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

Maria Evelina Fantacci, Chiara Sottocornola, Alessandra Retico, Guja Astrea, Roberta Battini, Michela Tosetti

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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.

Original languageEnglish
Title of host publication2015 IEEE International Symposium on Medical Measurements and Applications, MeMeA 2015 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages74-78
Number of pages5
ISBN (Print)9781479964765
DOIs
Publication statusPublished - Jun 30 2015
Event2015 IEEE International Symposium on Medical Measurements and Applications, MeMeA 2015 - Torino, Italy
Duration: May 7 2015May 9 2015

Other

Other2015 IEEE International Symposium on Medical Measurements and Applications, MeMeA 2015
CountryItaly
CityTorino
Period5/7/155/9/15

Keywords

  • Muscle MRI (Magnetic Resonance Imaging (MRI)
  • Muscle segmentation
  • Neuromusclular disorders

ASJC Scopus subject areas

  • Biomedical Engineering
  • Computer Science Applications

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