Comparison of manual and semi-automated algorithm for measuring architectural features during different isometric knee extension intensities: a reliability and comparative study in novice raters.

IF 1.3 Q3 REHABILITATION
Frontiers in rehabilitation sciences Pub Date : 2025-04-03 eCollection Date: 2025-01-01 DOI:10.3389/fresc.2025.1539804
Micheal J Luera, JoCarol E Shields, Emma Bozarth, Rob J MacLennan, Natalie P Walker, Jesus A Hernandez-Sarabia, Carlos A Estrada, Jason M DeFreitas, Scott K Crawford
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Abstract

Introduction: Ultrasound is a cost-effective and reliable method to determine skeletal muscle architecture. However, manual analysis of fascicle length (FL) and pennation angle (PA) can be arduous and subjective among raters, particularly among novice raters. Alternatives to manual processing have been proposed that expedite the evaluation of muscle architecture and afford more consistency. While using algorithms has provided dependable results of muscle architecture, it has often focused on variables of passive range of motion and submaximal contractions. To fully understand the impact of muscle architecture using semi-automated analysis, an investigation of a broad range of contraction intensities is needed. The purpose of this study was to develop and determine the intra-rater and inter-rater reliability of a custom, semi-automated algorithm to extract measures of muscle thickness, pennation angle, and fascicle length, and second to compare the semi-automated measures to measures extracted manually from the same novice raters while accounting for differences between contraction intensities.

Methods: Fifteen resistance-trained individuals (male: n = 6, female: n = 9) completed this study. Images were collected during four contraction intensities relative to maximal voluntary isometric contractions (MVIC) (at rest, 30%, 70%, and MVIC) and analyzed by three novice raters to compare the semi-automated algorithm and manual measurement in the vastus lateralis.

Results: Intra-rater reliability for manual measures was poor for FL (ICCs: 0-0.30), poor to good for PA (ICCs: 0.46-0.77), and moderate to good for muscle thickness (MT) (ICCs: 0.55-0.84). For the semi-automated algorithm, the intra-rater reliability was good to excellent for FL (range: 0.90-0.99), PA (range: 0.88-0.99), and MT (range: 0.996-0.999) across all contraction intensities.

Discussion: The findings of this study suggest that the reliability of manual measurement is lower when novice raters perform image analyses compared to the semi-automated method. Therefore, careful consideration and training should be provided when considering manual assessment of muscle architecture values, and standardized identification methods and features in algorithm development may be a better method for reproducibility.

在不同等距膝关节伸展强度下测量建筑特征的人工和半自动算法的比较:对新手评分者的可靠性和比较研究。
超声是一种经济、可靠的测定骨骼肌结构的方法。然而,手工分析束长(FL)和笔角(PA)可能是艰巨和主观的评分者,特别是新手评分。已经提出了人工处理的替代方案,以加快肌肉结构的评估并提供更多的一致性。虽然使用算法提供了可靠的肌肉结构结果,但它通常侧重于被动运动范围和次极大收缩的变量。为了充分了解使用半自动分析对肌肉结构的影响,需要对大范围的收缩强度进行调查。本研究的目的是开发和确定一种自定义的、半自动的算法来提取肌肉厚度、笔角和肌束长度的内部和内部可靠性,其次是比较半自动测量和从相同的新手评估者手动提取的测量,同时考虑收缩强度之间的差异。方法:15名阻力训练者(男6名,女9名)完成本研究。收集与最大自主等距收缩(MVIC)相关的四种收缩强度(静止、30%、70%和MVIC)的图像,并由三位新手评分者分析,比较半自动化算法和手动测量股外侧肌的效果。结果:人工测量的组内信度对于FL较差(ICCs: 0-0.30),对于PA较差到良好(ICCs: 0.46-0.77),对于肌肉厚度(MT)中等到良好(ICCs: 0.55-0.84)。对于半自动算法,在所有收缩强度下,FL(范围:0.90-0.99)、PA(范围:0.88-0.99)和MT(范围:0.996-0.999)的内部可靠性都很好。讨论:本研究的结果表明,与半自动方法相比,当新手评分者进行图像分析时,人工测量的可靠性较低。因此,在考虑人工评估肌肉结构值时,应该进行仔细的考虑和训练,在算法开发中标准化的识别方法和特征可能是更好的再现性方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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