PRAIM: Prospective, multicenter observational study of an integrated AI system with live monitoring to support early breast cancer detection.

The Vara software helps to assess compatible digital or digitized images of the human breast with regard to the presence or absence of cancer findings using mathematical methods or artificial intelligence (AI). Vara was developed by MX Health Care and successfully certified as a European Class IIb medical device in September 2019. Vara supports the creation of machine-readable medical reports. The software is intended for the detection of breast cancer (ICD C50) in an approved mammography screening unit. UKSH and MXH are jointly conducting a prospective observational study with the project title "A prospective, multicenter observational study of an integrated AI system with live monitoring to support breast cancer screening (short: PRAIM study)". The aim is to evaluate the detection rates for breast cancer in mammography screening. It is expected that AI can provide useful support for breast cancer detection. The study ran from January 2022 up to April 2025.

Abstract published in Eisemann, Bunk et al. (Nationwide real-world implementation of AI for cancer detection in population-based mammography screening. Nat Med 31, 917–924 (2025). https://doi.org/10.1038/s41591-024-03408-6):
"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."