Combined quantification of fatty infiltration, T1-relaxation times and T2*-relaxation times in normal-appearing skeletal muscle of controls and dystrophic patients
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To evaluate the combination of a fat–water separation method with an automated segmentation algorithm to quantify the intermuscular fatty-infiltrated fraction, the relaxation times, and the microscopic fatty infiltration in the normal-appearing muscle.
Materials and methods
MR acquisitions were performed at 1.5T in seven patients with facio-scapulo-humeral dystrophy and eight controls. Disease severity was assessed using commonly used scales for the upper and lower limbs. The fat–water separation method provided proton density fat fraction (PDFF) and relaxation times maps (T2* and T1). The segmentation algorithm distinguished adipose tissue and normal-appearing muscle from the T2* map and combined active contours, a clustering analysis, and a morphological closing process to calculate the index of fatty infiltration (IFI) in the muscle compartment defined as the relative amount of pixels with the ratio between the number of pixels within IMAT and the total number of pixels (IMAT + normal appearing muscle).
In patients, relaxation times were longer and a larger fatty infiltration has been quantified in the normal-appearing muscle. T2* and PDFF distributions were broader. The relaxation times were correlated to the Vignos scale whereas the microscopic fatty infiltration was linked to the Medwin-Gardner-Walton scale. The IFI was linked to a composite clinical severity scale gathering the whole set of scales.
The MRI indices quantified within the normal-appearing muscle could be considered as potential biomarkers of dystrophies and quantitatively illustrate tissue alterations such as inflammation and fatty infiltration.
KeywordsMagnetic resonance imaging Segmentation Muscle dystrophies
- 5.Akima H, Lott D, Senesac C, Deol J, Germain S, Arpan I, Bendixen R, Lee Sweeney H, Walter G, Vandenborne K (2012) Relationships of thigh muscle contractile and non-contractile tissue with function, strength, and age in boys with Duchenne muscular dystrophy. Neuromuscul Disord 22(1):16–25PubMedCrossRefGoogle Scholar
- 6.Cea G, Bendahan D, Manners D, Hilton-Jones D, Lodi R, Styles P, Taylor DJ (2002) Reduced oxidative phosphorylation and proton efflux suggest reduced capillary blood supply in skeletal muscle of patients with dermatomyositis and polymyositis: a quantitative 31P-magnetic resonance spectroscopy and MRI study. Brain 125(Pt 7):1635–1645PubMedCrossRefGoogle Scholar
- 13.Guiu B, Petit JM, Loffroy R, Ben Salem D, Aho S, Masson D, Robin I, Vergès B, Hillon P, Cercueil JP, Krausé D (2009) Quantification of liver fat content: comparison of triple-echo chemical shift gradient-echo imaging and in vivo proton MR spectroscopy. Radiology 250(1):95–102PubMedCrossRefGoogle Scholar
- 15.Leporq B, Ratiney H, Cavassila S, Pilleul F, Beuf O (2010). Fat content quantification errors using multiple gradient echo imaging: A phantom and simulation study. In: ISMRM-ESMRMB Joint Annual Meeting, Stockholm, p 2581Google Scholar
- 16.Hines CD, Frydrychowicz A, Hamilton G, Tudorascu DL, Vigen KK, Yu H, McKenzie CA, Sirlin CB, Brittain JH, Reeder SB (2011) T1 independent, T2* corrected chemical shift based fat-water separation with multi-peak fat spectral modeling is an accurate and precise measure of hepatic steatosis. J Magn Reson Imaging 33(4):873–881PubMedPubMedCentralCrossRefGoogle Scholar
- 19.Meisamy S, Hines CD, Hamilton G, Sirlin CB, McKenzie CA, Yu H, Brittain JH, Reeder SB (2011) Quantification of hepatic steatosis with T1-independent, T2-corrected MR imaging with spectral modeling of fat: blinded comparison with MR spectroscopy. Radiology 258(3):767–775PubMedPubMedCentralCrossRefGoogle Scholar
- 22.Yokoo T, Bydder M, Hamilton G, Middleton MS, Gamst AC, Wolfson T, Hassanein T, Patton HM, Lavine JE, Schwimmer JB, Sirlin CB (2009) Nonalcoholic fatty liver disease: diagnostic and fat-grading accuracy of low-flip-angle multiecho gradient-recalled-echo MR imaging at 1.5 T. Radiology 251(1):67–76PubMedPubMedCentralCrossRefGoogle Scholar
- 26.Gold GE, Han E, Stainsby J, Wright GA, Brittain J, Beaulieu C (2004) Musculoskeletal MRI at 3.0T: relaxation times and image contrast. Am J Neuroradiol 183:343–350Google Scholar
- 32.Alizai H, Nardo L, Karampinos DC, Joseph GB, Yap SP, Baum T, Krug R, Majumdar S, Link TM (2012) Comparison of clinical semi-quantitative assessment of muscle fat infiltration with quantitative assessment using chemical shift-based water/fat separation in MR studies of the calf of post-menopausal women. Eur Radiol 22(7):1592–1600PubMedPubMedCentralCrossRefGoogle Scholar
- 36.Arpan I, Forbes SC, Lott DJ, Senesac CR, Daniels MJ, Triplett WT et al (2013) T2 mapping provides multiple approaches for the characterization of muscle involvement in neuromuscular diseases: a cross-sectional study of lower leg muscles in 5-15-year-old boys with Duchenne muscular dystrophy. NMR Biomed 26(3):320–328PubMedCrossRefGoogle Scholar