20 research outputs found

    Patellar tendon properties distinguish elite from non-elite soccer players and are related to peak horizontal but not vertical power

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    Purpose: The aims of our study were to investigate differences in tendon properties between elite and non-elite soccer players, and to establish whether tendon properties were related to power assessed during unilateral jumps in different directions. Methods: Elite (n=16; age, 18.1 ± 1.0yrs) and non-elite (n=13; age, 22.3 ± 2.7yrs) soccer players performed three repetitions of each type (unilateral vertical, unilateral horizontal-forward and unilateral medial) of countermovement jump (CMJ) on a force plate. Patellar tendon (PT) cross-sectional area (CSA), elongation, stiffness and Young’s modulus (measured at the highest common force interval) were assessed with ultrasonography and isokinetic dynamometry. Results: Elite soccer players demonstrated greater PT elongation (6.83±1.87 vs. 4.92±1.88 mm, P=0.011) and strain (11.73±3.25 vs. 8.38±3.06 %, P=0.009) than non-elite. Projectile range and peak horizontal power during unilateral horizontal-forward CMJ correlated positively with tendon elongation (r=0.657 and 0.693, P<0.001) but inversely with Young’s modulus (r=-0.376 and -0.402, P=0.044 and 0.031). Peak medial power during unilateral medial CMJ correlated positively with tendon elongation (r=0.658, P=<0.001) but inversely with tendon stiffness (r=-0.368, P=0.050). No tendon property correlated with unilateral vertical CMJ performance (r≤0.168; P≥0.204). Conclusions: Patellar tendon strain was greater in elite vs. non-elite soccer players and can therefore be considered an indicator of elite soccer playing status. Moreover, a more compliant patellar tendon appears to facilitate unilateral horizontal-forward and medial, but not vertical CMJ performance in soccer players. These findings should be considered when prescribing the detail of talent selection and development protocols related to direction-specific power in elite soccer players

    Abstracts from the NIHR INVOLVE Conference 2017

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    Case 101: Lumbar Facet Synovial Cyst

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    Sequence Tolerant Segmentation System of Brain MRI

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    Abstract- An automatic human brain segmentation system for magnetic resonance images is presented. It has two main parts: a fuzzy clustering algorithm and a set of cluster combination rules. Images are segmented into ten classes by the unsupervised fuzzy c-means clustering algorithm. Then a knowledge-based system labels the clusters into the tissues of interest: cerebrospinal fluid, gray matter and white matter. This approach can process MRI data that comes from different scanners with different sequences and head coils, using several different spin-echo images (with different echo times) and different slice thickness. The system adapts without manual intervention. Segmented synthetic image data from the brainweb Simulated Normal Brain Database resulted in a one voxel away accuracy of 90%. The results from real data from various magnetic resonance imagers were compared with a radiologist’s segmentation and found to generally agree within 10%, the typical range of interrater radiologist agreement
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