AI-based triage and decision support in mammography and digital tomosynthesis for breast cancer screening: a paired, noninferiority trial.

Here this prospective, paired, noninferiority clinical trial evaluated whether AI could safely reduce workload by excluding low-risk exams from radiologist reading.

本项前瞻性、配对、非劣效性临床试验评估了AI是否可以通过排除低风险检查来安全地减少放射科医生的工作负担。

Between March 2022 and January 2024, 31,301 women were included in the trial and underwent routine mammograms.

2022年3月至2024年1月期间，共有31,301名女性参与了试验并接受了常规乳房X线摄影。

Two reading strategies were applied in parallel: standard double-blindreading and partially autonomous AI-supported screening, where cases classified by AI as low risk were assessed as normal and the rest were double read with AI support.

并行应用了两种阅片策略：标准的双盲阅片和部分自主的人工智能辅助筛查，其中人工智能分类为低风险的病例被评估为正常，其余的则在人工智能支持下进行双重阅片。

The primary outcomes were radiologist workload, cancer detection rate and recall rate.

主要结果包括放射科医生的工作量、癌症检出率和召回率。

In the AI strategy, radiologist workload was 63.6% lower; the cancer detection rate was 15.2% higher (95% confidence interval6.6%, 24.4%), increasing from 6.3 of 1,000 to 7.3 of 1,000, P < 0.001; and the recall rate was not noninferior and was 14.8% higher (95% confidence interval9.0%, 20.6%).

在人工智能策略中，放射科医生的工作量降低了63.6%；癌症检出率提高了15.2%（95%置信区间6.6%，24.4%），从每1000人中的6.3例增加到每1000人中的7.3例，P < 0.001；召回率没有显示出非劣效性，并且提高了14.8%（95%置信区间9.0%，20.6%）。

Subanalyses by modality highlighted a similar workload reduction in digital mammography (-62.1%) and digital breast tomosynthesis (-65.5%).

按检查方式的亚组分析突显了数字乳腺X线摄影(-62.1%)和数字乳腺断层扫描(-65.5%)的工作量减少相似。

However, in digital mammography, the cancer detection rate increased by 1.6 of 1,000 and the recall rate by 1.3%, while both remained stable in digital breast tomosynthesis.

然而，在数字乳腺X线摄影中，癌症检出率增加了每千人1.6例，召回率增加了1.3%，而在数字乳腺断层扫描中两者保持稳定。

These results demonstrate the feasibility of a partially automated AI workflow in breast cancer screening, avoiding human reading of studies classified as low risk.

这些结果展示了在乳腺癌筛查中部分自动化人工智能工作流程的可行性，避免了对被分类为低风险的研究进行人工阅读。

ClinicalTrials.gov: NCT04849776 .

ClinicalTrials.gov: NCT04849776 .