The toll of medical errors on the health of Americans is - perhaps surprisingly - enormous: approximately 8 times per day, surgeons operate on the wrong body part;over 40% of surgery patients meet with some form of adverse event;and taken together, medical errors constitute the sixth leading cause of death in the US and cost tens of billions of dollars per year to the healthcare system. With the operating room (OR) presenting a major source of such errors, the last decade saw a growing awareness and motivation to reduce preventable errors using new surgical workflow, checklists, preoperative time-outs, flat hierarchy in the OR, etc., but with little evidence to suggest a reversal of trends The proposed research brings intraoperative imaging technology to the fore motivated specifically to improve patient safety and OR quality assurance (QA). These advances leverage some of the same technologies emerging over the last decade for image-guided surgery - for example, intraoperative imaging (mobile C-arms for high-quality, low-dose 3D imaging), image registration (including 3D-2D and 3D-3D registration of intraoperative images with preoperative images and planning data), and image reconstruction (including model-based 3D image reconstruction methods demonstrating exciting advances in image quality and dose reduction in diagnostic imaging). In motivating such technology directly toward challenges of patient safety and OR QA, we realize a comparatively simple, low-cost form that could be well suited to mainstream utilization in a broad spectrum of surgeries (rather than limited to a fairly narrow scope of procedures requiring ever increasing levels of surgical precision despite complexity and cost). Specifically, we advance three enabling technologies to improve safety in the OR: (1) a new clinical prototype mobile C-arm (""""""""S1"""""""") deployed for the first time in clinical studies;(2) 3-2D image registration to automatically localize the surgical target and device trajectories directl in single-shot fluoroscopy or mobile radiographs;and (3) model-based 3D image reconstruction enabling high-quality low-dose cone-beam CT and yield high-quality images even in the presence of surgical devices. These technologies are brought to bear on major challenges in spine surgery via 4 Specific Aims following natural surgical workflow: (1) Localization of target vertebrae by robust 3D-2D registration directly on intraoperative fluoroscopy;(2) Guidance by 3D-2D registration without conventional trackers and maintaining accuracy throughout the procedure;(3) Qualitative Verification of the surgical product using high-quality mobile C-arm cone-beam CT at the conclusion of the case to verify the surgical product and detect complications and retained foreign bodies;and (4) Quantitative Verification based on joint registration and reconstruction to quantitatively measure screw placement and detect pedicle breach. The research encompasses the development, evaluation, and translation of each technology from the laboratory to safety and feasibility in first clinical studies.

Public Health Relevance

Medical errors affect nearly half of patients undergoing surgery and cost tens of billions of dollars each year. Among the alarmingly common challenges to operating room (OR) safety are: wrong-site surgery (~40 per week in the US), difficulty in detecting complications and retained foreign bodies in the OR (with potentially major morbidity and loss of function when detected hours later in post-operative care), and the lack of quantitative assessment of the surgical product in the OR (in time for revision if necessary). The proposed research advances new intraoperative imaging technology specifically motivated to reduce such errors and improve OR safety and quality - including tools to automatically label the surgical target and adjacent anatomy, reliably detect complications in the OR, and quantitatively assess the surgical product - and translates each technology from the laboratory to first clinical safety and feasibility studies in spine surgery.

National Institute of Health (NIH)
National Institute of Biomedical Imaging and Bioengineering (NIBIB)
Research Project (R01)
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Biomedical Imaging Technology Study Section (BMIT)
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Krosnick, Steven
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Johns Hopkins University
Biomedical Engineering
Schools of Medicine
United States
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