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首页> 外文期刊>Critical Reviews in Biomedical Engineering >Quantitative Ultrasound Using Texture Analysis of Myofascial Pain Syndrome in the Trapezius
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Quantitative Ultrasound Using Texture Analysis of Myofascial Pain Syndrome in the Trapezius

机译：定量超声使用纹理分析Trapezius中的肌筋膜疼痛综合征

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Objective-The objective of this study is to assess the discriminative ability of textural analyses to assist in the differentiation of the myofascial trigger point (MTrP) region from normal regions of skeletal muscle. Also, to measure the ability to reliably differentiate between three clinically relevant groups: healthy asymptomatic, latent MTrPs, and active MTrP, Methods-18 and 19 patients were identified with having active and latent MTrPs in the trapezius muscle, respectively. We included 24 healthy volunteers. Images were obtained by research personnel, who were blinded with respect to the clinical status of the study participant. Histograms provided first-order parameters associated with image grayscale. Haralick, Galloway, and histogram-related features were used in texture analysis. Blob analysis was conducted on the regions of interest (ROIs). Principal component analysis (PCA) was performed followed by multivariate analysis of variance (MANOVA) to determine the statistical significance of the features. Results—92 texture features were analyzed for factorability using Bartlett's test of sphericity, which was significant. The Kaiser-Meyer-Olkin measure of sampling adequacy was 0.94. PCA demonstrated rotated eigenvalues of the first eight components (each comprised of multiple texture features) explained 94.92% of the cumulative variance in the ultrasound image characteristics. The 24 features identified by PCA were included in the MANOVA as dependent variables, and the presence of a latent or active MTrP or healthy muscle were independent variables. Conclusion-Texture analysis techniques can discriminate between the three clinically relevant groups.
机译：目的 - 本研究的目的是评估纹理分析的判别能力，以协助从骨骼肌的正常区域分化肌蚕触发点（MTRP）区域的分化。此外，为了测量三个临床相关组之间可靠区分的能力：健康无症状，潜伏的MTRP和活性MTRP，方法-18和19例患者分别在梯形肌中具有活性和潜在的MTRP。我们包括24个健康的志愿者。通过研究人员获得的图像是由研究参与者的临床状况而蒙蔽的。直方图提供了与图像灰度相关联的一阶参数。 Haralick，Galloway和直方图相关的特征用于纹理分析。 BLOB分析在感兴趣的区域（ROI）进行。进行主成分分析（PCA），然后进行多变量分析方差（MANOVA）以确定特征的统计学意义。结果-92分析了使用Bartlett对球体的试验来分解的纹理特征，这是显着的。 Kaiser-Meyer-Olkin测量采样充足率为0.94。 PCA展示了前八种组分的旋转特征值（各个纹理特征组成）解释了超声图像特性中累积方差的94.92％。 PCA识别的24个特征被包括在Manova中作为依赖变量，并且存在潜在或活性MTRP或健康肌肉的存在是独立的变量。结论纹理分析技术可以区分三个临床相关群体。

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