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Purpose. Spine surgery involves complex workflows and disparate levels of system integration that challenge the introduction of emerging technologies. This work develops a computational simulation framework based on statistical surgical process models (SPM) to quantitatively evaluate variations in the workflow and implementation of image guidance systems in terms of key outcome measures in spine surgery. Method. A statistical SPM was developed for spine surgery to describe the effects of various intraoperative technologies (viz., fluoroscopy, CT, image-to-world registration, and planning methods) and a range of procedural variables (e.g., surgeon skill, patient body mass index (BMI), target vertebrae, and fusion length) on key outcome measures, including cycle time, radiation dose and the quality of surgical product (geometric accuracy in pedicle screw placement). The model was parameterized by statistical distributions informed by clinical observation, expert feedback, literature review, and clinical data. Results. The results quantify the advantages of intraoperative CT and/or long-length scout radiography for reduced cycle time in vertebral localization – (4.8-7.2) min, compared to (5.8-12.4) min by fluoroscopy. The models further demonstrate the cycle time for imaging, registration, and planning in surgical guidance: the mean procedure cycle time for 11-level fusion was 540 min by fluoroscopy compared to 441 min for CT + navigation. Analysis of radiation dose quantified the effective dose to the patient (and operating room) between fluoroscopy and CT. The geometric accuracy of pedicle screw placement showed median error of 2.7 mm for fluoroscopy compared to 1.8 mm for CT+navigation and a corresponding reduction in frequency of pedicle breach for the latter. Conclusions. A statistical SPM provides a powerful framework for procedure simulation, evaluation of emerging technologies, and optimization of procedural workflow. Such modeling provides a quantitative basis to evidence the value of emerging technologies and identify optimal means of integration / implementation in clinical workflow.
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