Evaluation of the Anatomical Cross-Sectional Area of Psoas Major Muscle Using an Ultrasound Imaging System Combined With an Inertial Measurement Unit: Improved Reliability in the US Using IMU-Based Positioning Techniques

利用超声成像系统结合惯性测量单元评估腰大肌的解剖横截面积:基于IMU定位技术的美国可靠性提高

阅读:1

Abstract

Introduction: Recently, ultrasound (US) imaging has been used to estimate the cross-sectional area of skeletal muscle, but the reliability is uncertain. To improve the reliability of the US, we investigated skeletal muscle thickness measurement using an inertial measurement unit (IMU) to determine the direction of US beam incidence based on posture angle information. In addition, we examined whether the anatomical cross-sectional area (ACSA) of muscle can be estimated from the muscle thickness measured using the US with the IMU. Methods: In Experiment 1, two examiners measured the right psoas major at the fourth lumbar vertebra level in 10 university students using the US with and without an IMU. The intraclass correlation coefficient (ICC) was used to examine intra- and inter-rater variability. In Experiment 2, the two examiners measured the muscle thickness of the right psoas major in 31 male subjects using the US with an IMU. In addition, the ACSA of this muscle was measured using MRI. Pearson's correlation coefficient was used to examine the relationship between muscle thickness and ACSA, and a single regression analysis was performed. Results: Both intrarater reliability ICC (1, 2) and inter-rater reliability ICC (2, 2) were higher when US was used with IMU compared to without IMU (Experiment 1). A significant positive correlation (r = 0.84, p < 0.01) was observed between muscle thickness and ACSA (Experiment 2). The regression equation was significant at R (2) = 0.71 (p < 0.01). Conclusion: Using an IMU during US measurement of the psoas major improves intra- and interexaminer reliability and can be used to estimate the ACSA of the muscle.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。