BACKGROUND: Although systems of 3-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. In this work, we assessed in real time a novel, 3-dimensional image-guided operation platform that incorporates soft tissue deformation. METHODS: A series of 125 alignment evaluations were performed across 20 patients. During the operation, the surgeon assessed the liver by swabbing an optically tracked stylus over the liver surface and viewing the image-guided operation display. Each patient had approximately 6 intraoperative comparative evaluations. For each assessment, 1 of only 2 types of alignments were considered: conventional rigid and novel deformable. The series of alignment types used was randomized and blinded to the surgeon. The surgeon provided a rating, R, from -3 to +3 for each display compared with the previous display, whereby a negative rating indicated degradation in fidelity and a positive rating an improvement. RESULTS: A statistical analysis of the series of rating data by the clinician indicated that the surgeons were able to perceive an improvement (defined as a R > 1) of the model-based registration over the rigid registration (P = .01) as well as a degradation (defined as R < -1) when the rigid registration was compared with the novel deformable guidance information (P = .03). CONCLUSION: This study provides evidence of the benefit of deformation correction in providing an accurate location for the liver for use in image-guided surgery systems.
RCT Entities:
BACKGROUND: Although systems of 3-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. In this work, we assessed in real time a novel, 3-dimensional image-guided operation platform that incorporates soft tissue deformation. METHODS: A series of 125 alignment evaluations were performed across 20 patients. During the operation, the surgeon assessed the liver by swabbing an optically tracked stylus over the liver surface and viewing the image-guided operation display. Each patient had approximately 6 intraoperative comparative evaluations. For each assessment, 1 of only 2 types of alignments were considered: conventional rigid and novel deformable. The series of alignment types used was randomized and blinded to the surgeon. The surgeon provided a rating, R, from -3 to +3 for each display compared with the previous display, whereby a negative rating indicated degradation in fidelity and a positive rating an improvement. RESULTS: A statistical analysis of the series of rating data by the clinician indicated that the surgeons were able to perceive an improvement (defined as a R > 1) of the model-based registration over the rigid registration (P = .01) as well as a degradation (defined as R < -1) when the rigid registration was compared with the novel deformable guidance information (P = .03). CONCLUSION: This study provides evidence of the benefit of deformation correction in providing an accurate location for the liver for use in image-guided surgery systems.
Authors: David M Cash; Michael I Miga; Tuhin K Sinha; Robert L Galloway; William C Chapman Journal: IEEE Trans Med Imaging Date: 2005-11 Impact factor: 10.048
Authors: Logan W Clements; Jarrod A Collins; Jared A Weis; Amber L Simpson; Lauryn B Adams; William R Jarnagin; Michael I Miga Journal: J Med Imaging (Bellingham) Date: 2016-03-23
Authors: Bernard J DuBray; Rebecca V Levy; Parvathi Balachandran; Kendra D Conzen; Gundumi A Upadhya; Christopher D Anderson; William C Chapman Journal: HPB (Oxford) Date: 2011-07-19 Impact factor: 3.647
Authors: Logan W Clements; Prashanth Dumpuri; William C Chapman; Benoit M Dawant; Robert L Galloway; Michael I Miga Journal: IEEE Trans Biomed Eng Date: 2011-04-25 Impact factor: 4.538
Authors: D Caleb Rucker; Yifei Wu; Logan W Clements; Janet E Ondrake; Thomas S Pheiffer; Amber L Simpson; William R Jarnagin; Michael I Miga Journal: IEEE Trans Med Imaging Date: 2013-09-20 Impact factor: 10.048