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Flow Cytometric Analysis of Biomarkers for Detecting Human Sperm Functional Defects

Flow Cytometric Analysis of Biomarkers for Detecting Human Sperm Functional Defects

Published on: April 21, 2022

A collective tracking method for preliminary sperm analysis.

Sung-Yang Wei¹, Hsuan-Hao Chao¹, Han-Ping Huang¹

¹Department of Electrophysics, National Chiao Tung University, Hsinchu, 30010, Taiwan.

Biomedical Engineering Online

|November 29, 2019

Summary

This summary is machine-generated.

A novel, simple frame-differencing method accurately evaluates total motile sperm count (TMSC) and curvilinear velocity (VCL) without complex computation. This technique offers a viable alternative to expensive computer-assisted sperm analysis (CASA) for infertility diagnostics.

Keywords:

Computer-assisted sperm analyzer (CASA)Curvilinear velocity (VCL)Frame differencing Object tracking Total motile sperm count (TMSC)

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Area of Science:

Reproductive biology
Medical imaging analysis
Biomedical engineering

Background:

Total motile sperm count (TMSC) and curvilinear velocity (VCL) are key metrics in male infertility assessment.
Traditional methods, manual counting and computer-assisted sperm analysis (CASA), have limitations like being exhausting or computationally intensive.
Overlapping sperm in dense semen samples pose challenges for existing analysis techniques.

Purpose of the Study:

To introduce a simplified, computationally efficient method for evaluating TMSC and VCL.
To overcome the limitations of individual point-tracking methods in CASA systems.
To develop a real-time sperm analysis technique suitable for broader applications.

Main Methods:

A frame-differencing method was developed to track motile sperm collectively using differential footprint trajectories (DFTs).
A theoretical DFT model was created to correlate DFT area with sperm count and speed.
Least square fitting was employed to determine TMSC and average VCL from measured DFT areas.

Main Results:

The proposed method successfully evaluated TMSC and VCL in 20 semen samples.
High Pearson correlation coefficients (PCC) were observed: 0.946 for TMSC and 0.771 for VCL when compared to CASA.
The method demonstrated accuracy comparable to CASA for TMSC and VCL evaluations.

Conclusions:

The collective DFT tracking method offers a computationally simpler alternative to individual point-tracking techniques.
This approach avoids complex image processing, making it more accessible.
Integration with mobile devices could lead to simple, cost-effective sperm analyzers for clinical or home use.