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Abstract #2103

Cardiac Strains from DENSE MRI: Evaluation of SNR Requirements and Strain Error using a Computational Phantom

Ilya Alexey Verzhbinsky1, Luigi Emanuele Perotti2, Kévin Moulin1, Tyler E Cork1, Michael Loecher1, and Daniel B Ennis1

1Radiological Sciences Laboratory, Stanford University, Stanford, CA, United States, 2Radiological Sciences, University of California - Los Angeles, Los Angeles, CA, United States

Displacement Encoding with Stimulated Echoes (DENSE) MRI encodes high-resolution cardiac tissue displacements into the phase of the complex MR signal. However, due to the inherent difficulty of obtaining ground truth strain measurements in the beating heart, it remains unclear how image SNR impacts the bias and range of error for computed cardiac strains. In this work, we present a computational deforming heart-like phantom to evaluate cardiac strains computed using a widely available, open-source DENSE Image Analysis Tool. We show that a strain error range within 0.05 and near-zero median error bias can be achieved with SNR>20.

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