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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