Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition
9 May 2026 – 14 May 2026 · Cape Town, South Africa
365-03-007 ISMRM Abstract

Evaluation of generalist, on-the-scanner, deep learning recon for M2SE cardiac DTI

Primary: Cardiovascular - Myocardium
Secondary: Diffusion - Diffusion Reconstruction
365-03-007 · Body Diffusion MRI Methods · Monday, 11 May, 1:50 PM–2:45 PM · Digital Posters Row F
Keywords: Denoising Deep-learning In Vivo M2-cDTI
Accepted
Daniel P Atkinson 1, Peter Gatehouse1, Vanessa M Ferreira1, Elizabeth M Tunnicliffe1, Rebecca Mills1, Betty Raman1, Patricia Lan2, Haonan Wang3, Xinzeng Wang4, Stephen Jermy5,6,7, James T Grist1,8,9, Damian Tyler1,9, Margarita Gorodezky10, Stefan K Piechnik1
1Oxford Centre for Clinical MR Research (OCMR), University of Oxford, Oxford, United Kingdom
2GE HealthCare, Menlo Park, United States of America
3GE HealthCare, San Ramon, United States of America
4GE Healthcare, Houston, United States of America
5Neuroscience Institute, University of Cape Town, Cape Town, South Africa
6Department of Human Biology, University of Cape Town, Cape Town, South Africa
7Cape Universities Body Imaging Centre (CUBIC), University of Cape Town, Cape Town, South Africa
8Department of Radiology, Oxford University Hospitals NHS Trust, Oxford, United Kingdom
9Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford, United Kingdom
10GE Healthcare, Munich, Germany
Presenting Author: Daniel P Atkinson

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References

1. Khalique, Z., Ferreira, P. F., Scott, A. D., Nielles-Vallespin, S., Firmin, D. N., & Pennell, D. J. (2020). Diffusion Tensor Cardiovascular Magnetic Resonance Imaging: A Clinical Perspective. JACC. Cardiovascular Imaging, 13(5), 1235. https://doi.org/10.1016/j.jcmg.2019.07.016 [doi]
2. Scott, A. D., Nielles-Vallespin, S., Ferreira, P. F., McGill, L.-A., Pennell, D. J., & Firmin, D. N. (2016). The effects of noise in cardiac diffusion tensor imaging and the benefits of averaging complex data. NMR in Biomedicine, 29(5), 588–599. https://doi.org/10.1002/nbm.3500 [doi]
3. Huang, J., Ferreira, P. F., Wang, L., Wu, Y., Aviles-Rivero, A. I., Schönlieb, C.-B., Scott, A. D., Khalique, Z., Dwornik, M., Rajakulasingam, R., De Silva, R., Pennell, D. J., Nielles-Vallespin, S., & Yang, G. (2024). Deep learning-based diffusion tensor cardiac magnetic resonance reconstruction: a comparison study. Scientific Reports, 14(1), Article 5658. https://doi.org/10.1038/s41598-024-55880-2 [doi]
4. Phipps, K., van de Boomen, M., Eder, R., Michelhaugh, S. A., Spahillari, A., Kim, J., Parajuli, S., Reese, T. G., Mekkaoui, C., Das, S., Gee, D., Shah, R., Sosnovik, D. E., & Nguyen, C. (2021). Accelerated in Vivo Cardiac Diffusion-Tensor MRI Using Residual Deep Learning–based Denoising in Participants with Obesity. Radiology. Cardiothoracic Imaging, 3(3), e200580. https://doi.org/10.1148/ryct.2021200580 [doi]
5. van der Velde, N., Hassing, H. C., Bakker, B. J., Wielopolski, P. A., Lebel, R. M., Janich, M. A., Kardys, I., Budde, R. P. J., & Hirsch, A. (2021). Improvement of late gadolinium enhancement image quality using a deep learning–based reconstruction algorithm and its influence on myocardial scar quantification. European Radiology, 31(6), 3846–3855. https://doi.org/10.1007/s00330-020-07461-w [doi]
6. Lebel, R. M. (2020). Performance characterization of a novel deep learning-based MR image reconstruction pipeline. https://doi.org/10.48550/arxiv.2008.06559 [doi]
7. Wang, X., Litwiller, D., Guidon, A., Lan, P., Sprenger, T. (2023) Robust Complex Signal Averaging for Diffusion Weighted Imaging, ISMRM 2023: 3963
8. Wang, X., Lan, P., Guidon, A. (2024) DL-based Phase Correction Enables Robust Real Diffusion-Weighted MRI with Increased Diffusion Contrast, ISMRM 2024: 2414
9. Stoeck, C. T., von Deuster, C., Genet, M., Atkinson, D., & Kozerke, S. (2016). Second-order motion-compensated spin echo diffusion tensor imaging of the human heart. Magnetic Resonance in Medicine, 75(4), 1669–1676. https://doi.org/10.1002/mrm.25784 [doi]
10. We thank the Multi-centre Investigation of Cardiac Diffusion Tensor Imaging in Healthy Volunteers by SCMR Cardiac Diffusion Special Interest Group NETwork (SIGNET; https://doi.org/10.1186/ISRCTN46174869) study for inputs on the data acquisition. [doi]
11. Tunnicliffe, E. M., Scott, A. D., Ferreira, P., Ariga, R., McGill, L.-A., Nielles-Vallespin, S., Neubauer, S., Pennell, D. J., Robson, M. D., & Firmin, D. N. (2014). Intercentre reproducibility of cardiac apparent diffusion coefficient and fractional anisotropy in healthy volunteers. Journal of Cardiovascular Magnetic Resonance, 16(1), Article 31. https://doi.org/10.1186/1532-429X-16-31 [doi]

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http://echo.ismrm.org/p/ISMRM2026/365-03-007