title: Simultaneous muscle water T2 and fat fraction mapping using transverse relaxometry with stimulated echo compensation.
abstract: Skeletal muscle inflammation/necrosis and fat infiltration are strong indicators of disease activity and progression in many neuromuscular disorders. They can be assessed by muscle T2 relaxometry and water-fat separation techniques, respectively. In the present work, we exploited differences between water and fat T1 and T2 relaxivities by applying a bi-component extended phase graph (EPG) fitting approach to simultaneously quantify the muscle water T2 and fat fraction from standard multi-slice multi-echo (MSME) acquisitions in the presence of stimulated echoes. Experimental decay curves were adjusted to the theoretical model using either an iterative non-negative least-squares (NNLS) procedure or a pattern recognition approach. Twenty-two patients (age, 49 ± 18 years) were selected to cover a large range of muscle fat infiltration. Four cases of chronic or subchronic juvenile dermatomyositis (age, 8 ± 3 years) were investigated before and 3 months following steroid treatment. For control, five healthy volunteers (age, 25 ± 2 years) were recruited. All subjects underwent the MSME sequence and EPG fitting procedure. The EPG fitting algorithm allowed a precise estimation of water T2 and fat fraction in diseased muscle, even in the presence of large B1(+) inhomogeneities. In the whole cohort of patients, there was no overall correlation between water T2 values obtained with the proposed method and the fat fraction estimated inside muscle tissues (R(2) = 0.02). In the patients with dermatomyositis, there was a significant decrease in water T2 (-4.09 ± 3.7 ms) consequent to steroid treatment. The pattern recognition approach resulted in a 20-fold decrease in processing time relative to the iterative NNLS procedure. The fat fraction derived from the EPG fitting approach correlated well with the fat fraction derived from a standard three-point Dixon method (≈1.5% bias). The bi-component EPG fitting analysis is a precise tool to monitor muscle tissue disease activity and is able to handle bias introduced by fat infiltration and B1(+) inhomogeneities.
authors.affiliation: Institute of Myology, NMR Laboratory, Paris, France.|CEA, DSV, I2BM, MIRCen, NMR Laboratory, Paris, France.
authors.forename: Benjamin
authors.initials: B
authors.lastname: Marty
authors.affiliation: Consultants for Research in Imaging and Spectroscopy, Tournai, Belgium.
authors.forename: Pierre-Yves
authors.initials: PY
authors.lastname: Baudin
authors.affiliation: Institute of Myology, NMR Laboratory, Paris, France.|CEA, DSV, I2BM, MIRCen, NMR Laboratory, Paris, France.
authors.forename: Harmen
authors.initials: H
authors.lastname: Reyngoudt
authors.affiliation: Institute of Myology, NMR Laboratory, Paris, France.|CEA, DSV, I2BM, MIRCen, NMR Laboratory, Paris, France.
authors.forename: Noura
authors.initials: N
authors.lastname: Azzabou
authors.affiliation: Institute of Myology, NMR Laboratory, Paris, France.|CEA, DSV, I2BM, MIRCen, NMR Laboratory, Paris, France.
authors.forename: Ericky C A
authors.initials: EC
authors.lastname: Araujo
authors.affiliation: Institute of Myology, NMR Laboratory, Paris, France.|CEA, DSV, I2BM, MIRCen, NMR Laboratory, Paris, France.
authors.forename: Pierre G
authors.initials: PG
authors.lastname: Carlier
authors.affiliation: Université de Strasbourg, CNRS, ICube, FMTS, Strasbourg, France.
authors.forename: Paulo L
authors.initials: PL
authors.lastname: de Sousa
mesh_terms: D000273:Adipose Tissue / Q000378:metabolism*; D000328:Adult; D000465:Algorithms; D002648:Child; D005260:Female; D006801:Humans; D007249:Inflammation / Q000473:pathology; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D008875:Middle Aged; D018482:Muscle, Skeletal / Q000378:metabolism*; D013848:Thigh; D014867:Water / Q000378:metabolism*
chemical_list: D014867:Water
keywords: MSME sequence; extended phase graph; fat fraction; fat infiltration; skeletal muscle; water T2