J Clin Densitom, 2015 · DOI: 10.1016/j.jocd.2014.04.124 · Published: January 1, 2015
This study addresses the challenge of accurately measuring muscle area and density in calf muscle scans when fat infiltrates the muscle, particularly affecting the precision of standard edge detection methods. The research compares a standard threshold-based edge detection method with a manual segmentation method guided by a watershed algorithm, evaluating their precision in different populations including younger adults, older adults, and those with spinal cord injury (SCI). The watershed algorithm method showed better precision and resulted in higher muscle density values, especially among adults with SCI, suggesting it's a more reliable method for populations with increased muscle fat infiltration.
Using the watershed algorithm enhances the precision of muscle density and area measurements in pQCT images, which is particularly beneficial in studies involving individuals with conditions leading to fatty infiltration of muscle.
The increased precision offered by the watershed method can improve the ability to detect changes in muscle composition over time in clinical trials, particularly those evaluating interventions targeting muscle health.
More reliable muscle density measurements can contribute to better diagnostic capabilities for conditions associated with muscle atrophy and fatty infiltration, such as diabetes and spinal cord injury.