الفهرس 
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Abstract
O
ver sixty years ago John Walton and Frederick Nattrass defined LGMD as a separate entity from the X-linked dystrophinopathies. Over the last few years, new and interesting studies have been published on LGMD. New LGMD genes have been discovered and the clinical and genetic heterogeneity in this group of muscular dystrophies has been further enlarged by the description of new forms of LGMD.
Despite this clinical and technological progress, the diagnosis of LGMD subtypes remains challenging due to clinical phenotypes as well as genetic defect variability besides, the low specificity of investigating tools and complex approaches of molecular genetics (Quijano-Roy et al., 2012). Neuromuscular imaging can be a helpful tool in LGMD subtypes diagnosis as muscle imaging value is increasingly established in the diagnosis of MDs (Weber et al., 2018).
It was found that the value of neuromuscular imaging in LGMD starts with the identification of pattern and degree of muscle involvement, which can limit differential diagnoses and aid clinical diagnosis, (Ortolan et al., 2015) followed by monitoring treatment and disease progression (Fischer et al., 2016).
Over the last two decades, ultrasound has developed into a useful technology for the evaluation of diseases of nerve and muscle. The use of musculoskeletal ultrasound continues to grow and there are several factors that impact MRI. The development of less expensive portable ultrasound machines has opened the market to non-radiologists, and applications for musculoskeletal ultrasound have broadened. selective substitution of musculoskeletal ultrasound for MRI can result in significant cost saving to the health care system.
Muscle ultrasound is a useful tool in the diagnosis of neuromuscular disorders. Several prospective studies have reported high sensitivities and specificities in the detection of neuromuscular disorders. Although not investigated in large series of patients, different neuromuscular disorders tend to show specific changes on muscle ultrasound, which can be helpful in the differential diagnosis.
This study aimed to measure the sensitivity and the specificity of muscle ultrasound in the assessment of suspected LGMD patients to be able to use it for diagnosis and follow-up of LGMD patients.
Study type: This study was a cross-sectional study.
Patients: Sixty patients with suspected LGMD from the neuromuscular unit, myology clinic, Ain Shams University hospitals, Cairo, Egypt, and a serial of healthy subjects were included in the study.
Inclusion Criteria: Age: any age above two years was included to avoid the inclusion of many congenital cases. Sex: both males and females were included.
Exclusion Criteria: Acute or subacute onset of symptoms, sensory manifestations, cranial nerves affection, or cognitive impairment. Clinical evidence of inflammatory myopathy or any manifestations of other neurodegenerative disorders.
Methods
This study was conducted in accordance with the Declaration of Cairo, Egypt, and reviewed and approved by The Ethical Committee of the Faculty of Medicine, Ain Shams University (approval number FWA 000017585). The date of 1st. approval was on 24/1/2017. All patients enrolled (or their guardians if younger than 18 years) completed the informed consent form.
All patients are subjected to a detailed history that includes family history of consanguinity, similar conditions, or other medical conditions, family pedigree, developmental history, history of other medical disorders, age of onset of weakness, duration of weakness. Muscle biopsy with a battery of histochemical tests, immunohistochemistry using both fluorescent and automated methods against a panel of antibodies was done. Muscle biopsy was used as the gold standard to measure the sensitivity and specificity of MUS in the diagnosis of suspected LGMD patients.
Muscle Ultrasound
MUS was performed using General Electric ultrasound machine, model GE Logiq P7 and General Electric 7.5 MHZ linear array ultrasound probe origin in the U.S.A. The probe was used in a transverse plane, perpendicular to the longitudinal axis of the examined muscle placed gently over the skin using a generous amount of water-soluble transmission gel to avoid pressure-induced alterations of the muscle tissue. Machine settings for image acquisition were saved as presets and held constants for all images and without adjusting the focal point, gain, or time-gain compensation settings. Gain and setting parameters were adjusted so that healthy muscle appeared nearly black. This setting was conserved in the ultrasound system as a fixed investigation program and not changed during the patients’ investigations, apart from the adjustment of the depth setting. To ensure objectivity, the ultrasound scan was done “blind” without knowledge of clinical presentation or results of any other investigations. The following muscles were inspected: (a) UL muscles: deltoid, biceps brachii, brachialis, triceps brachii, forearm flexors, and forearm extensors; (b) LL muscles: rectus femoris, vasti, biceps femoris, semitendinosus, and semimembranosus, tibialis anterior, medial & lateral head of gastrocnemius, and soleus.
All ultrasound images were obtained and scored by a single examiner and muscle echo intensity was visually graded semiquantitative according to a four-point scale, Heckmatt’s scale (Heckmatt et al., 1982), according to the intensity of echo reflected from the muscle. Muscle selectivity was determined and described if present. The sensitivity and specificity of muscle ultrasound were calculated in comparison to muscle biopsy as a gold standard diagnostic tool, in the assessment of LGMD patients.
Muscle MRI
Muscle MRI was done for a subgroup of 42 patients using 1.5 tesla MRI machine in radiology department, Ain Shams university. The results were compared to muscle ultrasound results.
Statistical analysis
Data entry, processing and statistical analysis was carried out using MedCalc ver. 18.11.3 (MedCalc, Ostend, Belgium). Tests of significance (McNemar’s tests, Spearman’s correlation Kappa statistics and ROC-Curve analysis were used. Data were presented and suitable analysis was done according to the type of data (parametric and non-parametric) obtained for each variable. P-values less than 0.05 (5%) was considered statistically significant.
Results
Statistical analysis revealed that by using ROC-curve analysis, total upper-limbs Heckmatt’s US score at a cutoff point (>1) predicted patients with dystrophy, with good (88%) accuracy, sensitivity= 100% and specificity= 75% (p < 0.01), total lower-limbs Heckmatt’s US score at a cutoff point (>1) predicted patients with dystrophy, with excellent (91%) accuracy, sensitivity= 100% and specificity= 75% (p < 0.01), and total Heckmatt’s US score at a cutoff point (>2) predicted patients with dystrophy, with good (89%) accuracy, sensitivity=100% and specificity=75% (p < 0.01). Thus, MUS can be considered a valid tool in the diagnosis of suspected LGMD patients.
We encourage more widespread use of MUS in the evaluation of suspected LGMD patients especially in clinical settings as it is a less expensive, non-invasive, real-time dynamic, easy to perform, and readily accessible bedside tool that can be used as a part of the clinical examination even when a relatively rapid qualitative assessment is used without additional quantification of size and echogenicity of the muscle.