Introduction: Early detection of malignant pulmonary nodules through screening has been shown to reduce lung cancer-related mortality by 20%. However, perceptual and cognitive factors that affect nodule detection are poorly understood. This review examines the cognitive and visual processes of various observers, with a particular focus on radiologists, during lung nodule detection. Methods: Four databases (Medline, Embase, Scopus and PubMed) were searched to extract studies on eye-tracking in pulmonary nodule detection. Studies were included if they used eye-tracking to assess the search and detection of lung nodules in computed tomography or 2D radiographic imaging. Data were charted according to identified themes and synthesised using a thematic narrative approach. Results: The literature search yielded 25 articles and five themes were discovered: 1functional visual field and satisfaction of search, 2expert search patterns, 3error classification through dwell time, 4the impact of the viewing environment and 5the effect of prevalence expectation on search. Functional visual field reduced to 2.7°in 3D imaging compared to 5°in 2D radiographs. Although greater visual coverage improved nodule detection, incomplete search was not responsible for missed nodules. Most radiological errors during lung nodule detection were decisionmaking errors (30%-45%). Dwell times associated with false-positive (FP) decisions informed feedback systems to improve diagnosis. Interruptions did not influence diagnostic performance; however, it increased viewing time by 8% and produced a 23.1% search continuation accuracy. Comparative scanning was found to increase the detection of low contrast nodules. Prevalence expectation did not directly affect diagnostic accuracy; however, decisionmaking time increased by 2.32 seconds with high prevalence expectations.
Conclusion:Visual and cognitive factors influence pulmonary nodule detection. Insights gained from eye-tracking can inform advancements in lung screening. Further exploration of eye-tracking in lung screening, particularly with lowdose computed tomography (LDCT), will benefit the future of lung cancer screening.