Abstract The flagellar movement of the mammalian sperm is essential for male fertility as it enables this cell to reach and fertilize an egg. In the female reproductive tract, human spermatozoa undergo a process called capacitation which promotes changes in their motility. Only those spermatozoa that change to hyperactivated (HA) motility are capable of fertilizing the egg; this type of motility is characterized by asymmetric flagellar bends of greater amplitude and lower frequency. Historically, clinical fertilization studies have used two-dimensional analysis to classify sperm motility, although, sperm motility is three-dimensional (3D). Recent studies have described several 3D beating features of sperm flagella, including curvature, torsion, and asymmetries. However, the 3D motility pattern of hyperactivated spermatozoa has not yet been characterized. One of the main difficulties in classifying these patterns in 3D is the lack of a ground-truth reference, as it can be difficult to visually assess differences in flagellar beat patterns. Additionally, only about 10 − 20% of sperm that have been induced to capacitate are truly capacitated (i.e., hyperactivated). In this work, we used an image acquisition system that can acquire, segment, and track sperm flagella in 3D+t. We developed a feature-based vector that describes the spatio-temporal flagellar sperm motility patterns by an envelope of ellipses. Our results demonstrate that the proposed descriptors can effectively be used to distinguish between hyperactivated and nonhyperactivated spermatozoa, providing a tool to characterize the 3D sperm flagellar beat motility patterns without prior training or supervision. We demonstrated the effectiveness of the descriptors by applying them to a dataset of human sperm cells and showing that they can accurately classify the motility patterns of the sperm cells. This work is potentially useful for assessing male fertility or for diagnosing.

Feature-Based 3D+t Descriptors of Hyperactivated Human Sperm Beat Patterns