Three-dimensional quantitative muscle ultrasound in a healthy population
SourceMuscle and Nerve, vol. 64, 2, (2021), pp. 199-205
Article / Letter to editor
Display more detailsDisplay less details
Muscle and Nerve
vol. vol. 64
SubjectRadboudumc 15: Urological cancers RIHS: Radboud Institute for Health Sciences; Radboudumc 16: Vascular damage RIHS: Radboud Institute for Health Sciences; Radboudumc 3: Disorders of movement DCMN: Donders Center for Medical Neuroscience
INTRODUCTION/AIMS: Quantitative muscle ultrasound offers biomarkers that aid in the diagnosis, detection, and follow-up of neuromuscular disorders. At present, quantitative muscle ultrasound methods are 2D and are often operator and device dependent. The aim of this study was to combine an existing device independent method with an automated ultrasound machine and perform 3D quantitative muscle ultrasound, providing new normative data of healthy controls. METHODS: In total, 123 healthy volunteers were included. After physical examination, 3D ultrasound scans of the tibialis anterior muscle were acquired using an automated ultrasound scanner. Image postprocessing was performed to obtain calibrated echo intensity values based on a phantom reference. RESULTS: Tibialis anterior muscle volumes of 61.2 ± 24.1 mL and 53.7 ± 22.7 mL were scanned in males and females, respectively. Echo intensity correlated with gender**, age**, fat fraction*, histogram kurtosis**, skewness* and standard deviation** (*P < .05, **P < .01). Outcome measures did not differ significantly for different acquisition presets. The 3D quantitative muscle ultrasound revealed the non-uniformity of echo intensity values over the length of the tibialis anterior muscle. DISCUSSION: Our method extended 2D measurements and confirmed previous findings. Our method and reported normative data of (potential) biomarkers can be used to study neuromuscular disorders.
This item appears in the following Collection(s)
- Academic publications 
Upload full text
Use your RU credentials (u/z-number and password) to log in with SURFconext to upload a file for processing by the repository team.