Embryo ranking agreement between embryologists and artificial intelligence algorithms.

OBJECTIVE: To evaluate the degree of agreement of embryo ranking between embryologists and eight artificial intelligence (AI) algorithms. DESIGN: Retrospective study. PATIENT(S): A total of 100 cycles with at least eight embryos were selected from the Weill Cornell Medicine database. For each embryo, the full-length time-lapse (TL) videos, as well as a single embryo image at 120 hours, were given to five embryologists and eight AI algorithms for ranking. INTERVENTION(S): None. MAIN OUTCOME MEASURE(S): Kendall rank correlation coefficient (Kendall's τ). RESULT(S): Embryologists had a high degree of agreement in the overall ranking of 100 cycles with an average Kendall's tau (K-τ) of 0.70, slightly lower than the interembryologist agreement when using a single image or video (average K-τ = 0.78). Overall agreement between embryologists and the AI algorithms was significantly lower (average K-τ = 0.53) and similar to the observed low inter-AI algorithm agreement (average K-τ = 0.47). Notably, two of the eight algorithms had a very low agreement with other ranking methodologies (average K-τ = 0.05) and between each other (K-τ = 0.01). The average agreement in selecting the best-quality embryo (1/8 in 100 cycles with an expected agreement by random chance of 12.5%; confidence interval [CI]95: 6%-19%) was 59.5% among embryologists and 40.3% for six AI algorithms. The incidence of the agreement for the two algorithms with the low overall agreement was 11.7%. Agreement on selecting the same top two embryos/cycle (expected agreement by random chance corresponds to 25.0%; CI95: 17%-32%) was 73.5% among embryologists and 56.0% among AI methods excluding two discordant algorithms, which had an average agreement of 24.4%, the expected range of agreement by random chance. Intraembryologist ranking agreement (single image vs. video) was 71.7% and 77.8% for single and top two embryos, respectively. Analysis of average raw scores indicated that cycles with low diversity of embryo quality generally resulted in a lower overall agreement between the methods (embryologists and AI models). CONCLUSION(S): To our knowledge, this is the first study that evaluates the level of agreement in ranking embryo quality between different AI algorithms and embryologists. The different concordance methods were consistent and indicated that the highest agreement was intraembryologist agreement, followed by interembryologist agreement. In contrast, the agreement between some of the AI algorithms and embryologists was similar to the inter-AI algorithm agreement, which also showed a wide range of pairwise concordance. Specifically, two AI models showed intra- and interagreement at the level expected from random selection.

Influence of blastocysts morphological score on pregnancy outcomes and neonate′s condition in vitrified-warmed transfer cycles / 实用医学杂志

Objective To estimate the effect of blastocysts morphological score on pregnancy outcomes and neonate′s condition in vitrified-warmed single-blastocyst transfer cycles. Methods A retrospective analysis of 586 cycles of vitrified-warmed single-blastocyst transfer from Mar. 2010 to Feb.2016 was performed and the influ-ence of day of vitrification,inner cell mass(ICM)and trophectoderm(TE)scores on pregnancy outcomes and neo-nate′s condition were observed. Results There were no significant differences in clinical pregnancy rate,birth weight and sex ration of newborn between different vitrification day,ICM score and TE score.The day of vitrifica-tion and ICM score can significantly influence pregnancy loss rate,and were the two primary predictors of pregnan-cy loss rate. Vitrification day,ICM score and TE score exerted significant influence on live birth rate(P < 0.05) and TE score was the primary factor of live birth rate. Conclusions Day 5 vitrified blastocysts with higher quality of ICM and TE can provide high live birth rate and low pregnancy loss rate,but it could not predict the weight and gender of the newborn.

The impact of age on blastocyst scoring after single and double embryo transfers.

OBJECTIVE: The aim of the present study was to assess the putative relationship between patient's age and blastocyst scores, in single (SET) or double (DET) transfer cycles, that resulted in single or twin pregnancy or non-pregnancy. Second, we analyzed the effect of maternal age on clinical gestation and implantation rates after single and double blastocyst transfers. METHODS: Retrospective analysis of 164 assisted reproduction cycles with embryo transfers. RESULTS: Data demonstrated that for both, young (<35 years of age) and older (≥35 years of age) women, trophectoderm (TE) score is the most important parameter to assess concerning embryo selection. However, inner cell mass (ICM) also plays an important role on blastocyst selection in the group of older patients. In addition, our data shows that for young women the transfer of a single blastocyst results in similar gestational rates as those for DET. CONCLUSION: We suggest that blastocyst grading for patients aged 35 years or above shall be performed using a strict grading policy, possibly not of a single parameter, but TE, ICM and expansion grades together, to choose the "best combined-score blastocyst". DETs should be considered, particularly after previous cycles with pregnancy failures.