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European journal of radiology · 2026

Guideline-concordant decision support in abdominal radiology: An expert-based evaluation of Gemini.

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Kaya Mehmet Fatih, Sabet Soheil

Аннотация

RATIONALE AND OBJECTIVES: Large language models may help radiologists apply increasingly complex imaging guidelines, but their safety and clinical usefulness as decision-support tools in abdominal radiology remain uncertain. We evaluated the usefulness, potential harm, guideline concordance, and triage performance of Gemini across different levels of case difficulty.

MATERIALS AND METHODS: In this expert-based cross-sectional study, 200 synthetic, guideline-based abdominal radiology cases were created by consensus across four domains: adrenal, renal, liver, and pancreatic lesions (50 cases each). Case difficulty was prospectively assigned as level 1, 2, or 3 before LLM querying. Using text-only case descriptions, Gemini 1.5 Flash generated an impression, recommendation, rationale, and final category for each case. Five abdominal radiologists independently rated usefulness (1-5) and harm (0-3). Two abdominal radiologists independently assessed impression concordance, final-category concordance, and triage appropriateness relative to the reference standard.

RESULTS: Median usefulness was 5 (IQR, 1), and median harm was 0 (IQR, 0). Overall impression concordance was 85.0 % (170/200), and final-category concordance was 77.5 % (155/200). Greater case difficulty was associated with lower usefulness (p < 0.001), higher harm (p < 0.001), lower concordance (both p < 0.001), and worse triage performance. Triage distributions differed by case difficulty (p = 0.012), with appropriate triage declining from 85.7 % in level 1 cases to 66.2 % in level 3 cases.

CONCLUSION: Gemini showed high perceived usefulness, low overall harm, and generally strong guideline concordance in abdominal radiology. However, declining performance with greater case difficulty supports its use as assistive decision support rather than autonomous management in complex or high-risk scenarios.

Предметные рубрики MeSH

ИП Урсолов Владлен Сергеевич

ИНН 500118482352 · ОГРНИП 314500117700049

Реквизиты и контакты