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Lower Extremity Muscle Morphology in Young Athletes: An MRI-Based Analysis


Medicine & Science in Sports & Exercise: January 2006 - Volume 38 - Issue 1 - p 122-128
doi: 10.1249/01.mss.0000179400.67734.01
Applied Sciences: Biodynamics

Purpose: This study was conducted to describe lower extremity muscle morphology (volume and peak cross-sectional area (CSA)) in young athletes and compare these with previously reported values. A second aim was to determine if muscle morphological values differ significantly between sides, implying that unilateral measurements cannot represent both limbs accurately.

Methods: Axial spin-echo T1-weighted magnetic resonance (MR) images were obtained between the ankle mortise and iliac crest in 10 athletes (age 18.8 ± 3.7 yr). Subsequently, each subject’s three-dimensional anatomy was digitally reconstructed. Muscle volume, peak CSA, and length were calculated for 13 muscles.

Results: The mean volumes and CSA for the current sample of athletes were larger than previously reported values (primarily from cadaver studies of nonathletes). The ratio of total quadriceps volume to total hamstrings volume averaged nearly 3:1 (2.9 ± 0.2), whereas previous reports have been closer to 2:1 (2.1 ± 0.2). The relative contribution of each muscle to the muscle group (hamstrings or quadriceps) volume was also different for these athletes. Significant differences in side-to-side muscle morphology were observed in several knee muscles (P < 0.03). Vastus medialis muscle volume was larger in the dominant leg (difference between sides: 59 ± 25 cm3, representing 15.9 ± 6.7% of its average volume), whereas vastus lateralis muscle volume was larger in the nondominant leg (difference: 54 ± 47 cm3 representing 9.6 ± 8.3% of its average). Despite this, total quadriceps volumes were similar between sides.

Conclusions: Findings suggest that the morphology data presented in this study should be used instead of data from cadavers when studying young athletic people. These data should improve the accuracy of biomechanical modeling in the athletic population.

1Center for Biomedical Engineering Research, University of Delaware, Newark, DE; and 2Graduate Program in Physical Therapy and Rehabilitation Science, University of Iowa, Iowa City, IA

Address for correspondence: Thomas S. Buchanan, Center for Biomedical Engineering Research, University of Delaware, 126 Spencer Laboratories, Newark, DE 19716; E-mail:

Submitted for publication December 2004.

Accepted for publication July 2005.

This work was supported, in part, by NIH R01-AR046386.

©2006The American College of Sports Medicine