Abstract #1570

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

Alberto De Luca^1,2, 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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