Vara and University of Lübeck kick off first-ever prospective AI study for breast cancer screening in Germany
March 2022: In participation with breast cancer screening units in the German Mammography Screening Programme, Vara and the University of Lübeck have begun the first of its kind nation-wide prospective observational study to evaluate the use of an AI application and workflow software to support breast cancer screening radiologists.
While many AI systems have demonstrated strong performance in simulations using historical screening data, prospective studies are the key to measuring the real-world effect of AI in clinical practice. These are required to determine how the use of AI will translate safely and efficiently to the clinical world.
The PRAIM Study (PRospective multicenter observational study of an integrated artificial intelligence (AI) system with live Monitoring) is led by Prof. Alexander Katalinic (University Hospital Schleswig Holstein, Lübeck) in collaboration with Vara. The study is embedded within the national population-based breast cancer screening programme and is guided clinically by an Advisory Board made up of the country's leading breast cancer screening radiologists. The study protocol was approved by the University of Lübeck Ethics Committee and is registered in the German Clinical Trials Register.
To date, less than a handful of prospective studies have begun globally which investigate the performance of AI solutions, and more importantly, how radiologists interact with this technology. Other studies [1,2,3] are small-scale, experimental and mainly focused on single-centre experiences. The PRAIM study has sites open across Germany. Over the course of the 1.5 year-study, we expect mammograms from at least 400,000 women will be evaluated. The wide-scale involvement of important stakeholders in the German Mammography Screening Programme allows for greater participation of screening units, a diverse study population, and a quick turnaround time for results. This is key for a rapidly evolving technology with growing adoption around the world.
The PRAIM study takes on a unique study design, allowing for direct observation of radiologist interaction with the technology, and comparison to current and historical “controls”. Important screening-related metrics can be compared between mammograms read with AI assistance, and those not. The study is observational, meaning women will undergo routine mammography screening following local guidelines.
Prof. Alexander Katalinic, University Hospital Schleswig Holstein, Lübeck, said: “ We want to understand how this CE-marked technology is currently being used in German mammography screening units: what works, and what doesn't. Using an observational study design was an important strategic decision to take. Such a study design is feasible, reflects the real healthcare situation and we can observe outcomes for more women in a quite short period of time. This way we can disseminate important findings more quickly to the radiologists who await this evidence.”
Vara's AI uses a unique decision referral approach that leverages the strengths of both the radiologist and the AI algorithm. This two-part system incorporates triage of normal exams with high accuracy, while also introducing a “safety net” to maintain a high degree of sensitivity by performing predictions on the presence or absence of cancerous findings as post-hoc decision support.
Prof. Katja Pinker-Domenig, Lead Medical Advisor at Vara, said: “AI has been hailed as the solution to many of the challenges of breast cancer screening, but the technology is simply not ready. The decision referral approach could be an effective solution to rapidly bringing AI into wider clinical use today.”
The decision referral approach has already been shown to improve the screening accuracy (sensitivity and specificity) of an average German radiologist based on a retrospective evaluation of screening data from eight screening units in the German Mammography Screening Programme (peer-reviewed publication pending). The prospective evaluation through the PRAIM Study will investigate the true performance of AI, interaction with radiologists and the most optimal integration in real-world settings.
The PRAIM Study is being supervised by an Advisory Board made up of the following breast imaging experts:
- Dr. Gerold Hecht, Reference Center Mammography North
- Professor Heywang-Köbrunner, Reference Center Mammography Munich
- Professor Katja Siegmann-Luz, Reference Center Mammamography Berlin
- Dr. Thilo Töllner, Klinik Dr. Hancken, Stade
- Dr. Toni Vomweg, Radiologisches Institut Dr. von Essen, Koblenz
- Regine Rathmann, Praxis Schwarzer Bär, Hannover
- Dr. Timo Gomille, Visiorad, Pinneberg