Computer-assisted sperm analysis (CASA): capabilities and potential developments

Computer-assisted sperm analysis (CASA) systems have evolved over approximately 40 years, through advances in devices to capture the image from a microscope, huge increases in computational power concurrent with amazing reduction in size of computers, new computer languages, and updated/expanded software algorithms. Remarkably, basic concepts for identifying sperm and their motion patterns are little changed. Older and slower systems remain in use. Most major spermatology laboratories and semen processing facilities have a CASA system, but the extent of reliance thereon ranges widely. This review describes capabilities and limitations of present CASA technology used with boar, bull, and stallion sperm, followed by possible future developments. Each marketed system is different. Modern CASA systems can automatically view multiple fields in a shallow specimen chamber to capture strobe-like images of 500 to >2000 sperm, at 50 or 60 frames per second, in clear or complex extenders, and in <2 minutes, store information for ≥ 30 frames and provide summary data for each spermatozoon and the population. A few systems evaluate sperm morphology concurrent with motion. CASA cannot accurately predict 'fertility' that will be obtained with a semen sample or subject. However, when carefully validated, current CASA systems provide information important for quality assurance of semen planned for marketing, and for the understanding of the diversity of sperm responses to changes in the microenvironment in research. The four take-home messages from this review are: (1) animal species, extender or medium, specimen chamber, intensity of illumination, imaging hardware and software, instrument settings, technician, etc., all affect accuracy and precision of output values; (2) semen production facilities probably do not need a substantially different CASA system whereas biology laboratories would benefit from systems capable of imaging and tracking sperm in deep chambers for a flexible period of time; (3) software should enable grouping of individual sperm based on one or more attributes so outputs reflect subpopulations or clusters of similar sperm with unique properties; means or medians for the total population are insufficient; and (4) a field-use, portable CASA system for measuring one motion and two or three morphology attributes of individual sperm is needed for field theriogenologists or andrologists working with human sperm outside urban centers; appropriate hardware to capture images and process data apparently are available.