Soler,et al.  Experimental in vitro mechanical characterization of porcine Glisson's capsule and hepatic veins. , 2011, Journal of biomechanics.

[7]  Michael I. Miga,et al.  The sparse data extrapolation problem: strategies for soft-tissue correction for image-guided liver surgery , 2011, Medical Imaging.

[8]  Nazim Haouchine,et al.  Patient-Specific Biomechanical Modeling for Guidance During Minimally-Invasive Hepatic Surgery , 2015, Annals of Biomedical Engineering.

[9]  Nazim Haouchine,et al.  Automatic Alignment of Pre and Intraoperative Data Using Anatomical Landmarks for Augmented Laparoscopic Liver Surgery , 2014, ISBMS.

[10]  Makoto Hashizume,et al.  Image-guided laparoscopic surgery in an open MRI operating theater , 2013, Surgical Endoscopy.

[11]  M. Choti,et al.  A Snapshot of the Effective Indications and Results of Surgery for Hepatocellular Carcinoma in Tertiary Referral Centers: Is It Adherent to the EASL/AASLD Recommendations? An Observational Study of the HCC East-West Study Group , 2013, Annals of surgery.