Inexperienced Evaluator Identification of Hand Ischemia Via Video Processed with Pigment-Enhancing Technology

Q3 Medicine

Journal of Hand Surgery Global Online Pub Date : 2025-01-01 DOI:10.1016/j.jhsg.2024.11.002

Max Horowitz BS , Aygul Iskandarova MD , Gabriel Yohe MS , Shihab Rahman BS , Nicholas Durr PhD , Aviram M. Giladi MD, MS

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Abstract

Purpose

Eulerian video magnification (EVM)+waveform is a novel video processing software that enhances visualization of tissue perfusion and has been shown to improve hand surgeon identification of ischemia via video alone. The purpose of this study is to determine whether EVM+waveform technology will support improved accuracy in identifying hand ischemia for less experienced persons, regardless of the evaluator’s health care experience or the melanin content of the hand in the video.

Methods

Healthy volunteers were recruited for us to record videos of their hands both perfused and under tourniquet-induced ischemia. Videos were processed with EVM+waveform and inserted into a 26-question survey. There were two types of questions presented in each survey. One format showed a video processed with EVM+waveform, and the respondent was asked if the hand was ischemic, perfused, or if they were unsure. The second format presented two side-by-side videos, one ischemic and one perfused. Both were processed with EVM+waveform, and the respondent had to choose which was ischemic. Respondents included both medical and non-medical professionals none of whom had experience with hand surgery.

Results

A total of 64 survey responses were recorded. The EVM+waveform technology significantly improved accuracy in determining ischemia regardless of the respondent’s health care experience. Respondents were divided into medical doctorate (MD; n = 15) and non-MD (n = 49) groups. Both groups demonstrated significant improvement in determining ischemia when using EVM+waveform. Within the non-MD cohort, accuracy percentages significantly improved across Fitzpatrick types IV, V, and VI. Within the MD cohort, accuracy percentages significantly improved across Fitzpatrick types III, V, and VI.

Conclusions

These findings further establish EVM+waveform as an effective modality for identifying ischemia via video alone, as it enhanced performance for inexperienced evaluators. EVM+waveform is effective for assessing various skin types, especially those with higher skin melanin content.