Search Results (15)

Since its inception in 1987, in vitro fertilization (IVF) has constituted a significant medical achievement in the field of fertility treatment, offering a viable solution to the challenge of infertility. The continuous evolution of assisted reproductive technology (ART) has brought its relationship with the rapidly developing field of artificial intelligence (AI), in particular with techniques such as machine learning (ML), a rapidly evolving area of specialization. In fact, it is responsible for significant developments in the field of precision medicine, as well as in preventive and predictive medicine. The analysis focuses on a large volume of clinical data and patient characteristics of those who underwent assisted reproduction treatments. Concurrently, the utilization of machine learning algorithms has facilitated the development and implementation of predictive models. The objective is to predict the success of treatments for external fertilization based on processed clinical data. This study encompasses statistical analysis techniques and artificial intelligence algorithms for the correlation of variables, such as patient characteristics, the history of pregnancies, and the clinical and embryological parameters. The analysis and creation of prognostic models were compared with the objective of identifying factors that influence the outcome of IVF treatments. The potential for implementing a predictive model in routine clinical practice was also investigated. The findings revealed trends and factors that warrant attention. Such findings may prompt questions regarding the impact of the patient’s age on treatment efficacy. Moreover, the value of developing a predictive model based entirely on patient data prior to the commencement of treatment was also investigated. This approach to the processing and utilization of clinical data demonstrates the potential for optimization and documentation of therapeutic procedures. The objective is to reduce costs and the emotional burden while increasing the success rate of IVF treatments. Full article

Female infertility is a multifaceted condition affecting millions of women worldwide, with causes ranging from hormonal imbalances and genetic predispositions to lifestyle and environmental factors. Traditional diagnostic approaches, such as hormonal assays, ultrasound imaging, and genetic testing, often require extensive time, resources, and expert interpretation. In recent years, artificial intelligence (AI) has emerged as a transformative tool in the field of reproductive medicine, offering advanced capabilities for improving the accuracy, efficiency, and personalization of infertility diagnosis and treatment. AI technologies demonstrate significant potential in analyzing vast and complex datasets, identifying hidden patterns, and providing data-driven insights that enhance clinical decision-making processes in assisted reproductive technologies (ART) services. This narrative review explores the current advancements in AI applications in female infertility diagnostics and therapeutics, highlighting key technological innovations, their clinical implications, and existing limitations. It also discusses the future potential of AI in revolutionizing reproductive healthcare. As AI-based technologies continue to evolve, their integration into reproductive medicine is expected to pave the way for more accessible, cost-effective, and personalized fertility care. Full article

Background: The implantation process is complex and involves numerous factors that can affect its success. In artificial reproductive treatments (ARTs), chronic inflammation seems to be associated with implantation failure, largely contributing to reproductive dysfunction. Pentraxin 3 (PTX3) is overexpressed in several pathological conditions by exerting a pivotal role both as a regulator and indicator of inflammatory response. Some literature data have shown that PTX3 could have an impact on follicle growth and development, influencing women’s fertility. This study aimed to detect PTX3 in follicular fluids collected during an ART protocol in relation to implantation outcomes. Methods: The PTX3/NF-kB/TLR4 pathway and other cytokines were assessed in the follicular fluid of 169 subjects, under the age of 40 years, undergoing IVF cycles, including females without achieved implantation (n = 98) and those with implantation (n = 71). Furthermore, subgroup analyses were performed to evaluate PTX3 values according to age difference. Results: From our data, PTX3 emerged as a strong predictor, more than TNFα and IL-1β, of implantation failure and related inflammatory follicular state. Overall, the results point to PTX3 as a potential biomarker for ART success, and their testing may be helpful in women whose successful implantation remains unexplained. Conclusions: Therefore, PTX3 could constitute a reliable biomarker and a valuable target to improve ART outcomes. Full article

The evolution of preimplantation genetic testing for aneuploidy (PGT-A) techniques has been crucial in assisted reproductive technologies (ARTs), improving embryo selection and increasing success rates in in vitro fertilization (IVF) treatments. Techniques ranging from fluorescence in situ hybridization (FISH) to next-generation sequencing (NGS) have relied on cellular material extraction through biopsies of blastomeres at the cleavage stage on day three or from trophectoderm (TE) cells of the blastocyst. However, this has raised concerns about its potential impact on embryo development. As a result, there has been growing interest in developing non-invasive techniques for detecting aneuploidies, such as the analysis of blastocoel fluid (BF), spent culture medium (SCM), and artificial intelligence (AI) models. Non-invasive methods represent a promising advancement in PGT-A, offering the ability to detect aneuploidies without compromising embryo viability. This article reviews the evolution and principles of PGT-A, analyzing both traditional techniques and emerging non-invasive approaches, while highlighting the advantages and challenges associated with these methodologies. Furthermore, it explores the transformative potential of these innovations, which could optimize genetic screening and significantly improve clinical outcomes in the field of assisted reproduction. Full article

This review aimed to bring a comprehensive analysis of key clinical strategies for enhancing reproductive efficiency in buffaloes, a species that exhibit low reproductive performance under conventional reproductive management compared to that exhibited by cattle. It considers key ART techniques including estrus synchronization for artificial insemination, and ovulation induction, highlighting their role in improving fertility and overall herd productivity. However, it also addresses common postpartum inflammatory and functional reproductive disorders, discussing their diagnosis and treatment protocols, stressing their impact on the overall reproductive outcome in buffalo farming. Full article

Artificial intelligence (AI) is experiencing advances and integration in all medical specializations, and this creates excitement but also concerns. This narrative review aims to critically assess the state of the art of AI in the field of endometriosis and adenomyosis. By enabling automation, AI may speed up some routine tasks, decreasing gynecologists’ risk of burnout, as well as enabling them to spend more time interacting with their patients, increasing their efficiency and patients’ perception of being taken care of. Surgery may also benefit from AI, especially through its integration with robotic surgery systems. This may improve the detection of anatomical structures and enhance surgical outcomes by combining intra-operative findings with pre-operative imaging. Not only that, but AI promises to improve the quality of care by facilitating clinical research. Through the introduction of decision-support tools, it can enhance diagnostic assessment; it can also predict treatment effectiveness and side effects, as well as reproductive prognosis and cancer risk. However, concerns exist regarding the fact that good quality data used in tool development and compliance with data sharing guidelines are crucial. Also, professionals are worried AI may render certain specialists obsolete. This said, AI is more likely to become a well-liked team member rather than a usurper. Full article

Male infertility has affected an increasingly large population over the past few decades, affecting over 186 million people globally. The advent of assisted reproductive technologies (ARTs) and artificial intelligence (AI) has changed the landscape of diagnosis and treatment of male infertility. Through an extensive literature review encompassing the PubMed, Google Scholar, and Scopus databases, various AI techniques such as machine learning (ML), artificial neural networks (ANNs), deep learning (DL), and natural language processing (NLP) were examined in the context of evaluating seminal quality, predicting fertility potential, and improving semen analysis. Research indicates that AI models can accurately estimate the quality of semen, diagnose problems with sperm, and provide guidance on reproductive health decisions. In addition, developments in smartphone-based semen analyzers and computer-assisted semen analysis (CASA) are indicative of initiatives to improve the price, portability, and accuracy of results. Future directions point to possible uses for AI in ultrasonography assessment, microsurgical testicular sperm extraction (microTESE), and home-based semen analysis. Overall, AI holds significant promise in revolutionizing the diagnosis and treatment of male infertility, offering standardized, objective, and efficient approaches to addressing this global health challenge. Full article

Postovulatory aging is known to impair the oocyte quality and embryo development due to oxidative stress in many different animal models, which reduces the success rate or pregnancy rate in human assisted reproductive technology (ART) and livestock timed artificial insemination (TAI), respectively. Salidroside (SAL), a phenylpropanoid glycoside, has been shown to exert antioxidant and antitumor effects. This study aimed to investigate whether SAL supplementation could delay the postovulatory oocyte aging process by alleviating oxidative stress. Here, we show that SAL supplementation decreases the malformation rate and recovers mitochondrial dysfunction including mitochondrial distribution, mitochondrial membrane potential (ΔΨ) and ATP content in aged oocytes. In addition, SAL treatment alleviates postovulatory aging-caused oxidative stress such as higher reactive oxygen species (ROS) level, lower glutathione (GSH) content and a reduced expression of antioxidant-related genes. Moreover, the cytoplasmic calcium ([Ca²⁺]c) and mitochondrial calcium ([Ca²⁺]mt) of SAL-treated oocytes return to normal levels. Notably, SAL suppresses the aging-induced DNA damage, early apoptosis and improves spindle assembly in aged oocytes, ultimately elevating the embryo developmental rates and embryo quality. Finally, the RNA-seq and confirmatory experience showed that SAL promotes protective autophagy in aged oocytes by activating the MAPK pathway. Taken together, our research suggests that supplementing SAL is an effective and feasible method for preventing postovulatory aging and preserving the oocyte quality, which potentially contributes to improving the successful rate of ART or TAI. Full article

Background and Objective: The aim of this retrospective cohort study is to evaluate the impact of assisted reproductive treatment (ART) on adverse maternal outcomes and the rate of hospitalization in maternal intensive care (MIC) in a tertiary university center in Liege, Belgium. Materials and Methods: This is a retrospective cohort study comparing two groups, 6557 patients who achieved pregnancy spontaneously and 330 patients who achieved pregnancy after ART, between January 2020 and December 2022. These patients were followed in the academic obstetrics department of Citadelle Hospital, Liège. The database of the ART center was compared with the database of the delivery unit to determine the cohort of patients who conceived after ART. Adverse maternal outcomes and MIC hospitalization rates were compared with between spontaneous pregnancies and ART groups. ART groups were also compared with each other. Results: The rate of hospitalization in maternal intensive care for patients who achieved pregnancy spontaneously was 12.1%, compared to 17.3% after ART. Comparing the rate of pre-eclampsia, 3.5% of spontaneous pregnancies were complicated by pre-eclampsia, while after ART, 10.9% of patients developed this complication during pregnancy. This rate was higher after IVF (12%) compared to intrauterine insemination and particularly after frozen embryo transfer (FET) in artificial cycle (17.9%). The birthweight of newborns after ART was also analyzed. A significant difference was obtained when comparing fresh embryo transfer with FET. Conclusions: Our study confirmed that FET in artificial cycle is a risk factor for pre-eclampsia and that fresh embryo transfer is associated with a higher rate of newborns with a lower percentile of birthweight. Our data showed that the rate of MIC hospitalization was significantly higher after ART but did not differ between groups. Full article

Assisted reproductive technologies (ART) significantly increase the chance of successful pregnancy and live birth in infertile couples. The different procedures for ART, including in vitro fertilization (IVF), intracytoplasmic sperm injection (ICSI), intrauterine insemination (IUI), and gamete intrafallopian tube transfer (GIFT), are widely used to overcome infertility-related problems. In spite of its inarguable usefulness, concerns about the health consequences of ART-conceived babies have been raised. There are reports about the association of ART with birth defects and health complications, e.g., malignancies, high blood pressure, generalized vascular functional disorders, asthma and metabolic disorders in later life. It has been suggested that hormonal treatment of the mother, and the artificial environment during the manipulation of gametes and embryos may cause genomic and epigenetic alterations and subsequent complications in the health status of ART-conceived babies. In the current study, we aimed to review the possible long-term consequences of different ART procedures on the subsequent health status of ART-conceived offspring, considering the confounding factors that might account for/contribute to the long-term consequences. Full article

Objective: To review the current knowledge concerning COVID-19 vaccination and assisted reproductive techniques (ART). Methods: A systematic review in Pubmed-Medline, the Cochrane Database, the Web of Science, and the National Guideline was performed. Studies were selected if they were primary studies, included vaccinated (case) and unvaccinated (control) patients, and described fertility treatment response. Results: A total of 24 studies were selected. Outcomes related to the association between COVID-19 vaccination and ART were collected. The vast majority of studies found no statistical differences concerning oocyte stimulation response, embryo quality, implantation rates, or pregnancy outcome (clinical or biochemical pregnancy rates and losses) when comparing cases and controls. Similarly, no differences were found when comparing different types of vaccines or distinct ART (artificial insemination, in vitro fertilization, and embryo transfer of frozen embryos). Conclusions: Patients receiving ART and health care professionals should be encouraged to complete and recommend COVID-19 vaccination, as the available evidence regarding assisted reproductive outcomes is reassuring. Full article

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. Full article

Infertility, although not a life-threatening condition, affects around 15% of couples trying for a pregnancy. The increasing availability of large datasets from various sources, together with advances in machine learning (ML) and artificial intelligence (AI), are enabling a transformational change in infertility care. However, real-world applications of data-driven medicine in infertility care are still relatively limited. At present, very little can prevent infertility from arising; more work is required to learn about ways to improve natural conception and the detection and diagnosis of infertility, improve assisted reproduction treatments (ART) and ultimately develop useful clinical-decision support systems to assure the successful outcome of either fertility preservation or infertility treatment. In this opinion article, we discuss recent influential work on the application of big data and AI in the prevention, diagnosis and treatment of infertility. We evaluate the challenges of the sector and present an interpretation of the different innovation forces that are driving the emergence of a systems approach to infertility care. Efforts including the integration of multi-omics information, collection of well-curated biological samples in specialised biobanks, and stimulation of the active participation of patients are considered. In the era of Big Data and AI, there is now an exciting opportunity to leverage the progress in genomics and digital technologies and develop more sophisticated approaches to diagnose and treat infertility disorders. Full article

Although there are large differences between horses and humans for reproductive anatomy, follicular dynamics, mono-ovulation, and embryo development kinetics until the blastocyst stage are similar. In contrast to humans, however, horses are seasonal animals and do not have a menstrual cycle. Moreover, horse implantation takes place 30 days later than in humans. In terms of artificial reproduction techniques (ART), oocytes are generally matured in vitro in horses because ovarian stimulation remains inefficient. This allows the collection of oocytes without hormonal treatments. In humans, in vivo matured oocytes are collected after ovarian stimulation. Subsequently, only intra-cytoplasmic sperm injection (ICSI) is performed in horses to produce embryos, whereas both in vitro fertilization and ICSI are applied in humans. Embryos are transferred only as blastocysts in horses. In contrast, four cells to blastocyst stage embryos are transferred in humans. Embryo and oocyte cryopreservation has been mastered in humans, but not completely in horses. Finally, both species share infertility concerns due to ageing and obesity. Thus, reciprocal knowledge could be gained through the comparative study of ART and infertility treatments both in woman and mare, even though the horse could not be used as a single model for human ART. Full article

Aim: This study examined the fertility performance of women after combined hysterolaparoscopic surgical management of endometriosis. Design: This study is a hospital-based retrospective review. Materials and Methods: Data collected from the records of all patients presented with endometriosis-related infertility using a checklist designed for the purpose. Result: A total of 81.3% (370/455) of women who have had the desire to have children became pregnant during the study period after the surgery. Of those who became pregnant, all three-hundred-forty-seven patients were followed to the end of their pregnancies. A successful live birth occurred in 94.2% (327/347) of individuals, and pregnancy loss occurred in 5.8% (20/347). The mean patient age was 34.1 ± 4.1 years, and the average duration of infertility was 3.4 ± 3.3 years. Pregnancy occurred spontaneously in 39.5% (146/370) of patients, after artificial insemination (AIH) in 3.8% (14/370) of women, and after in vitro fertilization-embryo transfer (IVF-ET) in 56.8% (210/370) of cases. Patients aged ≤ 35 years had a higher chance of conception post-surgery—84% versus 77%, respectively (p = 0.039). Based on the modes of pregnancy, the timely introduction of an assisted reproductive technique (ART) demonstrated a significant effect on fertility performance postsurgery. Comparatively, this effect was 91.3% vs. 74.1% among the ≤35- and >35-year-old age groups, respectively. There was no significant difference in reproductive performance based on stages of endometriosis, nor in the other parameters evaluated. Conclusion: Our data are consistent with previous clinical studies regarding the management options of endometriosis-related infertility. Overall, the combined hysterolaparoscopy treatment is a very effective and reliable procedure, and is even more effective when combined with ART. It enhances women’s wellbeing and quality of life, and significantly improves reproductive performance. Full article