Clinical Translation of the LevelCheck Decision Support Algorithm for Target Localization in Spine Surgery
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Recent work has yielded a method for automatic labeling of vertebrae in intraoperative radiographs as an assistant to manual level counting. The method, called LevelCheck, previously demonstrated promise in phantom studies and retrospective studies. This study aims to: (#1) Analyze the effect of LevelCheck on accuracy and confidence of localization in two modes: (a) Independent Check (labels displayed after the surgeon’s decision) and (b) Active Assistant (labels presented before the surgeon’s decision). (#2) Assess the feasibility and utility of LevelCheck in the operating room. Two studies were conducted: a laboratory study investigating these two workflow implementations in a simulated operating environment with 5 surgeons, reviewing 62 cases selected from a dataset of radiographs exhibiting a challenge to vertebral localization; and a clinical study involving 20 patients undergoing spine surgery. In Study #1, the median localization error without assistance was 30.4% (IQR = 5.2%) due to the challenging nature of the cases. LevelCheck reduced the median error to 2.4% for both the Independent Check and Active Assistant modes (p < 0.01). Surgeons found LevelCheck to increase confidence in 91% of cases. Study #2 demonstrated accuracy in all cases. The algorithm runtime varied from 17 to 72 s in its current implementation. The algorithm was shown to be feasible, accurate, and to improve confidence during surgery.
KeywordsSpine surgery Clinical translation Surgical workflow Intraoperative imaging LevelCheck Image-guided surgery
This work would have not been possible without the cooperation of Kelly Menon, Tangie Gaither-Bacon and Samantha Ernest as the Neurosurgical nursing team who supported the study in the operating rooms. Similarly, the support received from the radiology team is acknowledged—in particular: Rebecca Engberg, Jessica Enwright Wood, Charles Arterson, Joshua Shannon, Aris Thompson, and Lauryn Hancock. Finally, the authors would like to thank Ian Suk for his help and support.
Conflict of interest
The work was supported by the National Institutes of Health (NIH R01-EB-017226) and academic-industry partnership with Siemens Healthineers (XP Division, Erlangen, Germany). The authors have publicly available intellectual property associated with this work, yet apart from paid employment by Siemens employees (Sebastian Vogt and Gerhard Kleinszig), the authors have no personal financial interest in the work reported in this paper.
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