Quantitative Scoring of Muscle Involvement in MRI of Neuromuscular Diseases
Maria Evelina Fantacci, Guja Astrea, Roberta Battini, Alessandra Retico, Chiara Sottocornola, Michela Tosetti
2015
Abstract
An automated method to evaluate the fat infiltration in tissues has been developed and applied to images of the human leg. 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 Neuro-Muscular Diseases (NMD). 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 the eNMP index and the disease severity.
References
- Baudin, P.Y. et al., 2012. Prior Knowledge, Random Walks and Human Skeletal Muscle Segmentation. Lecture Notes in Computer Science 7510:569-576.
- Cerello, P. et al., 2010. 3-D object segmentation using ant colonies. Pattern Recognition 43(4):1476-1490.
- Dixon, W.T., 1984. Simple proton spectroscopic imaging. Radiology 153:189-194.
- Gaeta, M. et al., 2011. Muscle Fat Fraction in Neuromuscular Disorders: Dual-Echo Dual-FlipAngle Spoiled Gradient-Recalled MR Imaging Technique for Quantification-A Feasibility Study. Radiology 259(2):487-494.
- Gaeta, M. et al., 2012. Muscle fat-fraction and mapping in Duchenne muscular dystrophy: evaluation of disease distribution and correlation with clinical assessments. Skeletal Radiol 41:955-961.
- Makrogiannis, S. et al., 2012. Automated quantification of muscle and fat in the thigh from water-, fat-, and nonsuppressed MR images. J Magn Reson Imaging 35(5):1152-61.
- Mercuri, E. et al., 2002. Clinical and imaging findings in six cases of congenital muscular dystrophy with rigid spine syndrome linked to chromosome 1p (RSMD1). Neuromuscul Disord 12:631-638.
- Willis, T.A. et al., 2013. Quantitative Muscle MRI as an Assessment Tool for Monitoring Disease Progression in LGMD2I: A Multicentre Longitudinal Study. PLOS ONE 8/8: e70993.
- Wokke B.H. et al., 2013. Comparison of dixon and T1- weighted MR methods to assess the degree of fat infiltration in duchenne muscular dystrophy patients. J Magn Reson Imaging 38(3):619-624.
Paper Citation
in Harvard Style
Fantacci M., Astrea G., Battini R., Retico A., Sottocornola C. and Tosetti M. (2015). Quantitative Scoring of Muscle Involvement in MRI of Neuromuscular Diseases . In Proceedings of the International Conference on Bioimaging - Volume 1: BIOIMAGING, (BIOSTEC 2015) ISBN 978-989-758-072-7, pages 100-105. DOI: 10.5220/0005255801000105
in Bibtex Style
@conference{bioimaging15,
author={Maria Evelina Fantacci and Guja Astrea and Roberta Battini and Alessandra Retico and Chiara Sottocornola and Michela Tosetti},
title={Quantitative Scoring of Muscle Involvement in MRI of Neuromuscular Diseases},
booktitle={Proceedings of the International Conference on Bioimaging - Volume 1: BIOIMAGING, (BIOSTEC 2015)},
year={2015},
pages={100-105},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005255801000105},
isbn={978-989-758-072-7},
}
in EndNote Style
TY - CONF
JO - Proceedings of the International Conference on Bioimaging - Volume 1: BIOIMAGING, (BIOSTEC 2015)
TI - Quantitative Scoring of Muscle Involvement in MRI of Neuromuscular Diseases
SN - 978-989-758-072-7
AU - Fantacci M.
AU - Astrea G.
AU - Battini R.
AU - Retico A.
AU - Sottocornola C.
AU - Tosetti M.
PY - 2015
SP - 100
EP - 105
DO - 10.5220/0005255801000105