Intra- and inter-laboratory variability in the assessment of sperm morphology by strict criteria: impact of semen preparation, staining techniques and manual versus computerized analysis

Improving outcomes of assisted reproductive technologies using artificial intelligence for sperm selection

Within the field of assisted reproductive technology, artificial intelligence has become an attractive tool for potentially improving success rates. Recently, artificial intelligence-based tools for sperm evaluation and selection during intracytoplasmic sperm injection (ICSI) have been explored, mainly to improve fertilization outcomes and decrease variability within ICSI procedures. Although significant advances have been achieved in developing algorithms that track and rank single sperm in real-time during ICSI, the clinical benefits these might have in improving pregnancy rates from a single assisted reproductive technology cycle remain to be established.

A matter of agreement: The effect of the technique and evaluator on the analysis of morphologic defects in stallion sperm

Analysis of sperm morphology is an important part of the stallion breeding soundness evaluation since it provides an objective measure of a stallion's sperm quality and is one of many factors that estimate a stallion's fertility potential. To describe the effect of sperm quality level on the technique (Differential Interference Contrast - DIC; Phase-contrast - PH; Dip-Quick staining - DQ; and eosin-nigrosin staining - EN; semen samples fixed in buffered-formal saline) and evaluator (three evaluators; using only DIC), stallions were categorized based on sperm quality into three categories: High: >57% normal sperm, Moderate: 23-56% normal sperm, or Low: <23% normal sperm (four stallions per category). The data were analyzed using three different statistical methods: Analysis of Variance (ANOVA), correlative analysis, and Bland-Altman method (agreement). A higher level of agreement among techniques was observed between DIC and PH for morphologically normal sperm. The agreement between the alternative methods (EN, DQ, or PH) and the standard method (DIC) varied, depending on the sperm quality level (High, Moderate, or Low). Some morphological defects (e.g., AH, AMP) were constantly underestimated with the staining methods (DQ, EN) compared to DIC and PH, particularly in ejaculates with low sperm morphology. Underestimation of some abnormalities, due to the technique or the evaluator, has the potential to alter the clinical interpretation of stallion fertility.

Machine learning for sperm selection

Infertility rates and the number of couples seeking fertility care have increased worldwide over the past few decades. Over 2.5 million cycles of assisted reproductive technologies are being performed globally every year, but the success rate has remained at ~33%. Machine learning, an automated method of data analysis based on patterns and inference, is increasingly being deployed within the health-care sector to improve diagnostics and therapeutics. This technique is already aiding embryo selection in some fertility clinics, and has also been applied in research laboratories to improve sperm analysis and selection. Tremendous opportunities exist for machine learning to advance male fertility treatments. The fundamental challenge of sperm selection - selecting the most promising candidate from 10⁸ gametes - presents a challenge that is uniquely well-suited to the high-throughput capabilities of machine learning algorithms paired with modern data processing capabilities.

Lack of trusted diagnostic tools for undetermined male infertility

Semen analysis is the cornerstone of evaluating male infertility, but it is imperfect and insufficient to diagnose male infertility. As a result, about 20% of infertile males have undetermined infertility, a term encompassing male infertility with an unknown underlying cause. Undetermined male infertility includes two categories: (i) idiopathic male infertility-infertile males with abnormal semen analyses with an unknown cause for that abnormality and (ii) unexplained male infertility-males with "normal" semen analyses who are unable to impregnate due to unknown causes. The treatment of males with undetermined infertility is limited due to a lack of understanding the frequency of general sperm defects (e.g., number, motility, shape, viability). Furthermore, there is a lack of trusted, quantitative, and predictive diagnostic tests that look inside the sperm to quantify defects such as DNA damage, RNA abnormalities, centriole dysfunction, or reactive oxygen species to discover the underlying cause. To better treat undetermined male infertility, further research is needed on the frequency of sperm defects and reliable diagnostic tools that assess intracellular sperm components must be developed. The purpose of this review is to uniquely create a paradigm of thought regarding categories of male infertility based on intracellular and extracellular features of semen and sperm, explore the prevalence of the various categories of male factor infertility, call attention to the lack of standardization and universal application of advanced sperm testing techniques beyond semen analysis, and clarify the limitations of standard semen analysis. We also call attention to the variability in definitions and consider the benefits towards undetermined male infertility if these gaps in research are filled.

Optimized combination of multiple biomarkers to improve diagnostic accuracy in male fertility

Artificial insemination is the general method of breeding for genetic improvement in offspring. However, almost half of the insemination cases fail to achieve full-term pregnancy, due to male infertility or subfertility. To maximize the success of insemination, accurate semen quality testing is required prior to insemination. Even though basic semen analyses have been used to provide preliminary information, it cannot fully identify the superior or inferior fertility bulls. Therefore, more powerful and easy to use methods for the prediction of male fertility are required, such as proteomic or microarray chips. During past decades, omics approaches have been developed and suggested the numerous fertility-related potential biomarkers. Our previous study identified the fertility related protein markers, enolase1 (ENO1), ATP synthase, H⁺ transporting, mitochondrial F1 complex, beta subunit (ATP5B), voltage-dependent anion channel 2 (VDAC2), phospholipid hydroperoxide glutathione peroxide (GPx4), and ubiquinol-cytochrome-c reductase complex core protein 2 (UQCRC2) in bovine spermatozoa. In the present study, we perform a marker combination assay using the western blot data of ENO1, ATP5B, VDAC2, GPx4, and UQCRC2 from 20 individual bull semen samples. And then, we identified the predictive ability of these markers for normal (non-return rate (NRR) ≥ 70%) and normal fertility (NRR<70%) in bulls. ENO1, a single protein marker, achieved an area under the curve (AUC) of 0.86 and 90% discriminatory power between normal and below-normal fertility bulls, with 90% sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). Although no meaningful changes existed in overall accuracy (70-85%) to discriminate the normal and below-normal fertility between ENO1 single marker and combined marker panels, multiple marker combination methods using ENO1, VDAC2, GPx4, and UQCRC2 provided absolute sensitivity and NPV, with higher specificity (70%) and PPV (77%). ENO1 can be used as a fertility marker candidate, but there were limitations for providing absolute information about normal and below-normal fertility. Although the combined use of fertility-related markers cannot provide absolute accuracy, it can help in indicating below-normal fertility in bulls. These results may contribute to the maintenance cost in the animal industry, via selection of bulls with inferior fertility.

Knowledge gaps in male infertility: a reproductive endocrinology and infertility perspective

Reproductive research has moved forward at a remarkable pace. Some of these advances are the result of a separation between male and female specialties, allowing focused study in specific areas of the field. However, the different training programs between male and female fertility specialists has created an environment in which some discoveries are not put in the greater context of clinical care. At times, interventions have been measured against surrogate markers of outcome that may not impact the most meaningful outcome for patients—the delivery of a healthy neonate. For example, medical and surgical interventions that use changes in semen parameters may have a limited impact on the likelihood of achieving a live birth due to the limitations inherent in the semen analysis for predicting outcomes. Other commonly used tests, such as sperm DNA fragmentation assays provide promising biological plausibility to account for subfertility of some male partners. However, until well defined thresholds for predicting outcomes in different treatment scenarios are available, changes in sperm DNA fragmentation testing is not an adequate outcome for measuring the utility of interventions. The biggest limitation for these tests remains their analysis of bulk semen. Tests allowing interrogation of the reproductive competence of a given sperm, while allowing that sperm to be used in assisted reproductive technology procedures remain elusive. Progress toward reaching this end (whether by hyaluronic acid binding, IMSI, or Ramen spectroscopy) is underway, but much remains to be learned. Achieving testing and capture of individual sperm would better facilitate studies that measure the most meaningful outcome for patients and providers—the delivery of a healthy baby.

Revisiting The Relationship between The Ejaculatory Abstinence Period and Semen Characteristics

Variation in the ejaculatory abstinence period suggested by different guidance bodies have resulted in a growing concern among researchers and clinicians over what the precise period of ejaculatory abstinence ought to be for an optimal semen sample. Several studies have thus been undertaken to examine the association between the length of sexual abstinence and semen characteristics. Not all studies, however, have arrived at the same conclusions. This study aims to review all existing literature published during the past few decades pertaining to the influence of ejaculatory abstinence on semen quality. For the purpose of this systematic review, all data related to sexual abstinence duration and seminal parameters were re-analysed to homogenize the current data. Thorough PubMed, MEDLINE and Google Scholar, a literature search was conducted using the keywords "sexual abstinence", "ejaculatory abstinence", "semen", "spermatozoa", "semen analysis", "sperm parameters", "motility", "reactive oxygen species (ROS)" and "DNA fragmentation". After carefully reviewing all the literature, 30 relevant papers, both written in English and published between January 1979 and December 2016, were included in this review. The weight of the evidence suggests that the decline in semen volume and sperm concentration with shorter abstinence periods is accompanied by a substantial improvement in sperm motility characteristics, especially progressive motility and velocity. Nevertheless, available data are insufficient to support definitive conclusions regarding the influence of the ejaculatory abstinence period on advanced semen parameters (ROS, DNA fragmentation and seminal plasma antioxidant capacity) and pregnancy rates. In conclusion, taking all data into account, shortening of the abstinence period may be beneficial to sperm quality. Furthermore, we recommend that the current guidelines regarding the prescribed abstinence period should be revisited.

Automatic classification of human sperm head morphology

BACKGROUND AND OBJECTIVE

Infertility is a problem that affects up to 15% of couples worldwide with emotional and physiological implications and semen analysis is the first step in the evaluation of an infertile couple. Indeed the morphology of human sperm cells is considered to be a clinical tool dedicated to the fertility prognosis and serves, mainly, for making decisions regarding the options of assisted reproduction technologies. Therefore, a complete analysis of not only normal sperm but also abnormal sperm turns out to be critical in this context. This paper sets out to develop, implement and calibrate a novel methodology to characterize and classify sperm heads towards morphological sperm analysis. Our work is aimed at focusing on a depth analysis of abnormal sperm heads for fertility diagnosis, prognosis, reproductive toxicology, basic research or public health studies.

METHODS

We introduce a morphological characterization for human sperm heads based on shape measures. We also present a pipeline for sperm head classification, according to the last Laboratory Manual for the Examination and Processing of Human Semen of the World Health Organization (WHO). In this sense, we propose a two-stage classification scheme that permits to classify sperm heads among five different classes (one class for normal sperm heads and four classes for abnormal sperm heads) combining an ensemble strategy for feature selection and a cascade approach with several support vector machines dedicated to the verification of each class. We use Fisher's exact test to demonstrate that there is no statistically significant differences between our results and those achieved by domain experts.

RESULTS

Experimental evaluation shows that our two-stage classification scheme outperforms some state-of-the-art monolithic classifiers, exhibiting 58% of average accuracy. More interestingly, on the subset of data for which there is a total agreement between experts for the label of the samples, our system is able to provide 73% of average classification accuracy.

CONCLUSIONS

We show that our system behaves like a human expert; therefore it can be used as a supplementary source for labeling new unknown data. However, as sperm head classification is still a challenging issue due to the uncertainty on the class label of each sperm head, with the consequent high degree of variability among domain experts, we conclude that there are still opportunities for further improvement in designing a more accurate system by investigating other feature extraction methods and classification schemes.

Foreword to Sperm morphometrics today and tomorrow special issue in Asian Journal of Andrology

Early in his investigations, Leeuwenhoek (1670s)1 deduced that spermatozoa were alive and an integral part of semen, rather than artifacts or parasites. He eventually observed spermatozoa in the semen of men, dogs, horses, birds, fishes, amphibians, molluscs, and many insects, and concluded that they must be a universal feature of male reproduction. The huge differences in sperm form among species have been discussed in relation to evolutionary changes dictated by the egg and its investments.2 Spallanzani (1800s)1 was the first scientist to develop successful methods for artificial insemination, first with amphibians and later with dogs. With these experiments, he showed that physical contact between intact spermatozoa and ova was necessary to achieve the fertilization. Some years later (1820s), Prévost and Dumas1 performed the defining experiment to identify correctly the function of spermatozoa in reproduction.

Automatic detection and segmentation of sperm head, acrosome and nucleus in microscopic images of human semen smears

BACKGROUND AND OBJECTIVE

Manual assessment of sperm morphology is subjective and error prone so developing automatic methods is vital for a more accurate assessment. The first step in automatic evaluation of sperm morphology is sperm head detection and segmentation. In this paper a complete framework for automatic sperm head detection and segmentation is presented.

METHODS

After an initial thresholding step, the histogram of the Hue channel of HSV color space is used, in addition to size criterion, to discriminate sperm heads in microscopic images. To achieve an improved segmentation of sperm heads, an edge-based active contour method is used. Also a novel tail point detection method is proposed to refine the segmentation by locating and removing the midpiece from the segmented head. An algorithm is also proposed to separate the acrosome and nucleus using morphological operations. Dice coefficient is used to evaluate the segmentation performance. The proposed methods are evaluated using a publicly available dataset.

RESULTS

The proposed method has achieved segmentation accuracy of 0.92 for sperm heads, 0.84 for acrosomes and 0.87 for nuclei, with the standard deviation of 0.05, which significantly outperforms the current state-of-the-art. Also our tail detection method achieved true detection rate of 96%.

CONCLUSIONS

In this paper we presented a complete framework for sperm detection and segmentation which is totally automatic. It is shown that using active contours can improve the segmentation results of sperm heads. Our proposed algorithms for tail detection and midpiece removal further improved the segmentation results. The results indicate that our method achieved higher Dice coefficients with less dispersion compared to the existing solutions.

Gold-standard and improved framework for sperm head segmentation

Semen analysis is the first step in the evaluation of an infertile couple. Within this process, an accurate and objective morphological analysis becomes more critical as it is based on the correct detection and segmentation of human sperm components. In this paper, we present an improved two-stage framework for detection and segmentation of human sperm head characteristics (including acrosome and nucleus) that uses three different color spaces. The first stage detects regions of interest that define sperm heads, using k-means, then candidate heads are refined using mathematical morphology. In the second stage, we work on each region of interest to segment accurately the sperm head as well as nucleus and acrosome, using clustering and histogram statistical analysis techniques. Our proposal is also characterized by being fully automatic, where a user intervention is not required. Our experimental evaluation shows that our proposed method outperforms the state-of-the-art. This is supported by the results of different evaluation metrics. In addition, we propose a gold-standard built with the cooperation of a referent expert in the field, aiming to compare methods for detecting and segmenting sperm cells. Our results achieve notable improvement getting above 98% in the sperm head detection process at the expense of having significantly fewer false positives obtained by the state-of-the-art method. Our results also show an accurate head, acrosome and nucleus segmentation achieving over 80% overlapping against hand-segmented gold-standard. Our method achieves higher Dice coefficient, lower Hausdorff distance and less dispersion with respect to the results achieved by the state-of-the-art method.

Sperm morphology assessment using David's classification: time to switch to strict criteria? Prospective comparative analysis in a selected IVF population

The aim of this study was to compare assessment of sperm morphology by using David's classification (DC), a method of manual analysis most common in France, with a computer-assisted method (Integrated Visual Optical System) based on the strict criteria (CASA SC) for their ability to predict fertilization in a selected in vitro fertilization (IVF) population. A total of 120 couples engaged in IVF protocols were prospectively included in the study. To focus mainly on sperm morphology, couples were excluded in cases of abnormalities of sperm concentration and/or motility and immunological factors and when a low number of oocytes were collected. Sperm morphology analysis was performed on the day of oocyte retrieval by the same trained biologist. Our results showed a moderate correlation between the two techniques (r = 0.49). The DC sperm morphology analysis was less indicative of fertilization than CASA SC (r = 0.07, p = 0.47 vs. r = 0.22, p = 0.014). Using receiver-operating characteristics analysis, we showed that DC was not discriminating in the prediction of fertilization (AUC = 0.572). DC seemed less appropriate for the prediction of fertilization success or failure. In contrast, with CASA SC, the previously determined cut-off value of around 14% was confirmed (AUC = 0.735, cut-off = 6%). Our results argue in favour of the replacement of DC by SC to tend towards worldwide standardization.

[Which assisted reproduction technique as a function of sperm morphology?]

Semen analysis is routinely part of the evaluation of male fertility and includes sperm morphology. How sperm morphology can be a diagnostic tool to decide which ART to apply for infertile couples (insemination, classical IVF or ICSI)? Teratozoospermia has been reported to be one of the most relevant semen parameters of clinical interest compared with sperm concentration and sperm motility. However, the true potential of this parameter has some limitations because of several methodological factors: differences in the classification systems, influence of the staining method used, subjective nature of evaluation of sperm morphology, regular decreasing of the WHO threshold. According to Tygerberg strict criteria that is the most frequently used classification worldwide, poor fertilization has been reported when the rate of normal forms was less or equal to 4%, suggesting to perform ICSI. However, influence of sperm morphology on fertilization outcome remains much debated. Regarding David's classification, the threshold of 30% does seem helpful to discriminate in the prediction of fertilization success and should probably be reconsidered.

Comparison of three staining methods for the morphological evaluation of human spermatozoa

OBJECTIVE

To compare different staining methods to evaluate human sperm morphology.

DESIGN

Prospective study.

SETTING

Patients at the Departments of Dermatology and Urology, University of Jena, Germany.

PATIENT(S)

A total of 94 randomly collected patients attending the andrological outpatient clinics of the Departments of Dermatology and Urology, University of Jena, Germany.

INTERVENTION(S)

None.

MAIN OUTCOME MEASURE(S)

Statistical comparison of resultant standard morphological parameters (mean percentages) after staining according to Papanicolaou and Shorr methods and with Testsimplets prestained slides.

RESULT(S)

All morphological parameters investigated (percent normal morphology, percent head, midpiece, and flagellar abnormalities) correlated statistically significantly positively, however with markedly lower correlation coefficients for the Testsimplets results. As compared with the mean Papanicolaou (4.78% +/- 2.54%) and Shorr staining (4.75% +/- 2.64%) results, a statistically significantly lower percentage of morphologically normal spermatozoa was determined after using the Testsimplets slides (3.89% +/- 2.53%). In general, the mean values of all parameters differed for all comparisons with the Testsimplets slides and especially for the percentage of flagellar defects but not between the Papanicolaou and the Shorr staining results.

CONCLUSION(S)

The results show an extensive agreement between the Papanicolaou- and Shorr-stained smears, whereas Testsimplets staining exhibited statistically significant deviations. Because the correct evaluation of sperm morphology is of essence within the scope of assisted reproduction and in andrological diagnostics, the use of rapid staining methods cannot be recommended.

Mitochondrial membrane potential integrity and plasma membrane translocation of phosphatidylserine as early apoptotic markers: a comparison of two different sperm subpopulations

OBJECTIVE

To examine whether a relationship exists between loss of mitochondrial transmembrane potential and plasma membrane translocation of phosphatidylserine (PS) in subpopulations of human spermatozoa of men consulting for infertility.

SETTING

A tertiary institutional research center.

DESIGN

Prospective observational study.

PATIENT(S)

Twelve infertile men and five fertile controls were compared.

INTERVENTION(S)

Sperm subpopulations were compared after density gradient separation.

MAIN OUTCOME MEASURE(S)

Mitochondrial membrane potential was measured with a cationic dye, translocation of PS was evaluated with Annexin-V binding, and motion parameters were assessed manually.

RESULT(S)

In both the study and control groups and compared with the high-motility fraction, the low-motility fraction had significantly lower sperm motility and normal morphology, and significantly higher percentage of cells with disrupted mitochondrial membrane potential and plasma membrane PS translocation. There was a positive and significant correlation in both subfertile and control groups between the percentages of Annexin-V+ live cells and cells with mitochondrial membrane potential disruption (r = 0.82 and r = 0.85, respectively).

CONCLUSION(S)

The correlation of plasma membrane PS translocation and loss of mitochondrial membrane potential is suggestive of an early apoptosis phenotype, as is typically observed in somatic cells identified in sperm subpopulations with percentage of low-motile cells. We speculate that such changes might be used as diagnostic markers of sperm dysfunction(s) and that increased levels found in subfertile men might be indicators of reduced fertility potential.

Comparison of three computer methods of sperm head analysis

OBJECTIVE

Analysis of sperm heads using three different computer morphometrical tools and experimental conditions to find a more reliable and secure strategy among them.

DESIGN

Controlled experiments on sperm morphology analysis from volunteers.

SETTING

Laboratory of microscopy and imaging processing.

PATIENT(S)

Ten human semen samples donated by different zoospermic men.

INTERVENTION(S)

Semen samples were collected by masturbation after > or =72 hours of abstinence.

MAIN OUTCOME MEASURE(S)

Spermatozoon head morphology was compared by the use of different video-microscopy systems, three computer programs, and various staining conditions and manipulation by different operators. Nonbiological material in the form of latex beads was also used.

RESULT(S)

The data obtained suggest that the semiautomatic computer program is the most reliable and secure method for performing sperm analysis, besides the fact that it is a fast process compared with manual methods.

CONCLUSION(S)

Computer systems of sperm analysis should incorporate a step of interactive object identification to work properly, allowing the operator to confirm or correct possible computer misidentification. The latex beads were used to confirm the capability of all three computer programs to correctly evaluate nonbiological material.

The effects of subinguinal varicocelectomy on Kruger morphology and semen parameters

PURPOSE

We studied the effect of varicocele ligation on Kruger strict morphology criteria and semen parameters in patients with infertility.

MATERIALS AND METHODS

A total of 90 patients diagnosed with varicoceles and a normal morphological sperm ratio of less than 14% were evaluated before and 6 months after varicocelectomy. Preoperatively and postoperatively sperm density, motility and morphology using Kruger strict criteria were analyzed. The Wilcoxon test was used to measure levels of statistical significance in all analyses.

RESULTS

Significant improvement in sperm concentration and motility was evident after varicocele ligation (p <0.0002 and <0.0001, respectively). Using the Kruger classification sperm morphology evaluation revealed a significant increase in the percent of normal forms, and of forms with head and acrosome defects (p <0.0001, <0.0014 and <0.0028, respectively). There were no concomitant changes in strict morphology in forms with mid piece and tail defects or immature forms (p >0.05). Of the 90 patients 18 (20%) achieved a successful full-term pregnancy, including 14 via natural cycle intercourse and 4 by intrauterine insemination.

CONCLUSIONS

Surgical correction of varicocele was associated with significant improvement in density, motility and sperm morphology evaluated using the Kruger classification.

Assessment of human sperm morphology by strict criteria: comparison of wet preparation versus stained with the modified Diff-Quik method

Routine semen examination remains an important tool for the diagnosis and treatment in human subfertility. Of all semen parameters, sperm morphology seems to be one of the most powerful indicators of a man's fertilizing potential in vitro and in vivo. Lack of standardization of sperm morphology assessments remains the main reason for the usefulness of this parameter. The aim of this study was to analyze the agreement between the wet-stained preparations versus those stained with modified Diff-Quik for sperm morphology. A total of 100 unselected semen samples from infertile couples were analyzed. Sperm morphology was evaluated with unstained specimens and following modified Diff-Quik staining according to the strict (Kruger classification) criteria by two different examiners (intralaboratory blind assessment). Mean percentages of morphologically normal spermatozoa were identical on wet and stained preparation slides (4.79 vs. 4.61, p >.05). Wide divergence of results was found with respect to the percentage of sperm with head and midpiece defects with the two different preparations (p >.001). The percentage of sperm tail defects was similar in both methods (p >.05). Simple linear regression analysis between the two methods revealed very good correlation for the morphologically normal spermatozoa (r =.83), but poor correlation for the sperm head, midpiece, and tail defects (r =.25,.25, and.28, respectively). Wet preparation is suitable only for the morphologically normal spermatozoa, but to determine the percentage of the defective spermatozoa, staining the smear is recommended.

Comparison of normal sperm morphology outcomes from two different computer-assisted semen analysis systems

By eliminating the human evaluation variable, it was possible to carry out an investigation into the 'true' association between normal sperm morphology outcomes assessed according to the World Health Organization guidelines and strict criteria. Two computer-assisted semen analysis systems were used, IVOS and Mika, to evaluate Diff-Quik and Papanicolaou stained slides. As expected, the mean normal sperm morphology outcomes for the World Health Organization classification evaluations were markedly higher for both the Diff-Quik (mean difference = 40.13%) and the Papanicolaou (mean difference = 32.55%) stained slides. The association between the outcomes were low for the Diff-Quik stained slides (r = 0.379) and poor for the Papanicolaou stained slides (r = 0.110). While the association achieved with the computer-assisted semen analysis systems using Diff-Quik stained slides was comparable to the association between the manual evaluations (r = 0.386), the manual evaluation of Papanicolaou stained slides produced a relatively good association (r = 0.690). Although the numbers were small, the results show the probability of poor class correlations. Approximately 40% of outcomes were incorrectly classed at a 14% (strict criteria) and 50% (World Health Organization guidelines) cut-off point for both staining methods. This study confirms the fundamental differences between the two classification systems. The results also indicate that, of the two stains used, Diff-Quik should be the preferred staining method for computer-assisted sperm morphology evaluations.

Results of the American Association of Bioanalysts national proficiency testing programme in andrology

Proficiency testing samples for antisperm antibodies (ASAB), sperm count, morphology and vitality were mailed to participating laboratories. The majority participating utilized Immunobead ASAB procedures (81 versus 14% mixed antiglobulin reaction and 5% 'other'), and there was 95.6 +/- 1.2% agreement on the presence or absence of ASAB. The majority of laboratories utilized manual (79%) versus computer assisted semen analysis (CASA; 15%) methods. Approximately 64% used the haemocytometer and 26% used the Makler counting chambers for manual counts. Coefficients of variation (CV) in sperm counts ranged from 24 to 138%, with CASA displaying lower overall CV (53 +/- 8%) than manual methods (80 +/- 9%). A wide variation in the reports of percent normal morphology was noted (CVs calculated from arc sin transformed means ranged from 15 to 93%). Participants using American Society of Clinical Pathologists (ASCP) criteria reported sperm morphology values that were clustered in the 'normal' range (11 out of 12 samples), while those using strict criteria were clustered in the 'abnormal' range (10 out of 12 samples). Good agreement was observed in sperm vitality (overall mean CV = 18%). These data highlight the urgent need for improvement in overall quality of andrology testing and indicate that practical proficiency testing programmes can be made available on a large scale.