Characterizing the consistency of motion of spermatozoa through nanoscale motion tracing

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引用次数: 0

Abstract

Objective

To demonstrate nanoscale motion tracing of spermatozoa and present analysis of the motion traces to characterize the consistency of motion of spermatozoa as a complement to progressive motility analysis.

Design

Anonymized sperm samples were videographed under a quantitative phase microscope, followed by generating and analyzing superresolution motion traces of individual spermatozoa.

Setting

Not applicable.

Patient(s)

Centrifuged human sperm samples.

Intervention(s)

Not applicable.

Main Outcome Measure(s)

Precision of motion trace of individual sperms, presence of a helical pattern in the motion trace, mean and standard deviations of helical periods and radii of sperm motion traces, speed of progression.

Result(s)

Spatially sensitive quantitative phase imaging with a superresolution computational technique MUltiple SIgnal Classification ALgorithm allowed achieving motion precision of 340 nm using ×10, 0.25 numerical aperture lens whereas the diffraction-limited resolution at this setting was 1,320 nm. The motion traces thus derived facilitated new kinematic features of sperm, namely the statistics of helix period and radii per sperm.

Through the analysis, 47 sperms with a speed >25 μm/s were randomly selected from the same healthy donor semen sample, it is seen that the kinematic features did not correlate with the speed of the sperms. In addition, it is noted that spermatozoa may experience changes in the periodicity and radius of the helical path over time. Further, some very fast sperms (e.g., >70 μm/s) may demonstrate irregular motion and need further investigation.

Presented computational analysis can be used directly for sperm samples from both fertility patients with normal and abnormal sperm cell conditions.

We note that MUltiple SIgnal Classification ALgorithm is an image analysis technique that may vaguely fall under the machine learning category, but the conventional metrics for reporting found in Enhancing the QUAlity and Transparency Of health Research network do not apply. Alternative suitable metrics are reported, and bias is avoided through random selection of regions for analysis. Detailed methods are included for reproducibility.

Conclusion(s)

Kinematic features derived from nanoscale motion traces of spermatozoa contain information complementary to the speed of the sperms, allowing further distinction among the progressively motile sperms. Some highly progressive spermatozoa may have irregular motion patterns, and whether irregularity of motion indicates poor quality regarding artificial insemination needs further investigation. The presented technique can be generalized for sperm analysis for a variety of fertility conditions.

通过纳米级运动追踪表征精子运动的一致性。
目的:展示精子的纳米级运动轨迹,并分析精子运动的一致性,作为渐进运动分析的补充:展示精子的纳米级运动轨迹,并对运动轨迹进行分析,以确定精子运动的一致性,作为渐进式运动分析的补充:设计:在定量相显微镜下对匿名精子样本进行录像,然后生成并分析单个精子的超分辨率运动轨迹:离心人类精子样本:主要结果指标:单个精子运动轨迹的精确度、运动轨迹中是否存在螺旋模式、精子运动轨迹螺旋周期和半径的平均值和标准偏差、运动速度:利用超分辨率计算技术MUltiple SIgnal Classification ALgorithm (MUSICAL)进行空间敏感定量相位成像,使用10×、0.25 NA镜头可实现340纳米的运动精度,而在此设置下的衍射极限分辨率为1320纳米。由此得出的运动轨迹有助于获得精子的新运动学特征,即每个精子的螺旋周期和半径统计。通过对从同一健康捐精者的精液样本中随机抽取的速度大于 25 μm/sec 的 47 个精子进行分析,发现运动学特征与精子的速度无关。此外,我们还注意到,精子的螺旋路径周期和半径可能会随着时间的推移而发生变化。此外,一些速度极快的精子(例如>70微米/秒)可能会表现出不规则运动,这需要进一步研究。所提出的计算分析可直接用于正常和异常精子细胞条件的生育患者的精子样本。我们注意到,MUSICAL 是一种图像分析技术,可能隐约属于机器学习范畴,但 EQUATOR 中的传统报告指标并不适用。我们报告了其他合适的指标,并通过随机选择分析区域来避免偏差。报告中还包含了详细的方法,以确保可重复性:从精子的纳米级运动轨迹中得出的运动学特征包含精子速度的补充信息,可进一步区分渐进运动的精子。一些高度渐进的精子可能具有不规则的运动模式,而运动的不规则性是否表明人工授精的质量不佳,还需要进一步研究。该技术可用于各种生育条件下的精子分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
F&S science
F&S science Endocrinology, Diabetes and Metabolism, Obstetrics, Gynecology and Women's Health, Urology
CiteScore
2.00
自引率
0.00%
发文量
0
审稿时长
51 days
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