607-01-010 ISMRM Abstract

Deep Learning Assessment of Global Radial and Circumferential Strain in Single Ventricle Patients

Primary: Pediatrics - Cardiovascular

Secondary: Analysis Methods - Data Processing

607-01-010 · Advanced Cardiac Quantification Methods · Thursday, 14 May, 8:30 AM–10:20 AM · Meeting Room 1.40

Keywords: Deep learning Survival analysis Congenital Heart Disease Myocardial strain analysis

Accepted

Tina Yao ¹, Nicole St. Clair², Gabriel F Miller², Jennifer Steeden¹, Rahul H Rathod², Vivek Muthurangu¹

¹University College London, London, United Kingdom

²Boston Children's Hospital, Boston, United States of America

Presenting Author: Tina Yao

Synopsis

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References

1. Rajiah PS, Kalisz K, Broncano J, Goerne H, Collins JD, François CJ, et al. Myocardial Strain Evaluation with Cardiovascular MRI: Physics, Principles, and Clinical Applications. RadioGraphics. 2022. doi:10.1148/rg.210174 [doi]

2. Ghelani SJ, Colan SD, Azcue N, Keenan EM, Harrild DM, Powell AJ, et al. Impact of Ventricular Morphology on Fiber Stress and Strain in Fontan Patients. Circ Cardiovasc Imaging. 2018 July. doi:10.1161/CIRCIMAGING.117.006738 [doi]

3. Meyer SL, St CN, Powell AJ, Geva T, Rathod RH. Integrated Clinical and Magnetic Resonance Imaging Assessments Late After Fontan Operation. J Am Coll Cardiol. 2021 May. doi:10.1016/j.jacc.2021.03.312 [doi]

4. Fontan. Force Study Fontan Outcomes Registry Using Cmr Examinations [Internet]. 2023. Available from: https://www.forceregistry.org

5. Morales MA, van den Boomen M, Nguyen C, Kalpathy-Cramer J, Rosen BR, Stultz CM, et al. DeepStrain: A Deep Learning Workflow for the Automated Characterization of Cardiac Mechanics. Front Cardiovasc Med. doi:10.3389/fcvm.2021.730316 [doi]

6. Yao T, Clair NS, Miller GF, Dorfman AL, Fogel MA, Ghelani S, et al. A Deep Learning Pipeline for Assessing Ventricular Volumes from a Cardiac MRI Registry of Patients with Single Ventricle Physiology. Radiol Artif Intell. 2024. doi:10.1148/ryai.230132 [doi]

Cite this abstract

http://echo.ismrm.org/p/ISMRM2026/607-01-010