{"ID":2853980,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2510.16070","arxiv_id":"2510.16070","title":"Effect of Reporting Mode and Clinical Experience on Radiologists' Gaze and Image Analysis Behavior in Chest Radiography","abstract":"Structured reporting (SR) and artificial intelligence (AI) may transform how radiologists interact with imaging studies. This prospective study (July to December 2024) evaluated the impact of three reporting modes: free-text (FT), structured reporting (SR), and AI-assisted structured reporting (AI-SR), on image analysis behavior, diagnostic accuracy, efficiency, and user experience. Four novice and four non-novice readers (radiologists and medical students) each analyzed 35 bedside chest radiographs per session using a customized viewer and an eye-tracking system. Outcomes included diagnostic accuracy (compared with expert consensus using Cohen's $κ$), reporting time per radiograph, eye-tracking metrics, and questionnaire-based user experience. Statistical analysis used generalized linear mixed models with Bonferroni post-hoc tests with a significance level of ($P \\le .01$). Diagnostic accuracy was similar in FT ($κ= 0.58$) and SR ($κ= 0.60$) but higher in AI-SR ($κ= 0.71$, $P \u003c .001$). Reporting times decreased from $88 \\pm 38$ s (FT) to $37 \\pm 18$ s (SR) and $25 \\pm 9$ s (AI-SR) ($P \u003c .001$). Saccade counts for the radiograph field ($205 \\pm 135$ (FT), $123 \\pm 88$ (SR), $97 \\pm 58$ (AI-SR)) and total fixation duration for the report field ($11 \\pm 5$ s (FT), $5 \\pm 3$ s (SR), $4 \\pm 1$ s (AI-SR)) were lower with SR and AI-SR ($P \u003c .001$ each). Novice readers shifted gaze towards the radiograph in SR, while non-novice readers maintained their focus on the radiograph. AI-SR was the preferred mode. In conclusion, SR improves efficiency by guiding visual attention toward the image, and AI-prefilled SR further enhances diagnostic accuracy and user satisfaction.","short_abstract":"Structured reporting (SR) and artificial intelligence (AI) may transform how radiologists interact with imaging studies. This prospective study (July to December 2024) evaluated the impact of three reporting modes: free-text (FT), structured reporting (SR), and AI-assisted structured reporting (AI-SR), on image analysi...","url_abs":"https://arxiv.org/abs/2510.16070","url_pdf":"https://arxiv.org/pdf/2510.16070v1","authors":"[\"Mahta Khoobi\",\"Marc Sebastian von der Stueck\",\"Felix Barajas Ordonez\",\"Anca-Maria Iancu\",\"Eric Corban\",\"Julia Nowak\",\"Aleksandar Kargaliev\",\"Valeria Perelygina\",\"Anna-Sophie Schott\",\"Daniel Pinto dos Santos\",\"Christiane Kuhl\",\"Daniel Truhn\",\"Sven Nebelung\",\"Robert Siepmann\"]","published":"2025-10-17T08:33:07Z","proceeding":"cs.CV","tasks":"[\"cs.CV\",\"cs.AI\",\"cs.HC\",\"eess.IV\"]","methods":"[]","has_code":false}