R Han1, A Uneri1, R C Vijayan1, P Wu1, P Vagdargi2, N Sheth1, S Vogt3, G Kleinszig3, G M Osgood4, J H Siewerdsen5. 1. Department of Biomedical Engineering, The Johns Hopkins University, BaltimoreMD, United States. 2. Department of Computer Science, The Johns Hopkins University, BaltimoreMD, United States. 3. Siemens Healthineers, ErlangenGermany. 4. Department of Orthopaedic Surgery, The Johns Hopkins Hospital, BaltimoreMD, United States. 5. Department of Biomedical Engineering, The Johns Hopkins University, BaltimoreMD, United States. Electronic address: jeff.siewerdsen@jhu.edu.
Abstract
PURPOSES: Surgical reduction of pelvic fracture is a challenging procedure, and accurate restoration of natural morphology is essential to obtaining positive functional outcome. The procedure often requires extensive preoperative planning, long fluoroscopic exposure time, and trial-and-error to achieve accurate reduction. We report a multi-body registration framework for reduction planning using preoperative CT and intraoperative guidance using routine 2D fluoroscopy that could help address such challenges. METHOD: The framework starts with semi-automatic segmentation of fractured bone fragments in preoperative CT using continuous max-flow. For reduction planning, a multi-to-one registration is performed to register bone fragments to an adaptive template that adjusts to patient-specific bone shapes and poses. The framework further registers bone fragments to intraoperative fluoroscopy to provide 2D fluoroscopy guidance and/or 3D navigation relative to the reduction plan. The framework was investigated in three studies: (1) a simulation study of 40 CT images simulating three fracture categories (unilateral two-body, unilateral three-body, and bilateral two-body); (2) a proof-of-concept cadaver study to mimic clinical scenario; and (3) a retrospective clinical study investigating feasibility in three cases of increasing severity and accuracy requirement. RESULTS: Segmentation of simulated pelvic fracture demonstrated Dice coefficient of 0.92±0.06. Reduction planning using the adaptive template achieved 2-3 mm and 2-3° error for the three fracture categories, significantly better than planning based on mirroring of contralateral anatomy. 3D-2D registration yielded ~2 mm and 0.5° accuracy, providing accurate guidance with respect to the preoperative reduction plan. The cadaver study and retrospective clinical study demonstrated comparable accuracy: ~0.90 Dice coefficient in segmentation, ~3 mm accuracy in reduction planning, and ~2 mm accuracy in 3D-2D registration. CONCLUSION: The registration framework demonstrated planning and guidance accuracy within clinical requirements in both simulation and clinical feasibility studies for a broad range of fracture-dislocation patterns. Using routinely acquired preoperative CT and intraoperative fluoroscopy, the framework could improve the accuracy of pelvic fracture reduction, reduce radiation dose, and could integrate well with common clinical workflow without the need for additional navigation systems.
PURPOSES: Surgical reduction of pelvic fracture is a challenging procedure, and accurate restoration of natural morphology is essential to obtaining positive functional outcome. The procedure often requires extensive preoperative planning, long fluoroscopic exposure time, and trial-and-error to achieve accurate reduction. We report a multi-body registration framework for reduction planning using preoperative CT and intraoperative guidance using routine 2D fluoroscopy that could help address such challenges. METHOD: The framework starts with semi-automatic segmentation of fractured bone fragments in preoperative CT using continuous max-flow. For reduction planning, a multi-to-one registration is performed to register bone fragments to an adaptive template that adjusts to patient-specific bone shapes and poses. The framework further registers bone fragments to intraoperative fluoroscopy to provide 2D fluoroscopy guidance and/or 3D navigation relative to the reduction plan. The framework was investigated in three studies: (1) a simulation study of 40 CT images simulating three fracture categories (unilateral two-body, unilateral three-body, and bilateral two-body); (2) a proof-of-concept cadaver study to mimic clinical scenario; and (3) a retrospective clinical study investigating feasibility in three cases of increasing severity and accuracy requirement. RESULTS: Segmentation of simulated pelvic fracture demonstrated Dice coefficient of 0.92±0.06. Reduction planning using the adaptive template achieved 2-3 mm and 2-3° error for the three fracture categories, significantly better than planning based on mirroring of contralateral anatomy. 3D-2D registration yielded ~2 mm and 0.5° accuracy, providing accurate guidance with respect to the preoperative reduction plan. The cadaver study and retrospective clinical study demonstrated comparable accuracy: ~0.90 Dice coefficient in segmentation, ~3 mm accuracy in reduction planning, and ~2 mm accuracy in 3D-2D registration. CONCLUSION: The registration framework demonstrated planning and guidance accuracy within clinical requirements in both simulation and clinical feasibility studies for a broad range of fracture-dislocation patterns. Using routinely acquired preoperative CT and intraoperative fluoroscopy, the framework could improve the accuracy of pelvic fracture reduction, reduce radiation dose, and could integrate well with common clinical workflow without the need for additional navigation systems.
Authors: A Uneri; S Schafer; D J Mirota; S Nithiananthan; Y Otake; R H Taylor; G L Gallia; A J Khanna; S Lee; D D Reh; J H Siewerdsen Journal: Int J Comput Assist Radiol Surg Date: 2011-07-09 Impact factor: 3.421
Authors: Yoshito Otake; Adam S Wang; J Webster Stayman; Ali Uneri; Gerhard Kleinszig; Sebastian Vogt; A Jay Khanna; Ziya L Gokaslan; Jeffrey H Siewerdsen Journal: Phys Med Biol Date: 2013-11-18 Impact factor: 3.609
Authors: Tharindu De Silva; Sheng-Fu L Lo; Nafi Aygun; Daniel M Aghion; Akwasi Boah; Rory Petteys; Ali Uneri; Michael D Ketcha; Thomas Yi; Sebastian Vogt; Gerhard Kleinszig; Wei Wei; Markus Weiten; Xiaobu Ye; Ali Bydon; Daniel M Sciubba; Timothy F Witham; Jean-Paul Wolinsky; Jeffrey H Siewerdsen Journal: Spine (Phila Pa 1976) Date: 2016-10-15 Impact factor: 3.241
Authors: Prasad Vagdargi; Niral Sheth; Alejandro Sisniega; Ali Uneri; Tharindu De Silva; Greg M Osgood; Jeffrey H Siewerdsen Journal: J Med Imaging (Bellingham) Date: 2021-02-12