Realization of a biomechanical model-assisted image guidance system for breast cancer surgery using supine MRI

Abstract

Purpose Unfortunately, the current re-excision rates for breast conserving surgeries due to positive margins average 20–40%. The high re-excision rates arise from difficulty in localizing tumor boundaries intraoperatively and lack of real-time information on the presence of residual disease. The work presented here introduces the use of supine magnetic resonance (MR) images, digitization technology, and bio-mechanical models to investigate the capability of using an image guidance system to localize tumors intraoperatively. Methods Preoperative supine MR images were used to create patient-specific biomechanical models of the breast tissue, chest wall, and tumor. In a mock intraoperative setup, a laser range scanner was used to digitize the breast surface and tracked ultrasound was used to digitize the chest wall and tumor. Rigid registration combined with a novel non-rigid registration routine was used to align the preoperative and intraoperative patient breast and tumor. The registra tion framework is driven by breast surface data (laser range scan of visible surface), ultrasound chest wall surface, and MR-visible fiducials. Tumor localizations by tracked ultra-sound were only used to evaluate the fidelity of aligning preoperative MR tumor contours to physical patient space. The use of tracked ultrasound to digitize subsurface features to constrain our nonrigid registration approach and to assess the fidelity of our framework makes this work unique. Two patient subjects were analyzed as a preliminary investigation toward the realization of this supine image-guided approach. Results An initial rigid registration was performed using adhesive MR-visible fiducial markers for two patients scheduled for a lumpectomy. For patient 1, the rigid registration resulted in a root-mean-square fiducial registration error (FRE) of 7.5 mm and the difference between the intraoperative tumor centroid as visualized with tracked ultrasound imaging and the registered preoperative MR counterpart was 6.5 mm. Nonrigid correction resulted in a decrease in FRE to 2.9 mm and tumor centroid difference to 5.5 mm. For patient 2, rigid registration resulted in a FRE of 8.8 mm and a 3D tumor centroid difference of 12.5 mm. Following nonrigid correction for patient 2, the FRE was reduced to 7.4 mm and the 3D tumor centroid difference was reduced to 5.3 mm. Conclusion Using our prototype image-guided surgery platform, we were able to align intraoperative data with preoperative patient-specific models with clinically relevant accuracy; i.e., tumor centroid localizations of approximately 5.3–5.5 mm.

Breast tissue stiffness estimation for surgical guidance using gravity-induced excitation

“…These localization complications directly contribute to unacceptably high reoperation rates for breast conserving surgery (20–40% (Landercasper et al 2014)). For this reason, enhanced tumor localization strategies have been suggested and include using image guidance systems that rely on patient specific biomechanical breast models to predict tumor locations for biopsies and surgical removal (Carter et al 2005, Conley et al 2015). Image guided breast surgery (IGBS) is performed by registering pre-surgical images to the same 3D coordinate space as the operating room.…”

“…However, when contact forces or gravitational loading conditions are applied, absolute material property values are required. There are several models that incorporate gravitational loading and/or contact forces for applications in aligning prone and supine images (Eiben et al 2016), modeling mammographic compressions (Chung et al 2008b), and performing image-to-physical space registration of preoperative breast image volumes for use in guiding surgery (Conley et al 2015). In many of these studies, the material properties are estimated using literature values and are not patient specific.…”

Augmenting Surgery via Multi-scale Modeling and Translational Systems Biology in the Era of Precision Medicine: A Multidisciplinary Perspective

“…Going further, we should note that similar to the variation in surgical approaches to different organ systems, the translation of the type of alignment approaches shown here also requires equal specificity in order to include the adaptation to less invasive environments such as in laparoscopic procedures 47 . Nevertheless, while more work is still needed, it is encouraging to see investigators translating new directions in the field of model-driven computational surgery; e.g., areas such as prostate 6 , kidney 5 , lung 15 , and breast 24 to name several.…”

Computational Modeling for Enhancing Soft Tissue Image Guided Surgery: An Application in Neurosurgery

“…Emerging work on image guided liver and prostate surgery from several groups is underway to include approaches to nonrigid registration to account for surgical deformations reflecting the use of biomechanical models. 2,60 Very preliminary efforts towards kidney, 1 lung, 6 and breast 13 are appearing that also incorporate biomechanical models as part of their guidance frameworks. Computational models in surgery are also being extended past deformation mechanisms into other areas of mechanics associated with therapeutics.…”