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Updated: Apr 28, 2026
Flow Cytometric Analysis of Biomarkers for Detecting Human Sperm Functional Defects
Published on: April 21, 2022
High-throughput imaging cytometry paired with artificial intelligence identifies ultrarare sperm in men previously
Blair Stocks1, Aidan Boyne2, Amelia Oppenheimer1
1Scott Department of Urology, Division of Male Reproductive Medicine and Surgery, Baylor College of Medicine, Houston, Texas.
Objective:
To determine whether a novel diagnostic platform, which pairs high-throughput imaging cytometry with artificial intelligence (AI)-assisted image analysis, can identify ultrarare sperm in ejaculatory samples deemed clinically azoospermic.
Design:
A retrospective cohort review of remnant biobanked ejaculatory samples processed by high-throughput imaging cytometry and AI-assisted image analysis.
Subjects:
Remnant ejaculatory samples (n = 148) biobanked from December 2024 to September 2025 at a single high-volume male infertility clinic.
Exposure:
Image-based flow cytometry and convolutional neural network (CNN) driven image analysis for diagnostic classification.
Main Outcome Measures:
Diagnostic reclassification rate of remnant ejaculatory samples initially deemed clinically azoospermic using CNN-based morphologic assessment and corollary sperm specific protein expression.
Results:
Within the 83 azoospermic samples analyzed, 40 samples (48%) were found to have sperm using this high-fidelity diagnostic platform.
Conclusion:
We propose a new classification of sperm concentration, microzoospermia, a sperm concentration so low that only advanced image-based search technologies can reliably identify ultrarare sperm.
