Semen analysis standardization: is there any problem in Polish laboratories?

Normal sperm head morphometric reference values in fertile Asian males

Sperm head morphology is crucial for male factor infertility diagnosis and assessment of male reproductive potential. Several criteria are available to analyze sperm head morphology, but they are limited by poor methodology comparability and population applicability. This study aimed to explore comprehensive and new normal morphometric reference values for spermatozoa heads in fertile Asian males. An automated sperm morphology analysis system captured 23 152 stained spermatozoa from confirmed fertile males. Of these samples, 1856 sperm head images were annotated by three experienced laboratory technicians as "normal". We employed 14 novel morphometric features to describe sperm head size (head length, head width, length/width ratio, and girth), shape (ellipse intersection over union, girth intersection over union, short-axis symmetry, and long-axis symmetry), area (head, acrosome, postacrosomal areas, and acrosome area ratio), and degrees of acrosome and nuclear uniformity. This straight-forward method for the morphometric analysis of sperm by accurate visual measurements is clinically applicable. The measured parameters present valuable information to establish morphometric reference intervals for normal sperm heads in fertile Asian males. The presented detailed measurement data will be valuable for interlaboratory comparisons and technician training. In vitro fertilization and andrology laboratory technicians can use these parameters to perform objective morphology evaluation when assessing male fertilization potential.

Analytical variability and interpretation of results of a 3-category sperm motility assessment: 5 years' of an Australian external quality assurance programme

RESEARCH QUESTION

How do laboratories perform when assessing sperm motility with a 3-category system and interpreting results as per the fifth edition of the World Health Organization manual (WHO5), and will the use of a 4-category system as per the sixth edition of the WHO manual improve their performance?

DESIGN

Eighty video recordings of sperm samples were sent to over 200 laboratories spanning a 5-year period for the assessment of progressive motility. The results were reviewed relative to the all-laboratory trimmed mean (ALTM) in terms of the minimum and maximum values reported, the coefficient of variation and the proportion of laboratories indicating an abnormal result. A further 20 video recordings were sent over 1 year, with 6-11 laboratories per distribution adjusting to reporting rapid progressive motility using the 4-category system.

RESULTS

For the 3-category system, the videos covered a mean assessed progressive motility range of 12.0-81.1%. The mean difference between the minimum and maximum values per sample was 50.3% and the coefficients of variation were negatively correlated with the ALTM (r = -0.87, P < 0.00001). Progressive motility abnormality reporting formed a sigmoid curve, and the inflection point (50% of laboratories identifying an abnormality) gave an ALTM value of 32.01%. Preliminary results for laboratories using the 4-category system showed no performance improvement but the number of laboratories was small.

CONCLUSIONS

Analytical variation can result in laboratories crossing the clinical cut-off of the lower reference limit for samples whose motility is close to the WHO5 lower reference limit, but is less important for samples with extreme values. The benefits of a 4-category motility system are yet to be shown.

Evaluating an external quality assurance program for semen analysis in China during 2009-2020

INTRODUCTION

Semen analysis (SA) plays a key role in guiding treatments of male reproductive diseases and infertility due to male factors; however, it remains challenging to conduct an accurate SA due to lack of standardization, highly subjective assessments, and problems with automated procedures. Therefore, quality assurance (QA) and teaching courses are essential for making the laboratory results more consistent.

MATERIALS AND METHODS

The external quality assurance (EQA) scheme was organized by national human sperm bank technology training bases in Guangdong province in China between 2009 and 2020. Until 2020, 124 laboratories from China participated in the EQA program. The EQA scheme per year has been organized involving two semen aliquots for sperm concentration, two video recordings for motility, and two smears for sperm morphology. All samples used in the EQA scheme were obtained from different healthy donors or patients.

RESULTS

We estimated that the median coefficient of variation (CV) of sperm concentration, ignoring the method used, was 26.6%. Using a 100 µm deep counting chamber led to a decreasing CV of 13.6%. For sperm motility, the median CV of nonprogressive motility was high (50.8%), but the CV of progressive motility (13.2%), immotile sperm (14.3%), and total motility (11.8%) were acceptable. The morphology assessment revealed large variability (44.4%) irrespective of the classification criteria.

DISCUSSION

The reduction of interlaboratory variability is still a challenge during SA in China. Therefore, it is critical to increase awareness of joining EQA schemes and establish standardized training centers to follow WHO-recommended procedures toward Chinese standards.

The effect of adjusting settings within a Computer-Assisted Sperm Analysis (CASA) system on bovine sperm motility and morphology results

Semen motility is the most widely recognized semen quality parameter used by Artificial Insemination (AI) centers. With the increasing worldwide export of semen between AI centers there is an increasing need for standardized motility assessment methods. Computer-Assisted Sperm Analysis (CASA) technology is thought to provide an objective motility evaluation; however, results can still vary between laboratories. The aim of present study was to verify the impact of different setting values of the CASA IVOS II on motility, concentration, and morphology of bovine semen samples frozen in an extender with or without egg yolk and then decide on optimal settings for a further validation step across AI centers. Semen straws from 30 different bulls were analyzed using IVOS II with twelve modified settings. No significant changes were observed in semen concentration, percentage of motile sperm or kinetic results for either extender type. However, increasing settings for both STR and VAP progressive (%) from Low, Medium, and High cut-off values significantly (p<0.05) reduced the percentage of detected progressive spermatozoa, in egg yolk extender from 49.5±15.2, 37.2±11.9 to 11.9±5.3%, and in clear extender from 51.9±9.1, 35.8±7.3 to 10.0±2.4%, respectively. In clear extender only, the modification of droplet proximal head length significantly affected the detection of normal sperm percentages (88.0± 4.7 to 95.0±0.6 and 96.0±0.6%) and of the percentage of detected proximal droplets (12.2±4.7, 2.5±2.7 to 0.6±0.2%) for Low, Medium and High values respectively (p<0.05). The identification of sensitivity within the CASA system to changes in set parameters then led to the determination of an optimal IVOS II setting. The existing variability among centers for these phenotypes was reduced when the standardized settings were applied across different CASA units. The results clearly show the importance of applied settings for the final CASA results and emphasize the need for standardized settings to obtain comparable data.

Clinical Update on Home Testing for Male Fertility

Male factor infertility accounts for about 50% of the incidence of infertility in couples. In current practice, the men must attend a clinic or hospital facility to provide a semen analysis, which is key to the diagnosis of the male reproductive potential. However, many men are often embarrassed with the process and conventional semen analysis requires complex, labor intensive inspection with a microscope. To mitigate these problems, one of the solutions can be at-home semen analysis. In this review we examine the literature of currently available at home semen analysis test kits, describe their limitations, and compare them to the conventional lab-based methods.

Performance of four chambers to measure sperm concentration: results from an external quality assurance programme

RESEARCH QUESTION

What are the changes in the use of four types of counting chambers by laboratories enrolled in an Australian-based external quality assurance programme, and what are their accuracy and precision?

DESIGN

Samples of latex beads of known concentration up to 20 × 10⁶/ml were distributed quarterly to enrolled laboratories over a 12-year period. The results of each distribution were then used to calculate a bias relative to the target value as an indicator of accuracy and a coefficient of variation to indicate the level of precision.

RESULTS

The proportion of laboratories in 2007-2008 using improved Neubauer haemocytometers (44%), Makler® (9%) and Vetriplast chambers (19%) remained constant in 2018-2019, unlike Kova chamber users (20%), which reduced. The mean (range) bias of improved Neubauer haemocytometers (-2.8% [-22.5 to +32.0%]) was less than Makler® chambers (+17.0% [-2.9 to +41.2%]), Kova chambers (+33.9% [0.0 to 115.0%]) and Vetriplast chambers (+47.9% [0.0 to 170.0%]). The coefficient of variation of improved Neubauer haemocytometers (14.6% [8.7 to 25.0%]) was less than both Vetriplast (20.7% [8.8 to 36.4%]) and Makler® (24.1% [13.6 to 48.6%]) and Kova chambers (35.5% [15.9 to 123.0%]).

CONCLUSIONS

The improved Neubauer haemocytometer has been shown to be superior in accuracy and precision to the Makler®, Kova and Vetriplast chambers in their estimation of concentrations up to 20 × 10⁶/ml. Users of Makler® chambers, specifically designed for counting spermatozoa, should take care to monitor the performance of their own chambers, whereas Kova and Vetriplast chambers (designed for microscopic urinalysis) should not be used.

The current status and future of andrology: A consensus report from the Cairo workshop group

BACKGROUND

In attempting to formulate potential WHO guidelines for the diagnosis of male infertility, the Evidence Synthesis Group noted a paucity of high-quality data on which to base key recommendations. As a result, a number of authors suggested that key areas of research/evidence gaps should be identified, so that appropriate funding and policy actions could be undertaken to help address key questions.

OBJECTIVES

The overall objective of this Consensus workshop was to clarify current knowledge and deficits in clinical laboratory andrology, so that clear paths for future development could be navigated.

MATERIALS AND METHODS

Following a detailed literature review, each author, prior to the face-to-face meeting, prepared a summary of their topic and submitted a PowerPoint presentation. The topics covered were (a) Diagnostic testing in male fertility and infertility, (b) Male fertility/infertility in the modern world, (c) Clinical management of male infertility, and (d) The overuse of ICSI. At the meeting in Cairo on February 18, 2019, the evidence was presented and discussed and a series of consensus points agreed.

RESULTS

The paper presents a background and summary of the evidence relating to these four topics and addresses key points of significance. Following discussion of the evidence, a total of 36 consensus points were agreed.

DISCUSSION

The Discussion section presents areas where there was further debate and key areas that were highlighted during the day.

CONCLUSION

The consensus points provide clear statements of evidence gaps and/or potential future research areas/topics. Appropriate funding streams addressing these can be prioritized and consequently, in the short and medium term, answers provided. By using this strategic approach, andrology can make the rapid progress necessary to address key scientific, clinical, and societal challenges that face our discipline now and in the near future.

Adherence to WHO 2010 Recommendations in Relation to Semen Analysis Reports in the Laboratories of West Bengal

Background: In 2010, The World Health Organization (WHO) suggested the standards of reporting of semen analysis and the reference values. We tried to determine the adherence to the WHO 2010 standard regarding semen analysis among the laboratories of West Bengal.

Methods: An observational study was carried out by collecting the semen analysis reports from different laboratories. Compliance with the WHO 2010 recommendations regarding the reporting of semen analysis and references mentioned was subsequently analyzed.

Results: A total of 211 laboratory reports were collected; of which 15 were ART (Assisted Reproductive Technology)-laboratories (7%) and 196 were non-ART-laboratories (93%). More than half of the laboratories did not mention any reference values. Only 7.5% used the phrase “WHO 2010” as the reference. Only 3% of the laboratories reported all the six “important” parameters (volume, pH, sperm concentration, motility, morphology and vitality) and used the WHO 2010 references for all of them. The ART laboratories performed significantly better than their non-ART counterparts in reporting and quoting the WHO 2010 reference values.

Conclusion: Even nine years after its introduction, the compliance with the WHO 2010 recommendations on semen analysis was still low among our laboratories. There is need for increased awareness for the laboratory persons in this regard.

The effect of the staining technique on morphological and morphometric parameters of boar sperm

Sperm morphology and morphometry are important parameters in predicting fertility. Sperm are considered to be normal if the shape and size of the head, midpiece and tail fall within the classification for a given species. It is important to select the appropriate technique for staining the semen of a given species, because, as many authors have pointed out, some methods work well for one species but are not suitable for analysing another. The aim of the study was to assess the morphometric parameters of boar sperm following the use of different staining techniques and to verify the hypothesis that the staining technique affects the morphometric parameters of sperm. The staining method was found to significantly affect the dimensions of the boar sperm head. The semen stained by the SpermBlue technique had the closest morphometric sperm head parameters to those of the unstained sperm, so this technique, rather than the routinely used eosin and gentian complex, should be the leading technique in the evaluation of boar sperm morphometry. Silver nitrate staining reveals the structure of the sperm in the most detail; this method can be considered universal, and can be used independently or to supplement routine diagnostics. As the staining technique should interfere as little as possible with the structure of the sperm, while revealing its morphology in as much detail as possible, it is crucial to establish the natural dimensions of the unstained sperm head before determining the optimal technique and its reference values. The recommended or most commonly-used techniques are not always the best options for the staining and analysis of sperm of a given species.

An automated smartphone-based diagnostic assay for point-of-care semen analysis

Male infertility affects up to 12% of the world's male population and is linked to various environmental and medical conditions. Manual microscope-based testing and computer-assisted semen analysis (CASA) are the current standard methods to diagnose male infertility; however, these methods are labor-intensive, expensive, and laboratory-based. Cultural and socially dominated stigma against male infertility testing hinders a large number of men from getting tested for infertility, especially in resource-limited African countries. We describe the development and clinical testing of an automated smartphone-based semen analyzer designed for quantitative measurement of sperm concentration and motility for point-of-care male infertility screening. Using a total of 350 clinical semen specimens at a fertility clinic, we have shown that our assay can analyze an unwashed, unprocessed liquefied semen sample with <5-s mean processing time and provide the user a semen quality evaluation based on the World Health Organization (WHO) guidelines with ~98% accuracy. The work suggests that the integration of microfluidics, optical sensing accessories, and advances in consumer electronics, particularly smartphone capabilities, can make remote semen quality testing accessible to people in both developed and developing countries who have access to smartphones.

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.

[Inter-and intra-operator variability in the analysis of semen parameters: results from a quality control program]

Introduction

L’analyse du sperme est d’une importance majeure dans l’exploration de l'infertilité masculine. Afin de s’assurer de la fiabilité des résultats rendus, l’implantation du management de qualité en spermiologie est devenue une nécessité.Le but de ce travail a été d’évaluer la variabilité intra- et inter-opérateurau cours de l’analyse des paramètres spermatiques au sein de notre laboratoire de spermiologie, à travers la mise en place d’un programme de contrôle de qualité.

Méthodes

Quatre opérateurs ayant des niveaux d’expérience différents ont participé à l’étude. La variabilité inter-individuelle des résultats des lectures de la mobilité, la concentration et la morphologie spermatique a été évaluée sur plusieurs échantillons de sperme de qualités différentes. Pour chaque paramètre spermatique, la variabilité intra-individuelle a été évaluée en analysant les résultats des lectures de plusieurs aliquotes issus de chacun des échantillons utilisés.

Résultats

Les coefficients de variation moyens inter-opérateurs ont été de12.8%, 19.8% et 48.9% pour la mobilité, la concentration et la morphologie spermatique, respectivement. Les coefficients de variation moyens intra-opérateurs ont été de6.9%, 12.3%et 42.7% pour la mobilité, la concentration, et la morphologie spermatique, respectivement. Mis à part quelques écarts (erreurs aléatoires), la plupart des mesures réalisées ont été dans les limites d’acceptabilité pour l’ensemble des opérateurs.La variabilité de l’évaluation morphologique des spermatozoïdes a été particulièrement influencée par le niveau d’expérience de l’opérateur.

Conclusion

Les résultats de cette étude mettent l’accent sur la nécessité d’une formation adéquate du personnel de laboratoire, et de la participation régulière aux contrôles de qualité internes afin de minimiser les divergences et d’améliorer la fiabilité des résultats.

Accuracy Evaluation of The Depth of Six Kinds of Sperm Counting Chambers for both Manual and Computer-Aided Semen Analyses

Background

Although the depth of the counting chamber is an important factor influencing sperm counting, no research has yet been reported on the measurement and comparison of the depth of the chamber. We measured the exact depths of six kinds of sperm counting chambers and evaluated their accuracy.

Materials and Methods

In this prospective study, the depths of six kinds of sperm counting chambers for both manual and computer-aided semen analyses, including Makler (n=24), Macro (n=32), Geoffrey (n=34), GoldCyto (n=20), Leja (n=20) and Cell-VU (n=20), were measured with the Filmetrics F20 Spectral Reflectance Thin-Film Measurement System, then the mean depth, the range and the coefficient of variation (CV) of each chamber, and the mean depth, relative deviation and acceptability of each kind of chamber were calculated by the closeness to the nominal value. Among the 24 Makler chambers, 5 were new and 19 were used, and the other five kinds were all new chambers.

Results

The depths (mean ± SD, μm) of Makler (new), Macro and Geoffrey chambers were 11.07 ± 0.41, 10.19 ± 0.48 and 10.00 ± 0.28, respectively, while those of GoldCyto, Leja and Cell-VU chambers were 23.76 ± 2.15, 20.49 ± 0.22 and 24.22 ± 2.58, respectively. The acceptability of Geoffrey chambers was the highest (94.12%), followed by Macro (65.63%), Leja (35%) and Makler (20%), while that of the other two kinds and the used Makler chamber was zero.

Conclusion

There existed some difference between the actual depth and the corresponding nominal value for sperm counting chambers, and the overall acceptability was very low. Moreover, the abrasion caused by the long use, as of Makler chamber, for example, may result in unacceptability of the chamber. In order to ensure the accuracy and repeatability of sperm concentration results, the depth of the sperm counting chamber must be checked regularly.

'How to count sperm properly': checklist for acceptability of studies based on human semen analysis

STUDY QUESTION

Can a tool be developed for authors, reviewers and editors of the ESHRE Journals to improve the quality of published studies which rely on semen analysis data?

SUMMARY ANSWER

A basic checklist for authors, reviewers and editors has been developed and is presented.

WHAT IS KNOWN ALREADY

Laboratory work which includes semen analysis is burdened by a lack of standardization. This has significant negative effects on the quality of scientific and epidemiological studies, potential misclassification of patients and the potential to impair clinical treatments/diagnoses that rely on accurate semen quality information. Robust methods are available to reduce laboratory error in semen analysis, inducing adherence to World Health Organization techniques, participation in an external quality control scheme and appropriate training of laboratory personnel. However, journals have not had appropriate systems to assess if these methods have been used.

STUDY DESIGN, SIZE, DURATION

After discussion at a series of Associate Editor Meetings of the ESHRE Journals the authors of the present text were asked to propose a tool for authors, reviewers and editors of the ESHRE Journals to ensure a high quality assessment of submitted manuscripts which rely on semen analysis data, including a detailed verification of the relevance and the quality of the methods used.

PARTICIPANTS/MATERIALS, SETTING, METHODS

N/A.

MAIN RESULTS AND THE ROLE OF CHANCE

A basic checklist for authors, reviewers and editors is presented. The checklist contains key points which should be considered by authors when designing studies and which provides essential information for when the submitted manuscript is evaluated. For published articles the answers in the checklist are suitable to be available as supplementary data, which will also reduce the space necessary for technical details in the printed article.

LIMITATIONS, REASONS FOR CAUTION

Guidelines such as these should not be used uncritically. It is therefore important that submitting authors, in situations where their study does not comply with the basic requirements for semen analysis, not only explain all methodological deviations but also declare the level of uncertainty in their analyses and how it complies with, or might confound, the aims of the study.

WIDER IMPLICATIONS OF THE FINDINGS

The fundamental importance of appropriate and robust methodology to facilitate advances in scientific understanding and patient management and treatment, is now accepted as being paramount. Use of the semen analysis checklist should be part of this process, and when completed and signed by the corresponding author at the time of submitting a manuscript should result in greater transparency, and ultimately uniformity. It is hoped that this initiative will pave the way for wider adoption of the methodology/reporting by other biomedical, epidemiological and scientific journals, and ultimately become the standard of practice for papers reporting semen analysis results obtained in laboratory and clinical andrology. Systems to assist referees, authors and editors to present high quality findings should have a significant impact on the field of reproductive medicine.

STUDY FUNDING/COMPETING INTERESTS

No funding was obtained for this work. The authors have no competing interests in relation to the present publication and checklist.

TRIAL REGISTRATION NUMBER

N/A.

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.