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Published on: May 1, 2018
Quadriceps Muscle Morphology as a Marker of Performance Across Multiple Strength and Power Tests
Davi A G Mázala1, Daniel F McLaughlin1, Matheus B Guerrero2
1Department of Kinesiology, College of Health Professions, Towson University, Towson, Maryland, USA, towson.edu.
None:
Previous studies demonstrated that measures of muscle thickness (MT) and echo intensity (EI) show an association with functional tests, but results have been inconsistent. The aim of the current cross-sectional study was to determine which muscle from the quadriceps (QUAD) (i.e., vastus lateralis [VL], rectus femoris [RF], or vastus intermedius [VI]) and ultrasound measurements (i.e., MT and EI) better explain three different physical assessments: maximal isometric knee extension torque (MIVT), vertical jump peak power (VJPP), and lower limb muscle power (LLMP). Forty-three adults (23 women) participated in this cross-sectional study. Participants' body composition, ultrasound measurements from the dominant leg, and functional outcomes were evaluated on the same visit. Bivariate analyses indicated moderate to strong positive associations between all physical assessments and muscle morphology variables, supporting the use of multiple regression analyses. Also, given the multicollinearity among EI measures, a global EI index was generated and used in the multiple regression analyses. The multiple regression analysis showed that MIVT was independently associated with RF MT (p = 0.009) and global EI (p = 0.004), with the model explaining 63.5% of the variance. For VJPP, RF MT was the only variable that significantly contributed to the model (p = 0.041), explaining 61.9% of the variance. Lastly, LLMP was independently associated with RF MT (p = 0.003) and VI MT (p = 0.010), and the model explained 63.0% of the variance. Overall, these findings suggest that RF MT may be the most informative QUAD ultrasound measure for explaining performance in our data set. This is particularly important in clinical and research settings in which reducing testing time, participant burden, and analytic complexity can improve feasibility without substantially compromising the relevance of the evaluation.
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