Quantitative muscle analysis in facioscapulohumeral muscular dystrophy using whole-body fat-referenced MRI: Protocol development, multicenter feasibility, and repeatability.
facioscapulohumeral muscular dystrophy
magnetic resonance imaging
muscle disease
quantitative muscle analysis
volumetric magnetic resonance imaging
Journal
Muscle & nerve
ISSN: 1097-4598
Titre abrégé: Muscle Nerve
Pays: United States
ID NLM: 7803146
Informations de publication
Date de publication:
08 2022
08 2022
Historique:
revised:
09
05
2022
received:
23
09
2021
accepted:
13
05
2022
pubmed:
20
5
2022
medline:
23
7
2022
entrez:
19
5
2022
Statut:
ppublish
Résumé
Functional performance tests are the gold standard to assess disease progression and treatment effects in neuromuscular disorders. These tests can be confounded by motivation, pain, fatigue, and learning effects, increasing variability and decreasing sensitivity to disease progression, limiting efficacy assessment in clinical trials with small sample sizes. We aimed to develop and validate a quantitative and objective method to measure skeletal muscle volume and fat content based on whole-body fat-referenced magnetic resonance imaging (MRI) for use in multisite clinical trials. Subjects aged 18 to 65 years, genetically confirmed facioscapulohumeral muscular dystrophy 1 (FSHD1), clinical severity 2 to 4 (Ricci's scale, range 0-5), were enrolled at six sites and imaged twice 4-12 weeks apart with T1-weighted two-point Dixon MRI covering the torso and upper and lower extremities. Thirty-six muscles were volumetrically segmented using semi-automatic multi-atlas-based segmentation. Muscle fat fraction (MFF), muscle fat infiltration (MFI), and lean muscle volume (LMV) were quantified for each muscle using fat-referenced quantification. Seventeen patients (mean age ± SD, 49.4 years ±13.02; 12 men) were enrolled. Within-patient SD ranged from 1.00% to 3.51% for MFF and 0.40% to 1.48% for MFI in individual muscles. For LMV, coefficients of variation ranged from 2.7% to 11.7%. For the composite score average of all muscles, observed SDs were 0.70% and 0.32% for MFF and MFI, respectively; composite LMV coefficient of variation was 2.0%. We developed and validated a method for measuring skeletal muscle volume and fat content for use in multisite clinical trials of neuromuscular disorders.
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
183-192Informations de copyright
© 2022 Wiley Periodicals LLC.
Références
Leung DG. Magnetic resonance imaging patterns of muscle involvement in genetic muscle diseases: a systematic review. J Neurol. 2017;264(7):1320-1333.
Dahlqvist JR, Widholm P, Leinhard OD, Vissing J. MRI in neuromuscular diseases: an emerging diagnostic tool and biomarker for prognosis and efficacy. Ann Neurol. 2020;88(4):669-681.
Hollingsworth KG, de Sousa PL, Straub V, Carlier PG. Towards harmonization of protocols for MRI outcome measures in skeletal muscle studies: consensus recommendations from two TREAT-NMD NMR workshops, may 2, 2010, Stockholm, Sweden, 1-2 October 2009, Paris, France. Neuromuscul Disord. 2012;22(Suppl 2):S54-S67.
Leung DG. Advancements in magnetic resonance imaging-based biomarkers for muscular dystrophy. Muscle Nerve. 2019;60(4):347-360.
Warman Chardon J, Díaz-Manera J, Tasca G, et al. MYO-MRI diagnostic protocols in genetic myopathies. Neuromuscul Disord. 2019;29(11):827-841.
Andersen G, Dahlqvist JR, Vissing CR, Heje K, Thomsen C, Vissing J. MRI as outcome measure in facioscapulohumeral muscular dystrophy: 1-year follow-up of 45 patients. J Neurol. 2017;264(3):438-447.
Morrow JM, Sinclair CDJ, Fischmann A, et al. MRI biomarker assessment of neuromuscular disease progression: a prospective observational cohort study. Lancet Neurol. 2016;15(1):65-77.
Nuñez-Peralta C, Alonso-Pérez J, Llauger J, et al. Follow-up of late-onset Pompe disease patients with muscle magnetic resonance imaging reveals increase in fat replacement in skeletal muscles. J Cachexia Sarcopenia Muscle. 2020;11(4):1032-1046.
Arrigoni F, De Luca A, Velardo D, et al. Multiparametric quantitative MRI assessment of thigh muscles in limb-girdle muscular dystrophy 2A and 2B. Muscle Nerve. 2018;58(4):550-558.
Ropars J, Gravot F, Ben Salem D, Rousseau F, Brochard S, Pons C. Muscle MRI: A biomarker of disease severity in Duchenne muscular dystrophy? A systematic review. Neurology. 2020;94(3):117-133.
Willcocks RJ, Rooney WD, Triplett WT, et al. Multicenter prospective longitudinal study of magnetic resonance biomarkers in a large duchenne muscular dystrophy cohort. Ann Neurol. 2016;79(4):535-547.
Tasca G, Monforte M, Ottaviani P, et al. Magnetic resonance imaging in a large cohort of facioscapulohumeral muscular dystrophy patients: pattern refinement and implications for clinical trials. Ann Neurol. 2016;79(5):854-864.
Diaz-Manera J, Fernandez-Torron RJLL, James MK, et al. Muscle MRI in patients with dysferlinopathy: pattern recognition and implications for clinical trials. J Neurol Neurosurg Psychiatry. 2018;89(10):1071-1081.
Dahlqvist JR, Andersen G, Khawajazada T, Vissing C, Thomsen C, Vissing J. Relationship between muscle inflammation and fat replacement assessed by MRI in facioscapulohumeral muscular dystrophy. J Neurol. 2019;266(5):1127-1135.
Dahlqvist JR, Poulsen NS, Ostergaard ST, et al. Evaluation of inflammatory lesions over 2 years in facioscapulohumeral muscular dystrophy. Neurology. 2020;95(9):e1211-e1221.
Yiu EM, Kornberg AJ. Duchenne muscular dystrophy. J Paediatr Child Health. 2015;51(8):759-764.
Hooijmans MT, Niks EH, Burakiewicz J, et al. Non-uniform muscle fat replacement along the proximodistal axis in Duchenne muscular dystrophy. Neuromuscul Disord. 2017;27(5):458-464.
Vidt ME, Santago AC 2nd, Tuohy CJ, et al. Assessments of fatty infiltration and muscle atrophy from a single magnetic resonance image slice are not predictive of 3-dimensional measurements. Art Ther. 2016;32(1):128-139.
Karlsson A, Rosander J, Romu T, et al. Automatic and quantitative assessment of regional muscle volume by multi-atlas segmentation using whole-body water-fat MRI. J Magn Reson Imaging. 2015;41(6):1558-1569.
West J, Romu T, Thorell S, et al. Precision of MRI-based body composition measurements of postmenopausal women. PLoS One. 2018;13(2):e0192495.
Borga M, Ahlgren A, Romu T, Widholm P, Dahlqvist Leinhard O, West J. Reproducibility and repeatability of MRI-based body composition analysis. Magn Reson Med. 2020;84(6):3146-3156.
Ricci E, Galluzzi G, Deidda G, et al. Progress in the molecular diagnosis of facioscapulohumeral muscular dystrophy and correlation between the number of KpnI repeats at the 4q35 locus and clinical phenotype. Ann Neurol. 1999;45(6):751-757.
Karlsson A, Peolsson A, Romu T, et al. The effect on precision and T1 bias comparing two flip angles when estimating muscle fat infiltration using fat-referenced chemical shift-encoded imaging. NMR Biomed. 2021;34:e4581.
Romu T, Borga M, Dahlqvist O. MANA-Multi Scale Adaptive Normalized Averaging. IEEE International Symposium on Biomedical Imaging: From Nano to Macro; 2011:361-364.
Dahlqvist Leinhard O, Johansson A, Rydell J, Smedby O, Nystrom F, Lundberg P, Borga M. Quantitative Abdominal Fat Estimation Using MRI2009. 1-4 p.
Aisen AM, Chenevert TL. MR spectroscopy: clinical perspective. Radiology. 1989;173(3):593-599.
Bartlett JW, Frost C. Reliability, repeatability and reproducibility: analysis of measurement errors in continuous variables. Ultrasound Obstet Gynecol. 2008;31(4):466-475.
Reeder SB, Cruite I, Hamilton G, Sirlin CB. Quantitative assessment of liver fat with magnetic resonance imaging and spectroscopy. J Magn Reson Imaging. 2011;34(4):729-749.
Morrow JM, Sinclair CD, Fischmann A, et al. Reproducibility, and age, body-weight and gender dependency of candidate skeletal muscle MRI outcome measures in healthy volunteers. Eur Radiol. 2014;24(7):1610-1620.
Forbes SC, Walter GA, Rooney WD, et al. Skeletal muscles of ambulant children with Duchenne muscular dystrophy: validation of multicenter study of evaluation with MR imaging and MR spectroscopy. Radiology. 2013;269(1):198-207.
Monforte M, Laschena F, Ottaviani P, et al. Tracking muscle wasting and disease activity in facioscapulohumeral muscular dystrophy by qualitative longitudinal imaging. J Cachexia Sarcopenia Muscle. 2019;10(6):1258-1265.
Thomas MS, Newman D, Leinhard OD, et al. Test-retest reliability of automated whole body and compartmental muscle volume measurements on a wide bore 3T MR system. Eur Radiol. 2014;24(9):2279-2291.