Selection of preimplantation embryos using time‐lapse microscopy in in vitro fertilization: State of the technology and future directions

Abstract

In this review, our aim is to give an overview of the state of the technology and clinical outcomes of time-lapse microscopy in improving embryo selection as a key step in in vitro fertilization (IVF). Using traditional incubators, morphologic assessment of the fertilized embryos is limited to snapshots at a few discrete points in time, reducing the amount of information that could potentially be obtained. Time-lapse monitoring overcomes this limitation without exposing the embryos to environmental changes. Moreover, time-lapse may introduce new dynamic markers of embryo competence as well as a versatile embryo evaluation and provides novel information regarding human embryo development. In the last few years, various algorithms have been developed correlating the kinetics of early embryo development to blastocyst formation, implantation potential, chromosomal content and live birth rate. There is not yet a universally accepted algorithm, and significant knowledge gaps remain that can provide opportunities for further research in this field.

Outcome of in vitro fertilization cycles with automatic time‐lapse instrumentation combined with the early embryo viability assessment score

“…Although morphology is important, there was a discrepancy between the EEVA score and the Veeck score in this study, therefore, embryo selection using a TLT system, as well as conventional morphology, should be considered. Freur et al unsuccessfully developed a previously published model to forecast implantation based on morphokinetic categories, 21 and Aparicio‐Ruitz et al reported that there is a direct correlation between the blastocyst rate and the percentage of optimal blastocysts according to each of these categories 22 . Moreover, Liu et al revealed that a morphokinetic algorithm based on quantitative‐timing parameters may vary between laboratories but emphasized that qualitative measures improve reproducibility in each laboratory 23 .…”

Are we approaching automated assisted reproductive technology? Embryo culture, metabolomics, and cryopreservation

“…To date, a universally accepted morphokinetic algorithm does not exist (52). Embryo development is influenced by a variety of factors that range from laboratory settings to patient clinical parameters.…”

Novel and conventional embryo parameters as input data for artificial neural networks: an artificial intelligence model applied for prediction of the implantation potential

“…The events more frequently used to predict implantation were cc2, t5 and s2 (13,(28)(29)(30)(31)(32). Even though morphokinetic parameters are not enough to predict ploidy (33), most of the embryos with abnormal cell division times have chromosomal alterations (5,29,34). It is also reported that aneuploid embryos are delayed compared to euploid ones in different morphokinetic parameters, such as the timing of morula and blastocyst formation (35)(36)(37).…”