Detection of exercise load‐associated differences in hip muscles by texture analysis

Abstract

We examined whether specific physical exercise loading is associated with texture parameters from hip muscles scanned with magnetic resonance imaging (MRI). Ninety-one female athletes representing five distinct exercise-loading groups (high-impact, odd-impact, low-impact, nonimpact and high-magnitude) and 20 nonathletic female controls underwent MRI of the hip. Texture parameters were computed from the MRI images of four hip muscles (gluteus maximus, gluteus medius, iliopsoas and obturator internus). Differences in muscle texture between the athlete groups and the controls were evaluated using Mann-Whitney U-test. Significant (P < 0.05) textural differences were found between the high-impact (triple and high jumpers) and the control group in gluteus medius, iliopsoas and obturator internus muscles. Texture of the gluteus maximus, gluteus medius and obturator internus muscles differed significantly between the odd impact (soccer and squash players) and the control group. Textures of all studied muscles differed significantly between the low impact (endurance runners) and the controls. Only the gluteus medius muscle differed significantly between the nonimpact (swimmers) and the controls. No significant difference in muscle texture was found between the high-magnitude (powerlifters) and the control group. In conclusion, MRI texture analysis provides a quantitative method capable of detecting textural differences in hip muscles that are associated with specific types of long-term exercise loadings.

Advancements in magnetic resonance imaging‐based biomarkers for muscular dystrophy

“…The use of radiomics offers a novel way of overcoming the inherent subjectivity of traditional scoring systems by employing fully automated and systematic methods of quantitatively analyzing imaging data across multiple sequences. These methods may also improve tissue characterization by detecting muscle features that cannot be perceived by visual inspection …”

“…These methods may also improve tissue characterization by detecting muscle features that cannot be perceived by visual inspection. 119,120 Another potential challenge in developing quantitative analysis techniques is the difficulty of establishing reproducibility. Manual muscle segmentation may be subject to variability in how muscles are selected and defined.…”

Application of texture analysis to muscle MRI: 1-What kind of information should be expected from texture analysis?

“…In the same way, Nketiah et al [38] have detected texture differences in MRI of hip muscles associated with different level of long term exercise loading in female athletes (jumpers) and controls.…”

Avaliação não invasiva de modelos murinos para doenças musculares genéticas

“…In a less extensive amount, different mouse models for muscle dystrophies were studied by NMR (Cole et al, 2002;Pacak et al, 2007;Schmidt et al, 2009;Tardif-de Géry et al, 2000;Walter et al, 2005), as the golden retriever muscular dystrophy dog (Claire et al, 2012;Fan et al, 2014;Thibaud et al, 2007Thibaud et al, , 2012Yokota et al, 2009). In addition to the variable NMR methods capable to identify changes in the affected muscles, the use of mathematical tools for image texture analysis is gaining space, since it can identify subtle differences in the pattern of distribution of muscle lesions (Mahmoud-Ghoneim et al, 2006;Nketiah et al, 2014;Pratt et al, 2013;Škoch et al, 2004;Wang et al, 2013). A deeper bibliographic review of genetic muscle disorders and non-invasive muscle evaluation, for both human patients and animal models, is presented in Chapter 1.…”

“…Texture analysis is an emerging approach that includes several techniques to quantify variations in the image intensity or patterns. When applied to muscle MRI, texture analysis has demonstrated to be a potential tool to evaluate subtle differences in the pattern of distribution of muscle lesions (Mahmoud-Ghoneim et al, 2006;Nketiah et al, 2014;Škoch et al, 2004). In the mdx mouse (Pratt et al, 2013) and the GRMD dystrophic dog (Fan et al, 2014), longitudinal studies were able to correlate texture parameters with age and progression of the disease.…”