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Abstract #4289

Applying diffusion signal representation further than DTI improves cardiac dMRI insights

Justino Rafael Rodríguez-Galván1, Susana Merino-Caviedes1, David Filgueiras-Rama2, Javier Sánchez-González3, Antonio Tristán-Vega1, and Carlos Alberola-López1
1Laboratorio de Procesado de Imagen (LPI) Universidad de Valladolid, Valladolid, Spain, 2Centro Nacional de Investigaciones Cardiovasculares, Madrid, Spain, 3Philips Ibérica, Madrid, Spain

Synopsis

Keywords: Myocardium, Diffusion/other diffusion imaging techniquesDiffusion MRI in the brain has undergone tremendous advances in the last two decades while cardiac and general diffusion in the body show a lower speed. As for modelling, either isotropic or diffusion tensor imaging (DTI) are, by far, the methods used outside the brain. In this abstract we intend to quantify the better modeling capabilities of higher order (HO) methods than DTI, i.e., than Gaussian distributions. We show, by means of ex-vivo diffusion in pig hearts, that non-Gaussianity is observable and that diffusion weighted images (DWI) generated out of a HO model show more closeness to reality than DTI.

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