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Abstract #2824

Tissue separation of multi-shell DW-MRI with a physiologically constrained multi compartment model and spherical deconvolution

Alberto De Luca 1,2 , Marco Castellaro 1 , Stefania Montemezzi 3 , Massimiliano Calabrese 4 , and Alessandra Bertoldo 1

1 Department of Information Engineering, University of Padova, Padova, PD, Italy, 2 Department of Neuroimaging, Scientific Institute, IRCCS "Eugenio Medea", Bosisio Parini, LC, Italy, 3 Radiology Unit, Azienda Ospedaliera di Verona, Verona, Italy, 4 Neurology Section, Department Of Neurological and Movement Sciences, University Hospital of Verona, Verona, Italy

In this work we present a non-linear multi compartmental model based on spherical deconvolution to fit multi-shell diffusion data. The first two parameters of the model provide parametric maps highly correlated to T1 segmentation (up to 85%), while the last parameter leads to a map of diffusivity useful for lesion detection purposes. The residuals are random dispersed around zero and average coefficients of variation between 4 and 24%. Application of the model to a multiple sclerosis subject show that the diffusivity map is sensible to abnormally diffusing voxels, revealing lesions that are confirmed from a FLAIR scan.

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