Karlien Mul1, Sanne C C Vincenten2, Nicol C Voermans2, Richard J L F Lemmers2, Patrick J van der Vliet2, Silvère M van der Maarel2, George W Padberg2, Corinne G C Horlings2, Baziel G M van Engelen2. 1. From the Department of Neurology (K.M., S.C.C.V., N.C.V., G.W.P., C.G.C.H., B.G.M.v.E.), Radboud University Medical Center, Nijmegen; and Department of Human Genetics (R.J.L.F.L., P.J.v.d.V., S.M.v.d.M.), Leiden University Medical Center, the Netherlands. karlien.mul@radboudumc.nl. 2. From the Department of Neurology (K.M., S.C.C.V., N.C.V., G.W.P., C.G.C.H., B.G.M.v.E.), Radboud University Medical Center, Nijmegen; and Department of Human Genetics (R.J.L.F.L., P.J.v.d.V., S.M.v.d.M.), Leiden University Medical Center, the Netherlands.
Abstract
OBJECTIVE: To add quantitative muscle MRI to the clinical trial toolbox for facioscapulohumeral muscular dystrophy (FSHD) by correlating it to clinical outcome measures in a large cohort of genetically and clinically well-characterized patients with FSHD comprising the entire clinical spectrum. METHODS: Quantitative MRI scans of leg muscles of 140 patients with FSHD1 and FSHD2 were assessed for fatty infiltration and TIRM hyperintensities and were correlated to multiple clinical outcome measures. RESULTS: The mean fat fraction of the total leg musculature correlated highly with the motor function measure, FSHD clinical score, Ricci score, and 6-minute walking test (correlation coefficients -0.845, 0.835, 0.791, -0.701, respectively). Fat fraction per muscle group correlated well with corresponding muscle strength (correlation coefficients up to -0.82). The hamstring muscles, adductor muscles, rectus femoris, and gastrocnemius medialis were affected most frequently, also in early stage disease and in patients without leg muscle weakness. Muscle involvement was asymmetric in 20% of all muscle pairs and fatty infiltration within muscles showed a decrease from distal to proximal of 3.9%. TIRM hyperintense areas, suggesting inflammation, were found in 3.5% of all muscles, with and without fatty infiltration. CONCLUSIONS: We show a strong correlation between quantitative muscle MRI and clinical outcome measures. Muscle MRI is able to detect muscle pathology before clinical involvement of the leg muscles. This indicates that quantitative leg muscle MRI is a promising biomarker that captures disease severity and motor functioning and can thus be included in the FSHD trial toolbox.
OBJECTIVE: To add quantitative muscle MRI to the clinical trial toolbox for facioscapulohumeral muscular dystrophy (FSHD) by correlating it to clinical outcome measures in a large cohort of genetically and clinically well-characterized patients with FSHD comprising the entire clinical spectrum. METHODS: Quantitative MRI scans of leg muscles of 140 patients with FSHD1 and FSHD2 were assessed for fatty infiltration and TIRM hyperintensities and were correlated to multiple clinical outcome measures. RESULTS: The mean fat fraction of the total leg musculature correlated highly with the motor function measure, FSHD clinical score, Ricci score, and 6-minute walking test (correlation coefficients -0.845, 0.835, 0.791, -0.701, respectively). Fat fraction per muscle group correlated well with corresponding muscle strength (correlation coefficients up to -0.82). The hamstring muscles, adductor muscles, rectus femoris, and gastrocnemius medialis were affected most frequently, also in early stage disease and in patients without leg muscle weakness. Muscle involvement was asymmetric in 20% of all muscle pairs and fatty infiltration within muscles showed a decrease from distal to proximal of 3.9%. TIRM hyperintense areas, suggesting inflammation, were found in 3.5% of all muscles, with and without fatty infiltration. CONCLUSIONS: We show a strong correlation between quantitative muscle MRI and clinical outcome measures. Muscle MRI is able to detect muscle pathology before clinical involvement of the leg muscles. This indicates that quantitative leg muscle MRI is a promising biomarker that captures disease severity and motor functioning and can thus be included in the FSHD trial toolbox.
Authors: Barbara H Janssen; Nicoline B M Voet; Christine I Nabuurs; Hermien E Kan; Jacky W J de Rooy; Alexander C Geurts; George W Padberg; Baziel G M van Engelen; Arend Heerschap Journal: PLoS One Date: 2014-01-14 Impact factor: 3.240
Authors: Rianne J M Goselink; Karlien Mul; Caroline R van Kernebeek; Richard J L F Lemmers; Silvère M van der Maarel; Tim H A Schreuder; Corrie E Erasmus; George W Padberg; Jeffrey M Statland; Nicol C Voermans; Baziel G M van Engelen Journal: Neurology Date: 2018-12-19 Impact factor: 9.910
Authors: Karlien Mul; Chad Heatwole; Katy Eichinger; Nuran Dilek; William B Martens; Baziel G M Van Engelen; Rabi Tawil; Jeffrey M Statland Journal: Muscle Nerve Date: 2018-04-17 Impact factor: 3.217
Authors: Amy E Campbell; Andrea E Belleville; Rebecca Resnick; Sean C Shadle; Stephen J Tapscott Journal: Hum Mol Genet Date: 2018-08-01 Impact factor: 6.150
Authors: Saskia Lassche; Nicol C Voermans; Robbert van der Pijl; Marloes van den Berg; Arend Heerschap; Hieronymus van Hees; Benno Kusters; Silvère M van der Maarel; Coen A C Ottenheijm; Baziel G M van Engelen Journal: Neurology Date: 2020-01-21 Impact factor: 9.910