NDLI: A non-invasive method for a quantitative evaluation of muscle involvement in MRI of Neuromuscular Diseases

Content Provider	IEEE Xplore Digital Library
Author	Fantacci, M.E. Sottocornola, C. Retico, A. Astrea, G. Battini, R. Tosetti, M.
Copyright Year	2015
Description	Author affiliation: Stella Maris Sci. Inst., Pisa, Italy (Astrea, G.; Battini, R.) \|\| Dept. of Phys., Univ. of Pisa, Pisa, Italy (Fantacci, M.E.; Sottocornola, C.) \|\| IMAGO7, IRCCS Stella Maris Sci. Inst., Pisa, Italy (Tosetti, M.) \|\| Sez. di Pisa, INFN, Pisa, Italy (Retico, A.)
Abstract	This work reports a study of Neuromuscular Diseases (NMD) by Magnetic Resonance Imaging as reliable and non invasive instrument for NMD diagnosis and follow up. The evaluation of the images is now only visual, while standardization procedures and quantitative methods could be very useful instruments to optimize the diagnostic performances. We propose a new method to evaluate the fat infiltration in tissues developed and retrospectively applied to images of the human leg. Through a muscle segmentation algorithm on structural T1-weighted magnetic resonance images (MRIs), the estimated non-muscle percentage (eNMP) in the segmented muscle area has been evaluated in healthy subjects as a reference value. A semi-automated procedure allows extending the algorithm to MRIs of NMD patients. A strong correlation has been demonstrated between this index and the disease severity. The final aim is to obtain a quantitative evaluation of fat infiltration percentage and to relate it to the grade of muscle impairment in subjects affected by Neuromuscular Diseases.
Starting Page	74
Ending Page	78
File Size	922947
Page Count	5
File Format	PDF
ISBN	9781479964772
DOI	10.1109/MeMeA.2015.7145175
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-05-07
Publisher Place	Italy
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Muscles Magnetic resonance imaging Diseases Image segmentation Thigh Indexes Standards Muscle segmentation Neuromusclular disorders Muscle MRI (Magnetic Resonance Imaging (MRI)
Content Type	Text
Resource Type	Article

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