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Using artificial intelligence (AI) and time-lapse to improve human blastocyst morphology evaluation
Abstract
Abstracts of the
34th Annual Meeting of the
European Society of
Human Reproduction and Embryology
Purpose of review:
The study of embryonic development through conventional microscopy has contributed significantly to the success of IVF. However, clinical pregnancy rates per transfer remain as low as 30% according to the latest records of European society if human reproduction and society if assisted reproduction. Considering the increased need to reduce the number of multiple pregnancies, the embryologist is required to improve embryo selection methods to reduce the number of embryos transferred and identify those with the highest implantation potential. This represents a big challenge considering that applying this strategy could jeopardize the overall success rates. New strategies have been proposed including the use of time-lapse systems among others. Although this technology has been used for a decade in IVF labs controversies still exist regarding its potential to substitute conventional morphology for embryo evaluation.
Recent findings:
Lately, different algorithms have been developed correlating embryo kinetics to blastocyst formation, implantation potential, chromosomal content and live birth rate. Moreover, automation and the use of artificial intelligence have recently been introduced to improve this technology.
Summary:
The present review describes the time-lapse technology and the models available, using a Strength, Weaknesses, Opportunities and Threats analysis based on the clinical experience and published data since 2010.
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