Eisemann Nora, Bunk Stefan, Mukama Trasias, Baltus Hannah, Elsner Susanne A, Gomille Timo, Hecht Gerold, Heywang-Köbrunner Sylvia, Rathmann Regine, Siegmann-Luz Katja, Töllner Thilo, Vomweg Toni Werner, Leibig Christian, Katalinic Alexander
Institute for Social Medicine and Epidemiology, University of Lübeck, Lubeck, Germany.
Vara, Berlin, Germany.
Nat Med. 2025 Mar;31(3):917-924. doi: 10.1038/s41591-024-03408-6. Epub 2025 Jan 7.
Artificial intelligence (AI) in mammography screening has shown promise in retrospective evaluations, but few prospective studies exist. PRAIM is an observational, multicenter, real-world, noninferiority, implementation study comparing the performance of AI-supported double reading to standard double reading (without AI) among women (50-69 years old) undergoing organized mammography screening at 12 sites in Germany. Radiologists in this study voluntarily chose whether to use the AI system. From July 2021 to February 2023, a total of 463,094 women were screened (260,739 with AI support) by 119 radiologists. Radiologists in the AI-supported screening group achieved a breast cancer detection rate of 6.7 per 1,000, which was 17.6% (95% confidence interval: +5.7%, +30.8%) higher than and statistically superior to the rate (5.7 per 1,000) achieved in the control group. The recall rate in the AI group was 37.4 per 1,000, which was lower than and noninferior to that (38.3 per 1,000) in the control group (percentage difference: -2.5% (-6.5%, +1.7%)). The positive predictive value (PPV) of recall was 17.9% in the AI group compared to 14.9% in the control group. The PPV of biopsy was 64.5% in the AI group versus 59.2% in the control group. Compared to standard double reading, AI-supported double reading was associated with a higher breast cancer detection rate without negatively affecting the recall rate, strongly indicating that AI can improve mammography screening metrics.
人工智能（AI）在乳腺钼靶筛查中的应用在回顾性评估中已显示出前景，但前瞻性研究较少。PRAIM是一项观察性、多中心、真实世界、非劣效性实施研究，比较了在德国12个地点接受有组织乳腺钼靶筛查的50至69岁女性中，人工智能支持的双人读片与标准双人读片（无人工智能）的表现。本研究中的放射科医生自愿选择是否使用人工智能系统。2021年7月至2023年2月，119名放射科医生共筛查了463,094名女性（260,739名接受人工智能支持）。人工智能支持筛查组的放射科医生实现了每1000人6.7例的乳腺癌检出率，比对照组（每1000人5.7例）高出17.6%（95%置信区间：+5.7%，+30.8%），且在统计学上具有优越性。人工智能组的召回率为每1000人37.4例，低于对照组（每1000人38.3例）且非劣于对照组（百分比差异：-2.5%（-6.5%，+1.7%））。人工智能组召回的阳性预测值（PPV）为17.9%，而对照组为14.9%。人工智能组活检的PPV为64.5%，而对照组为59.2%。与标准双人读片相比，人工智能支持的双人读片与更高的乳腺癌检出率相关，且不会对召回率产生负面影响，这有力地表明人工智能可以改善乳腺钼靶筛查指标。
