#91 : Development of a Combined Artificial Intelligence Score for Evaluating Both Embryo Ploidy and Viability to Aid in Embryo Selection During IVF

Autor: Sonya Diakiw, Matthew VerMilyea, Michelle Perugini, Tuc Nguyen, Don Perugini, Jonathan Hall
Jazyk: angličtina
Rok vydání: 2023
Předmět:
Zdroj: Fertility & Reproduction, Vol 05, Iss 04, Pp 463-463 (2023)
Druh dokumentu: article
ISSN: 26613182
2661-3174
2661-3182
DOI: 10.1142/S266131822374239X
Popis: Background and Aims: Artificial intelligence (AI) is being increasingly used for non-invasive evaluation of embryo quality during IVF. Previous studies described development of AI for selecting embryos likely to be euploid (genetics AI), or likely to lead to clinical pregnancy (viability AI), based on analysis of images of blastocysts on day 5 of development. The aim of this study was to determine if a combination of these AI scores could be used to effectively evaluate both outcomes. Method: 936 embryo images with pre-implantation genetic testing for aneuploidies (PGT-A) outcomes, and 479 embryo images with clinical pregnancy outcomes, were retrospectively obtained from 12 IVF clinics in 5 countries. Performance was evaluated for each AI score alone, and the average score of the two AIs. The ability to select euploid or viable embryos was evaluated using ROC-AUC analyses, and a simulated cohort ranking method reported in the literature. Results: The average score of the two AIs was generally as effective at selecting euploid embryos as the genetics AI, and just as effective at selecting viable embryos as the viability AI. Results for both analyses are presented below. Conclusion: An AI score that can evaluate both embryo ploidy and viability simultaneously is useful for selecting preferred embryos for analysis or transfer. These results suggest that it is feasible to generate a single score for evaluating overall embryo quality using a non-invasive approach.
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