Embryo selection: the role of time-lapse monitoring
- PMID: 25510244
- PMCID: PMC4290130
- DOI: 10.1186/1477-7827-12-124
Embryo selection: the role of time-lapse monitoring
Abstract
In vitro fertilization has been available for over 3 decades. Its use is becoming more widespread worldwide, and in the developed world, up to 5% of children have been born following IVF. It is estimated that over 5 million children have been conceived in vitro. In addition to giving hope to infertile couples to have their own family, in vitro fertilization has also introduced risks as well. The risk of multiple gestation and the associated maternal and neonatal morbidity/mortality has increased significantly over the past few decades. While stricter transfer policies have eliminated the majority of the high-order multiples, these changes have not yet had much of an impact on the incidence of twins. A twin pregnancy can be avoided by the transfer of a single embryo only. However, the traditionally used method of morphologic embryo selection is not predictive enough to allow routine single embryo transfer; therefore, new screening tools are needed. Time-lapse embryo monitoring allows continuous, non-invasive embryo observation without the need to remove the embryo from optimal culturing conditions. The extra information on the cleavage pattern, morphologic changes and embryo development dynamics could help us identify embryos with a higher implantation potential. These technologic improvements enable us to objectively select the embryo(s) for transfer based on certain algorithms. In the past 5-6 years, numerous studies have been published that confirmed the safety of time-lapse technology. In addition, various markers have already been identified that are associated with the minimal likelihood of implantation and others that are predictive of blastocyst development, implantation potential, genetic health and pregnancy. Various groups have proposed different algorithms for embryo selection based on mostly retrospective data analysis. However, large prospective trials are needed to study the full benefit of these (and potentially new) algorithms before their introduction into daily practice can be recommended.
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