Effect of morphokinetics and morphological dynamics of cleavage stage on embryo developmental potential: A time-lapse study.

Objective: Using a non-invasive method to select the most competent embryo is essential in in vitro fertilization (IVF). Since the beginning of clinical application of time-lapse technology, several studies have proposed models using the time-lapse imaging system for predicting the IVF outcome. This study used both morphokinetic and morphological dynamic parameters to select embryos with the highest developmental potential.

Materials And Methods: A total of 23 intracytoplasmic sperm injection treatment cycles with 138 fertilized oocytes were included in this study. All embryos were cultured to the blastocyst stage, and embryo development was recorded every 10 min by using a time-lapse imaging system. Morphokinetic parameters and eight major abnormal division behaviors were studied to determine their effects on blastocyst formation. The most influential variables were used in hierarchical classification for blastocyst formation prediction.

Results: Several parameters were significantly related to the developmental potential. Embryos with the timing of pronuclear fading (tPNF) of >26.4 h post insemination (hpi), the timing of division to two cells (t2) of >29.1 hpi, and the timing of division to four cells (t4) of >41.3 hpi showed the lowest blastocyst formation rate. The abnormal division behaviors of fragmentation >50%, direct cleavage, reverse cleavage, and delayed division or developmental arrest were found to be detrimental to blastocyst formation. On the basis of these results, we propose a hierarchical model classification, in which embryos are classified into groups A-D according to their developmental potential. The blastocyst formation rates of groups A, B, C, and D were 80.0%, 77.8%, 53.7%, and 22.2% (p < 0.001). The good blastocyst rates of groups A, B, C, and D were 60.0%, 44.4%, 14.6%, and 11.1% (p = 0.007).

Conclusion: We propose a hierarchical classification system for blastocyst formation prediction, which provides information for embryo selection by using a time-lapse imaging system.