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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

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Abstract

Purpose

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.

Methods

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.

Results

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.

Conclusions

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.

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Fig. 1
Fig. 2

taken from the field-of-view camera of the head-mounted eye-tracker (HMET). The location of the wearer’s point-of-gaze is indicated by the red circle, the larger the diameter the longer the fixation. Areas of Interest (AOI’s) used for analysis are shown over the imaging (green) and the survey (orange)

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Abbreviations

3D:

Three-dimensional

3D-AV:

Three-dimensional anatomic visualization

AOI:

Areas of interest

CT:

Computed tomography

ETM:

Eye tracking metrics

HMET:

Head-mounted eye-trackers

MPD:

Mean pupil diameter

PN:

Partial nephrectomy

RN:

Radical nephrectomy

PCS:

Renal collecting system

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Funding

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Authors and Affiliations

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

    Rachel Melnyk, Yuxin Chen, Tyler Holler, Nathan Schuler, Patrick Saba & Ahmed Ghazi

  2. Department of Urology, URMC, Rochester, NY, USA

    Scott Quarrier, Jonathan Bloom, William Tabayoyong, Thomas Frye, Hani Rashid, Jean Joseph & Ahmed Ghazi

Authors
  1. Rachel Melnyk
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  2. Yuxin Chen
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  3. Tyler Holler
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  4. Nathan Schuler
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  5. Patrick Saba
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  6. Scott Quarrier
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  7. Jonathan Bloom
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  8. William Tabayoyong
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  9. Thomas Frye
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  10. Hani Rashid
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  11. Jean Joseph
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  12. Ahmed Ghazi
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Contributions

Protocol/project development: RM, TH, AG. Data collection/management: RM, TH, PS, AG, SQ, JB, WT, TF, HR, JJ. Data analysis: RM, YC, TH, NS, AG. Manuscript writing/editing: RM, TH, PS, NS, AG.

Corresponding author

Correspondence to Rachel Melnyk.

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Ethical approval

Ethical approval was waived by the RSRB of University of Rochester (STUDY00003003) in view of the retrospective nature of the study and all the procedures being performed were part of the routine care.

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Melnyk, R., Chen, Y., Holler, T. et al. 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. World J Urol 40, 651–658 (2022). https://doi.org/10.1007/s00345-021-03906-z

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  • DOI: https://doi.org/10.1007/s00345-021-03906-z

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