Image: Mismatch between the liver shape on a CT scan (green) and intraoperative tracing (Photo courtesy of Vanderbilt University).
Novel three-dimensional (3D) tissue deformation correction software can help accurately locate the liver during image-guided surgery.
Developed by researchers at Vanderbilt University (Nashville, TN, USA) and Memorial Sloan-Kettering Cancer Center (MSKCC; New York, NY, USA), the software generates a computer model out of the original image of the liver and simulates different forces applied during surgery, for example by emulating a packed gauze lifting the liver. The computerized tomography (CT)-derived surgical navigation map can thus better match the exposed organ shape in the operating room (OR).
In a study of the system, surgeons were shown six or seven CT images for 20 liver tumor patients in the OR, for a total of 125 alignment evaluations. Surgeons also assessed the liver during the procedure by swabbing an optically tracked stylus over its surface, and viewing it on the display. For each assessment, either conventional rigid or novel deformable alignment were presented in a randomized, blinded fashion; the surgeon provided a rating for each display compared to the previous display, whereby a negative rating indicated degradation in fidelity and a positive rating an improvement.
Statistical analysis of the series of clinician rating data indicated that the surgeons were able to perceive an improvement of the model-based registration over the rigid registration, as well as degradation when the rigid registration was compared with the novel deformable guidance information. Overall, surgeons were able to detect the variations correctly in 73% of evaluations. The researchers say that deformation correction technology could be integrated into most image-guided surgery systems. The study was published on July 10, 2017, in Surgery.
“Although systems of three-dimensional image-guided surgery are a valuable adjunct across numerous procedures, differences in organ shape between that reflected in the preoperative image data and the intraoperative state can compromise the fidelity of such guidance based on the image,” concluded senior author professor of biomedical engineering Michael Miga, PhD, of Vanderbilt University. “We assessed in real time a novel, three-dimensional image-guided operation platform that incorporates soft tissue deformation.”
Memorial Sloan-Kettering Cancer Center