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Abstract #0001

Non-invasive pressure estimations by virtual fields – cardiovascular pressure drops from 4D flow MRI

David Marlevi 1,2, Bram Ruijsink3, Maximilian Balmus3, Desmond Dillon-Murphy3, Daniel Fovargue3, Kuberan Pushparajah3,4, Pablo Lamata3, C. Alberto Figueroa3,5, Massimiliano Colarieti-Tosti1,6, Matilda Larsson1, Reza Razavi3,4, and David A. Nordsletten3

1Department of Medical Engineering, KTH Royal Institute of Technology, Stockholm, Sweden, 2Clinical Sciences, Karolinska Institutet, Stockholm, Sweden, 3Division of Imaging Sciences and Biomedical Engineering, King's College London, London, United Kingdom, 4Department of Congenital Heart Disease, Evelina Children’s Hospital, London, United Kingdom, 5Departments of Surgery and Biomedical Engineering, University of Michigan, Ann Arbor, MI, United States, 6Department of Clinical Science, Intervention and Technology (CLINTEC), Karolinska Institutet, Stockholm, Sweden

4D-flow-MRI enables the non-invasive assessment of cardiovascular pressure drops; however, estimation accuracy depends on vascular topology and acquisition noise. Here, we present a method that minimizes the impact of these by using virtual fields to isolate and probe hemodynamic pressure drops. We show that, in-silico, the method accurately assesses pressure drops over multiple segments of a patient-specific co-arcted aorta (average error below 22%), independent of anatomical bifurcations. Additionally, the method compares successfully against catheter measurements, using 4D-flow-MRI in-vivo (average error at peak systole below 15%). With this, the method represents a refined tool for hemodynamic analysis of cardiovascular flow.

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