Utilizing head-mounted eye trackers to analyze patterns and decision-making strategies of 3D virtual modelling platform (IRIS™) during preoperative planning for renal cancer surgeries.

IRIS™ provides interactive, 3D anatomical visualizations of renal anatomy for pre-operative planning that can be manipulated by altering transparency, rotating, zooming, panning, and overlaying the CT scan. Our objective was to analyze how eye tracking metrics and utilization patterns differ between preoperative surgical planning of renal masses using IRIS and CT scans.

Seven surgeons randomly reviewed IRIS and CT images of 9 patients with renal masses [5 high complexity (RENAL score ≥ 8), 4 low complexity (≤ 7)]. Surgeons answered a series of questions regarding patient anatomy, perceived difficulty (/100), confidence (/100), and surgical plan. Eye tracking metrics (mean pupil diameter, number of fixations, and gaze duration) were collected.

Surgeons spent significantly less time interpreting data from IRIS than CT scans (- 67.1 s, p < 0.01) and had higher inter-rater agreement of surgical approach after viewing IRIS (α = 0.16-0.34). After viewing IRIS, surgical plans although not statistically significant demonstrated a greater tendency towards a more selective ischemia approaches which positively correlated with improved identification of vascular anatomy. Planned surgical approach changed in 22/59 of the cases. Compared to viewing the CT scan, left and right mean pupil diameter and number/duration of fixations were significantly lower when using IRIS (p < 0.01, p < 0.01, p = 0.42, p < 0.01, respectively), indicating interpreting information from IRIS required less mental effort despite under-utilizing its interactive features.

Surgeons extrapolated more detailed information in less time with less mental effort using IRIS than CT scans and proposed surgical approaches with potential to enhanced surgical outcomes.

World journal of urology. 2022 Jan 23 [Epub ahead of print]

Rachel Melnyk, Yuxin Chen, Tyler Holler, Nathan Schuler, Patrick Saba, Scott Quarrier, Jonathan Bloom, William Tabayoyong, Thomas Frye, Hani Rashid, Jean Joseph, Ahmed Ghazi

Simulation Innovation Lab, University of Rochester Medical Center (URMC), 601 Elmwood Ave, Rochester, NY, USA. ., Simulation Innovation Lab, University of Rochester Medical Center (URMC), 601 Elmwood Ave, Rochester, NY, USA., Department of Urology, URMC, Rochester, NY, USA.

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