![]() ![]() In addition, the time-lapse systems from Vitrolife contain a decision support tool, the KIDScore D5™ (EmbryoViewer software Vitrolife), which increases the objectivity and consistency of embryo evaluation by ranking embryos according to probability of implantation. Nowadays, there are few time-lapse incubators that include specific computer software capable of detecting division time points and embryo morphological features ( Kragh et al., 2019). Finally, the most innovative approach is the use of AI to directly predict pregnancy, implantation or even live birth by using only time-lapse images ( Khosravi et al., 2019 Tran et al., 2019 Bori et al., 2020a). In this case, AI is employed in an indirect way to optimize the daily workflow based on existing traditional parameters. Embryo selection can be automated by using artificial intelligence (AI) to predict morphokinetic and morphology parameters ( Kragh et al., 2019). These values are then used in models of clinical outcome prediction ( Meseguer et al., 2011 Basile et al., 2015 Motato et al., 2016). The conventional approach is for embryologists to manually annotate a number of morphological and/or morphokinetic parameters to evaluate the quality of the embryo. Confounding factors that can affect the reliability of time-lapse technology algorithms include the environment and the techniques used in each laboratory, patient characteristics and the subjectivity of manual annotations ( Sundvall et al., 2013 Martínez-Granados et al., 2017 ESHRE Working Group on Time-Lapse Technology et al., 2020).Ĭurrently, there are three main options for embryo evaluation and selection with time-lapse systems. The lack of reproducibility is the main obstacle to a universal use of existing algorithms ( Fréour et al., 2015 Barrie et al., 2017). initiation of blastulation, morula formation time, or trophectoderm quality) have been identified as the most reliable predictors of live birth ( Fishel et al., 2017, 2018 Rienzi et al., 2019). The length of the second cell cycle, the division time to five cells, the second synchrony (the time interval between division from three to four cells) and the time of pronuclei fading are the most influential parameters of embryo implantation potential, according to the review of time-lapse technology by Del Gallego et al. Early cleavage ( Milewski et al., 2015) and time of morula formation ( Motato et al., 2016) have been used to predict blastocyst formation. Manual annotations of quantitative and qualitative parameters have been used to predict blastocyst formation, implantation potential or even live birth. However, this method of evaluation has often involved a loss of information, and an inability to observe embryo developmental events related to treatment outcome, such as the existence of multinucleated blastomeres ( Meseguer et al., 2011), direct cleavage ( Rubio et al., 2012 Desai et al., 2018) or reverse cleavage ( Liu et al., 2014).Ĭharacterizing the morphokinetic parameters of embryo development went hand-in-hand with the introduction of time-lapse technology in IVF laboratories, and several algorithms have been created in an attempt to find out relevant variables that can improve embryo selection ( Meseguer et al., 2011 Cruz et al., 2012 Dal Canto et al., 2012 Motato et al., 2016). Prior to the introduction of time-lapse technologies, morphological features were assessed at specific time points during embryo development. ![]() Evaluation in vitro has been based on embryo morphology since the beginning of assisted reproduction. KIDScore D5™, automatic embryo scoring, implantation, live birth, time-lapse, preimplantation genetic testing for aneuploidy, embryo morphology, automatism IntroductionĮmbryo assessment and selection are defining factors in the successful outcome of IVF treatment.
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