570-01-170 ISMRM Abstract

Comparative Analysis of AI and Radiologist Assessments for Breast Cancer Detection on MRI

Primary: Body - Breast

Secondary: Analysis Methods - Foundation Models

570-01-170 · AI Applications in Body MRI · Wednesday, 13 May, 8:20 AM–9:15 AM · Traditional Posters | Exhibition Hall

Keywords: MRI for Breast Screening Diagnostic performance Clinical Workflow Integration Breast Cancer Detection AI for Breast MRI

Accepted

Nika Rasoolzadeh ^1,2, Koen Eppenhof³, Ritse M Mann^1,2

¹Department of Medical Imaging, Radboud University Medical Center, Nijmegen, Netherlands

²Department of Radiology, the Netherlands Cancer Institute, Amsterdam, Netherlands

³ScreenPoint Medical BV, Nijmegen, Netherlands

Presenting Author: Nika Rasoolzadeh

Synopsis

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References

1. Mann, R. M., Kuhl, C. K., & Moy, L. (2019). Contrast-enhanced MRI for breast cancer screening. Journal of magnetic resonance imaging : JMRI, 50(2), 377–390. https://doi.org/10.1002/jmri.26654 [doi]

2. Mann, R. M., Cho, N., & Moy, L. (2019). Breast MRI: State of the Art. Radiology, 292(3), 520–536. https://doi.org/10.1148/radiol.2019182947 [doi]

3. Hernström, V., Josefsson, V., Sartor, H., Schmidt, D., Larsson, A. M., Hofvind, S., Andersson, I., Rosso, A., Hagberg, O., & Lång, K. (2025). Screening performance and characteristics of breast cancer detected in the Mammography Screening with Artificial Intelligence trial (MASAI): A randomised, controlled, parallel group, non inferiority, single blinded, screening accuracy study. The Lancet Digital Health, 7(3), e175–e183. https://doi.org/10.1016/S2589 7500(24)00267 X [doi]

4. Díaz, O., Rodríguez-Ruíz, A., & Sechopoulos, I. (2024). Artificial intelligence for breast cancer detection: Technology, challenges, and prospects. European Journal of Radiology, 175, 111457. https://doi.org/10.1016/j.ejrad.2024.111457 [doi]

Cite this abstract

http://echo.ismrm.org/p/ISMRM2026/570-01-170