Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition
9 May 2026 – 14 May 2026 · Cape Town, South Africa
503-02-008 ISMRM Abstract

Neural Controlled Differential Equation (NCDE) for IVIM Analysis in Flow Phantom and Multisite Breast Tumor Patients

Primary: Diffusion - IVIM
Secondary: Body - Breast
503-02-008 · Body Diffusion MRI · Wednesday, 13 May, 1:40 PM–3:30 PM · Auditorium 1
Keywords: Analysis/Processing IVIM Breast cancer Multi-site MRI Diffusion phantom
Accepted
Dibash Basukala1,2, Artem Mikheev1,2, Daan Kuppens3, Nima Gilani1,2, Linda Moy1,2, Savannah Partridge4, Mami Iima5, Oliver J Gurney-Champion3, Sunitha B Thakur6, Eric Sigmund 1,2
1Center for Advanced Imaging Innovation and Research (CAI²R), New York University Grossman School of Medicine, New York, United States of America
2Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, New York, United States of America
3Department of Radiology and Nuclear Medicine, Amsterdam University Medical Center, University of Amsterdam, Amsterdam, Netherlands
4Department of Radiology, University of Washington, Seattle, United States of America
5Fundamental Development for Advanced Low Invasive Diagnostic Imaging, Nagoya University Graduate School of Medicine, Nagoya, Japan
6Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, United States of America
Presenting Author: Eric Sigmund

Synopsis

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References

1. Basukala D, Mikheev A, Li X, Goldberg JD, Gilani N, Moy L, et al. Retrospective BReast Intravoxel Incoherent Motion Multisite (BRIMM) multisoftware study. Front Oncol. 2025;15:1524634.
2. Iima M, Honda M, Sigmund EE, Ohno Kishimoto A, Kataoka M, Togashi K. Diffusion MRI of the breast: Current status and future directions. J Magn Reson Imaging. 2020;52(1):70-90.
3. Sigmund EE, Cho GY, Basukala D, Sutton OM, Horvat JV, Mikheev A, et al. Evaluating Breast Cancer Intravoxel Incoherent Motion MRI Biomarkers across Software Platforms. Radiol Imaging Cancer. 2025;7(5):e240115.
4. Sigmund EE, Cho GY, Kim S, Finn M, Moccaldi M, Jensen JH, et al. Intravoxel Incoherent Motion Imaging of Tumor Microenvironment in Locally Advanced Breast Cancer. Magn Reson Med. 2011;65(5):1437-47.
5. Lu YG, Jansen JFA, Stambuk HE, Gupta G, Lee N, Gonen M, et al. Comparing Primary Tumors and Metastatic Nodes in Head and Neck Cancer Using Intravoxel Incoherent Motion Imaging: A Preliminary Experience. J Comput Assist Tomo. 2013;37(3):346-52.
6. Suo ST, Lin N, Wang H, Zhang LB, Wang R, Zhang S, et al. Intravoxel incoherent motion diffusion-weighted MR imaging of breast cancer at 3.0 tesla: Comparison of different curve-fitting methods. J Magn Reson Imaging. 2015;42(2):362-70.
7. Cho GY, Moy L, Zhang JL, Baete S, Lattanzi R, Moccaldi M, et al. Comparison of Fitting Methods and b-Value Sampling Strategies for Intravoxel Incoherent Motion in Breast Cancer. Magn Reson Med. 2015;74(4):1077-85.
8. Luciani A, Vignaud A, Cavet M, Van Nhieu JT, Mallat A, Ruel L, et al. Liver Cirrhosis: Intravoxel Incoherent Motion MR Imaging-Pilot Study. Radiology. 2008;249(3):891-9.
9. Orton MR, Collins DJ, Koh DM, Leach MO. Improved Intravoxel Incoherent Motion Analysis of Diffusion Weighted Imaging by Data Driven Bayesian Modeling. Magn Reson Med. 2014;71(1):411-20.
10. While PT. A comparative simulation study of bayesian fitting approaches to intravoxel incoherent motion modeling in diffusion-weighted MRI. Magn Reson Med. 2017;78(6):2373-87.
11. Barbieri S, Gurney-Champion OJ, Klaassen R, Thoeny HC. Deep learning how to fit an intravoxel incoherent motion model to diffusion-weighted MRI. Magn Reson Med. 2020;83(1):312-21.
12. Kaandorp MPT, Barbieri S, Klaassen R, van Laarhoven HWM, Crezee H, While PT, et al. Improved unsupervised physics-informed deep learning for intravoxel incoherent motion modeling and evaluation in pancreatic cancer patients. Magn Reson Med. 2021;86(4):2250-65.
13. Mastropietro A, Procissi D, Scalco E, Rizzo G, Bertolino N. A supervised deep neural network approach with standardized targets for enhanced accuracy of IVIM parameter estimation from multi-SNR images. Nmr Biomed. 2022;35(10).
14. Kidger P, Morrill J, Foster J, Lyons T. Neural controlled differential equations for irregular time series. Proceedings of the 34th International Conference on Neural Information Processing Systems; Vancouver, BC, Canada: Curran Associates Inc.; 2020. p. Article 562.
15. Kuppens D, Barbieri S, van den Berg D, Schouten P, Thoeny HC, van Laarhoven HWM, et al. Acquisition-Independent Deep Learning for Quantitative MRI Parameter Estimation using Neural Controlled Differential Equations. Med Image Anal. 2025:103768.
16. Basukala D, Mikheev A, Sevilimedu V, Gilani N, Moy L, Pinker K, et al. Multisite MRI Intravoxel Incoherent Motion Repeatability and Reproducibility across 3 T Scanners in a Breast Diffusion Phantom: A BReast Intravoxel Incoherent Motion Multisite (BRIMM) Study. J Magn Reson Imaging. 2024;59(6):2226-37.

Cite this abstract

http://echo.ismrm.org/p/ISMRM2026/503-02-008