Quantitative muscle ultrasound in FSHD type 1 patients.

Anno
2018
Proponente -
Struttura
Sottosettore ERC del proponente del progetto
Componenti gruppo di ricerca
Abstract

Muscular imaging represents an important diagnostic tool for the identification and quantification of muscular alterations in patients affected by muscular disorders. Although MRI represents the gold standard to investigate the muscular structure, ultrasound (US) is an emerging tool to study muscle diseases. Muscular dystrophies are characterized by a chronic muscle atrophy and weakness due to a progressive fibro-fatty replacement of muscle tissue, resulting in thinning and increase in echo intensity at US study. The aim of this work is to evaluate the applicability of quantitative muscular ultrasonography (QMUS) in the study of muscle involvement in patients affected by facioscapulohumeral muscular dystrophy type 1 (FSHD1). In our study we will recruit a total of 15 patients with genetically determined FSHD type 1 and 15 controls matched by sex, age and BMI. In each subject we will bilaterally analyze, with a linear transducer (7-14 MHz) five different muscles: pectoralis major, deltoid, rectus femoris, tibialis anterior and semimembranosus muscles. In each image QMUS will be performed calculating the mean muscle echo intensity by computer assisted gray-scale analysis, keeping gain, depth, number of focuses and transducer pressure constant. We will then compare median echo intensities to evaluate whether a difference between healthy and affected muscles exists and to see if there is a correlation between echo intensity and clinical severity. Finally, by comparing MRI and US data we want to evaluate how complementary these techniques are in detecting neuromuscular alterations. This pilot study is a pioneer project to apply US tool in the study of FSHD1 and could open new prospective to forthcoming studies for the application of ultrasonography as a useful biomarker of muscle injury in FSHD1 and other muscular dystrophies.

ERC
SH3_9
Keywords:
NEUROIMAGING E NEUROSCIENZA COMPUTAZIONALE, TECNICHE DI IMAGING, MALATTIE RARE

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