Comparison of human sperm morphometry assessment models based on zona pellucida selectivity.
Computer image analysis improves the objectivity and reproducibility of conventional assessments of sperm morphology. We have extended this objectivity by using the physiological process of sperm-zona pellucida (ZP) binding to classify 'normal' sperm morphometry. Linear regression analysis of the morphometric differences between sperm in semen, swim-up and ZP bound samples (n=53) was used to establish 12 "zona preferred" morphometric parameters from which two different morphometric evaluations of an individual sperm's potential for motility and ability to bind to the ZP of human oocytes were calculated. The two models, %Z and %ZB, were then tested, together with conventional morphometry assessments of percent "normal" and other semen variables, against experimental sperm-ZP binding rates (n=64) and natural pregnancy rates in sub-fertile couples (n= 1191). Although %ZB was the most significantly related semen variable to sperm-ZP binding rate, the simpler %Z was more significant in the Cox regression model for natural pregnancy rates in sub-fertile couples. In multivariate analysis, the only additional significant covariates were sperm straight line velocity and female age. %Z is therefore the most appropriate and also easiest of our morphometry assessments to be applied to commercial CASA systems which offer a morphometry module with stain density analysis.
Garrett
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Department of Obstetrics and Gynaecology, and Reproductive Services, University of Melbourne, Royal Women's Hospital, Carlton 3053, Australia. garrettc@unimelb.edu.au
Liu
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Baker
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D005307:Fertilization in Vitro / Q000379:methods; D006801:Humans; D007090:Image Interpretation, Computer-Assisted; D007248:Infertility, Male / Q000473:pathology; D008297:Male; D008954:Models, Biological; D016016:Proportional Hazards Models; D013048:Specimen Handling; D013077:Sperm Head / Q000473:pathology / Q000648:ultrastructure*; D013084:Sperm-Ovum Interactions