The Journal of urology · 2022
Staining-free, Automated Sperm Analysis for In Vitro Fertilization Lab Use.
СтатьяПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод пока не подготовлен
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Dai Changsheng, Shan Guanqiao, Jahangiri Sahar, Chen Wenyuan, Gholamhoseini Banafshe, Zhang Zhuoran, Moskovtsev Sergey, Librach Clifford, Jarvi Keith, Sun Yu
Аннотация
PURPOSE: Computer-aided sperm analysis is typically used in andrology labs, not in in vitro fertilization labs, which requires staining for sperm morphology measurement. In in vitro fertilization labs, sperm analysis still relies on manual observation and suffers from subjectivity and inconsistency. We developed a system for automated measurement of sperm concentration, motility, and morphology without the need for sperm staining. The reproducibility and reliability of the system were evaluated.
MATERIALS AND METHODS: Thirty-five fresh semen and 25 washed samples were obtained from male partners attending for fertility investigations. Sperm concentration, motility, and morphology were automatically measured simultaneously, leveraging robust sperm tracking for concentration and motility measurement and low contrast image segmentation for morphology measurement of live sperm. Reproducibility of sperm measurements was evaluated by intraclass correlation coefficients. Reliability of sperm measurement was evaluated by Passing and Bablok regression analysis and Bland-Altman analysis.
RESULTS: Automated measurement of concentration, motility, and morphology had intraclass correlation coefficients higher than 0.97. The regression and Bland-Altman analysis indicated that automated measurement and off-line manual benchmarking with zoomed-in images were interchangeable. Further analysis on semen and washed samples and the measurement on progressive and nonprogressive motility also showed high reproducibility and reliability.
CONCLUSIONS: Automated sperm analysis revealed high reproducibility and reliability. The system is designed for routine use in in vitro fertilization labs to perform quantitative sperm analysis on live samples.
MATERIALS AND METHODS: Thirty-five fresh semen and 25 washed samples were obtained from male partners attending for fertility investigations. Sperm concentration, motility, and morphology were automatically measured simultaneously, leveraging robust sperm tracking for concentration and motility measurement and low contrast image segmentation for morphology measurement of live sperm. Reproducibility of sperm measurements was evaluated by intraclass correlation coefficients. Reliability of sperm measurement was evaluated by Passing and Bablok regression analysis and Bland-Altman analysis.
RESULTS: Automated measurement of concentration, motility, and morphology had intraclass correlation coefficients higher than 0.97. The regression and Bland-Altman analysis indicated that automated measurement and off-line manual benchmarking with zoomed-in images were interchangeable. Further analysis on semen and washed samples and the measurement on progressive and nonprogressive motility also showed high reproducibility and reliability.
CONCLUSIONS: Automated sperm analysis revealed high reproducibility and reliability. The system is designed for routine use in in vitro fertilization labs to perform quantitative sperm analysis on live samples.