Selecting embryos with the highest implantation potential using data mining and decision tree based on classical embryo morphology and morphokinetics.

Abstract

The objective of this work was to determine which embryonic morphokinetic parameters up to D3 of in vitro development have predictive value forimplantation for the selection of embryos for transfer in clinical practice based upon information generated from embryo transfers with known implantation data (KID). A total of 800 KID embryos (100% implantation rate (IR) per transfer and 0% IR per transfer) cultured in an incubator with Time-Lapse system were retrospectively analysed. Of them, 140 embryos implanted, whereas 660 did not. The analysis of morphokinetic parameters, together with the embryo morphology assessment on D3, enabled us to develop a hierarchical model that places the classical morphological score, the t4 and t8 morphokinetic values, as the variables with the best prognosis of implantation. In our decision tree, the classical morphological score is the most predictive parameter. Among embryos with better morphological scores, morphokinetics permits deselection of embryos with the lowest implantation potential.