Asadi Borhan, Pujol-Fuentes Clara, Carcasona-Otal Alberto, Calvo Sandra, Herrero Pablo, Lapuente-Hernández Diego
Department of Physiatry and Nursing, Faculty of Health Sciences, University of Zaragoza, 50009 Zaragoza, Spain.
iHealthy Research Group, Instituto de Investigación Sanitaria (IIS) Aragon, University of Zaragoza, 50009 Zaragoza, Spain.
J Clin Med. 2024 Dec 20;13(24):7800. doi: 10.3390/jcm13247800.
Strokes remain a major global health concern, contributing significantly to disability and healthcare costs. Currently, there are no established indicators to accurately assess the degree of muscle tissue impairment in stroke-affected individuals. However, ultrasound imaging with an echotexture analysis shows potential as a quantitative tool to assess muscle tissue quality. This study aimed to identify specific echotexture features in the gastrocnemius medialis that effectively characterize muscle impairment in post-stroke individuals. : An observational study was conducted with 22 post-stroke individuals. A total of 21 echotexture features were extracted and analyzed, including first-order metrics, a grey-level co-occurrence matrix, and a grey-level run length matrix. The modified Heckmatt scale was also applied to correlate with the most informative echotexture features. : Among the features analyzed, echovariation (EV), echointensity, and kurtosis emerged as the most informative indicators of muscle tissue quality. The EV was highlighted as the primary feature due to its strong and significant correlation with the modified Heckmatt scale (r = -0.81, < 0.001) and its clinical and technical robustness. Lower EV values were associated with poorer muscle tissue quality, while higher values indicated better quality. : The EV may be used as a quantitative indicator for characterizing the gastrocnemius medialis muscle tissue quality in post-stroke individuals, offering a more nuanced assessment than traditional qualitative scales. Future studies should investigate the correlation between the EV and other clinical outcomes and explore its potential to monitor the treatment efficacy, enhancing its applicability in clinical practice.
中风仍然是全球主要的健康问题，对残疾和医疗成本有重大影响。目前，尚无既定指标可准确评估中风患者肌肉组织损伤的程度。然而，具有回声纹理分析功能的超声成像显示出作为评估肌肉组织质量的定量工具的潜力。本研究旨在确定内侧腓肠肌中能够有效表征中风后个体肌肉损伤的特定回声纹理特征。：对22名中风后个体进行了一项观察性研究。总共提取并分析了21个回声纹理特征，包括一阶指标、灰度共生矩阵和灰度游程长度矩阵。还应用了改良的赫克马特量表来与最具信息量的回声纹理特征相关联。：在分析的特征中，回声变化（EV）、回声强度和峰度成为肌肉组织质量最具信息量的指标。由于EV与改良的赫克马特量表具有强烈且显著的相关性（r = -0.81，<0.001）及其临床和技术稳健性，因此被突出为主要特征。较低的EV值与较差的肌肉组织质量相关，而较高的值表明质量较好。：EV可作为表征中风后个体内侧腓肠肌肌肉组织质量的定量指标，提供比传统定性量表更细致入微的评估。未来的研究应调查EV与其他临床结果之间的相关性，并探索其监测治疗效果的潜力，以提高其在临床实践中的适用性。
