Abstract #1650

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

Jérôme Yerly^1,2, Christopher W Roy¹, Bastien Milani¹, Davide Piccini^1,3, Aurélien Bustin^1,4,5, Mariana B.L. Falcão¹, Ruud B. van Heeswijk¹, and Matthias Stuber^1,2,4

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

Synopsis

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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