Background and Objectives:Limb-Girdle Muscular Dystrophy autosomal recessive type 12 (LGMDR12) is a rare hereditary muscular dystrophy for which outcome measures are currently lacking. We evaluated quantitative MRI and clinical outcome measures to track disease progression, in order to determine which tests could be useful in future clinical trials to evaluate potential therapies.Methods:We prospectively measured the following outcome measures in all participants at baseline and after 1 and 2 years: six-minute walk distance (6MWD), 10-meter walk test (10MWT), Medical Research Council (MRC) sum scores, Biodex® isometric dynamometry, serum creatine kinase (CK) and 6-point Dixon MRI of the thighs.Results:We included 24 genetically confirmed, adult LGMDR12 patients and 24 age- and sex-matched healthy controls. Patients with intermediate stage thigh muscle fat replacement at baseline (proton density fat fraction (PDFF) 20-70%) already showed a significant increase in PDFF in 8/14 evaluated thigh muscles after one year. The standardized response mean (SRM) demonstrated a high responsiveness to change in PDFF for 6 individual muscles over 2 years in this group. However, in patients with early (<20%) or end stage (>70%) muscle fat replacement, PDFF did not increase significantly over two years of follow-up.Biodex® isometric dynamometry showed a significant decrease of muscle strength in all patients in the right and left hamstrings (-6.2Nm, p<0.002 and -4.6 Nm, p<0.009, respectively) and right quadriceps muscles (-9 Nm, p=0.044) after 1 year of follow-up, whereas the 6MWD, 10MWT, and MRC sum scores were not able to detect a significant decrease in muscle function/strength even after two years. There was a moderately strong correlation between total thigh PDFF and clinical outcome measures at baseline.Discussion:Thigh muscle PDFF imaging is a sensitive outcome measure to track progressive muscle fat replacement in selected LGMDR12 patients even after one year of follow-up and correlates with clinical outcome measures. Biodex® isometric dynamometry can reliably capture loss of muscle strength over the course of one year in LGMDR12 patients and should be included as an outcome measure in future clinical trials as well.

Muscular dystrophies (MD) are a class of rare genetic diseases resulting in progressive muscle weakness affecting specific muscle groups, depending on the type of disease. Disease progression is characterized by the gradual replacement of muscle tissue by fat, which can be assessed with fat-sensitive magnetic resonance imaging (MRI) and objectively evaluated by quantifying the fat fraction percentage (FF%) per muscle. Volumetric quantification of fat replacement over the full 3D extent of each muscle is more precise and potentially more sensitive than 2D quantification in few selected slices only, but it requires an accurate 3D segmentation of each muscle individually, which is time consuming when this has to be performed manually for a large number of muscles. A reliable, largely automated approach for 3D muscle segmentation is thus needed to facilitate the adoption of fat fraction quantification as a measure of MD disease progression in clinical routine practice, but this is challenging due to the variable appearance of the images and the ambiguity in the discrimination of the contours of adjacent muscles, especially when the normal image contrast is affected and diminished by the fat replacement. To deal with these challenges, we used deep learning to train AI-models to segment the muscles in the proximal leg from knee to hip in Dixon MRI images of healthy subjects as well as patients with MD. We demonstrate state-of-the-art segmentation results of all 18 muscles individually in terms of overlap (Dice score, DSC) with the manual ground truth delineation for images of cases with low fat infiltration (mean overall FF%: 11.3%; mean DSC: 95.3% per image, 84.4–97.3% per muscle) as well as with medium and high fat infiltration (mean overall FF%: 44.3%; mean DSC: 89.0% per image, 70.8–94.5% per muscle). In addition, we demonstrate that the segmentation performance is largely invariant to the field of view of the MRI scan, is generalizable to patients with different types of MD and that the manual delineation effort to create the training set can be drastically reduced without significant loss of segmentation quality by delineating only a subset of the slices.

Background Despite the widespread use of proton density fat fraction (PDFF) measurements with magnetic resonance imaging (MRI) to track disease progression in muscle disorders, it is still unclear how these findings relate to histopathological changes in muscle biopsies of patients with limb‐girdle muscular dystrophy autosomal recessive type 12 (LGMDR12). Furthermore, although it is known that LGMDR12 leads to a selective muscle involvement distinct from other muscular dystrophies, the spatial distribution of fat replacement within these muscles is unknown. Methods We included 27 adult patients with LGMDR12 and 27 age‐matched and sex‐matched healthy controls and acquired 6‐point Dixon images of the thighs and T1 and short tau inversion recovery (STIR) MR images of the whole body. In 16 patients and 15 controls, we performed three muscle biopsies, one in the semimembranosus, vastus lateralis, and rectus femoris muscles, which are severely, intermediately, and mildly affected in LGMDR12, respectively. We correlated the PDFF to the fat percentage measured on biopsies of the corresponding muscles, as well as to the Rochester histopathology grading scale. Results In patients, we demonstrated a strong correlation of PDFF on MRI and muscle biopsy fat percentage for the semimembranosus (r = 0.85, P < 0.001) and vastus lateralis (r = 0.68, P = 0.005). We found similar results for the correlation between PDFF and the Rochester histopathology grading scale. Out of the five patients with inflammatory changes on muscle biopsy, three showed STIR hyperintensities in the corresponding muscle on MRI. By modelling the PDFF on MRI for 18 thigh muscles from origin to insertion, we observed a significantly inhomogeneous proximo‐distal distribution of fat replacement in all thigh muscles of patients with LGMDR12 (P < 0.001), and different patterns of fat replacement within each of the muscles. Conclusions We showed a strong correlation of fat fraction on MRI and fat percentage on muscle biopsy for diseased muscles and validated the use of Dixon fat fraction imaging as an outcome measure in LGMDR12. The inhomogeneous fat replacement within thigh muscles on imaging underlines the risk of analysing only samples of muscles instead of the entire muscles, which has important implications for clinical trials.