Treffer: EMBRYO AND OOCYTE VITRIFICATION 'THE POST WARMING' CONSEQUENCES.

The ability to cryopreserve human oocytes and embryos has been a significant milestone in the field of assisted reproduction. According to the latest 2023 data from the European IVF Monitoring Consortium (EIM) for the European Society of Human Reproduction and Embryology (ESHRE), the number of vitrified oocytes and frozen embryo transfers has grown consistently each year, reaching the highest levels ever recorded in Europe. Cryopreservation's success has led to its widespread use in daily clinical practice, proving to be a reliable and effective option for various clinical scenarios. These include cases where there is a risk of ovarian hyperstimulation, unfavorable endometrial conditions, storing surplus embryos, managing pre-implantation genetic diagnosis cycles, fertility preservation, and within oocyte donation programs. Vitrification has become the method of choice for freezing oocytes and embryos, establishing the gold standard in terms of safety and achieving excellent clinical results, with survival rates ranging from 90% to 95% for oocytes and blastocyst-stage embryos. The vitrification process involves exposing oocytes and embryos to a concentrated cryoprotectant solution, which displaces much of the intracellular water, followed by rapid immersion into liquid nitrogen. During warming, the culture medium used facilitates the gradual dilution of the cryoprotectants and progressive rehydration of the cells. Over the course of 3 to 5 hours, the embryo is incubated to promote re-expansion, a critical stage where the blastocele fluid is restored to almost its pre-vitrification volume before the embryo is transferred to the patient's uterus. The ability to re-expand shortly after warming and the extent of re-expansion are key markers of blastocyst viability. While this approach is significantly less damaging than the outdated slow-freezing method, the high concentration of cryoprotectants and resulting dehydration can still affect the integrity of oocytes and embryos, potentially compromising their viability. As a result, many embryos that were graded highly in terms of morphology before vitrification may not retain the same quality upon thawing. This deterioration often manifests as a decline in overall quality, with some embryos experiencing collapse (where more than 50% of the trophectoderm detaches from the zona pellucida) or partial/total cell degeneration. Although fresh embryo collapse has been associated with negative clinical outcomes and aneuploidy, collapse after thawing shows no such correlation. However, necrotic foci and high cytoplasmic granularity are poor prognostic signs. As vitrified blastocysts are increasingly used, it has become essential to establish consistent criteria for selecting the most viable embryos. Several factors prior to vitrification have been linked to clinical success. For instance, while higher degrees of expansion may reduce the likelihood of survival after vitrification, they are associated with better implantation and live birth rates. Trophectoderm quality, although debated, is considered by some as a significant indicator of post-thaw embryo viability. Furthermore, survival rates at thawing are generally higher for day 5 blastocysts compared to day 6. Simple logistic regression models have been developed in various studies, using discrete variables like re-expansion and pre-vitrification morphology to predict embryo survival after warming and treatment outcomes. Additionally, time-lapse (TL) data from thawed embryos has been incorporated into predictive models, with TL technology offering a non-invasive method of capturing dynamic information, including re-expansion events after warming. To push beyond traditional methods, artificial intelligence (AI) is emerging as a transformative tool, offering a more objective and comprehensive analysis. New AI models, which combine computer vision with deep learning, are being developed to evaluate embryo quality and predict clinical outcomes based on static images. In this lecture, we will explore whether an AI algorithm can predict the presence of a fetal heartbeat in vitrified-warmed oocytes and embryo images. [ABSTRACT FROM AUTHOR]