Biceps Femoris Long-Head Architecture Assessed Using Different Sonographic Techniques

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Abstract

Purpose

To assess the repeatability of, and measurement agreement between, four sonographic techniques used to quantify biceps femoris long head (BFlh) architecture: (i) static-image with linear extrapolation; extended field-of-view (EFOV) with linear ultrasound probe path (linear-EFOV), using either (ii) straight or (iii) segmented analyses; and (iv) EFOV with nonlinear probe path and segmented analysis (nonlinear-EFOV) to follow the complex fascicle trajectories.

Methods

Twenty individuals (24.4 ± 5.7 yr; 175 ± 0.8 cm; 73 ± 9.0 kg) without history of hamstrings strain injury were tested in two sessions separated by 1 h. An ultrasound scanner coupled with 6-cm linear probe was used to assess BFlh architecture in B-mode.

Results

The ultrasound probe was positioned at 52.0% ± 5.0% of femur length and 57.0% ± 6.0% of BFlh length. We found an acceptable repeatability when assessing BFlh fascicle length (ICC3,k = 0.86–0.95; SEM = 1.9–3.2 mm) and angle (ICC3,k = 0.86–0.97; SEM = 0.8°–1.1o) using all sonographic techniques. However, the nonlinear-EFOV technique showed the highest repeatability (fascicle length ICC3,k = 0.95; fascicle angle, ICC3,k = 0.97). The static-image technique, which estimated 35.4% ± 7.0% of the fascicle length, overestimated fascicle length (8%–11%) and underestimated fascicle angle (8%–9%) compared with EFOV techniques. Also, the rank order of individuals varied by approximately 15% between static-image and nonlinear-EFOV (segmented) when assessing the fascicle length.

Conclusions

Although all techniques showed good repeatability, absolute errors were observed using static-image (7.9 ± 6.1 mm for fascicle length) and linear-EFOV (between 3.7 ± 3.0 and 4.2 ± 3.7 mm), probably because the complex fascicle trajectories were not followed. The rank order of individuals for fascicle length and angle were also different between static-image and nonlinear-EFOV, so different muscle function and injury risk estimates could likely be made when using this technique.

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