Are morphokinetic parameters of embryo development associated with adverse perinatal outcomes following fresh blastocyst transfer?

An artificial intelligence algorithm for automated blastocyst morphometric parameters demonstrates a positive association with implantation potential

Blastocyst selection is primarily based on morphological scoring systems and morphokinetic data. These methods involve subjective grading and time-consuming techniques. Artificial intelligence allows for objective and quick blastocyst selection. In this study, 608 blastocysts were selected for transfer using morphokinetics and Gardner criteria. Retrospectively, morphometric parameters of blastocyst size, inner cell mass (ICM) size, ICM-to-blastocyst size ratio, and ICM shape were automatically measured by a semantic segmentation neural network model. The model was trained on 1506 videos with 102 videos for validation with no overlap between the ICM and trophectoderm models. Univariable logistic analysis found blastocyst size and ICM-to-blastocyst size ratio to be significantly associated with implantation potential. Multivariable regression analysis, adjusted for woman age, found blastocyst size to be significantly associated with implantation potential. The odds of implantation increased by 1.74 for embryos with a blastocyst size greater than the mean (147 ± 19.1 μm). The performance of the algorithm was represented by an area under the curve of 0.70 (p < 0.01). In conclusion, this study supports the association of a large blastocyst size with higher implantation potential and suggests that automatically measured blastocyst morphometrics can be used as a precise, consistent, and time-saving tool for improving blastocyst selection.

Correlation between an annotation-free embryo scoring system based on deep learning and live birth/neonatal outcomes after single vitrified-warmed blastocyst transfer: a single-centre, large-cohort retrospective study

Propose

Does an annotation-free embryo scoring system based on deep learning and time-lapse sequence images correlate with live birth (LB) and neonatal outcomes?

Methods

Patients who underwent SVBT cycles (3010 cycles, mean age: 39.3 ± 4.0). Scores were calculated using the iDAScore software module in the Vitrolife Technology Hub (Vitrolife, Gothenburg, Sweden). The correlation between iDAScore, LB rates, and total miscarriage (TM), including 1st- and 2nd-trimester miscarriage, was analysed using a trend test and multivariable logistic regression analysis. Furthermore, the correlation between the iDAScore and neonatal outcomes was analysed.

Results

LB rates decreased as iDAScore decreased (P < 0.05), and a similar inverse trend was observed for the TM rates. Additionally, multivariate logistic regression analysis showed that iDAScore significantly correlated with increased LB (adjusted odds ratio: 1.811, 95% CI: 1.666–1.976, P < 0.05) and decreased TM (adjusted odds ratio: 0.799, 95% CI: 0.706–0.905, P < 0.05). There was no significant correlation between iDAScore and neonatal outcomes, including congenital malformations, sex, gestational age, and birth weight. Multivariate logistic regression analysis, which included maternal and paternal age, maternal body mass index, parity, smoking, and presence or absence of caesarean section as confounding factors, revealed no significant difference in any neonatal characteristics.

Conclusion

Automatic embryo scoring using iDAScore correlates with decreased miscarriage and increased LB and has no correlation with neonatal outcomes.

Supplementary information

The online version contains supplementary material available at 10.1007/s10815-022-02562-5.

Blastocyst Transfer: A Risk Factor for Gestational Diabetes Mellitus in Women Undergoing In Vitro Fertilization

BACKGROUND

The risk of developing gestational diabetes mellitus (GDM) is higher in women undergoing assisted reproductive treatment than in women conceiving spontaneously.

OBJECTIVES

To determine whether the GDM risk after day-3 embryo transfer differs from the GDM risk after day-5 blastocyst transfer.

METHODS

Prospective observational study in women becoming pregnant after first fresh embryo or blastocyst transfer.

RESULTS

A total of 1579 women got pregnant and had live birth; 1300 women got day-3 embryo transfer only, whereas 279 women received at least 1 blastocyst. Of 1579 women, 252 developed GDM. Age, body mass index, baseline estradiol, baseline high-density lipoprotein, and progesterone on the day of human chorionic gonadotropin injection were not different in women receiving day-3 embryos only vs women receiving at least 1 blastocyst. The number and quality of retrieved oocytes were not different in women receiving day-3 embryo transfer from those receiving blastocysts. Our study confirmed already established GDM risk factors such as age and body mass index, baseline estradiol, and high-density lipoprotein, as well as progesterone after ovarian stimulation. We furthermore demonstrate that the GDM incidence in women receiving day-5 blastocyst transfer was significantly higher than those who received day-3 embryo transfer (21.15% vs 14.85%; P = 0.009). Considering confounding factors, we likewise saw that blastocyst transfer was an independent procedure-related GDM risk factor [P = 0.009, Exp (B): 1.56, 95% CI: 1.12-2.18].

CONCLUSION

Blastocyst transfer after in vitro fertilization/intracytoplasmic sperm injection increases the risk of developing GDM.