Human kinematic and morphometric sperm subpopulation analysis using CASA technology: A new approach to spermatozoa classification

Introduction

Semen analysis is a clinical method aimed at determining the fertility of a male individual. The traditional subjective method lacks the reliability that can be achieved by computer-assisted sperm analysis (CASA) technology. Unfortunately, this technology has only been used when taking into consideration individually different sperm characteristics. The aim of this work is to present an integrative mathematical approach that considers different seminal variables to establish human sperm subpopulations.

Methods

Samples were obtained from thirteen volunteers via masturbation and were analyzed by the routine subjective method and two objective systems, CASA Motility (CASA-Mot) and CASA Morphology (CASA-Morph).

Results

Seminogram variables were reduced to three principal components (PC) showing two subpopulations. Kinematics and morphometric variables each rendered three PCs for four subpopulations.

Conclusions

These results lay the foundations for future studies including different geographical, social, ethnic and age range conditions with the aim of achieving a definitive view of the human semen picture.