Simple Muscle Architecture Analysis (SMA): an ImageJ macro tool to automate measurements in B-mode ultrasound scans

TL;DR

This paper introduces SMA, an ImageJ macro that automates muscle architecture measurements from ultrasound scans, providing a reliable, efficient alternative to manual analysis for clinical and research applications.

Contribution

The study presents a novel, accessible ImageJ macro tool that automates muscle architecture analysis, reducing manual effort and increasing reliability in ultrasound image measurements.

Findings

SMA provides measurements comparable to manual analysis without bias.

The macro is effective across various ultrasound settings and muscle types.

Automates the entire analysis process, saving time and reducing errors.

Abstract

In vivo measurements of muscle architecture (i.e. the spatial arrangement of muscle fascicles) are routinely included in research and clinical settings to monitor muscle structure, function and plasticity. However, in most cases such measurements are performed manually, and more reliable and time-efficient automated methods are either lacking completely, or are inaccessible to those without expertise in image analysis. In this work, we propose an ImageJ script to automate the entire analysis process of muscle architecture in ultrasound images: Simple Muscle Architecture Analysis (SMA). Images are filtered in the spatial and frequency domains with built-in commands and external plugins to highlight aponeuroses and fascicles. Fascicle dominant orientation is then computed in regions of interest using the OrientationJ plugin. Bland-Altman plots of analyses performed manually or with SMA indicates that the automated analysis does not induce any systematic bias and that both methods agree equally through the range of measurements. Our test results illustrate the suitability of SMA to analyse images from superficial muscles acquired with a broad range of ultrasound settings.