Novel methods to enhance surgical sperm retrieval: a systematic review

Technologies to improve sperm retrieval in men undergoing micro-TESE for NOA

ABSTRACT

Nonobstructive azoospermia (NOA) is considered the most challenging clinical scenario for infertile men and current treatments leave many men unsuccessful at being able to achieve a pregnancy with their partner using their own sperm. Microdissection testicular sperm extraction (micro-TESE) is the choice for men with NOA desiring to father children with their own gametes. Micro-TESE results in the highest numbers of sperm cells retrieved for use with in vitro fertilization/intracytoplasmic sperm injection. With suboptimal micro-TESE success rates of sperm retrieval and then pregnancy and live birth using the retrieved sperm with in vitro fertilization/intracytoplasmic sperm injection, advances to improve outcomes are necessary. This article comprehensively reviews the technologies investigated to date to improve the outcomes for men undergoing micro-TESE.

Current and Future Applications of Artificial Intelligence to Diagnose and Treat Male Infertility

Artificial intelligence (AI) models are being increasingly applied to modern medicine. Within the field of urology, reproductive urology specifically offers many opportunities to utilize this advanced computational technology for diagnostic and therapeutic benefit. While the use of AI models in diagnosing and treating male infertility remains in its early days, current and future applications of these models include automation of semen analysis testing; predicting semen quality; identifying subsets of infertile men most likely to benefit from surgical treatment (i.e., varicocelectomy, surgical sperm retrieval); identifying rare sperm from testis tissue; and selecting optimal sperm for in vitro fertilization (IVF) with intracytoplasmic sperm injection (ICSI). In this chapter, we review the current literature surrounding these applications and discuss opportunities for future research.

AI predictive models and advancements in microdissection testicular sperm extraction for non-obstructive azoospermia: a systematic scoping review

STUDY QUESTION

How accurately can artificial intelligence (AI) models predict sperm retrieval in non-obstructive azoospermia (NOA) patients undergoing micro-testicular sperm extraction (m-TESE) surgery?

SUMMARY ANSWER

AI predictive models hold significant promise in predicting successful sperm retrieval in NOA patients undergoing m-TESE, although limitations regarding variability of study designs, small sample sizes, and a lack of validation studies restrict the overall generalizability of studies in this area.

WHAT IS KNOWN ALREADY

Previous studies have explored various predictors of successful sperm retrieval in m-TESE, including clinical and hormonal factors. However, no consistent predictive model has yet been established.

STUDY DESIGN SIZE DURATION

A comprehensive literature search was conducted following PRISMA-ScR guidelines, covering PubMed and Scopus databases from 2013 to 15 May 2024. Relevant English-language studies were identified using Medical Subject Headings (MeSH) terms. We also used PubMed's 'similar articles' and 'cited by' features for thorough bibliographic screening to ensure comprehensive coverage of relevant literature.

PARTICIPANTS/MATERIALS SETTING METHODS

The review included studies on patients with NOA where AI-based models were used for predicting m-TESE outcomes, by incorporating clinical data, hormonal levels, histopathological evaluations, and genetic parameters. Various machine learning and deep learning techniques, including logistic regression, were employed. The Prediction Model Risk of Bias Assessment Tool (PROBAST) evaluated the bias in the studies, and their quality was assessed using the Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis (TRIPOD) guidelines, ensuring robust reporting standards and methodological rigor.

MAIN RESULTS AND THE ROLE OF CHANCE

Out of 427 screened articles, 45 met the inclusion criteria, with most using logistic regression and machine learning to predict m-TESE outcomes. AI-based models demonstrated strong potential by integrating clinical, hormonal, and biological factors. However, limitations of the studies included small sample sizes, legal barriers, and challenges in generalizability and validation. While some studies featured larger, multicenter designs, many were constrained by sample size. Most studies had a low risk of bias in participant selection and outcome determination, and two-thirds were rated as low risk for predictor assessment, but the analysis methods varied.

LIMITATIONS REASONS FOR CAUTION

The limitations of this review include the heterogeneity of the included research, potential publication bias and reliance on only two databases (PubMed and Scopus), which may limit the scope of the findings. Additionally, the absence of a meta-analysis prevents quantitative assessment of the consistency of models. Despite this, the review offers valuable insights into AI predictive models for m-TESE in NOA.

WIDER IMPLICATIONS OF THE FINDINGS

The review highlights the potential of advanced AI techniques in predicting successful sperm retrieval for NOA patients undergoing m-TESE. By integrating clinical, hormonal, histopathological, and genetic factors, AI models can enhance decision-making and improve patient outcomes, reducing the number of unsuccessful procedures. However, to further enhance the precision and reliability of AI predictions in reproductive medicine, future studies should address current limitations by incorporating larger sample sizes and conducting prospective validation trials. This continued research and development is crucial for strengthening the applicability of AI models and ensuring broader clinical adoption.

STUDY FUNDING/COMPETING INTERESTS

The authors would like to acknowledge Mashhad University of Medical Sciences, Mashhad, Iran, for financial support (Grant ID: 4020802). The authors declare no competing interests.

REGISTRATION NUMBER

N/A.

The Andrological Landscape in the Twenty-First Century: Making Sense of the Advances in Male Infertility Management for the Busy Clinicians

Male infertility represents a significant global problem due to its essential health, social, and economic implications. It is unsurprising that scientific research is very active in this area and that advances in the diagnostic and therapeutic fields are notable. This review presents the main diagnostic advances in male infertility, starting from the changes made in the latest WHO Manual of semen analysis and discussing the more molecular aspects inherent to "omics". Furthermore, the usefulness of artificial intelligence in male infertility diagnostics and the latest advances in varicocele diagnosis will be discussed. In particular, the diagnostic path of male infertility is increasingly moving towards a personalized approach to the search for the specific biomarkers of infertility and the prediction of treatment response. The treatment of male infertility remains empirical in many regards, but despite that, advances have been made to help formulate evidence-based recommendations. Varicocele, the most common correctable cause of male infertility, has been explored for expanded indications for repair. The following expanded indications were discussed: elevated sperm DNA fragmentation, hypogonadism, orchalgia, and the role of varicocele repair in non-obstructive azoospermia. Moving forward with the available data, we discussed the stepwise approach to surgical sperm retrieval techniques and the current measures that have been investigated for optimizing such patients before testicular sperm extraction. Finally, the key points and expert recommendations regarding the best practice for diagnosing and treating men with infertility were summarized to conclude this review.

Effectiveness of, and Satisfaction with, a Microsurgical Testicular Sperm Extraction Knowledge and Skills Masterclass for a World-Wide Audience

PURPOSE

This is the first study to assess the impact of an online microsurgical testicular sperm extraction (mTESE) masterclass. We: 1) describe the masterclass's scientific content; 2) appraise the participants' acquisition of knowledge; 3) gauge whether the extent of improvement of the participants' knowledge/skills was influenced by demographic/professional attributes; and 4) evaluate the participants' satisfaction.

MATERIALS AND METHODS

This masterclass comprised five didactic lectures followed by 4 case discussions. Online surveys assessed the above objectives using a baseline questionnaire including demographics and past mTESE experience/training, a 24-question pre- and post-quiz, and a satisfaction questionnaire.

RESULTS

Participants were between 20-70 years old, with 80.37% males, mainly from Asia, Africa, and Europe, from clinical backgrounds (69.3%), and in public practice (64.4%). Half the sample reported no past mTESE training and very low skills, ≈60% wanted considerably more training, and 50% felt that good training was not readily available. Satisfaction was 98% to >99%. Pre- and post-quiz comparisons confirmed remarkable improvements in knowledge/skills, exhibiting five striking characteristics. Improvements were a) Broad i.e., across 19 of the 24 mTESE questions; b) Deep, of magnitude, as pre-/post-quiz scores improved from mean 13.71±4.13 to 17.06±4.73; c) Highly significant, consistently with p-values <0.001; d) Inclusive i.e., all participants enhanced their mTESE knowledge/skills regardless of demographic/professional attributes; and, e) Differential, e.g., non-clinical/clinical participants improved, but the former improved relatively significantly more, those with ≤5-year experience improved significantly more than those with >5-year, those in public practice significantly more than private practice participants, and those with lower self-rating in performing mTESE significantly more than those with higher self-rating.

CONCLUSIONS

The masterclass was successful with very high satisfaction levels, and markedly improved mTESE knowledge/skills among the participants. Global Andrology Forum's model can be adopted by organizations with similar goals. Future research needs to evaluate such training to develop a practically non-existent evidence base.

The prospect of artificial intelligence to personalize assisted reproductive technology

Infertility affects 1-in-6 couples, with repeated intensive cycles of assisted reproductive technology (ART) required by many to achieve a desired live birth. In ART, typically, clinicians and laboratory staff consider patient characteristics, previous treatment responses, and ongoing monitoring to determine treatment decisions. However, the reproducibility, weighting, and interpretation of these characteristics are contentious, and highly operator-dependent, resulting in considerable reliance on clinical experience. Artificial intelligence (AI) is ideally suited to handle, process, and analyze large, dynamic, temporal datasets with multiple intermediary outcomes that are generated during an ART cycle. Here, we review how AI has demonstrated potential for optimization and personalization of key steps in a reproducible manner, including: drug selection and dosing, cycle monitoring, induction of oocyte maturation, and selection of the most competent gametes and embryos, to improve the overall efficacy and safety of ART.

MicroRNAs in Male Fertility

Around 50% of all occurrences of infertility are attributable to the male factor, which is a significant global public health concern. There are numerous circumstances that might interfere with spermatogenesis and cause the body to produce abnormal sperm. While evaluating sperm, the count, the speed at which they migrate, and their appearance are the three primary characteristics that are analyzed. MicroRNAs, also known as miRNAs, are present in all physiological fluids and tissues. They participate in both physiological and pathological processes. Researches have demonstrated that the expression of microRNA genes differs in infertile men. These genes regulate spermatogenesis at various stages and in several male reproductive cells. Hence, microRNAs have the potential to act as useful indicators in the diagnosis and treatment of male infertility and other diseases affecting male reproduction. Despite this, additional research is necessary to determine the precise miRNA regulation mechanisms.

Noninvasive Prediction of Sperm Retrieval Using Diffusion Tensor Imaging in Patients with Nonobstructive Azoospermia

Microdissection testicular sperm extraction (mTESE) is the first-line treatment plan for nonobstructive azoospermia (NOA). However, studies reported that the overall sperm retrieval rate (SRR) was 43% to 63% among men with NOA, implying that nearly half of the patients fail sperm retrieval. This study aimed to evaluate the diagnostic performance of parameters derived from diffusion tensor imaging (DTI) in predicting SRR in patients with NOA. Seventy patients diagnosed with NOA were enrolled and classified into two groups based on the outcome of sperm retrieval during mTESE: success (29 patients) and failure (41 patients). Scrotal magnetic resonance imaging was performed, and the DTI parameters, including mean diffusivity and fractional anisotropy, were analyzed between groups. The results showed that there was a significant difference in mean diffusivity values between the two groups, and the area under the curve for mean diffusivity was calculated as 0.865, with a sensitivity of 72.2% and a specificity of 97.5%. No statistically significant difference was observed in fractional anisotropy values and sex hormone levels between the two groups. This study demonstrated that the mean diffusivity value might serve as a useful noninvasive imaging marker for predicting the SRR of NOA patients undergoing mTESE.

In Contemporary Reproductive Medicine Human Beings are Not Yet Dispensable

In the past few years almost every aspect of an IVF cycle has been investigated, including research on sperm, color doppler in follicular studies, prediction of embryo cleavage, prediction of blastocyst formation, scoring blastocyst quality, prediction of euploid blastocysts and live birth from blastocysts, improving the embryo selection process, and for developing deep machine learning (ML) algorithms for optimal IVF stimulation protocols. Also, artificial intelligence (AI)-based methods have been implemented for some clinical aspects of IVF, such as assessing patient reproductive potential and individualizing gonadotropin stimulation protocols. As AI has the inherent capacity to analyze "Big" data, the goal will be to apply AI tools to the analysis of all embryological, clinical, and genetic data to provide patient-tailored individualized treatments. Human skillsets including hand eye coordination to perform an embryo transfer is probably the only step of IVF that is outside the realm of AI & ML today. Embryo transfer success is presently human skill dependent and deep machine learning may one day intrude into this sacred space with the advent of programed humanoid robots. Embryo transfer is arguably the rate limiting step in the sequential events that complete an IVF cycle. Many variables play a role in the success of embryo transfer, including catheter type, atraumatic technique, and the use of sonography guidance before and during the procedure of embryo transfer. In contemporary Reproductive Medicine human beings are not yet dispensable.

A Narrative Review Discussing Vasectomy-Related Impact upon the Status of Oxidative Stress and Inflammation Biomarkers and Semen Microbiota

Background: Male contraceptive approaches besides tubal sterilization involve vasectomy and represent the method of choice among midlife men in developing countries thanks to many advantages. However, the subsidiary consequences of this intervention are insufficiently explored since the involved mechanisms may offer insight into a much more complex picture. Methods: Thus, in this manuscript, we aimed to reunite all available data by searching three separate academic database(s) (PubMed, Web of Knowledge, and Scopus) published in the past two decades by covering the interval 2000–2023 and using a predefined set of keywords and strings involving “oxidative stress” (OS), “inflammation”, and “semen microbiota” in combination with “humans”, “rats”, and “mice”. Results: By following all evidence that fits in the pre-, post-, and vasectomy reversal (VR) stages, we identified a total of n = 210 studies from which only n = 21 were finally included following two procedures of eligibility evaluation. Conclusions: The topic surrounding this intricate landscape has created debate since the current evidence is contradictory, limited, or does not exist. Starting from this consideration, we argue that further research is mandatory to decipher how a vasectomy might disturb homeostasis.

A Comparative Analysis of Ergonomic Risk Utilizing the 4K-3D Exoscope Versus Standard Operating Microscope for Male Fertility Microsurgery

OBJECTIVE

To stratify ergonomic risk in a urologic microsurgeon using the 4K-3D exoscope versus the operating microscope (OM) with wearable technology.

METHODS

The surgeon was calibrated with wearable sensor inertial measurement units (IMUs) on the head and upper arms. Each inertial measurement units contained an accelerometer, magnetometer, and gyroscope to measure surgeon joint angle change during microscopic procedures for male fertility. The validated modified rapid upper limb assessment was used to determine the proportion of time spent in ranges of risk. Categories 1-4 were assigned for the head and upper extremities (4= highest ergonomic risk). Chi-squared analysis was used to analyze differences in proportions.

RESULTS

A total of 500 and 479 minutes from 4K-3D exoscope and OM guided surgeries were analyzed. The 4K-3D exoscope significantly favored upper arm category 1 positioning compared to the OM (56.2% vs 37.7%; P < .0001). The OM exposed the surgeon to higher category 3 positioning (14.6% vs 1.6%; P <.0001). More time was spent with the neck "extended" using the 4K-3D exoscope (51.8% vs 19.5%; P < .0001) with 67% of neck extension between 0-10° (category 1). Overall, more time was spent with the neck in risk group 1-2 with the OM (P < .0001).

CONCLUSION

The 4K-3D exoscope offers favorable ergonomic positioning for the upper extremities which may reduce work stress-related injury. More operative time was spent with the neck in mild extension with 4K-3D exoscope utilization. However, the OM favored longer operative times in low-risk neck ergonomic positions.

Future of Male Infertility Evaluation and Treatment: Brief Review of Emerging Technology

Over the past few decades, there have been significant advances in male infertility, particularly in the development of novel diagnostic tools. Unfortunately, there remains a substantial number of patients that remain infertile despite these improvements. In this review, we take heed of the emerging technologies that will shape the future of male infertility diagnosis, evaluation and treatment. Improvement in computer-assisted semen analyses and portability allow males to obtain basic semen parameters from the comfort of their home. Additionally, breakthrough ultrasound technology allows for preoperative prediction of potential areas of spermatogenesis within the testes, high-resolution optics permits better visualization during microdissection testicular sperm extraction (mTESE), and artificial intelligence improves sperm selection and identification.