Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition
9 May 2026 – 14 May 2026 · Cape Town, South Africa
365-04-009 ISMRM Abstract

Deep Learning Analysis of Breast Diffusion MRI for Cancer Assessment Using Biophysically Informed Signal Representations

Primary: Body - Breast
Secondary: Diffusion - Diffusion Analysis & Visualization
365-04-009 · Body MR: Potpourri of Techniques in Uterine, Cervical, Liver, and Kidney Imaging · Monday, 11 May, 2:45 PM–3:40 PM · Digital Posters Row F
Keywords: Quantitative Imaging Breast cancer Deep learning Diffusion-weighted MRI IVIM DKI
Accepted
Mami Iima 1,2,3, Ryosuke Mizuno2,4, Denis LE BIHAN5, Kaito Nonoyama2, Rintaro Ito2,6, Keiho Imanishi7, Hiroko Satake2, Yusuke Jo2, Ryota Hyodo1,2, MASAKO Y KATAOKA8, Aki Mano2, Shinji Naganawa2
1Fundamental Development for Advanced Low Invasive Diagnostic Imaging, Nagoya University Graduate School of Medicine, Nagoya, Japan
2Department of Radiology, Nagoya University Graduate School of Medicine, Nagoya, Japan
3Diagnostic imaging and Nuclear medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
4A.I. System Research Co. Ltd, Kyoto, Japan
5Neurospin, CEA Paris Saclay, France
6Department of Innovative Biomedical Visualization, Nagoya University Graduate School of Medicine, Nagoya, Japan
7e-Growth Co., Ltd, Japan
8Preemptive Medicine & Lifestyle-related Disease Research C., Kyoto University Hospital, Kyoto, Japan
Presenting Author: Mami Iima

Synopsis

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References

1. Iima, Mami, Ryosuke Mizuno, Masako Kataoka, Kazuki Tsuji, Toshiki Yamazaki, Akihiko Minami, Maya Honda, Keiho Imanishi, Masahiro Takada, and Yuji Nakamoto. 2025. “Deep Learning Applied to Diffusion-Weighted Imaging for Differentiating Malignant from Benign Breast Tumors without Lesion Segmentation.” Radiology. Artificial Intelligence 7 (1): e240206. PMID: 39565222 DOI: 10.1148/ryai.240206 [doi] [pmid]
2. Mariko Goto, Denis Le Bihan, Mariko Yoshida, Koji Sakai, Kei Yamada Adding a Model-free Diffusion MRI Marker to BI-RADS Assessment Improves Specificity for Diagnosing Breast Lesions PMID: 31112086 DOI: 10.1148/radiol.2019181780 [doi] [pmid]
3. Iima, Mami, Masako Kataoka, Shotaro Kanao, Natsuko Onishi, Makiko Kawai, Akane Ohashi, Rena Sakaguchi, Masakazu Toi, and Kaori Togashi. 2018. “Intravoxel Incoherent Motion and Quantitative Non-Gaussian Diffusion MR Imaging: Evaluation of the Diagnostic and Prognostic Value of Several Markers of Malignant and Benign Breast Lesions.” Radiology 287 (2): 432–41 PMID: 29095673 DOI: 10.1148/radiol.2017162853 [doi] [pmid]
4. Le Bihan D, Iima M, Yano K, patent WO2015133363

Cite this abstract

http://echo.ismrm.org/p/ISMRM2026/365-04-009