365-03-004 ISMRM Abstract

Image Quality in Breast DWI Using DL readout-segmented EPI: A Comparison with Standard readout-segmented EPI at 3T

Primary: Diffusion

Secondary: Acquisition & Reconstruction

365-03-004 · Body Diffusion MRI Methods · Monday, 11 May, 1:50 PM–2:45 PM · Digital Posters Row F

Keywords: EPI Deep learning Diffusion-Weighted Imaging Image Quality Assessment Breast MRI

Accepted

Zoia Laraib ¹, Marialena Tsarouchi^1,2, Carla Sitges³, Antonio Portaluri^1,2, Gregor Thoermer⁴, Marnix C Maas¹, Elisabeth Weiland⁴, Wei Liu⁴, Ritse M Mann^1,2

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

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

³Diagnostic Imaging Center, hospital clinic de barcelona, Barcelona, Spain

⁴Research & clinical Translation, Magnetic Resonance, Siemens Healthineers AG, Erlangen, Germany

Presenting Author: Zoia Laraib

Synopsis

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References

1. Mann RM, Cho N, Moy L. Breast MRI: State of the Art. Radiology. 2019;292(3):520-536. doi:10.1148/radiol.2019182947 [doi]

2. Honda M, Sigmund EE, Le Bihan D, et al. Advanced breast diffusion-weighted imaging: what are the next steps? A proposal from the EUSOBI International Breast Diffusion-weighted Imaging working group. Eur Radiol. 2025;35(4):2130-2140. doi:10.1007/s00330-024-11010-0 [doi]

3. Olthof S-C, Weiland E, Benkert T, Wessling D, Leyhr D, Afat S, Nikolaou K, Preibsch H. Optimizing Image Quality with High-Resolution, Deep-Learning-Based Diffusion-Weighted Imaging in Breast Cancer Patients at 1.5 T. Diagnostics. 2024; 14(16):1742. https://doi.org/10.3390/diagnostics14161742 [doi]

4. Tsarouchi M, Portaluri A, Maas M, Mann RM. Comparing DWI image quality of deep-learning-reconstructed EPI with RESOLVE in breast lesions at 3.0T: a pilot study https://doi.org/10.48550/arXiv.2410.00018 [doi]

5. Wilpert C, Neubauer C, Rau A, et al. Accelerated Diffusion-Weighted Imaging in 3 T Breast MRI Using a Deep Learning Reconstruction Algorithm With Superresolution Processing: A Prospective Comparative Study. Invest Radiol. 2023;58(12):842-852. DOI: 10.1097/RLI.0000000000000997 [doi]

6. Liu W, Darwish O, Benkert T, et al (2024) Improved readout-segmented EPI using deep learning reconstruction. Proc. Intl.Soc. Mag.Reson.Med.32:5106

7. Grand Challenge. BRADS: Breast Reader Analysis of Diffusion Sequences—Reader Study. Accessed October 28, 2025. Available from: https://grand-challenge.org/reader-studies/brads/

Cite this abstract

http://echo.ismrm.org/p/ISMRM2026/365-03-004