Home sperm testing device versus laboratory sperm quality analyzer: comparison of motile sperm concentration

Amateur vs Professional Users of the YO Home Sperm Test: An Assessment of Usability

OBJECTIVE

To assess the accuracy of the YO home sperm test by real-world/amateur users.

METHODS

This multisite study investigated whether amateur users could use the FDA-cleared YO Home Sperm Test to obtain accurate motile sperm concentration (MSC) results when compared to trained laboratory technicians. The qualitative MSC results of amateur and professional YO users were compared to each other as well as to the results of an established automated sperm quality analyzer (SQA-V) above and below a 6 m/mL MSC cut-off.

RESULTS

This was a blinded, prospective study of 316 amateur users and 3 professional laboratory technicians across 3 study sites. Amateur vs Professional YO users demonstrated an accuracy of >97%. Qualitative results of amateurs and professionals vs SQA-V results showed a >95.7% accuracy.

CONCLUSION

Amateur users with no prior training were able to follow the YO test directions to receive highly accurate qualitative motile sperm concentration (MSC) results. The YO test is user-friendly and can be used as an effective initial home screening tool to gain preliminary insight into the fertility status of the male in a real-world setting. Furthermore, the YO test results correlated with those obtained by the FDA-cleared SQA-V laboratory analyzer, confirming that the YO test delivers accurate MSC results in the hands of amateur users.

Contraceptive efficacy: Determining the threshold for effective suppression based on sperm concentration, motility, and morphology

INTRODCTION

Human spermatogenesis is a complex process that transforms spermatogonial stem cells through mitosis and meiosis to spermatozoa. Testosterone is the key regulator of the terminal stages of meiosis, adherence of spermatids to Sertoli cells, and spermiation. Follicle-stimulating hormone (FSH) may be required for early spermatogenesis and is important for maintaining normal spermatogenesis in men. Hormonal contraception suppresses FSH, luteinizing hormone, and intratesticular testosterone concentration, resulting in marked suppression of sperm output.

RESULTS

Clinical trials using testosterone alone or testosterone plus progestin demonstrate that sustained suppression of sperm concentration to ≤1 million/mL is sufficient to prevent pregnancy in the female partner. New agents that target spermatogenesis could use this as a target for contraceptive efficacy while others that block sperm function or transport may require a lower threshold. When sperm concentrations are suppressed to such low levels, measurement of sperm motility and morphology is technically difficult and unnecessary. With current data from fertile and infertile men, it is not possible to establish a lower limit of sperm motility or percent normal morphology that equates to the prevention of conception. New compounds that decrease sperm motility or alter sperm morphology may need to demonstrate a complete absence of sperm motility or altered morphology in all spermatozoa in the ejaculate. Sperm function tests may be useful depending on the mechanism of action of each new compound.

CONCLUSION

Monitoring of sperm surrogate markers to ensure effective contraception relies on laboratories experienced in semen analyses. The development of at-home tests to assess sperm parameters has progressed rapidly. Some tests have been assessed in clinical trials and approved by regulatory agencies for at-home use for fertility assessment. However, caution must be exercised in using these tests as many have not been rigorously validated against semen parameters measured in laboratories by trained technologists using standardized tests defined in the World Health Organization Semen Manual.

Biomarker-based human and animal sperm phenotyping: the good, the bad and the ugly†

Conventional, brightfield-microscopic semen analysis provides important baseline information about sperm quality of an individual; however, it falls short of identifying subtle subcellular and molecular defects in cohorts of "bad," defective human and animal spermatozoa with seemingly normal phenotypes. To bridge this gap, it is desirable to increase the precision of andrological evaluation in humans and livestock animals by pursuing advanced biomarker-based imaging methods. This review, spiced up with occasional classic movie references but seriously scholastic at the same time, focuses mainly on the biomarkers of altered male germ cell proteostasis resulting in post-testicular carryovers of proteins associated with ubiquitin-proteasome system. Also addressed are sperm redox homeostasis, epididymal sperm maturation, sperm-seminal plasma interactions, and sperm surface glycosylation. Zinc ion homeostasis-associated biomarkers and sperm-borne components, including the elements of neurodegenerative pathways such as Huntington and Alzheimer disease, are discussed. Such spectrum of biomarkers, imaged by highly specific vital fluorescent molecular probes, lectins, and antibodies, reveals both obvious and subtle defects of sperm chromatin, deoxyribonucleic acid, and accessory structures of the sperm head and tail. Introduction of next-generation image-based flow cytometry into research and clinical andrology will soon enable the incorporation of machine and deep learning algorithms with the end point of developing simple, label-free methods for clinical diagnostics and high-throughput phenotyping of spermatozoa in humans and economically important livestock animals.

Introducing a New Smartphone Applied Semen Analyzer, SpermCell™: A Cross-Sectional Validation Study with a Comparative Analysis and a Mini Patient Questionnaire on a Large Sample Cohort

(1) Background: Standard semen analysis methods may exhibit variability between observers and/or human error; therefore, additional methods are needed to overcome these handicaps. We aimed to present a new smartphone-applied semen analyzer, Sperm Cell™, investigate its diagnostic efficacy by comparing it with the standard analysis method, and determine its user-friendly nature. (2) Methods: A cross-sectional study was conducted on a large sample cohort, including 102 men. Three semen analyses were performed for each semen sample. The first employed the standard manual method, whereas the others were smartphone-based analyses performed by technicians and patients. We compared major semen parameters between the three semen analyses. The user-friendly nature of the analyzer was also evaluated with a mini-questionnaire completed by the participants. (3) Results: The determined median sperm count, motile sperm count, and percentage of motile sperms, on standard manual semen analysis, were 50.00 × 106/mL (0-160 × 106/mL), 23.94 × 106/mL (0-108 × 106/mL) and 50.00% (0-73.00%), respectively. Median sperm count and motile sperm count were 50.52 × 106/mL (<1-150 × 106/mL) vs. 55.77 × 106/mL (<1-160 × 106/mL) and 23.34 × 106/mL (0-105 × 106/mL) vs. 23.53 × 106/mL (0-104 × 106/mL) for SpermCell™-based semen analysis performed by a technician and patients themselves, respectively. The percentages of motile sperms were 47.40% (0-67.00%) vs. 47.61% (0-80.20%), respectively. All the parameters were statistically similar between the three semen analysis methods (p > 0.05 for each). The SpermCell™ analysis results were correlated with the standard manual method with up to 0.85 correlation coefficients. Moreover, substantial diagnostic accuracy, sensitivity and specificity were obtained in determining the oligospermia and asthenozoospermia via the device-based analyses performed by technician and patients. The mini-questionnaire results revealed that the analyzer is useful. (4) Conclusions: The novel smartphone-applied semen analyzer is a helpful tool with acceptable diagnostic accuracy in determining the major semen parameters. It can be used as an efficient at-home point-of-care testing method in the initial assessment of couples with infertility concerns.

Artificial Intelligence in Andrology: From Semen Analysis to Image Diagnostics

Artificial intelligence (AI) in medicine has gained a lot of momentum in the last decades and has been applied to various fields of medicine. Advances in computer science, medical informatics, robotics, and the need for personalized medicine have facilitated the role of AI in modern healthcare. Similarly, as in other fields, AI applications, such as machine learning, artificial neural networks, and deep learning, have shown great potential in andrology and reproductive medicine. AI-based tools are poised to become valuable assets with abilities to support and aid in diagnosing and treating male infertility, and in improving the accuracy of patient care. These automated, AI-based predictions may offer consistency and efficiency in terms of time and cost in infertility research and clinical management. In andrology and reproductive medicine, AI has been used for objective sperm, oocyte, and embryo selection, prediction of surgical outcomes, cost-effective assessment, development of robotic surgery, and clinical decision-making systems. In the future, better integration and implementation of AI into medicine will undoubtedly lead to pioneering evidence-based breakthroughs and the reshaping of andrology and reproductive medicine.

Application of artificial intelligence in gametes and embryos selection

Gamete and embryo quality are critical to the success rate of Assisted Reproductive Technology (ART) cycles, but there remains a lack of methods to accurately measure the quality of sperm, oocytes and embryos. The ability of Artificial Intelligence (AI) technology to analyze large amounts of data, especially video and images, is particularly useful in gamete and embryo assessment and selection. The well-trained model has fast calculation speed and high accuracy, which can help embryologists to perform more objective gamete and embryo selection. Various artificial intelligence models have been developed for gamete and embryo assessment, some of which exhibit good performance. In this review, we summarize the latest applications of AI technology in semen analysis, as well as selection for sperm, oocyte and embryo, and discuss the existing problems and development directions of artificial intelligence in this field.

Evolution of the basic semen analysis and processing sperm

PURPOSE OF REVIEW

The sixth edition of the World Health Organization (WHO) laboratory manual for the examination and processing of human semen was recently published with specific step-by-step instructions for semen evaluation and sperm processing. Point-of-care (POC) testing for semen evaluation and microfluidics for sperm processing are rapidly evolving technologies that could impact how we evaluate and process sperm. Understanding the updated manual in the context of these novel technologies is important.

RECENT FINDINGS

Proper standardization of semen evaluation and sperm processing will allow for consistent high-quality results among laboratories worldwide. POC testing could improve access to semen evaluations that generate referrals to male infertility specialists for further assessment. Microfluidics can select functional sperm with decreased DNA fragmentation in semen and testicular biopsy samples for assisted reproductive technology (ART). Clinical outcomes, such as pregnancy rates and live birth rates, have not been shown to be consistently improved with these technologies compared to conventional techniques, although high level evidence research in this area is limited.

SUMMARY

POC testing and microfluidics have the potential to be combined with machine learning technologies to improve fertility care. If these technologies are appropriately optimized, they could change how we evaluate and process sperm, and potentially lead to improved ART outcomes.

The Future Is Coming: Artificial Intelligence in the Treatment of Infertility Could Improve Assisted Reproduction Outcomes-The Value of Regulatory Frameworks

Infertility is a global health issue affecting women and men of reproductive age with increasing incidence worldwide, in part due to greater awareness and better diagnosis. Assisted reproduction technologies (ART) are considered the ultimate step in the treatment of infertility. Recently, artificial intelligence (AI) has been progressively used in the many fields of medicine, integrating knowledge and computer science through machine learning algorithms. AI has the potential to improve infertility diagnosis and ART outcomes estimated as pregnancy and/or live birth rate, especially with recurrent ART failure. A broad-ranging review has been conducted, focusing on clinical AI applications up until September 2022, which could be estimated in terms of possible applications, such as ultrasound monitoring of folliculogenesis, endometrial receptivity, embryo selection based on quality and viability, and prediction of post implantation embryo development, in order to eliminate potential contributing risk factors. Oocyte morphology assessment is highly relevant in terms of successful fertilization rate, as well as during oocyte freezing for fertility preservation, and substantially valuable in oocyte donation cycles. AI has great implications in the assessment of male infertility, with computerised semen analysis systems already in use and a broad spectrum of possible AI-based applications in environmental and lifestyle evaluation to predict semen quality. In addition, considerable progress has been made in terms of harnessing AI in cases of idiopathic infertility, to improve the stratification of infertile/fertile couples based on their biological and clinical signatures. With AI as a very powerful tool of the future, our review is meant to summarise current AI applications and investigations in contemporary reproduction medicine, mainly focusing on the nonsurgical aspects of it; in addition, the authors have briefly explored the frames of reference and guiding principles for the definition and implementation of legal, regulatory, and ethical standards for AI in healthcare.

Assessment of sperm motility in livestock: Perspectives based on sperm swimming conditions in vivo

Evaluation of sperm motility is well-established in farm animals for quickly selecting ejaculates for semen processing into insemination doses and for evaluating the quality of preserved semen. Likewise, sperm motility is a fundamental parameter used by spermatologists in basic and applied science. Motility is commonly assessed using computer-assisted semen analysis (CASA). Recent increases in computational power, as well as utilization of mobile CASA systems and open-source CASA programs, broaden the possibilities for motility evaluation. Despite this technological progress, the potential of computer-generated motility data to assess male fertility remains challenging and may be limited. Relevance for fertility assessment could be improved if measurement conditions would more closely mimic the in vivo situation. Hence, this review is focused on the current trends of automated semen assessment in livestock and explores perspectives for future use with respect to the physiological and physical conditions encountered by sperm in the female reproductive tract. Validation of current CASA systems with more complex, microfluidic-based devices mimicking the female reproductive tract environment could improve the value of sperm kinematic data for assessing the fertilizing capacity of semen samples, not only for application in livestock but also for use in conducting assisted reproduction techniques in other species.

Smartphone in medicine — from a reference book to a diagnostic system. Overview of the current state of the issue

The paper provides a brief overview of the modern possibilities of using a smartphone as a diagnostic device of a wide profile. In some cases, additional specialized attachments are required. In others, the diagnostic algorithm uses only standard cameras, a microphone and various built-in smartphone sensors. The development of the smartphone integration into the healthcare system is modern, relevant and very promising, given the widespread use of smartphones among the global population.

Increase in Direct-to-Consumer Telemedicine in Urology

Purpose of Review

Direct-to-consumer telemedicine has vastly expanded in recent years, and urologic conditions are a common target for these companies. We aim to identify the urologic conditions being treated by direct-to-consumer telemedicine platforms and review the feasibility of adherence to evidence-based practice guidelines via this relatively new healthcare model.

Recent Findings

Erectile dysfunction, premature ejaculation, testosterone deficiency, and male infertility are being treated with direct-to-consumer telemedicine. Such platforms treating erectile dysfunction perform modestly in practice guideline adherence. Guidelines-based treatment of other urologic conditions via telemedicine is feasible, however, the treatment of these conditions through popular direct-to-consumer telemedicine platforms is largely unstudied.

Summary

The impact of direct-to-consumer telemedicine on the field of urology is vast and likely to continue to grow. Future studies should inspect direct-to-consumer telemedicine companies’ practice patterns and treatment outcomes to ensure the field’s standards of care are being met. Guidelines specific to the treatment of various urologic conditions via telemedicine are needed.

A Sperm Quality Detection System Based on Microfluidic Chip and Micro-Imaging System

Sperm quality assessment is the main method to predict the reproductive ability of livestock. The detection of sperm quality of livestock is of great significance to the application of artificial insemination and in vitro fertilization. In order to comprehensively evaluate sperm quality and improve the real-time and portability of sperm quality detection, a portable microscopic imaging system based on microfluidic chip is developed in this paper. The system can realize the comprehensive evaluation of sperm quality by detecting sperm vitality and survival rate. On the hardware side, a microfluidic chip is designed, which can automatically mix samples. A set of optical system with a magnification of 400 times was developed for microscopic observation of sperm. In the aspect of software, aiming at the comprehensive evaluation of sperm quality based on OpenCV, a set of algorithms for identifying sperm motility and survival rate is proposed. The accuracy of the system in detecting sperm survival rate is 94.0%, and the error rate is 0.6%. The evaluation results of sperm motility are consistent with those of computer-aided sperm analysis (CASA). The system's identification time is 9 s. Therefore, the system is absolutely suitable for sperm quality detection.

Extended semen examinations in the sixth edition of the World Health Organization manual on semen analysis: contributing to the understanding of the function of the male reproductive system

In the sixth edition of the World Health Organization manual for the examination and processing of human semen, extended examination methods to provide key diagnostics in the investigation of the male reproductive system function are elaborated. These go beyond the basic analysis of semen and may be useful in more specifically guiding the clinical characterization of fertile or infertile men. Among the extended examinations included in the chapter, the use of multiparametric scoring for sperm morphological defects, sperm DNA fragmentation, and the roles for computer-assisted analysis of sperm or semen are arguably those that will be the most widely used and may also cause the most debate.

Effect of keishibukuryogan combined with tocopherol nicotinate on sperm parameters in patients with a varicocele

OBJECTIVE

To evaluate the efficacy of keishibukuryogan, a traditional Kampo formula known to be an anti-Oketsu (impaired microcirculation and non-physiological blood congestion) drug, in combination with an anti-oxidant for the treatment of varicoceles.

METHODS

We retrospectively analyzed 119 patients with palpable and subclinical varicoceles who were treated with 7.5 g/day of keishibukuryogan and 600 mg/day of tocopherol nicotinate. Their motile sperm concentrations at the start of medication and after 3 months were compared. As a subgroup analysis, a comparison test was carried out between patients with a high-grade varicocele and those with a low-grade varicocele.

RESULTS

The mean age of the study patients was 35.6 years. Among them, 17, 41, 44 and 17 had subclinical, grade 1, grade 2 and grade 3 varicoceles, respectively. Overall, the differences in motile sperm concentration (millions/mL) before and after treatment were not significant (median 0.58, 95% confidence interval -0.12 to 1.56; P = 0.115). The results of the subgroup analysis showed that the motile sperm concentration in patients with a low-grade varicocele significantly increased (median 1.21, 95% confidence interval 0.45-2.47; P = 0.024); however, no significant improvements were seen in patients with a high-grade varicocele.

CONCLUSIONS

The results of the present study showed that the combination of keishibukuryogan and an anti-oxidant had a limited effect on varicoceles, but they suggest that it is effective for the treatment of low-grade varicoceles.

Accuracy comparison study of new smartphone-based semen analyzer versus laboratory sperm quality analyzer

Purpose

This study aimed to test the clinical efficacy of a portable smartphone-based App assisted semen analysis (SA) system, O'VIEW-M PRO® to clinically accurate in comparison with results of laboratory-based conventional semen analyses including manual microscopic and computer-assisted semen analysis (CASA) for self-evaluation of seminal parameters.

Materials and Methods

From January to May 2021, a total of 39 semen samples were analyzed for the sperm concentration and motility with new smartphone-based App assisted semen analyzer, O'VIEW-M PRO®, and results compared with those from laboratory-based manual microscopic SA with Makler Counting Chamber and CASA.

Results

The coefficient factors among the results of the measurement with Makler chamber and laboratory-based CASA comparing to O'VIEW-M PRO® were 0.666 and 0.655 for sperm density, 0.662 and 0.658 for sperm motility, respectively. There were no particular problems with clinical use of the O'VIEW-M PRO®. Device performance in classifying samples is positive (<15×10⁶ sperm/mL) and negative (>15×10⁶ sperm/mL) for sperm concentration criteria, and positive (<40%) and negative (>40%) for sperm motility criteria. The smartphone-based App assisted SA O'VIEW-M PRO® showed a sensitivity of 92.6%, a specificity of 66.7%, and overall accuracy rate of 84.6%.

Conclusions

This study shows a novel smartphone-based App assisted SA system. O'VIEW-M PRO® can easily obtain semen parameter information through self-diagnosis at home and induce infertile men's treatment and help patients after receiving infertile men's treatment before receiving treatment.

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.

Perceptions of Infertility and Semen Analysis Testing Among American Men Without Children

OBJECTIVE

To determine whether health-conscious men are more likely to be concerned about infertility and self-initiate semen analysis at a laboratory/clinic or through a direct-to-consumer at-home product without a health care provider recommendation.

METHODS

Cross-sectional survey conducted online via ResearchMatch.org between November 2019 and January 2020. Men age 18 and older without children (n = 634) were included for analysis. Outcomes were likelihood of self-initiating a semen analysis, prevalence of infertility concern.

RESULTS

Of the 634 participants, 186 expressed concern about infertility but only 29% were likely to discuss these concerns with a health care provider. More men would self-initiate a semen analysis using an at-home product than through a traditional laboratory/clinic (14.2% vs 10.4%, P = .04). Odds of self-initiating a traditional semen analysis were higher for men concerned about low testosterone (odds ratio [OR] 2.30, 95% confidence interval [CI] 1.12-4.74, P = .023) and infertility (OR 3.91, 95% CI 2.14-7.15, P <.001). Self-initiating an at-home semen analysis was associated with concern for low testosterone and infertility as well as middle age (age 40-59: OR 3.02, 95% CI 1.16-7.88, P = .024) and fitness tracker use (OR: 1.95, 95% CI 1.12-3.39, P = .018).

CONCLUSION

Many men were unlikely to discuss infertility concerns with a health care provider. Middle aged men and those who used fitness trackers were more likely to self-initiate fertility evaluation through at-home semen analysis. Concern about low serum testosterone was pervasive and strongly associated with concern for being infertile and self-initiating a semen analysis of any kind.

Adaptive adversarial neural networks for the analysis of lossy and domain-shifted datasets of medical images

In machine learning for image-based medical diagnostics, supervised convolutional neural networks are typically trained with large and expertly annotated datasets obtained using high-resolution imaging systems. Moreover, the network's performance can degrade substantially when applied to a dataset with a different distribution. Here, we show that adversarial learning can be used to develop high-performing networks trained on unannotated medical images of varying image quality. Specifically, we used low-quality images acquired using inexpensive portable optical systems to train networks for the evaluation of human embryos, the quantification of human sperm morphology and the diagnosis of malarial infections in the blood, and show that the networks performed well across different data distributions. We also show that adversarial learning can be used with unlabelled data from unseen domain-shifted datasets to adapt pretrained supervised networks to new distributions, even when data from the original distribution are not available. Adaptive adversarial networks may expand the use of validated neural-network models for the evaluation of data collected from multiple imaging systems of varying quality without compromising the knowledge stored in the network.

Simplified sperm testing devices: a possible tool to overcome lack of accessibility and inconsistency in male factor infertility diagnosis. An opportunity for low- and middle- income countries

Background

Manual semen assessment (MSA) is a key component in a male’s fertility assessment. Clinicians rely on it to make diagnostic and treatment decisions. When performed manually, this routine laboratory test is prone to variability due to human intervention which can lead to misdiagnosis and consequently over- or under- treatment. For standardisation, continuous training, quality control (QC) programs and pricy Computer-Assisted Sperm Analysis (CASA) systems have been proposed, yet, without resolving intra- and inter-laboratory variability. In response, promising simplified sperm testing devices, able to provide cost-effective point-of-care male infertility diagnosis are prospected as a plausible solution to resolve variability and increase access to sperm testing.

Materials and methods

A throughout literature research for semen testing, sperm analysis, smart-phone assisted semen analysis, ‘at-home’ semen testing, male infertility, infertility in developing countries, infertility in low- and middle-income countries (LMIC) and quantitative sperm analysis was performed. A total of 14 articles, specific to ‘at-home’ simplified sperm assessment, were included to treat the core subject.

Results

Continuous training and consistent QC, are sine qua none conditions to achieve accurate and comparable MSA. Compliance does not rule-out variability, nevertheless. Emerging simplified sperm assessment devices are an actual alternative to resolve the lack of standardisation and accessibility to sperm analysis. YO ® , SEEM ® , and ExSeed ® are commercially available, user-friendly smartphone-based devices which can accurately measure volume, sperm concentration (millions/ml) and total motile sperm count. More broadly, by cost-effectiveness, availability, accuracy and convenient application, these devices could effectively select patients for first-line artificial reproduction treatments such as intrauterine insemination.

Conclusions

Accuracy and cost-effectiveness make smart-phone based sperm testing devices a practical and realistic solution to overcome variability in MSA. Importantly, these tools represent an actual opportunity to standardise and improve male subfertility diagnosis and treatment, especially in LMIC. However, before clinical application is possible, guidelines, further testing with special attention on accuracy in washed sperm, availability, cost-benefit and reliability are required.

Development and validation of a novel mail-in semen analysis system and the correlation between one hour and delayed semen analysis testing

OBJECTIVE

To develop and validate a novel, mail-in semen analysis (SA) system.

DESIGN

Prospective cohort.

SETTING

Not applicable.

PATIENT(S)

Ejaculates from normospermic men.

INTERVENTION(S)

One-hour SA, then repeat SAs (on same ejaculate) over 52 hours using a novel technique for maintaining sperm viability.

MAIN OUTCOME MEASURE(S)

World Health Organization SA parameters.

RESULT(S)

One-hour SA on 104 ejaculates in the validation phase of the study demonstrated normal semen parameters. With up to 52 hours of observation and four subsequent SA measurements/ejaculate, concentration remained stable, motility decreased by 0.39%/h, and normal morphology decreased by 0.1%/h. Measured 1-hour and calculated motility (correlation coefficients 0.87) and morphology (correlation coefficients 0.82) strongly were correlated.

CONCLUSION

This novel, mail-in, Clinical Laboratory Improvement Amendments-approved SA testing system demonstrates a strong degree of correlation between 1-hour and delayed SA testing. Given the linear motility and morphology decrease and stability of sperm concentration, this test may be used in clinical practice to evaluate semen quality for fertility evaluations. Furthermore, this approach significantly improves the ease, comfort, and efficiency of obtaining a SA, likely breaking down early barriers to accessing successfully a male fertility evaluation.

Point-of-care semen analysis of patients with infertility via smartphone and colorimetric paper-based diagnostic device

Male infertility affects millions of males worldwide and is rising in prevalence due to social and environmental conditions. However, men often feel too embarrassed to receive a semen analysis in the hospital due to social stigmas. To overcome this problem, we developed a 3-(4,5-Dimethyl-2-thiazolyl)-2,5-diphenyl-2H-tetrazolium bromide test strip to distinguish semen samples with low total motile sperm concentration from those with normal motile sperm concentration. This is a point-of-care colorimetric semen analytical method with a one-step, inexpensive, equipment-free evaluation process, and adequate accuracy validated in a 42-sample clinical trial. In this study, results were evaluated visually and with a smartphone application. Using visual observation methods, the area under the curve (AUC) was 0.71 (95% of confidence interval = 0.55-0.86; p = 0.021), sensitivity was 41%, specificity was 95%, positive predictive value was 90%, negative predictive value (NPV) was 59.4%, and accuracy was 67%. Using a smartphone recording and analytical system, AUC was 0.766 (95% of confidence interval = 0.612-0.92; p = 0.003), sensitivity was 96%, specificity was 65%, PPV was 75%, NPV was 92.9%, and accuracy was 80.9%. This work demonstrated a screening tool that could elevate semen analysis to the level of routine healthcare and provide for private, in-home self-assessment.

Recent advances and controversies in diagnosing and treating male infertility

Interest in male infertility has increased, as it plays an important role in up to 50% of couples struggling with infertility, which is an estimated 48.5 million couples globally. Despite recent advances, diagnosing and treating male infertility remain a significant clinical challenge owing to complex multifactorial pathways and the diversity of treatment options. This review will assess current controversial topics on male infertility such as the use of home-based semen testing, management of subclinical varicocele, and recent advances in the field of sperm proteomics.

Web- and Artificial Intelligence-Based Image Recognition For Sperm Motility Analysis: Verification Study

Background

Human sperm quality fluctuates over time. Therefore, it is crucial for couples preparing for natural pregnancy to monitor sperm motility.

Objective

This study verified the performance of an artificial intelligence–based image recognition and cloud computing sperm motility testing system (Bemaner, Createcare) composed of microscope and microfluidic modules and designed to adapt to different types of smartphones.

Methods

Sperm videos were captured and uploaded to the cloud with an app. Analysis of sperm motility was performed by an artificial intelligence–based image recognition algorithm then results were displayed. According to the number of motile sperm in the vision field, 47 (deidentified) videos of sperm were scored using 6 grades (0-5) by a male-fertility expert with 10 years of experience. Pearson product-moment correlation was calculated between the grades and the results (concentration of total sperm, concentration of motile sperm, and motility percentage) computed by the system.

Results

Good correlation was demonstrated between the grades and results computed by the system for concentration of total sperm (r=0.65, P<.001), concentration of motile sperm (r=0.84, P<.001), and motility percentage (r=0.90, P<.001).

Conclusions

This smartphone-based sperm motility test (Bemaner) accurately measures motility-related parameters and could potentially be applied toward the following fields: male infertility detection, sperm quality test during preparation for pregnancy, and infertility treatment monitoring. With frequent at-home testing, more data can be collected to help make clinical decisions and to conduct epidemiological research.

Recent advances in clinical diagnosis and treatment of male factor infertility

Infertility is a significant global health issue affecting around 8-12% of couples worldwide with male factor infertility accounting for a substantial proportion of these cases. Despite significant advances within the past few decades, an etiology for male factor infertility cannot be identified in up to 80% of patients and thus, this continues to be an area of active study. This review aims to provide an update on recent advances in the field of male infertility including semen analysis and at-home semen testing, genetics, DNA fragmentation, surgical approaches, and the rise of telemedicine in the era of COVID19.

Methodological considerations for examining the relationship between sperm morphology and motility

Sperm cells of all taxa share a common goal to reach and fertilize an ovum, yet sperm are one of the most diverse cell types in nature. While the structural diversity of these cells is well recognized, the functional significance of variation in sperm design remains elusive. An important function of spermatozoa is a need to migrate toward the ova, often over long distances in a foreign environment, which may include a complex and hostile female reproductive tract. Several comparative and experimental studies have attempted to address the link between sperm morphology and motility, yet the conclusions drawn from these studies are often inconsistent, even within the same taxa. Much of what we know about the functional significance of sperm design in internally fertilizing species has been gleaned from in vitro studies, for which experimental parameters often vary among studies. We propose that discordant results from these studies are in part due to a lack of consistency of methods, conditions that do not replicate those of the female reproductive tract, and the overuse of simple linear measures of sperm shape. Within this review, we provide a toolkit for imaging, quantifying, and analyzing sperm morphology and movement patterns for in vitro studies and discuss emerging approaches. Results from studies linking morphology to motility enhance our understanding of the evolution of adaptive sperm traits and the mechanisms that regulate fertility, thus offering new insights into methods used in assisted reproductive technologies in animal science, conservation and public health.

A Novel Approach to Improving the Reliability of Manual Semen Analysis: A Paradigm Shift in the Workup of Infertile Men

Conventional semen analysis (SA) is an essential component of the male infertility workup, but requires laboratories to rigorously train and monitor technicians as well as regularly perform quality assurance assessments. Without such measures there is room for error and, consequently, unreliable results. Furthermore, clinicians often rely heavily on SA results when making diagnostic and treatment decisions, however conventional SA is only a surrogate marker of male fecundity and does not guarantee fertility. Considering these challenges, the last several decades have seen the development of many advances in SA methodology, including tests for sperm DNA fragmentation, acrosome reaction, and capacitation. While these new diagnostic tests have improved the scope of information available to clinicians, they are expensive, time-consuming, and require specialized training. The latest advance in laboratory diagnostics is the measurement of seminal oxidation-reduction potential (ORP). The measurement of ORP in an easy, reproducible manner using a new tool called the Male Infertility Oxidative Stress System (MiOXSYS) has demonstrated ORP's potential as a feasible adjunct test to conventional SA. Additionally, the measurement of ORP by this device has been shown to be predictive of both poor semen quality and male infertility. Assessing ORP is a novel approach to both validating manual SA results and identifying patients who may benefit from treatment of male oxidative stress infertility.

Male contraception: where are we going and where have we been?

Progress in developing new reversible male contraception has been slow. While the hormonal approach has been clearly shown to be capable of providing effective and reversible contraception, there remains no product available. Currently, trials of a self-administered gel combination of testosterone and the progestogen Nestorone® are under way, complementing the largely injectable methods previously investigated. Novel long-acting steroids with both androgenic and progestogenic activity are also in early clinical trials. The non-hormonal approach offers potential advantages, with potential sites of action on spermatogenesis, and sperm maturation in the epididymis or at the vas, but remains in preclinical testing. Surveys indicate the willingness of men, and their partners, to use a new male method, but they continue to lack that opportunity.

Validation of a smartphone-based, computer-assisted sperm analysis system compared with laboratory-based manual microscopic semen analysis and computer-assisted semen analysis

Purpose

This study aimed to evaluate the clinical efficacy of a portable smartphone-based system for computer-assisted semen analysis (CASA) compared with the results of manual microscopic semen analysis (SA) and laboratory-based CASA for self-evaluation of semen parameters by a male partner.

Materials and Methods

From July 2017 to February 2018, a total of 28 samples were analyzed for concentration and motility with a smartphone-based CASA system and the results compared with those from laboratory-based CASA and manual microscopic SA with a Makler Counting Chamber (SEFI Medical Instruments, Israel).

Results

Sperm concentration and motility measured with the smartphone-based CASA system were positively correlated with the microscopic-based results. Likewise, sperm motility calculated with smartphone-based CASA was positively correlated with the laboratory-based CASA results. These results suggest that the smartphone-based CASA system can be used for clinical semen diagnosis.

Conclusions

A portable smartphone-based CASA system can play a role in motivating infertile males to visit clinics, thus resulting in early diagnosis and treatment with cost-effectiveness. The device can be used for easy follow-up on a screening basis by the male partner before visiting a clinic for fertility evaluation or by infertile males after receiving medical management. Additionally, future software advancements and post-marketing consumer surveys will make possible wider applications, including assessment of sperm morphology, in the coming future.

Sperm quality in fish: Determinants and affecting factors

Fish sperm quality assessment is helpful for optimizing production and for monitoring the environmental state. Sperm can be monitored relatively easy and, to date, various analyses have been applied and proven to be helpful in this task. Among them, sperm motility parameters such as sperm speed are one of the main performance traits during assisted fish reproduction. Apart from motility the sperm concentration, volume, and seminal plasma pH and osmolality are also frequently evaluated and are the main sperm quality indicators measured in fish sperm. However, other parameters also determine sperm fertilization potential. Recent knowledge reveals several additional parameters of high importance for sperm function. Among them are DNA integration, membrane stability, mitochondria status and enzymatic activity. Measuring all these parameters in fish sperm provides complex knowledge regarding male fertility and helps to improve broodstock maintenance protocols as well as gamete handling and fertilization processes. This review focuses on the presentation of the sperm quality measures for freshwater and marine species of the fish and provides information regarding recent methods of sperm quality evaluation.