ECR 2026

RPS 1002 - Breast cancer screening technology, tools and trends

From Screening to Clinical Diagnosis: Can AI Match Expert Eyes in Mammography?

Speaker: Manuel Rafael López De La Torre Carretero, Pamplona/Spain

Date and time: March 5, 14:30 - 16:00 CET

Evaluates the performance of Transpara in classifying mammograms from screening vs clinical (diagnostic) settings and finds that Transpara demonstrates robust performance in screening settings.

RPS 1102 - Revolutionising breast imaging with artificial intelligence

The effect of AI on retrospectively visible interval cancers in mammography screening – results from the randomised controlled MASAI trial

Speaker: Dr. Veronica Hernstrom, Lund/Sweden

Date and time: March 5, 16:30 - 18:00 CET

The use of AI in mammography screening yielded fewer interval cancers with minimal signs (14 [17%] vs 26 [28%]) at screening compared with standard double reading, indicating its ability to aid in detecting subtle malignancies. A further reduction of interval cancer may be achievable since a substantial proportion of the retrospectively visible interval cancers were assigned elevated risk scores and were correctly localised by AI.

Influence of AI-informed Disease Prevalence on Radiologist Performance: Insights from the Mammography Screening with Artificial Intelligence trial (MASAI)

Speaker: Dr. Jessie Gommers, Nijmegen/Netherlands

Date and time: March 5, 16:30 - 18:00 CET

In the MASAI trial, AI-informed reading helped radiologists focus effort where it mattered most. Transpara reduced false positives in low-risk examinations, while increasing cancer detection in high-risk cases (from ~60% to over 77%), showing how risk stratification can improve screening efficiency while maintaining cancer detection overall.

Artificial Intelligence in Mammography Screening in Norway (AIMS Norway): a randomized controlled trial

(Featuring Transpara® 2.1)

Speaker: Dr. Solveig Hofvind, Oslo/Norway

Date and time: March 5, 16:30 - 18:00 CET

A large randomised trial has launched in Norway, aiming to enrol around 140,000 women to evaluate AI-supported mammography screening. The study will assess whether Transpara, used with one or two radiologists, can safely match standard double reading in real-world screening.

AI risk score for a new versus old version of a CE-marked AI model for breast cancer detection

(Featuring Transpara® 2.1)

Speaker: Dr. Solveig Hofvind, Oslo/Norway

Date and time: March 5, 16:30 - 18:00 CET

Among the screen-detected cancer cases, 7.9% (58/737) had higher AI score in the new versus old version. Among the interval cancers, 11.5% (23/200) had higher score in the new versus old version. An updated version of the AI model resulted in a higher detection of cancers in the high AI risk score group. These findings highlight that as AI models evolve, risk threshold and clinical workflow may need to be adjusted to maintain efficiency.

Can artificial intelligence detect additional cancers on screening digital breast tomosynthesis?

(Featuring Transpara® 2.1)

Speaker: Dr. Victor Carl Martin Dahlblom, Tygelsjö/Sweden

Date and time: March 5, 16:30 - 18:00 CET

Using Transpara to analyse DBT, around 23% of interval cancers and 26% of screen-detected cancers received the highest AI score at first screening. In contrast, only a small fraction of exams without cancer were flagged, indicating that AI could help surface additional cancers on DBT.

RPS 1402 - Hot Topic: Personalised imaging

Epidemiological and deep learning breast cancer risk models compared for an increased-risk population

Speaker: Dr. Machteld Keupers, Leuven/Belgium

Date and time: March 6, 12:30 - 13:30 CET                      

Transpara showed stronger five-year breast cancer risk prediction than Mirai and established epidemiological models (CanRisk and IBIS) in an increased-risk population. These findings highlight the potential of Transpara risk to better capture short-term breast cancer risk compared to traditional models.

RPS 1905 - Building the AI breast imaging service: from deployment to clinical practice

Beyond Screening: AI Performance in Mammographic Breast Cancer Recurrence Detection

(Featuring Transpara® 2.1)

Speaker: M.D. Zahra Agham, NKI/Amsterdam/Netherlands

Date and time: March 7, 12:30 - 13:30 CET

In a post-surgical population, stand-alone AI was less sensitive than radiologists at matched specificity, but it demonstrated strong overall discrimination (AUC 0.95). Increases in Transpara detection category over time were strongly associated with local recurrence, indicating potential value for longitudinal monitoring.

Comparing the Performance of Top Ranked AI Models from the RSNA 2023 Screening Mammography Breast Cancer Detection AI Challenge to Commercial AI Models

Speaker: Dr. Yan Chen, Nottingham/UK

Date and time: March 7, 12:30 - 13:30 CET

Top-performing AI models from the RSNA 2023 Screening Mammography Challenge performed on par with commercially available AI systems in a multi-national screening dataset. This suggests that mature commercial AI solutions can match state-of-the-art research models in real-world screening data.