Quantitative ultrasound of the first dorsal interosseous muscle: A novel mathematical model for muscle thickness

Research Objectives: To investigate the reliability and validity of a novel mathematical model for quantitative muscle ultrasound of the first dorsal interosseous (FDI) muscle.

Design: This was a repeated-measures, cross-sectional study. For each subject, three axial images were separately acquired from the right FDI by three junior sonographers. Three repeat FDI strength measurements per subject were subsequently taken with pinch grip dynamometry. Mathematical modeling and statistical analysis was performed on SPSS by one ultrasonographer.

Setting: Single center, research institute as part of a tertiary care hospital.

Participants: Participants were healthy volunteers recruited from the local university community. n=20 (M=9. F=11), mean age= 27, SD= 6.5.

Interventions: N/A.

Main Outcome Measures: Outcome measures were acquired for each of the three traditional analysis techniques and the novel mathematical model used to determine muscle thickness. Firstly, inter-rater reliability amongst the three junior sonographers was assessed with intraclass correlation. Secondly, validity was assessed via a linear regression analysis with pinch grip dynamometry strength measures.

Results: The validity revealed profoundly higher correlation for the new mathematical model (R-Squared=0.70) compared to the traditional analysis techniques (R-Squared=0.42-0.50). Inter-rater reliability is higher with the new mathematical model (ICC range: 0.839-0.964) compared to traditional analysis techniques (ICC range: 0.671-0.946). Visual modeling qualitatively contrasts the robustness of new and traditional models to variability in FDI morphologies commonly seen across the population.

Conclusions: The new mathematical model has higher validity and higher inter-rater reliability compared to traditional methods for the ultrasound analysis of axial FDI muscle thickness. Visual modeling depicts the limitations of the traditional methods to account for variations in muscle eccentricity and convexity across the population. Visual modeling further illustrates that the new mathematical model is more robust across a wider range of FDI architectural parameters.

Author(s) Disclosures: None.