P-257 Building on a commercialized time-lapse algorithm to improve the predictive power for embryo ploidy status
Authors: Choucair F , ElTaha L , AlMohammadi A , Chouliaras S , Prabhu S , Awwad J 
Published: July 2024

Study question

Would incorporating oocyte morphometric parameters into a predefined algorithmic model (KIDscore) enhance its ability to predict embryo ploidy status?

Summary answer

While larger oocyte area is significantly associated with embryo euploidy, its integration into a commercial algorithm did not add a clinical value to its predictivity.

What is known already

Currently, the genetic status of embryos is primarily assessed using preimplantation genetic testing for aneuploidy (PGT-A) following embryo biopsy. Concerns about potential harm to the embryo have spurred research into less invasive predictive tools, including time-lapse imaging (TLI). While numerous time-lapse data points have been explored, the literature is scarce when assessing the value of oocyte morphometric characteristic in predicting embryo euploidy.

Study design, size, duration

The study design was observational and retrospective. A total of 414 embryos from 98 cycles of preimplantation genetic testing for aneuploidies were included (January 2019 to December 2023).

Participants/materials, setting, methods

Trophectoderm samples were analyzed by preimplantation genetic testing for aneuploidies (PGT-A). Manually annotated time-lapse data points were recorded from which predictive models of embryo aneuploidy were developed. Measurements of the oocyte area were recorded and the automatic embryo KID scores calculated using an in-built commercial software. Multiple regression analyses were performed and a Receiver Operating Characteristic (ROC) analysis conducted.

Main results and the role of chance

The mean age of female participants included in the study was 34.5 ± 4.6 years. The rate of embryo aneuploidy detected was 41.8%. When a univariate analysis of different time-lapse data was performed, a large number of variables showed statistically significant differences between the euploid and aneuploid embryo groups. The mean oocyte area (µm2) in the euploid group was found to be significantly larger than in the aneuploid group (10151.4 ±621.6 vs 9915.3 ± 950.4; P &lt; 0.01). There was also a significant positive association between oocyte area and embryo euploid status after adjusting for confounders (P &lt;0.01). The Area Under the Curve (AUC) value was 0.62 for the aneuploidy explanatory model when oocyte area was combined with the KID score, compared to an AUC of 0.60 for the KID score alone. Although significant associations were detected, the predictive power of oocyte area measurement did not translate into a clinically useful value.

Limitations, reasons for caution

The limitations of this study stem from its retrospective nature. The low number of observations also limits the strength of the findings.

Wider implications of the findings

Although it is possible to predict embryo aneuploidy from some oocyte characteristics, the discriminatory power of designed time-lapse predictive models remained suboptimal for use in current clinical practice.

Trial registration number

Not applicable