New frontiers in embryo selection.

Human infertility is a major global public health issue estimated to affect one out of six couples, while the number of assisted reproduction cycles grows impressively year over year. Efforts to alleviate infertility using advanced technology are gaining traction rapidly as infertility has an enormous impact on couples and the potential to destabilize entire societies if replacement birthrates are not achieved. Artificial intelligence (AI) technologies, leveraged by the highly advanced assisted reproductive technology (ART) industry, are a promising addition to the armamentarium of tools available to combat global infertility. This review provides a background for current methodologies in embryo selection, which is a manual, time-consuming, and poorly reproducible task. AI has the potential to improve this process (among many others) in both the clinician's office and the IVF laboratory. Embryo selection is evolving through digital methodologies into an automated procedure, with superior reliability and reproducibility, that is likely to result in higher pregnancy rates for patients. There is an emerging body of data demonstrating the utility of AI applications in multiple areas in the IVF laboratory. AI platforms have been developed to evaluate individual embryologist performance; to provide quality assurance for culture systems; to correlate embryologist's assessments and AI systems; to predict embryo ploidy, implantation, fetal heartbeat, and live birth outcome; and to replace the current "analogue" system of embryo selection with a digital paradigm. AI capability will distinguish high performing, high profit margin, low-cost, and highly successful IVF clinic business models. We think it will become the standard, "new normal" in IVF labs, as rapidly and thoroughly as vitrification, blastocyst culture, and intracytoplasmic sperm injection replaced their predecessor technologies. At the time of this review, the AI technology to automate embryo evaluation and selection has robustly matured, and therefore, it is the main focus of this review.

Premature luteinization and in vitro fertilization outcome in gonadotropin/gonadotropin-releasing hormone antagonist cycles in women with polycystic ovary syndrome.

OBJECTIVE: To determine the incidence of premature luteinization in patients with polycystic ovary syndrome (PCOS) undergoing controlled ovarian hyperstimulation (COH) with exogenous gonadotropin/GnRH antagonist (GnRH-a); to compare clinical outcomes in patients with and without premature luteinization. DESIGN: Retrospective case series. SETTING: IVF clinic. PATIENT(S): Thirty-five treatment cycles in 30 patients with PCOS. INTERVENTION(S): Controlled ovarian hyperstimulation with gonadotropin/GnRH-a protocol. MAIN OUTCOME MEASURE(S): Premature luteinization defined as a P concentration of >/=1.3 ng/mL on the day of hCG administration; number of oocytes and two pronuclei (2PN) embryos; implantation and clinical pregnancy rates (PR). RESULT(S): The incidence of premature luteinization was 28%. Compared with those without premature luteinization, patients with premature luteinization had a higher number of oocytes retrieved (24.1 +/- 13.3 vs. 12.0 +/- 5.9) and greater number of mature oocytes (19.7 +/- 11.7 vs. 9.5 +/- 4.5), respectively. The number of good quality embryos and embryos transferred was not significantly different between groups. Although implantation rates (56% vs. 40%) and clinical PRs (36% vs. 30%) were higher in patients without premature luteinization, the differences were not statistically significant. CONCLUSION(S): The patients with PCOS with premature luteinization had a higher number of oocytes retrieved and mature oocytes, and similar clinical PRs as patients with PCOS without premature luteinization.