Brandon Chan1, Jason Auyeung2, John F Rudan3, Randy E Ellis1,2,3,4, Manuela Kunz5,6. 1. School of Computing, Queen's University, 557 Goodwin Hall, Kingston, ON, K7L 2N8, Canada. 2. Department of Biomedical and Molecular Sciences, Queen's University, Botterell Hall, 18 Stuart Street, Kingston, ON, K7L 3N6, Canada. 3. Department of Surgery, Queen's University, Kingston General Hospital, 76 Stuart Street, Kingston, ON, K7L 2V7, Canada. 4. Department of Mechanical and Materials Engineering, Queen's University, McLaughlin Hall, Kingston, ON, K7L 3N6, Canada. 5. School of Computing, Queen's University, 557 Goodwin Hall, Kingston, ON, K7L 2N8, Canada. kunz@queensu.ca. 6. Human Mobility Research Centre, Queen's University and Kingston General Hospital, Kingston General Hospital, 76 Stuart Street, Kingston, Ontario, K7L 2V7, Canada. kunz@queensu.ca.
Abstract
PURPOSE: Structured light scanning is an emerging technology that shows potential in the field of medical imaging and image-guided surgery. The purpose of this study was to investigate the feasibility of applying a hand-held structured light scanner in the operating theatre as an intraoperative image modality and registration tool. METHODS: We performed an in vitro study with three fresh frozen knee specimens and a clinical pilot study with three patients (one total knee arthroplasty and two hip replacements). Before the procedure, a CT scan of the affected joint was obtained and isosurface models of the anatomies were created. A conventional surgical exposure was performed, and a hand-held structured light scanner (Artec Group, Palo Alto, USA) was used to scan the exposed anatomy. Using the texture information of the scanned model, bony anatomy was selected and registered to the CT models. Registration RMS errors were documented, and distance maps between the scanned model and the CT model were created. RESULTS: For the in vitro trial, the average RMS error was 1.00 mm for the femur and 1.17 mm for the tibia registration. We found comparable results during clinical trials, with an average RMS error of 1.3 mm. CONCLUSIONS: The results of this preliminary study indicate that structured light scanning could be applied accurately and safely in a surgical environment. This could result in a variety of applications for these scanners in image-guided interventions as intraoperative imaging and registration tools.
PURPOSE: Structured light scanning is an emerging technology that shows potential in the field of medical imaging and image-guided surgery. The purpose of this study was to investigate the feasibility of applying a hand-held structured light scanner in the operating theatre as an intraoperative image modality and registration tool. METHODS: We performed an in vitro study with three fresh frozen knee specimens and a clinical pilot study with three patients (one total knee arthroplasty and two hip replacements). Before the procedure, a CT scan of the affected joint was obtained and isosurface models of the anatomies were created. A conventional surgical exposure was performed, and a hand-held structured light scanner (Artec Group, Palo Alto, USA) was used to scan the exposed anatomy. Using the texture information of the scanned model, bony anatomy was selected and registered to the CT models. Registration RMS errors were documented, and distance maps between the scanned model and the CT model were created. RESULTS: For the in vitro trial, the average RMS error was 1.00 mm for the femur and 1.17 mm for the tibia registration. We found comparable results during clinical trials, with an average RMS error of 1.3 mm. CONCLUSIONS: The results of this preliminary study indicate that structured light scanning could be applied accurately and safely in a surgical environment. This could result in a variety of applications for these scanners in image-guided interventions as intraoperative imaging and registration tools.
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