Comparison of euploid blastocyst expansion with subgroups of single chromosome, multiple chromosome, and segmental aneuploids using an AI platform from donor egg embryos

The Istanbul Consensus update: a revised ESHRE/ALPHA consensus on oocyte and embryo static and dynamic morphological assessment† ‡

This European Society of Human Reproduction and Embryology (ESHRE)/Alpha Scientists in Reproductive Medicine (ALPHA) consensus document provides several novel recommendations to assess oocyte and embryo morphology and rank embryos for transfer. A previous ALPHA/ESHRE consensus on oocyte and embryo morphological assessment was published in 2011. After more than a decade, and the integration of time-lapse technology into embryo culture and assessment, a thorough review and update was needed. A working group consisting of ALPHA members and ESHRE Special interest group of Embryology members formulated recommendations on oocyte and embryo assessment. The working group included 17 internationally recognized experts with extensive experience in clinical embryology. Seven members represented ALPHA and eight members represented ESHRE, along with two methodological experts from the ESHRE central office. Based on a systematic literature search and discussion of existing evidence, the recommendations of the Istanbul Consensus (2011) were reassessed and, where appropriate, updated based on consensus within the working group. A stakeholder review was organized after the updated draft was finalized. The final version was approved by the working group, the ALPHA Executive Committee and the ESHRE Executive Committee. This updated consensus paper provides 20 recommendations focused on the timeline of preimplantation developmental events and morphological criteria for oocyte, zygote and embryo assessment. Based on the duration of embryo culture, recommendations are given on the frequency and timing of assessments to ensure consistency and effectiveness. Several criteria relevant to oocyte and embryo morphology have not been well studied, leading to either a recommendation against their use for grading or for their use in ranking rather than grading. Future updates may require further revision of these recommendations. This document provides embryologists with advice on best practices when assessing oocyte and embryo quality based on the most recent evidence.

The Istanbul consensus update: a revised ESHRE/ALPHA consensus on oocyte and embryo static and dynamic morphological assessment†,‡

STUDY QUESTION

What are the current recommended criteria for morphological assessment of oocytes, zygotes, and embryos?

SUMMARY ANSWER

The present ESHRE/Alpha Scientists in Reproductive Medicine consensus document provides several novel recommendations to assess oocyte and embryo morphology and rank embryos for transfer.

WHAT IS KNOWN ALREADY

A previous Alpha Scientists in Reproductive Medicine/ESHRE consensus on oocyte and embryo morphological assessment was published in 2011. After more than a decade, and the integration of time-lapse technology into embryo culture and assessment, a thorough review and update was needed.

STUDY DESIGN, SIZE, DURATION

A working group consisting of Alpha Scientists in Reproductive Medicine executive committee members and ESHRE Special interest group of Embryology members formulated recommendations on oocyte and embryo assessment.

PARTICIPANTS/MATERIALS, SETTING, METHODS

The working group included 17 internationally recognized experts with extensive experience in clinical embryology. Seven members represented Alpha Scientists in Reproductive Medicine and eight members represented ESHRE, along with to two methodological experts from the ESHRE central office. Based on a systematic literature search and discussion of existing evidence, the recommendations of the Istanbul Consensus (2011) were reassessed and, where appropriate, updated based on consensus within the working group. A stakeholder review was organized after the updated draft was finalized. The final version was approved by the working group, the Alpha executive committee and the ESHRE Executive Committee.

MAIN RESULTS AND THE ROLE OF CHANCE

This updated consensus paper provides 20 recommendations focused on the timeline of preimplantation developmental events and morphological criteria for oocyte, zygote, and embryo assessment. Based on duration of embryo culture, recommendations are given on the frequency and timing of assessments to ensure consistency and effectiveness.

LIMITATIONS, REASONS FOR CAUTION

Several criteria relevant to oocyte and embryo morphology have not been well studied, leading to either a recommendation against their use for grading or for their use in ranking rather than grading. Future updates may require further revision of these recommendations.

WIDER IMPLICATIONS OF THE FINDINGS

This document provides embryologists with advice on best practices when assessing oocyte and embryo quality based on the most recent evidence.

STUDY FUNDING/COMPETING INTEREST(S)

The consensus meeting and writing of the paper were supported by funds from ESHRE and Alpha Scientists in Reproductive Medicine. The working group members did not receive any payment. G.C. declared payments or honoraria for lectures from Gedeon Richter and Cooper Surgical. A.C. declared text book royalties (Mastering Clinical Embryology, published 2024), consulting fees from Cooper Surgical, Gedeon Richter and TMRW Life Sciences, honoraria for lectures from Merck, Ferring, and Gedeon Richter, and participation in the HFEA Scientific Advances Committee; she also disclosed being treasurer and vice-president of Alpha Scientists in Reproductive Medicine, a shareholder in Care Fertility Limited and Fertile Mind Limited, and having stock options in TMRW Life Sciences and U-Ploid Biotechnology Ltd. L.R. declared consulting fees from Organon, payments or honoraria for lectures from Merck, Organon, IBSA, Finox, Geden Richter, Origio, Organon, Ferring, Fundation IVI; she also disclosed being a member of the Advisory Scientific Board of IVIRMA (Paid) and a member of the Advisory Scientific Board of Nterilizer (unpaid). I.S. declared payments or honoraria for lectures from Vitrolife and Cooper Surgical, and stock options from Alife Health. M.A. declared payments or honoraria for lectures from Vitrolife and support for attending meetings from Vitrolife and Cooper Surgical (both unrelated to this manuscript). The other authors have no conflicts of interest to declare.

DISCLAIMER

This Good Practice Recommendations (GPRs) document represents the consensus views of the members of this working group based on the scientific evidence available at the time of the meeting. GPRs should be used for information and educational purposes. They should not be interpreted as setting a standard of care or be deemed inclusive of all proper methods of care or be exclusive of other methods of care reasonably directed to obtaining the same results. They do not replace the need for application of clinical judgement to each individual presentation, or variations based on locality and facility type.

Deep learning applications for human embryo assessment using time-lapse imaging: scoping review

Background

The integration of deep learning (DL) and time-lapse imaging technologies offers new possibilities for improving embryo assessment and selection in clinical in vitro Fertilization (IVF).

Objectives

This scoping review aims to explore the range of deep learning model applications in the evaluation and selection of embryos monitored through time-lapse imaging systems.

Methods

A total of 6 electronic databases (Scopus, MEDLINE, EMBASE, ACM Digital Library, IEEE Xplore, and Google Scholar) were searched for peer-reviewed literature published before May 2024. We adhered to the PRISMA guidelines for reporting scoping reviews.

Results

Out of the 773 articles reviewed, 77 met the inclusion criteria. Over the past four years, the use of DL in embryo analysis has increased rapidly. The primary applications of DL in the reviewed studies included predicting embryo development and quality (61%, n = 47) and forecasting clinical outcomes, such as pregnancy and implantation (35%, n = 27). The number of embryos involved in the studies exhibited significant variation, with a mean of 10,485 (SD = 35,593) and a range from 20 to 249,635 embryos. A variety of data types have been used, namely images of blastocyst-stage embryos (47%, n = 36), followed by combined images of cleavage and blastocyst stages (23%, n = 18). Most of the studies did not provide maternal age details (82%, n = 63). Convolutional neural networks (CNNs) were the predominant deep learning architecture used, accounting for 81% (n = 62) of the studies. All studies utilized time-lapse video images (100%) as training data, while some also incorporated demographics, clinical and reproductive histories, and IVF cycle parameters. Most studies utilized accuracy as the discriminative measure (58%, n = 45).

Conclusion

Our results highlight the diverse applications and potential of deep learning in clinical IVF and suggest directions for future advancements in embryo evaluation and selection techniques.

Quantitative Standardized Expansion Assay: An Artificial Intelligence-Powered Morphometric Description of Blastocyst Expansion and Zona Thinning Dynamics

Artificial intelligence applied to time-lapse microscopy may revolutionize embryo selection in IVF by automating data collection and standardizing the assessments. In this context, blastocyst expansion dynamics, although being associated with reproductive fitness, have been poorly studied. This retrospective study (N = 2184 blastocysts from 786 cycles) exploited both technologies to picture the association between embryo and inner-cell-mass (ICM) area in µm2, the ICM/Trophectoderm ratio, and the zona pellucida thickness in µm (zp-T) at sequential blastocyst expansion stages, with (i) euploidy and (ii) live-birth per transfer (N = 548 transfers). A quantitative-standardized-expansion-assay (qSEA) was also set-up; a novel approach involving automatic annotations of all expansion metrics every 30 min across 5 h following blastulation. Multivariate regressions and ROC curve analyses were conducted. Aneuploid blastocysts were slower, expanded less and showed thicker zp. The qSEA outlined faster and more consistent zp thinning processes among euploid blastocysts, being more or as effective as the embryologists in ranking euploid embryo as top-quality of their cohorts in 69% of the cases. The qSEA also outlined faster and more consistent blastocyst expansion and zp thinning dynamics among euploid implanted versus not implanted blastocysts, disagreeing with embryologists' priority choice in about 50% of the cases. In conclusion, qSEA is a promising objective, quantitative, and user-friendly strategy to predict embryo competence that now deserves prospective validations.

Single-cell DNA sequencing reveals a high incidence of chromosomal abnormalities in human blastocysts

Aneuploidy, a deviation from the normal chromosome copy number, is common in human embryos and is considered a primary cause of implantation failure and early pregnancy loss. Meiotic errors lead to uniformly abnormal karyotypes, while mitotic errors lead to chromosomal mosaicism: the presence of cells with at least 2 different karyotypes within an embryo. Knowledge about mosaicism in blastocysts mainly derives from bulk DNA sequencing (DNA-Seq) of multicellular trophectoderm (TE) and/or inner cell mass (ICM) samples. However, this can only detect an average net gain or loss of DNA above a detection threshold of 20%-30%. To accurately assess mosaicism, we separated the TE and ICM of 55 good-quality surplus blastocysts and successfully applied single-cell whole-genome sequencing (scKaryo-Seq) on 1,057 cells. Mosaicism involving numerical and structural chromosome abnormalities was detected in 82% of the embryos, in which most abnormalities affected less than 20% of the cells. Structural abnormalities, potentially caused by replication stress and DNA damage, were observed in 69% of the embryos. In conclusion, our findings indicated that mosaicism was prevalent in good-quality blastocysts, whereas these blastocysts would likely be identified as normal with current bulk DNA-Seq techniques used for preimplantation genetic testing for aneuploidy.