Clinical validation of an artificial intelligence system to improve the quality, efficiency and experience of breast cancer screening

Imperial College London0 个研究点目标入组 68,000 人开始时间: 2022年6月6日最近更新: 2022年6月20日

适应症

试验速览

暂无简介。

•1. Women undergoing routine breast cancer screening (age 50-70 years) as part of the national breast screening programme from January 2016 onwards
•2. Mammography images acquired using Hologic/Lorad, Siemens, or GE devices

•1. Women attending an assessment clinic or symptomatic clinic (i.e. not routine screening)
•2. Women undergoing annual screening due to:
•2.1. High risk (lifetime risk >30% - e.g. faulty BRCA1, BRCA2, TP53)
•2.2. Moderate risk (lifetime risk 17-30%)
•2.3. Personal stratified follow up (e.g. indeterminate B3 lesions)
•3. Presence of breast implants
•4. Screens with incomplete (<4 standard screening views - e.g. due to abandoned screen)
•5. Poor diagnostic quality imaging (which would be repeated)
•6. Non-standard acquisitions beyond the routine 4 screening views
•7. For negative or benign cases, women without a negative follow up screen approximately 3 years later (at least 31 months after initial screen), as this would preclude determination of a robust ground truth
•Same dataset as defined in Part A, with the same inclusion and exclusion criteria

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