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通过平面形态测量法对精子进行表征。

Characterization of spermatozoa by planar morphometry.

作者信息

Harr R

机构信息

Department of Medical Technology, Bowling Green State University, OH, USA.

出版信息

Clin Lab Sci. 1997 Jul-Aug;10(4):190-6.

Abstract

OBJECTIVE

To define the morphometric characteristics of normal sperm heads, and compare them to sperm head measurements used to define normal morphology using strict criteria.

DESIGN

Computerized image analysis of selected normal and abnormal seminal fluid specimens collected for routine male fertility studies.

SETTING

Research laboratory at the Department of Medical Technology, Bowling Green State University, Bowling Green, OH.

PATIENTS

Sixty adult male patients who submitted semen samples for routine analysis. Fifty percent had normal seminal fluid analysis results. The remaining 50% demonstrated abnormal sperm morphology. CRITERION STANDARD: Microscopic evaluation of sperm head morphology. Sperm fitting the criteria of normal as defined by WHO (1987 and 1992) and Kruger (1988) were classified as normal. Sperm with a post nuclear area of less than 40% were classified as acrosomal deficient.

MAIN OUTCOME MEASURES

Measurements made from stained seminal fluid smears included sperm head area, perimeter, acrosomal area, percent acrosome, Ferret's diameters, aspect ratio, shape factor, and specific length. Normal sperm heads (NL group) were compared to sperm heads demonstrating an acrosomal deficiency (AD group) for statistically significant differences using multivariate analysis of variance (MANOVA) and analysis of variance (ANOVA). Stepwise discriminant analysis was used to remove duplicating variables. Discriminant analysis was used to classify the sperm heads into NL and AD groups. Receiver-operating characteristic (ROC) curves were applied to the 2 most influential variables in order to identify a cutoff that best distinguishes normal from acrosomal deficient sperm heads.

RESULTS

MANOVA and ANOVA showed all 10 variables to be statistically significant (p < .002). Discriminant analysis correctly assigned 98.7% of the normal sperm heads to the NL group and 99.0% of sperm with acrosomal deficiency to the AD group. The percent acrosome and acrosomal area were determined to be the 2 most influential variables. ROC analysis identified a cutoff of 3.6 mu2 for acrosomal area as having the highest sensitivity and specificity (99.7% and 88.0%, respectively). Similarly, a cutoff of 44% for percent acrosome gave a sensitivity of 92.3% and a specificity of 88.7%. The coefficient of variation (CV) for each of the 10 variables determined from 20 day-to-day replicates of a normal semen smear ranged from 2.6% to 8.4%.

CONCLUSION

Computerized image analysis is able to define a reference range for sperm head area, percent acrosome, and acrosomal area that may be used to differentiate normal form abnormal sperm heads. Maximum and minimum Ferret's diameters measure sperm head length and width, respectively. Mean maximum Ferret's diameter, minimum Ferret's diameter, and maximum-minimum Ferret's diameter ratio correspond closely to the WHO (1987) midpoint for normal sperm head length, width, and length-width ratio. The average percent acrosome of normal sperm heads determined by morphometry closely correlate to the WHO (1992) and Kruger (1988) midpoints for percent acrosome.

摘要

目的

确定正常精子头部的形态测量特征,并将其与使用严格标准定义正常形态时所采用的精子头部测量值进行比较。

设计

对为男性生育力常规研究收集的选定正常和异常精液标本进行计算机图像分析。

地点

俄亥俄州鲍灵格林州立大学医学技术系研究实验室。

患者

60名成年男性患者提交精液样本进行常规分析。其中50%精液分析结果正常。其余50%精子形态异常。标准:精子头部形态的显微镜评估。符合世界卫生组织(1987年和1992年)及克鲁格(1988年)所定义正常标准的精子被分类为正常。核后区域小于40%的精子被分类为顶体缺陷型。

主要观察指标

对染色精液涂片进行的测量包括精子头部面积、周长、顶体面积、顶体百分比、费雷特直径、长宽比、形状因子和比长度。使用多变量方差分析(MANOVA)和方差分析(ANOVA)比较正常精子头部(NL组)与表现为顶体缺陷的精子头部(AD组)的统计学显著差异。采用逐步判别分析去除重复变量。判别分析用于将精子头部分类为NL组和AD组。将受试者工作特征(ROC)曲线应用于两个最具影响力的变量,以确定最能区分正常与顶体缺陷精子头部的临界值。

结果

MANOVA和ANOVA显示所有10个变量均具有统计学显著性(p <.002)。判别分析将98.7%的正常精子头部正确分类到NL组,将99.0%的顶体缺陷精子分类到AD组。顶体百分比和顶体面积被确定为两个最具影响力的变量。ROC分析确定顶体面积的临界值为3.6μm²时具有最高的敏感性和特异性(分别为99.7%和88.0%)。同样,顶体百分比的临界值为44%时,敏感性为92.3%,特异性为88.7%。从正常精液涂片的20次日常重复测量中确定的10个变量中每个变量的变异系数(CV)范围为2.6%至8.4%。

结论

计算机图像分析能够确定精子头部面积、顶体百分比和顶体面积的参考范围,可用于区分正常与异常精子头部。最大和最小费雷特直径分别测量精子头部的长度和宽度。平均最大费雷特直径、最小费雷特直径和最大-最小费雷特直径比与世界卫生组织(1987年)正常精子头部长度、宽度和长宽比的中点密切相关。通过形态测量确定的正常精子头部的平均顶体百分比与世界卫生组织(1992年)及克鲁格(1988年)的顶体百分比中点密切相关。

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