Can eye-tracking metrics be used to better pair radiologists in a mammogram reading task?

Medical Physics
Ziba GandomkarClaudia Mello-Thoms

Abstract

To propose a framework for optimal pairing of radiologists when reading mammograms based on their search patterns. Four experienced and four less-experienced radiologists were asked to assess 120 cases (59 with cancers) while their eye positions were tracked. Fourteen eye-tracking metrics were extracted to quantify the differences among radiologists' visual search pattern. For each radiologist and metric, less-experienced radiologists and expert readers were ranked based on the level of similarities in gaze patterns (from the most different to the most similar). Less-experienced readers and experts were also ranked based on the values of area under the receiver operating characteristic curve (AUC) after pairing (the best possible way of ranking). Using the Kendall's tau distance, rankings based on different metrics were compared with the best possible ranking. Using paired Wilcoxon signed-rank test, the AUC values when pairing in the best way were compared with pairing based on different metrics. Finally, we investigated the robustness of pairing strategies against the small sample size. For ranking the experienced radiologists, results from eight metrics were as good as the best possible ranking. For the less-experienced ones,...Continue Reading

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Apr 26, 2018·Medical Physics·Ziba GandomkarClaudia Mello-Thoms

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Citations

Jul 10, 2019·The British Journal of Radiology·Ziba Gandomkar, Claudia Mello-Thoms
Feb 24, 2019·Cognitive Research: Principles and Implications·Tad T BrunyéJoann G Elmore
Feb 6, 2022·Breast Cancer : the Journal of the Japanese Breast Cancer Society·Ziba GandomkarPatrick C Brennan

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