Baseline fat fraction is a strong predictor of disease progression in Becker muscular dystrophy

Autor: Nienke M. Van de Velde, Jurriaan De Groot, Erik Niks, Melissa Hooijmans, Thom Veeger, Kevin Keene, Andrew Webb, Hermien Kan
Přispěvatelé: Radiology and Nuclear Medicine, AMS - Ageing & Vitality, AMS - Sports
Jazyk: angličtina
Rok vydání: 2022
Předmět:
Zdroj: NMR in Biomedicine, 35(7). WILEY
NMR in biomedicine, 35(7):e4691. John Wiley and Sons Ltd
ISSN: 0952-3480
Popis: 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 (Delta FF). 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 spinecho MRI and 7-T P-31 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 T-2 (stdT(2)) and the phosphodiester (PDE) over ATP ratio at baseline had additional value to FFbase for predicting Delta FF. The association between FFbase and Delta FF was described by the derivative of a sigmoid function and resulted in a peak Delta FF around 0.45 FFbase (fourth-order polynomial term: t = 3.7, p < .001). StdT(2) and PDE/ATP were not significantly associated with Delta FF if FFbase was included in the model. The relationship between FFbase and Delta 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.
Databáze: OpenAIRE