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UROKIN: A Software to Enhance Our Understanding of Urogenital Motion

Overview of attention for article published in Annals of Biomedical Engineering, February 2018
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Title
UROKIN: A Software to Enhance Our Understanding of Urogenital Motion
Published in
Annals of Biomedical Engineering, February 2018
DOI 10.1007/s10439-018-1989-7
Pubmed ID
Authors

Catriona S. Czyrnyj, Michel R. Labrosse, Ryan B. Graham, Linda McLean

Abstract

Transperineal ultrasound (TPUS) allows for objective quantification of mid-sagittal urogenital mechanics, yet current practice omits dynamic motion information in favor of analyzing only a rest and a peak motion frame. This work details the development of UROKIN, a semi-automated software which calculates kinematic curves of urogenital landmark motion. A proof of concept analysis, performed using UROKIN on TPUS video recorded from 20 women with and 10 women without stress urinary incontinence (SUI) performing maximum voluntary contraction of the pelvic floor muscles. The anorectal angle and bladder neck were tracked while the motion of the pubic symphysis was used to compensate for the error incurred by TPUS probe motion during imaging. Kinematic curves of landmark motion were generated for each video and curves were smoothed, time normalized, and averaged within groups. Kinematic data yielded by the UROKIN software showed statistically significant differences between women with and without SUI in terms of magnitude and timing characteristics of the kinematic curves depicting landmark motion. Results provide insight into the ways in which UROKIN may be useful to study differences in pelvic floor muscle contraction mechanics between women with and without SUI and other pelvic floor disorders. The UROKIN software improves on methods described in the literature and provides unique capacity to further our understanding of urogenital biomechanics.

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Geographical breakdown

Country Count As %
Unknown 37 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 6 16%
Student > Bachelor 6 16%
Other 4 11%
Student > Ph. D. Student 3 8%
Professor 2 5%
Other 6 16%
Unknown 10 27%
Readers by discipline Count As %
Engineering 6 16%
Nursing and Health Professions 6 16%
Medicine and Dentistry 6 16%
Agricultural and Biological Sciences 2 5%
Biochemistry, Genetics and Molecular Biology 1 3%
Other 4 11%
Unknown 12 32%