Local Texture Anisotropy as an Estimate of Muscle Quality in Ultrasound Imaging

Abstract

This study introduces local pattern texture anisotropy as a novel parameter to differentiate healthy and disordered muscle and to gauge the severity of muscle impairments based on B-mode ultrasound images. Preliminary human results are also presented. A local pattern texture anisotropy index (TAI) was computed in one region of interest in the short head of the biceps brachii. The effects of gain settings and box sizes required for TAI computation were investigated. Between-day reliability was studied in patients with sporadic inclusion body myositis (n = 26). The ability of the TAI to discriminate dystrophic from healthy muscle was evaluated in patients with Duchenne muscular dystrophy and healthy controls (n = 16). TAI values were compared with a gray-scale index (GSI). TAI values were less influenced by gain settings than were GSI values. TAI had lower between-day variability (typical error = 2.3%) compared with GSI (typical error = 2.3% vs. 8.3%, respectively). Patients with Duchenne muscular dystrophy had lower TAIs than controls (0.76 ± 0.06 vs. 0.87 ± 0.03, respectively, p <0.05). At 40% gain, TAI values correlated with percentage predicted elbow flexor strength in inclusion body myositis (R = 0.63, p <0.001). The TAI may be a promising addition to other texture-based approaches for quantitative muscle ultrasound imaging.

Muscle ultrasound: Present state and future opportunities

“…Another recently developed technique made use of the degree of uniformity in muscle fiber orientation in the longitudinal direction, assessing texture anisotropy 12 . Patients with DMD had lower texture anisotropy than healthy controls, and that the quantified texture anisotropy was much less affected by gain settings of the ultrasound machine than quantified grayscale levels.…”

“…A progressive increase in muscle stiffness was shown in boys with Duchenne muscular dystrophy, making elastography a potential biomarker for research on the treatment response in muscular dystrophy 11 . Extracting higher order features from the muscle ultrasound image, such as local tissue anisotropy, can also help identify abnormal muscle tissue architecture in a way that might be less dependent on the ultrasound machine settings 12 …”

Quantitative Ultrasound Texture Analysis to Assess the Spastic Muscles in Stroke Patients

“…Because the shear wave propagation speed is affected by the fiber orientation. Previous studies have attempted to use asymmetry of SWV with fiber orientation to determine anisotropy in muscle fibers, suggesting that disorientated fiber architecture may be a useful feature for distinguishing active myofascial trigger points [28] and Duchenne muscular dystrophy from normal muscle [7]. Although SWV is feasible for measuring spasticity, most SWV algorithms are designed assuming that soft tissues are elastic, isotropic, and locally homogeneous.…”

“…In contrast to EI, textural descriptors are less affected by ultrasound scanner settings and may have an advantage of providing more complete description of tissue composition [7]. Several texture features, such as the Haralick and Galloway features, are useful for the diagnosis, characterization, and detection of neuromuscular diseases [8][9][10][11].…”

Muscle Shear Wave Elastography in Inclusion Body Myositis: Feasibility, Reliability and Relationships with Muscle Impairments

“…with Ii the intensity of the pixel i in a ROI of n × m. A lower GSI value corresponds to greater muscle echo intensity (Dubois et al 2018). As mentioned above, gain and all other ultrasound settings were kept constant for all subjects (Caresio et al 2015).…”