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 Pushparajah^3,4, Pablo Lamata³, C. Alberto Figueroa^3,5, Massimiliano Colarieti-Tosti^1,6, Matilda Larsson¹, Reza Razavi^3,4, 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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