瑞典筛查性乳腺钼靶摄影中用于乳腺癌检测的人工智能：一项前瞻性、基于人群、配对读者、非劣效性研究。

Artificial intelligence for breast cancer detection in screening mammography in Sweden: a prospective, population-based, paired-reader, non-inferiority study.

机构信息

Breast Imaging Unit, Department of Radiology, Capio Sankt Göran Hospital, Sankt Göransplan, Stockholm, Sweden; Department of Oncology-Pathology, Karolinska Institutet, Stockholm, Sweden.

Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.

出版信息

Lancet Digit Health. 2023 Oct;5(10):e703-e711. doi: 10.1016/S2589-7500(23)00153-X. Epub 2023 Sep 8.

DOI:10.1016/S2589-7500(23)00153-X

PMID:37690911

Abstract

BACKGROUND

Artificial intelligence (AI) as an independent reader of screening mammograms has shown promise, but there are few prospective studies. Our aim was to conduct a prospective clinical trial to examine how AI affects cancer detection and false positive findings in a real-world setting.

METHODS

ScreenTrustCAD was a prospective, population-based, paired-reader, non-inferiority study done at the Capio Sankt Göran Hospital in Stockholm, Sweden. Consecutive women without breast implants aged 40-74 years participating in population-based screening in the geographical uptake area of the study hospital were included. The primary outcome was screen-detected breast cancer within 3 months of mammography, and the primary analysis was to assess non-inferiority (non-inferiority margin of 0·15 relative reduction in breast cancer diagnoses) of double reading by one radiologist plus AI compared with standard-of-care double reading by two radiologists. We also assessed single reading by AI alone and triple reading by two radiologists plus AI compared with standard-of-care double reading by two radiologists. This study is registered with ClinicalTrials.gov, NCT04778670.

FINDINGS

From April 1, 2021, to June 9, 2022, 58 344 women aged 40-74 years underwent regular mammography screening, of whom 55 581 were included in the study. 269 (0·5%) women were diagnosed with screen-detected breast cancer based on an initial positive read: double reading by one radiologist plus AI was non-inferior for cancer detection compared with double reading by two radiologists (261 [0·5%] vs 250 [0·4%] detected cases; relative proportion 1·04 [95% CI 1·00-1·09]). Single reading by AI (246 [0·4%] vs 250 [0·4%] detected cases; relative proportion 0·98 [0·93-1·04]) and triple reading by two radiologists plus AI (269 [0·5%] vs 250 [0·4%] detected cases; relative proportion 1·08 [1·04-1·11]) were also non-inferior to double reading by two radiologists.

INTERPRETATION

Replacing one radiologist with AI for independent reading of screening mammograms resulted in a 4% higher non-inferior cancer detection rate compared with radiologist double reading. Our study suggests that AI in the study setting has potential for controlled implementation, which would include risk management and real-world follow-up of performance.

FUNDING

Swedish Research Council, Swedish Cancer Society, Region Stockholm, and Lunit.

摘要

背景

人工智能（AI）作为一种独立的乳腺 X 线筛查阅读设备，已显示出一定的应用前景，但目前仍缺乏前瞻性研究。本研究旨在开展一项前瞻性临床试验，以探讨在真实环境下 AI 对癌症检出和假阳性结果的影响。

方法

ScreenTrustCAD 是一项在瑞典斯德哥尔摩 Capio Sankt Göran 医院进行的前瞻性、基于人群、配对读者、非劣效性研究。研究纳入了年龄在 40-74 岁、无乳房植入物、正在参加研究医院地理覆盖范围内基于人群的筛查的连续女性。主要结局是在乳腺 X 线摄影后 3 个月内检出的乳腺癌，主要分析是评估一名放射科医生加 AI 的双读与两名放射科医生标准护理双读相比的非劣效性（乳腺癌诊断相对减少 0.15）。我们还评估了 AI 单独单读和两名放射科医生加 AI 三读与两名放射科医生标准护理双读相比的情况。本研究在 ClinicalTrials.gov 上注册，编号为 NCT04778670。

结果

从 2021 年 4 月 1 日至 2022 年 6 月 9 日，共有 58344 名年龄在 40-74 岁的女性接受了常规乳腺 X 线筛查，其中 55581 名女性纳入了研究。根据初次阳性读片，269 名（0.5%）女性被诊断为筛查检出的乳腺癌：一名放射科医生加 AI 的双读与两名放射科医生的双读相比，在癌症检出方面非劣效（261[0.5%]例 vs 250[0.4%]例；相对比例 1.04[95%CI 1.00-1.09]）。AI 单读（246[0.4%]例 vs 250[0.4%]例；相对比例 0.98[0.93-1.04]）和两名放射科医生加 AI 的三读（269[0.5%]例 vs 250[0.4%]例；相对比例 1.08[1.04-1.11]）也与两名放射科医生的双读非劣效。