P-174 Do culture conditions alter the efficacy of embryo selection algorithms using time-lapse technology? Development of novel embryo selection model with embryos cultured in different conditions

Abstract

Abstract Study question Is the efficacy of embryo selection models altered by the conditions employed for embryo culture? Summary answer The predictive capacity of morphology and morphokinetics-based selection models might be dependent on the incubator and culture conditions employed. What is known already Morphological assessment remains the gold-standard for embryo selection. However, since the introduction of time-lapse technology to the incubators used for embryo culture, many selection algorithms based on morphokinetic annotations have been developed, adding objectivity to the embryo selection process. The efficacy and reproducibility of these algorithms have been questioned by other authors, being potentially influenced by characteristics of the patients and differing culture conditions. Nowadays, there are several incubators with time-lapse technology in the market, some of them providing novel features such as culture in high humidity conditions, which has been related to differences in the morphokinetics of embryo development. Study design, size, duration Retrospective external validation of an embryo selection algorithm based on morphokinetic annotations, in a set of 555 transferred blastocysts cultured in a time-lapse system in dry (DC, n = 281) or humid conditions (HC, n = 274), and comparison with selection by morphological criteria. A novel selection model was developed considering morphokinetic annotations of our embryo dataset, including blastocysts cultured in DC and HC. Embryos belong to autologous and oocyte-donation ICSI cycles performed in a clinic over 3 years. Participants/materials, setting, methods Embryos were cultured in a Geri incubator (Genea Biomedx) and automatically annotated (Connect&Assess2.0). The efficacy of the algorithm published by Motato et al, 2016, and ASEBIR morphological grading was assessed by Generalized Estimating Equations (GEE), considering possible confounders. Efficacy was quantified by the Area Under the ROC Curve (AUC), its 95% confidence interval (CI) and statistical significance was assessed by the Mann-Whitney test. A novel algorithm was developed aided by the visual tool FertAI (Merck). Main results and the role of chance Transferred blastocysts with known implantation data were classified A-D in base of the algorithm published by Motato et al, 2016, according to the optimal range of 2 morphokinetic parameters, tEB and s3, empirically-obtained in embryos cultured in an Embryoscope incubator. The algorithm had an AUC = 0.591, 95%CI(0.542−0.64), resulting significantly predictive of implantation (P<0.001), but lower than the efficacy reported by the authors (AUC = 0.602, 95%CI(0.559−0.645)). The efficacy was different in the two culture conditions: AUC(DC) = 0.608, 95%CI(0.54−0.676), P = 0.002; AUC(HC) = 0.588, 95%CI(0.518−0.657), P = 0.103. The morphological evaluation (3 categories: A (best) to C (worse)) resulted statistically predictive of implantation: AUC of 0.596, 95%CI(0.547−0.646), P<0.001. Again, its efficacy was different in DC (AUC = 0.626, 95%CI(0.559−0.693), P<0.001) and HC (AUC = 0.589, 95%CI(0.52−0.657), P = 0.013). The lower efficacy shown by these algorithms might be associated with different morphokinetic development of embryos cultured in a different incubator and different culture conditions. Hence, a novel scoring model was developed with empirically-determinated optimal ranges of three morphokinetic parameters, considering, for the first time, embryos cultured in DC and HC: tEB<113.874; (t5-t3)/(t5-t2) = [0.521, 0.554] and cc2 = [10.34, 11.58], yielding a score from 0 to 3. The selection model resulted in an AUC = 0.637, 95%CI(0.59−0.684), and was equally efficient in DC and HC: AUC(DC) = 0.645, 95%CI(0.579−0.712); AUC(HC) = 0.645, 95%CI(0.579−0.711); P<0.001). Limitations, reasons for caution This is a primary approach to a development of a selection algorithm using morphokinetic data of embryos cultured until blastocyst stage in a Geri incubator. The efficacy and reproducibility of the model must be validated in a different dataset. Wider implications of the findings The lower efficacy shown by a selection algorithm developed in a different incubator supports the necessity of adjusting selection tools for the specific culture conditions employed by each IVF laboratory. This is the first scoring model developed for selection of blastocysts using morphokinetic parameters recorded in a Geri time-lapse incubator. Trial registration number Not applicable