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4 October 2017 CASAnova: A multiclass support vector machine model for the classification of human sperm motility patterns
Summer G. Goodson, Sarah White, Alicia M. Stevans, Sanjana Bhat, Chia-Yu Kao, Scott Jaworski, Tamara R. Marlowe, Martin Kohlmeier, Leonard McMillan, Steven H. Zeisel, Deborah A. O'Brien
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Abstract

The ability to accurately monitor alterations in sperm motility is paramount to understanding multiple genetic and biochemical perturbations impacting normal fertilization. Computer-aided sperm analysis (CASA) of human sperm typically reports motile percentage and kinematic parameters at the population level, and uses kinematic gating methods to identify subpopulations such as progressive or hyperactivated sperm. The goal of this study was to develop an automated method that classifies all patterns of human spermmotility during in vitro capacitation following the removal of seminal plasma. We visually classified CASA tracks of 2817 sperm from 18 individuals and used a support vector machine-based decision tree to compute four hyperplanes that separate five classes based on their kinematic parameters. We then developed a web-based program, CASAnova, which applies these equations sequentially to assign a single classification to each motile sperm. Vigorous sperm are classified as progressive, intermediate, or hyperactivated, and nonvigorous sperm as slow or weakly motile. This program correctly classifies sperm motility into one of five classes with an overall accuracy of 89.9%. Application of CASAnova to capacitating sperm populations showed a shift from predominantly linear patterns of motility at initial time points to more vigorous patterns, including hyperactivated motility, as capacitation proceeds. Both intermediate and hyperactivated motility patterns were largely eliminated when sperm were incubated in noncapacitating medium, demonstrating the sensitivity of this method. The five CASAnova classifications are distinctive and reflect kinetic parameters of washed human sperm, providing an accurate, quantitative, and high-throughput method for monitoring alterations in motility.

Summary Sentence

A CASA-based support vector machine model of human sperm motility provides rapid, accurate, and quantitative analysis of all motile sperm in a population.

© The Authors 2017. Published by Oxford University Press on behalf of Society for the Study of Reproduction. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com
Summer G. Goodson, Sarah White, Alicia M. Stevans, Sanjana Bhat, Chia-Yu Kao, Scott Jaworski, Tamara R. Marlowe, Martin Kohlmeier, Leonard McMillan, Steven H. Zeisel, and Deborah A. O'Brien "CASAnova: A multiclass support vector machine model for the classification of human sperm motility patterns," Biology of Reproduction 97(5), 698-708, (4 October 2017). https://doi.org/10.1093/biolre/iox120
Received: 6 March 2017; Accepted: 1 October 2017; Published: 4 October 2017
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KEYWORDS
capacitation
CASA
CASAnova
hyperactivation
sperm motility
support vector machine
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