Your browser doesn't support javascript.
loading
Baseline fat fraction is a strong predictor of disease progression in Becker muscular dystrophy.
Veeger, Thom T J; van de Velde, Nienke M; Keene, Kevin R; Niks, Erik H; Hooijmans, Melissa T; Webb, Andrew G; de Groot, Jurriaan H; Kan, Hermien E.
Afiliación
  • Veeger TTJ; C. J. Gorter Center for High Field MRI, Department of Radiology, Leiden University Medical Center (LUMC), Leiden, The Netherlands.
  • van de Velde NM; Department of Neurology, Leiden University Medical Center (LUMC), Leiden, The Netherlands.
  • Keene KR; Duchenne Center Netherlands, The Netherlands.
  • Niks EH; Department of Neurology, Leiden University Medical Center (LUMC), Leiden, The Netherlands.
  • Hooijmans MT; Department of Neurology, Leiden University Medical Center (LUMC), Leiden, The Netherlands.
  • Webb AG; Duchenne Center Netherlands, The Netherlands.
  • de Groot JH; Department of Radiology & Nuclear Medicine, Amsterdam University Medical Centers, Amsterdam, The Netherlands.
  • Kan HE; C. J. Gorter Center for High Field MRI, Department of Radiology, Leiden University Medical Center (LUMC), Leiden, The Netherlands.
NMR Biomed ; 35(7): e4691, 2022 07.
Article en En | MEDLINE | ID: mdl-35032073
In Becker muscular dystrophy (BMD), muscle weakness progresses relatively slowly, with a highly variable rate among patients. This complicates clinical trials, as clinically relevant changes are difficult to capture within the typical duration of a trial. Therefore, predictors for disease progression are needed. We assessed if temporal increase of fat fraction (FF) in BMD follows a sigmoidal trajectory and whether fat fraction at baseline (FFbase) could therefore predict FF increase after 2 years (ΔFF). Thereafter, for two different MR-based parameters, we tested the additional predictive value to FFbase. We used 3-T Dixon data from the upper and lower leg, and multiecho spin-echo MRI and 7-T 31 P MRS datasets from the lower leg, acquired in 24 BMD patients (age: 41.4 [SD 12.8] years). We assessed the pattern of increase in FF using mixed-effects modelling. Subsequently, we tested if indicators of muscle damage like standard deviation in water T2 (stdT2 ) and the phosphodiester (PDE) over ATP ratio at baseline had additional value to FFbase for predicting ∆FF. The association between FFbase and ΔFF was described by the derivative of a sigmoid function and resulted in a peak ΔFF around 0.45 FFbase (fourth-order polynomial term: t = 3.7, p < .001). StdT2 and PDE/ATP were not significantly associated with ∆FF if FFbase was included in the model. The relationship between FFbase and ∆FF suggests a sigmoidal trajectory of the increase in FF over time in BMD, similar to that described for Duchenne muscular dystrophy. Our results can be used to identify muscles (or patients) that are in the fast progressing stage of the disease, thereby facilitating the conduct of clinical trials.
Asunto(s)
Palabras clave

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Distrofia Muscular de Duchenne Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Adult / Humans Idioma: En Revista: NMR Biomed Asunto de la revista: DIAGNOSTICO POR IMAGEM / MEDICINA NUCLEAR Año: 2022 Tipo del documento: Article País de afiliación: Países Bajos

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Distrofia Muscular de Duchenne Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Adult / Humans Idioma: En Revista: NMR Biomed Asunto de la revista: DIAGNOSTICO POR IMAGEM / MEDICINA NUCLEAR Año: 2022 Tipo del documento: Article País de afiliación: Países Bajos