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Abstract #1650

Numerical optimization of 5D cardiac and respiratory motion-resolved CMR imaging for the assessment of left ventricular function

Jérôme Yerly1,2, Christopher W Roy1, Bastien Milani1, Davide Piccini1,3, Aurélien Bustin1,4,5, Mariana B.L. Falcão1, Ruud B. van Heeswijk1, and Matthias Stuber1,2,4
1Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland, 2CIBM Center for Biomedical Imaging, Lausanne, Switzerland, 3Advanced Clinical Imaging Technology, Siemens Healthcare, Lausanne, Switzerland, 4Electrophysiology and Heart Modeling Institute, IHU LIRYC, Bordeaux, France, 5Cardiovascular Imaging, Hôpital Cardiologique du Haut-Lévêque, CHU de Bordeaux, Bordeaux, France


The free-running framework (FRF) was recently proposed to address the limitations of current techniques to assess left ventricular (LV) ejection fraction (LVEF). However, the accuracy of FRF to assess LVEF has yet to be quantitatively examined. This work rigorously quantifies and optimizes the effect of the regularization weights on LVEF and several image quality metrics using a numerical phantom with well-controlled boundary conditions, and validates the results in in-vivo 5D FRF data. The results demonstrated that the combination of regularization weights that are optimal in terms of image quality do not correspond to the optimal weights for LVEF assessment.

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