M Wagner1, M Gondan2, C Zöllner3, J J Wünscher1, F Nickel1, L Albala1, A Groch3, S Suwelack4, S Speidel4, L Maier-Hein3, B P Müller-Stich1, H G Kenngott5. 1. Department of Surgery, Heidelberg University Hospital, Im Neuenheimer Feld 110, 69120, Heidelberg, Germany. 2. Department of Psychology, University of Copenhagen, Copenhagen, Denmark. 3. Junior Group Computer-Assisted Interventions, German Cancer Research Center, Heidelberg, Germany. 4. Institute for Anthropomatics and Robotics, Karlsruhe Institute of Technology, Karlsruhe, Germany. 5. Department of Surgery, Heidelberg University Hospital, Im Neuenheimer Feld 110, 69120, Heidelberg, Germany. hannes.kenngott@med.uni-heidelberg.de.
Abstract
BACKGROUND: Laparoscopic resection is a minimally invasive treatment option for rectal cancer but requires highly experienced surgeons. Computer-aided technologies could help to improve safety and efficiency by visualizing risk structures during the procedure. The prerequisite for such an image guidance system is reliable intraoperative information on iatrogenic tissue shift. This could be achieved by intraoperative imaging, which is rarely available. Thus, the aim of the present study was to develop and validate a method for real-time deformation compensation using preoperative imaging and intraoperative electromagnetic tracking (EMT) of the rectum. METHODS: Three models were compared and evaluated for the compensation of tissue deformation. For model A, no compensation was performed. Model B moved the corresponding points rigidly to the motion of the EMT sensor. Model C used five nested linear regressions with increasing level of complexity to compute the deformation (C1-C5). For evaluation, 14 targets and an EMT organ sensor were fit into a silicone-molded rectum of the OpenHELP phantom. Following a computed tomography, the image guidance was initiated and the rectum was deformed in the same way as during surgery in a total of 14 experimental runs. The target registration error (TRE) was measured for all targets in different positions of the rectum. RESULTS: The mean TRE without correction (model A) was 32.8 ± 20.8 mm, with only 19.6% of the measurements below 10 mm (80.4% above 10 mm). With correction, the mean TRE could be reduced using the rigid correction (model B) to 6.8 ± 4.8 mm with 78.7% of the measurements being <10 mm. Using the most complex linear regression correction (model C5), the error could be reduced to 2.9 ± 1.4 mm with 99.8% being below 10 mm. CONCLUSION: In laparoscopic rectal surgery, the combination of electromagnetic organ tracking and preoperative imaging is a promising approach to compensating for intraoperative tissue shift in real-time.
BACKGROUND: Laparoscopic resection is a minimally invasive treatment option for rectal cancer but requires highly experienced surgeons. Computer-aided technologies could help to improve safety and efficiency by visualizing risk structures during the procedure. The prerequisite for such an image guidance system is reliable intraoperative information on iatrogenic tissue shift. This could be achieved by intraoperative imaging, which is rarely available. Thus, the aim of the present study was to develop and validate a method for real-time deformation compensation using preoperative imaging and intraoperative electromagnetic tracking (EMT) of the rectum. METHODS: Three models were compared and evaluated for the compensation of tissue deformation. For model A, no compensation was performed. Model B moved the corresponding points rigidly to the motion of the EMT sensor. Model C used five nested linear regressions with increasing level of complexity to compute the deformation (C1-C5). For evaluation, 14 targets and an EMT organ sensor were fit into a silicone-molded rectum of the OpenHELP phantom. Following a computed tomography, the image guidance was initiated and the rectum was deformed in the same way as during surgery in a total of 14 experimental runs. The target registration error (TRE) was measured for all targets in different positions of the rectum. RESULTS: The mean TRE without correction (model A) was 32.8 ± 20.8 mm, with only 19.6% of the measurements below 10 mm (80.4% above 10 mm). With correction, the mean TRE could be reduced using the rigid correction (model B) to 6.8 ± 4.8 mm with 78.7% of the measurements being <10 mm. Using the most complex linear regression correction (model C5), the error could be reduced to 2.9 ± 1.4 mm with 99.8% being below 10 mm. CONCLUSION: In laparoscopic rectal surgery, the combination of electromagnetic organ tracking and preoperative imaging is a promising approach to compensating for intraoperative tissue shift in real-time.
Entities:
Keywords:
Image-guided surgery; Laparoscopy; Motion compensation; Rectal cancer
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