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Abstract #1570

Multi-parametric characterization of highly fat infiltrated muscular dystrophy patients: results of a multi-variate analysis.

Alberto De Luca1,2, Alessandra Bertoldo1, Denis Peruzzo2, Maria Grazia D'Angelo3, Martijn Froeling4, and Filippo Arrigoni2

1Department of Information Engineering, University of Padova, Padova, Italy, 2Neuroimaging Lab, Scientific Institute IRCCS Eugenio Medea, Bosisio Parini (LC), Italy, 3Functional Rehabilitation Unit, Neuromuscular Disorders, Scientific Institute IRCCS Eugenio Medea, Bosisio Parini (LC), Italy, 4Radiology Department, University Medical Center Utrecht, Utrecht, Netherlands

Limb Girdle Muscular Dystrophies (LGMD) are a family of myopathies characterized by progressive degeneration and fat infiltration of muscular tissue. In the context of a study that includes Dixon, T2 quantification and diffusion MRI (dMRI), we investigated a multi-variate analysis to remove the effect of fat from concurrent measures and correlate them with clinical indexes of strength. In our dataset of highly infiltrated patients, T2 and dMRI metrics were strongly biased by fat. Our results show that it is possible to mitigate the bias by multi-variate modeling of the FF effect while retaining disease specific effects.

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