Muscle Quantitative MR Imaging and Clustering Analysis in Patients with Facioscapulohumeral Muscular Dystrophy Type 1.

Facioscapulohumeral muscular dystrophy type 1 (FSHD1) is the third most common inherited muscular dystrophy. Considering the highly variable clinical expression and the slow disease progression, sensitive outcome measures would be of interest.Using muscle MRI, we assessed muscular fatty infiltration in the lower limbs of 35 FSHD1 patients and 22 healthy volunteers by two methods: a quantitative imaging (qMRI) combined with a dedicated automated segmentation method performed on both thighs and a standard T1-weighted four-point visual scale (visual score) on thighs and legs. Each patient had a clinical evaluation including manual muscular testing, Clinical Severity Score (CSS) scale and MFM scale. The intramuscular fat fraction measured using qMRI in the thighs was significantly higher in patients (21.9 ± 20.4%) than in volunteers (3.6 ± 2.8%) (p<0.001). In patients, the intramuscular fat fraction was significantly correlated with the muscular fatty infiltration in the thighs evaluated by the mean visual score (p<0.001). However, we observed a ceiling effect of the visual score for patients with a severe fatty infiltration clearly indicating the larger accuracy of the qMRI approach. Mean intramuscular fat fraction was significantly correlated with CSS scale (p ≤ 0.01) and was inversely correlated with MMT score, MFM subscore D1 (p ≤ 0.01) further illustrating the sensitivity of the qMRI approach. Overall, a clustering analysis disclosed three different imaging patterns of muscle involvement for the thighs and the legs which could be related to different stages of the disease and put forth muscles which could be of interest for a subtle investigation of the disease progression and/or the efficiency of any therapeutic strategy.The qMRI provides a sensitive measurement of fat fraction which should also be of high interest to assess disease progression and any therapeutic strategy in FSHD1 patients

Long-term follow-up of MRI changes in thigh muscles of patients with Facioscapulohumeral dystrophy: A quantitative study

International audienceFacioscapulohumeral muscular dystrophy (FSHD) is one of the most common hereditary muscular disorders. Currently FSHD has no known effective treatment and detailed data on the natural history are lacking. Determination of the efficacy of a given therapeutic approach might be difficult in FSHD given the slow and highly variable disease progression. Magnetic resonance imaging (MRI) has been widely used to qualitatively and quantitatively evaluate in vivo the muscle alterations in various neuromuscular disorders. The main aim of the present study was to investigate longitudinally the time-dependent changes occurring in thigh muscles of FSHD patients using quantitative MRI and to assess the potential relationships with the clinical findings. Thirty-five FSHD1 patients (17 females) were enrolled. Clinical assessment tools including manual muscle testing using medical research council score (MRC), and motor function measure (MFM) were recorded each year for a period ranging from 1 to 2 years. For the MRI measurements, we used a new quantitative index, i.e., the mean pixel intensity (MPI) calculated from the pixel-intensity distribution in T1 weighted images. The corresponding MPI scores were calculated for each thigh, for each compartment and for both thighs totally (MPItotal). The total mean pixel intensity (MPItotal) refers to the sum of each pixel signal intensity divided by the corresponding number of pixels. An increased MPItotal indicates both a raised fat infiltration together with a reduced muscle volume thereby illustrating disease progression. Clinical scores did not change significantly over time whereas MPItotal increased significantly from an initial averaged value of 39.6 to 41.1 with a corresponding rate of 0.62/year. While clinical scores and MPItotal measured at the start of the study were significantly related, no correlation was found between the rate of MPItotal and MRC sum score changes, MFMtotal and MFM subscores. The relative rate of MPItotal change was 2.3% (0.5-4.3)/year and was significantly higher than the corresponding rates measured for MRCS 0% (0-1.7) /year and MFMtotal 0% (0-2.0) /year (p = 0.000). On the basis of these results, we suggested that muscle MRI and more particularly the MPItotal index could be used as a reliable biomarker and outcome measure of disease progression. In slowly progressive myopathies such as FSHD, the MPItotal index might reveal subclinical changes, which could not be evidenced using clinical scales over a short period of time

T1 weighted MRI images of thighs and legs from 3 FSHD1 patients illustrating three different patterns of muscular involvement.

<p>(a): a normal appearing imaging pattern, (b): a selective muscle involvement pattern; (c): global fatty infiltration pattern with selective muscle sparing</p

Fat fraction (%) in FSHD1 patients and healthy volunteers.

<p>***: p<0.001.</p

Mean visual scores for the fatty infiltration in each muscle of the lower limb.

<p>a: Thigh muscles for the whole group of patients, b: thigh muscles for T1 sub group, c: thigh muscles for T2 sub group, d: thigh muscles for T3 sub group, e: leg muscles for the whole group of patients, f: leg muscles for L1 sub group, g: leg muscles for L2 sub group, h: the leg muscles for L3 sub group. Legs: GL = Gastrocnemius lateralis, GM = Gastrocnemius medialis, P = Peroneus, S = Soleus, TA = Tibialis anterior, TP = Tibialis posterior. Thighs: ADD = Adductors; BF = Biceps Femoris; G = Gracilis; R = Rectus Femoris, S = Sartorius, SMM = Semimembranosus, SMT = Semitendinosus, VI = Vastus intermediaris, VL = Vastus lateralis, VM = Vastus medialis.</p

Examples of MR images.

<p>Examples of a successful automated segmentation in a control subject (a) and two patients (b and c). Examples of MR images with manual correction of the segmentation process (d).</p

Correlation of intramuscular fat fraction with mean visual score of muscular fatty infiltration.

<p>A: Correlation between the mean visual score of the thighs and the intramuscular fat fraction. B: Correlation between the mean visual score of the thighs and the Log of the intramuscular fat fraction.</p

Steps of the automated segmentation algorithm.

<p>Steps of the automated segmentation algorithm.</p

Pipeline of the four-step image processing.

<p>Pipeline of the four-step image processing.</p