Development of a generally applicable morphokinetic algorithm capable of predicting the implantation potential of embryos transferred on Day 3

Clinical effectiveness and safety of time-lapse imaging systems for embryo incubation and selection in in-vitro fertilisation treatment (TILT): a multicentre, three-parallel-group, double-blind, randomised controlled trial

BACKGROUND

Time-lapse imaging systems for embryo incubation and selection might improve outcomes of in-vitro fertilisation (IVF) and intracytoplasmic sperm injection (ICSI) treatment due to undisturbed embryo culture conditions, improved embryo selection, or both. However, the benefit remains uncertain. We aimed to evaluate the effectiveness of time-lapse imaging systems providing undisturbed culture and embryo selection, and time-lapse imaging systems providing only undisturbed culture, and compared each with standard care without time-lapse imaging.

METHODS

We conducted a multicentre, three-parallel-group, double-blind, randomised controlled trial in participants undergoing IVF or ICSI at seven IVF centres in the UK and Hong Kong. Embryologists randomly assigned participants using a web-based system, stratified by clinic in a 1:1:1 ratio to the time-lapse imaging system for undisturbed culture and embryo selection (time-lapse imaging group), time-lapse imaging system for undisturbed culture alone (undisturbed culture group), and standard care without time-lapse imaging (control group). Women were required to be aged 18-42 years and men (ie, their partners) 18 years or older. Couples had to be receiving their first, second, or third IVF or ICSI treatment and could not participate if using donor gametes. Participants and trial staff were masked to group assignment, embryologists were not. The primary outcome was live birth. We performed analyses using the intention-to-treat principle and reported the main analysis in participants with primary outcome data available (full analysis set). The trial is registered on the International Trials Registry (ISRCTN17792989) and is now closed.

FINDINGS

1575 participants were randomly assigned to treatment groups (525 participants per group) between June 21, 2018, and Sept 30, 2022. The live birth rates were 33·7% (175/520) in the time-lapse imaging group, 36·6% (189/516) in the undisturbed culture group, and 33·0% (172/522) in the standard care group. The adjusted odds ratio was 1·04 (97·5% CI 0·73 to 1·47) for time-lapse imaging arm versus control and 1·20 (0·85 to 1·70) for undisturbed culture versus control. The risk reduction for the absolute difference was 0·7 percentage points (97·5% CI -5·85 to 7·25) between the time-lapse imaging and standard care groups and 3·6 percentage points (-3·02 to 10·22) between the undisturbed culture and standard care groups. 79 serious adverse events unrelated to the trial were reported (n=28 in time-lapse imaging, n=27 in undisturbed culture, and n=24 in standard care).

INTERPRETATION

In women undergoing IVF or ICSI treatment, the use of time-lapse imaging systems for embryo culture and selection does not significantly increase the odds of live birth compared with standard care without time-lapse imaging.

FUNDING

Barts Charity, Pharmasure Pharmaceuticals, Hong Kong OG Trust Fund, Hong Kong Health and Medical Research Fund, Hong Kong Matching Fund.

Artificial intelligence-powered assisted ranking of sibling embryos to increase first cycle pregnancy rate

RESEARCH QUESTION

Could EMBRYOLY, an artificial intelligence embryo evaluation tool, assist embryologists to increase first cycle pregnancy rate and reduce cycles to pregnancy for patients?

DESIGN

Data from 11,988 embryos were collected via EMBRYOLY from 2666 egg retrievals (2019-2022) across 11 centres in France, Spain and Morocco using three time-lapse systems (TLS). Data from two independent clinics were also examined. EMBRYOLY's transformer-based model was applied to transferred embryos to evaluate ranking performances against pregnancy and birth outcomes. It was applied to cohorts to rank sibling embryos (including non-transferred) according to their likelihood of clinical pregnancy and to compute the agreement with the embryologist's highest ranked embryo. Its effect on time to pregnancy and first cycle pregnancy rate was evaluated on cohorts with multiple single blastocyst transfers, assuming the embryologist would have considered EMBRYOLY's ranking on the embryos favoured for transfer.

RESULTS

EMBRYOLY's score correlated significantly with clinical pregnancies and live births for cleavage and blastocyst transfers. This held true for clinical pregnancies from blastocyst transfers in two independent clinics. In cases of multiple single embryo transfers, embryologists achieved a 19.8% first cycle pregnancy rate, which could have been improved to 44.1% with the adjunctive use of EMBRYOLY (McNemar's test: P < 0.001). This could have reduced cycles to clinical pregnancy from 2.01 to 1.66 (Wilcoxon test: P < 0.001).

CONCLUSIONS

EMBRYOLY's potential to enhance first cycle pregnancy rates when combined with embryologists' expertise is highlighted. It reduces the number of unsuccessful cycles for patients across TLS and IVF centres.

Machine learning in time-lapse imaging to differentiate embryos from young vs old mice†

Time-lapse microscopy for embryos is a non-invasive technology used to characterize early embryo development. This study employs time-lapse microscopy and machine learning to elucidate changes in embryonic growth kinetics with maternal aging. We analyzed morphokinetic parameters of embryos from young and aged C57BL6/NJ mice via continuous imaging. Our findings show that aged embryos accelerated through cleavage stages (from 5-cells) to morula compared to younger counterparts, with no significant differences observed in later stages of blastulation. Unsupervised machine learning identified two distinct clusters comprising of embryos from aged or young donors. Moreover, in supervised learning, the extreme gradient boosting algorithm successfully predicted the age-related phenotype with 0.78 accuracy, 0.81 precision, and 0.83 recall following hyperparameter tuning. These results highlight two main scientific insights: maternal aging affects embryonic development pace, and artificial intelligence can differentiate between embryos from aged and young maternal mice by a non-invasive approach. Thus, machine learning can be used to identify morphokinetics phenotypes for further studies. This study has potential for future applications in selecting human embryos for embryo transfer, without or in complement with preimplantation genetic testing.

Abnormal cleavage up to Day 3 does not compromise live birth and neonatal outcomes of embryos that have achieved full blastulation: a retrospective cohort study

STUDY QUESTION

Do embryos displaying abnormal cleavage (ABNCL) up to Day 3 have compromised live birth rates and neonatal outcomes if full blastulation has been achieved prior to transfer?

SUMMARY ANSWER

ABNCL is associated with reduced full blastulation rates but does not impact live birth rates and neonatal outcomes once full blastulation has been achieved.

WHAT IS KNOWN ALREADY?

It is widely accepted that ABNCL is associated with reduced implantation rates of embryos when transferred at the cleavage stage. However, evidence is scarce in the literature reporting birth outcomes from blastocysts arising from ABNCL embryos, likely because they are ranked low priority for transfer.

STUDY DESIGN, SIZE, DURATION

This retrospective cohort study included 1562 consecutive autologous in vitro fertilization cycles (maternal age 35.1 ± 4.7 years) performed at Fertility North, Australia between January 2017 and June 2022. Fresh transfers were performed on Day 3 or 5, with remaining embryos cultured up to Day 6 before vitrification. A total of 6019 embryos were subject to blastocyst culture, and a subset of 664 resulting frozen blastocysts was included for live birth and neonatal outcome analyses following single transfers.

PARTICIPANTS/MATERIALS, SETTING, METHODS

ABNCL events were annotated from the first mitotic division up to Day 3, including direct cleavage (DC), reverse cleavage (RC) and <6 intercellular contact points at the 4-cell stage (<6ICCP). For DC and RC in combination, the ratios of affected blastomeres over the total number of all blastomeres up to Day 3 were also recorded. All pregnancies were followed up until birth with gestational age, birthweight, and sex of the baby being recorded.

MAIN RESULTS AND THE ROLE OF CHANCE

Full blastulation rates for embryos showing DC (19.5%), RC (41.7%), <6ICCP (58.8%), and mixed (≥2) ABNCL types (26.4%) were lower than the rates for those without ABNCL (67.2%, P < 0.01 respectively). Subgroup analysis showed declining full blastulation rates with increasing ratios of combined DC/RC affected blastomeres over all blastomeres up to the 8-cell stage (66.2% when 0 affected, 47.0% when 0.25 affected, 27.4% when 0.5 affected, 14.5% when 0.75 affected, and 7.7% when all affected, P < 0.01). However, once full blastulation had been achieved, no difference was detected between DC, RC, <6ICCP, and no ABNCL blastocysts following single frozen transfers in subsequent live birth rates (25.9%, 33.0%, 36.0% versus 30.8%, P > 0.05, respectively), gestational age (38.7 ± 1.6, 38.5 ± 1.2, 38.3 ± 3.5 versus 38.5 ± 1.8 weeks, P > 0.05, respectively) and birthweight (3343.0 ± 649.1, 3378.2 ± 538.4, 3352.6 ± 841.3 versus 3313.9 ± 509.6 g, P > 0.05, respectively). Multiple regression (logistic or linear as appropriate) confirmed no differences in all of the above measures after accounting for potential confounders.

LIMITATIONS, REASONS FOR CAUTION

Our study is limited by its retrospective nature, making it impossible to control every known or unknown confounder. Embryos in our dataset, being surplus after selection for fresh transfer, may not represent the general embryo population.

WIDER IMPLICATIONS OF THE FINDINGS

Our findings highlight the incremental impact of ABNCL, depending on the ratio of affected blastomeres up to Day 3, on subsequent full blastulation. The reassuring live birth and neonatal outcomes of ABNCL blastocysts imply a potential self-correction mechanism among those embryos reaching the blastocyst stage, which provides valuable guidance for clinical practice and patient counseling.

STUDY FUNDING/COMPETTING INTEREST(S)

This research is supported by an Australian Government Research Training Program (RTP) Scholarship. All authors report no conflict of interest.

TRIAL REGISTRATION NUMBER

N/A.

Assessment of artificial intelligence model and manual morphokinetic annotation system as embryo grading methods for successful live birth prediction: a retrospective monocentric study

PURPOSE

The introduction of the time-lapse monitoring system (TMS) and the development of predictive algorithms could contribute to the optimal embryos selection for transfer. Therefore, the present study aims at investigating the efficiency of KIDScore and iDAScore systems for blastocyst stage embryos in predicting live birth events.

METHODS

The present retrospective study was conducted in a private IVF Unit setting throughout a 10-month period from October 2021 to July 2022, and included the analysis of 429 embryos deriving from 91 IVF/ICSI cycles conducted due to infertility of various etiologies. Embryos incubated at the Embryoscope+ timelapse incubator were analyzed through the established scoring systems: KIDScore and iDAScore®. The main outcome measure was the comparison of the two scoring systems in terms of live birth prediction. Embryos with the higher scores at day 5 (KID5 score/iDA5 score) were transferred or cryopreserved for later use.

RESULTS

Embryos with high KID5 and iDA5 scores positively correlated with the probability of successful live birth, with KID5 score yielding a higher efficiency in predicting a successful reproductive outcome compared to a proportionally high iDA5 score. KID5 demonstrated conservative performance in successfully predicting live birth compared to iDA5 score, indicating that an efficient prediction can be either provided by a relatively lower KID5 score or a relatively higher iDA5 score.

CONCLUSION

The developed artificial intelligence tools should be implemented in clinical practice in conjunction with the conventional morphological assessment for the conduction of optimized embryo transfer in terms of a successful live birth.

Evaluating the heterogeneous effect of extended culture to blastocyst transfer on the implantation outcome via causal inference in fresh ICSI cycles

PURPOSE

In IVF treatments, extended culture to single blastocyst transfer is the recommended protocol over cleavage-stage transfer. However, evidence-based criteria for assessing the heterogeneous implications on implantation outcomes are lacking. The purpose of this work is to estimate the causal effect of blastocyst transfer on implantation outcome.

METHODS

We fit a causal forest model using a multicenter observational dataset that includes an exogenous source of variability in treatment assignment and has a strong claim for satisfying the assumptions needed for valid causal inference from observational data.

RESULTS

We quantified the probability difference in embryo implantation if transferred as a blastocyst versus cleavage stage. Blastocyst transfer increased the average implantation rate; however, we revealed a subpopulation of embryos whose implantation potential is predicted to increase via cleavage-stage transfer.

CONCLUSION

Relative to the current policy, the proposed embryo transfer policy retrospectively improves implantation rate from 0.2 to 0.27. Our work demonstrates the efficacy of implementing causal inference in reproductive medicine and motivates its utilization in medical disciplines that are dominated by retrospective datasets.

Seeking arrangements: cell contact as a cleavage-stage biomarker

RESEARCH QUESTION

What can three-dimensional cell contact networks tell us about the developmental potential of cleavage-stage human embryos?

DESIGN

This pilot study was a retrospective analysis of two Embryoscope imaging datasets from two clinics. An artificial intelligence system was used to reconstruct the three-dimensional structure of embryos from 11-plane focal stacks. Networks of cell contacts were extracted from the resulting embryo three-dimensional models and each embryo's mean contacts per cell was computed. Unpaired t-tests and receiver operating characteristic curve analysis were used to statistically analyse mean cell contact outcomes. Cell contact networks from different embryos were compared with identical embryos with similar cell arrangements.

RESULTS

At t4, a higher mean number of contacts per cell was associated with greater rates of blastulation and blastocyst quality. No associations were found with biochemical pregnancy, live birth, miscarriage or ploidy. At t8, a higher mean number of contacts was associated with increased blastocyst quality, biochemical pregnancy and live birth. No associations were found with miscarriage or aneuploidy. Mean contacts at t4 weakly correlated with those at t8. Four-cell embryos fell into nine distinct cell arrangements; the five most common accounted for 97% of embryos. Eight-cell embryos, however, displayed a greater degree of variation with 59 distinct cell arrangements.

CONCLUSIONS

Evidence is provided for the clinical relevance of cleavage-stage cell arrangement in the human preimplantation embryo beyond the four-cell stage, which may improve selection techniques for day-3 transfers. This pilot study provides a strong case for further investigation into spatial biomarkers and three-dimensional morphokinetics.

A brief history of artificial intelligence embryo selection: from black-box to glass-box

With the exponential growth of computing power and accumulation of embryo image data in recent years, artificial intelligence (AI) is starting to be utilized in embryo selection in IVF. Amongst different AI technologies, machine learning (ML) has the potential to reduce operator-related subjectivity in embryo selection while saving labor time on this task. However, as modern deep learning (DL) techniques, a subcategory of ML, are increasingly used, its integrated black-box attracts growing concern owing to the well-recognized issues regarding lack of interpretability. Currently, there is a lack of randomized controlled trials to confirm the effectiveness of such black-box models. Recently, emerging evidence has shown underperformance of black-box models compared to the more interpretable traditional ML models in embryo selection. Meanwhile, glass-box AI, such as interpretable ML, is being increasingly promoted across a wide range of fields and is supported by its ethical advantages and technical feasibility. In this review, we propose a novel classification system for traditional and AI-driven systems from an embryology standpoint, defining different morphology-based selection approaches with an emphasis on subjectivity, explainability, and interpretability.

Artificial intelligence in time-lapse system: advances, applications, and future perspectives in reproductive medicine

With the rising demand for in vitro fertilization (IVF) cycles, there is a growing need for innovative techniques to optimize procedure outcomes. One such technique is time-lapse system (TLS) for embryo incubation, which minimizes environmental changes in the embryo culture process. TLS also significantly advances predicting embryo quality, a crucial determinant of IVF cycle success. However, the current subjective nature of embryo assessments is due to inter- and intra-observer subjectivity, resulting in highly variable results. To address this challenge, reproductive medicine has gradually turned to artificial intelligence (AI) to establish a standardized and objective approach, aiming to achieve higher success rates. Extensive research is underway investigating the utilization of AI in TLS to predict multiple outcomes. These studies explore the application of popular AI algorithms, their specific implementations, and the achieved advancements in TLS. This review aims to provide an overview of the advances in AI algorithms and their particular applications within the context of TLS and the potential challenges and opportunities for further advancements in reproductive medicine.

Associations between the artificial intelligence scoring system and live birth outcomes in preimplantation genetic testing for aneuploidy cycles

BACKGROUND

Several studies have demonstrated that iDAScore is more accurate in predicting pregnancy outcomes in cycles without preimplantation genetic testing for aneuploidy (PGT-A) compared to KIDScore and the Gardner criteria. However, the effectiveness of iDAScore in cycles with PGT-A has not been thoroughly investigated. Therefore, this study aims to assess the association between artificial intelligence (AI)-based iDAScore (version 1.0) and pregnancy outcomes in single-embryo transfer (SET) cycles with PGT-A.

METHODS

This retrospective study was approved by the Institutional Review Board of Chung Sun Medical University, Taichung, Taiwan. Patients undergoing SET cycles (n = 482) following PGT-A at a single reproductive center between January 2017 and June 2021. The blastocyst morphology and morphokinetics of all embryos were evaluated using a time-lapse system. The blastocysts were ranked based on the scores generated by iDAScore, which were defined as AI scores, or by KIDScore D5 (version 3.2) following the manufacturer's protocols. A single blastocyst without aneuploidy was transferred after examining the embryonic ploidy status using a next-generation sequencing-based PGT-A platform. Logistic regression analysis with generalized estimating equations was conducted to assess whether AI scores are associated with the probability of live birth (LB) while considering confounding factors.

RESULTS

Logistic regression analysis revealed that AI score was significantly associated with LB probability (adjusted odds ratio [OR] = 2.037, 95% confidence interval [CI]: 1.632-2.542) when pulsatility index (PI) level and types of chromosomal abnormalities were controlled. Blastocysts were divided into quartiles in accordance with their AI score (group 1: 3.0-7.8; group 2: 7.9-8.6; group 3: 8.7-8.9; and group 4: 9.0-9.5). Group 1 had a lower LB rate (34.6% vs. 59.8-72.3%) and a higher rate of pregnancy loss (26% vs. 4.7-8.9%) compared with the other groups (p < 0.05). The receiver operating characteristic curve analysis verified that the iDAScore had a significant but limited ability to predict LB (area under the curve [AUC] = 0.64); this ability was significantly weaker than that of the combination of iDAScore, type of chromosomal abnormalities, and PI level (AUC = 0.67). In the comparison of the LB groups with the non-LB groups, the AI scores were significantly lower in the non-LB groups, both for euploid (median: 8.6 vs. 8.8) and mosaic (median: 8.0 vs. 8.6) SETs.

CONCLUSIONS

Although its predictive ability can be further enhanced, the AI score was significantly associated with LB probability in SET cycles. Euploid or mosaic blastocysts with low AI scores (≤ 7.8) were associated with a lower LB rate, indicating the potential of this annotation-free AI system as a decision-support tool for deselecting embryos with poor pregnancy outcomes following PGT-A.

The morphokinetic signature of human blastocysts with mosaicism and the clinical outcomes following transfer of embryos with low-level mosaicism

BACKGROUND

Genetic mosaicism is commonly observed in human blastocysts. Embryos' morphokinetic feature observed from time-lapse monitoring (TLM) is helpful to predict the embryos' ploidy status in a non-invasive way. However, morphokinetic research on mosaic embryos is extremely limited. Moreover, transfer of mosaic embryos is a new attempt in reproductive medicine, while studies regarding the clinical and neonatal outcomes following transfer of embryos with different levels and types of mosaicism are needed. This study aimed to investigate the morphokinetic characteristics of mosaic blastocysts, uncover clinical outcomes of mosaic embryos, and evaluate the effect of level and type of mosaicism on transfer outcomes.

RESULTS

A total of 923 blastocysts from 229 preimplantation genetic testing cycles were cultured in TLM incubators in a single fertilization center between July 2016 and July 2021. Multivariate logistic regression models showed mosaic embryos had significantly shorter time to reach morula when compared with euploid (P = 0.002), mosaic with aneuploid (P = 0.005), and aneuploid (P = 0.005) embryos after adjusting the potential confounders. KIDScore is an artificial intelligence scoring program from time lapse incubation system to predict embryo implantation potential. Mosaic with aneuploid embryos had significantly lower KIDScore than euploid (P = 6.47e-4), mosaic (P = 0.005), and aneuploid (P = 0.004) embryos after adjustment. Meanwhile, we compared the clinical outcomes following transfer of low-level (< 50%) mosaic embryos (N = 60) with euploid embryos (N = 1301) matched using propensity scoring collected from September 2020 to January 2023. Mosaic embryos had significantly lower clinical pregnancy rate (41.67% vs. 57.65%, P = 0.015) and live birth rate (38.33% vs. 51.35%, P = 0.048) than the euploid embryos. Subgroup analyses showed the whole, segmental, and complex chromosome mosaic embryos had the similar clinical outcomes.

CONCLUSIONS

The shortened time to reach morula in mosaic embryos and the low KIDScore in mosaic with aneuploid embryos revealed innovative clues to embryo selection with the non-invasive TLM and provided new insights into biological mechanism of chromosomal abnormality. The analyses of overall and subgroups of mosaic embryo transfer outcomes helped to optimize embryo transfer scheme for in-vitro fertilization procedures. Multi-center prospective studies with large sample sizes are warranted to validate our results in the future.

Developmental competence and neonatal outcomes of nonpronuclear zygotes following single vitrified-warmed blastocyst transfers using propensity score matching analysis

PURPOSE

To investigate developmental competence and neonatal outcomes of nonpronuclear (0PN) zygotes following single vitrified-warmed blastocyst transfers (VBT).

METHODS

The clinical, laboratorial and neonatal data of 996 patients with ≤ 38 years who underwent blastocyst culture and single VBT were retrospectively analyzed. The pregnancy and neonatal outcomes of VBT were compared between 0PN and 2PN blastocysts using propensity score matching (PSM). Moreover, Day 3 (D3) embryo development and blastocyst formation were compared between 0PN and 2PN zygotes.

RESULTS

There were no significant differences in clinical pregnancy rate (CPR), live birth rate (LBR) and neonatal outcomes of VBT between the 0PN and 2PN blastocysts irrespectively of whether PSM was used. However, early abortion rate (EAR) was higher in blastocysts from 0PN D3 embryos > 10 cells (p < 0.05) before PSM. Moreover, the early developmental competence of 0PN zygotes was different from that of 2PN zygotes presenting higher percentages of D3 embryos ≤ 6 cells (p < 0.01) and > 10 cells (p < 0.01), lower available blastocyst formation rate (ABFR) (p < 0.01) and good-quality blastocyst formation rate (GBFR) (p < 0.01) in D3 embryos with 4-6 cells. ABFR and GBFR increased with cell number when compared among embryos with 4-6 cells, 7-10 cells and > 10 cells, irrespectively of 0PN or 2PN embryos.

CONCLUSION

The early developmental competence of 0PN zygotes was different from that of 2PN zygotes, but did not influence pregnancy and neonatal outcomes following VBT. ABFR and GBFR increased with cell number, irrespectively of 0PN or 2PN embryos.

Interpretable artificial intelligence-assisted embryo selection improved single-blastocyst transfer outcomes: a prospective cohort study

RESEARCH QUESTION

What is the pregnancy and neonatal outcomes of an interpretable artificial intelligence (AI) model for embryo selection in a prospective clinical trial?

DESIGN

This single-centre prospective cohort study was carried out from October 2021 to March 2022. A total of 330 eligible patients were assigned to their preferred groups, with 250 patients undergoing a fresh single-blastocyst transfer cycle after the exclusion criteria had been applied. For the AI-assisted group (AAG), embryologists selected the embryos for transfer based on the ranking recommendations provided by an interpretable AI system, while with the manual group, embryologists used the Gardner grading system to make their decisions.

RESULTS

The implantation rate was significantly higher in the AAG than the manual group (80.87% versus 68.15%, P = 0.022). No significant difference was found in terms of monozygotic twin rate, miscarriage rate, live birth rate and ectopic pregnancy rate between the groups. Furthermore, there was no significant difference in terms of neonatal outcomes, including gestational weeks, premature birth rate, birth height, birthweight, sex ratio at birth and newborn malformation rate. The consensus rate between the AI and retrospective analysis by the embryologists was significantly higher for good-quality embryos (i.e. grade 4BB or higher) versus poor-quality embryos (i.e. less than 4BB) (84.71% versus 25%, P < 0.001).

CONCLUSIONS

These prospective trial results suggest that the proposed AI system could effectively help embryologists to improve the implantation rate with single-blastocyst transfer compared with traditional manual evaluation methods.

The effect of embryo selection using time-lapse monitoring on IVF/ICSI outcomes: A systematic review and meta-analysis

AIM

To explore the effect of embryo selection using the time-lapse monitoring (TLM) system compared with conventional morphological selection (CMS) on in vitro fertilization/intracytoplasmic sperm injection (IVF/ICSI) outcomes.

METHODS

We searched PubMed, Ovid-Embase, and The Cochrane Library for the following studies: At Comparison 1, embryo selection using TLM images in a TLM incubator based on morphology versus embryo selection using CMS in a conventional incubator based on morphology; at Comparison 2, embryo selection using TLM based on morphokinetics versus embryo selection using CMS based on morphology. The primary outcomes were the live birth rate (LBR), ongoing pregnancy rate (OPR), clinical pregnancy rate (CPR), and implantation rate (IR), and the secondary outcome was the miscarriage rate (MR).

RESULTS

A total of 14 randomized control trials (RCTs) were included. Both based on morphology, TLM incubators increased the IR (risk ratio [RR]: 1.10; 95% confidence interval [CI]: 1.01, 1.18; I2  = 0%, moderate-quality evidence) compared to conventional incubators. Low- to moderate-quality evidence suggests that TLM incubators did not improve LBR, OPR, CPR, and MR compared to conventional incubators. In addition, low- to moderate-quality evidence indicates that embryo selection using TLM based on morphokinetics did not improve LBR, OPR, CPR, IR, or MR compared to CMS based on morphology.

CONCLUSIONS

Low- to moderate-quality evidence suggests that neither TLM incubators nor embryo selection using TLM based on morphokinetics improved clinical outcomes (LBR, OPR, CPR, and MR) compared with CMS based on morphology. TLM is still an investigational procedure for IVF/ICSI practice.

Using blastocyst re-expansion rate for deciding when to warm a new blastocyst for single vitrified-warmed blastocyst transfer

RESEARCH QUESTION

Can predictive post-warm parameters that support the decision to transfer a warmed blastocyst or to warm another blastocyst be identified in women with multiple frozen-vitrified blastocysts?

DESIGN

Retrospective single-centre observational cohort analysis. A total of 1092 single vitrified-warmed blastocyst transfers (SVBT) with known Gardner score, maternal age and live birth were used to develop live birth prediction models based on logistic regression, including post-warm re-expansion parameters. Time-lapse incubation was used for pre-vitrification and post-warm embryo culture. A dataset of 558 SVBT with the same inclusion criteria was used to validate the model, but with known clinical pregnancy outcome instead of live birth outcome.

RESULTS

Three different logistic regression models were developed for predicting live birth based on post-warm blastocyst re-expansion. Different post-warm assessment times indicated that a 2-h post-warm culture period was optimal for live birth prediction (model 1). Adjusting for pre-vitrification Gardner score (model 2) and in combination with maternal age (model 3) further increased predictability (area under the curve [AUC] = 0.623, 0.633, 0.666, respectively). Model validation gave an AUC of 0.617, 0.609 and 0.624, respectively. The false negative rate and true negative rate for model 3 were 2.0 and 10.1 in the development dataset and 3.5 and 8.0 in the validation dataset.

CONCLUSIONS

Clinical application of a simple model based on 2 h of post-warm re-expansion data, pre-vitrification Gardner score and maternal age can support a standardized approach for deciding if warming another blastocyst may increase the likelihood of live birth in SVBT.

Is there a relationship between morphokinetic parameters and neonatal sex in fresh embryo transfers?

To investigate whether morphokinetic parameters differ between male and female embryos in IVF embryos resulting in live births, a retrospective cohort study was undertaken. Files of all live births resulting from a single embryo transfer (SET) cultured in time-lapse incubators between 2013 and 2019 in two tertiary care centres were reviewed. The study group consisted of 187 SETs resulted in 187 live births, of which 100 were females (53.5%) and 87 were males (46.5%). Embryo selection for transfer was based on the known implantation data (KID) score provided by the Embryoscope and morphological assessment by experienced embryologists. Neonatal sex was confirmed through live birth documentation. Morphokinetic parameters and day 3 and day 5 KID scores of male and female embryos were compared. Maternal baseline and treatment characteristics were similar between groups. Morphokinetic time-lapse parameters of male and female embryos including: pronuclei fading; cleavage timings (t2-t9); second and third cell cycle durations; synchrony of the second and third cleavages; late morphokinetic parameters and KID scores did not differ between groups. In conclusion, time-lapse morphokinetic parameters and embryo selection methods do not seem to differ between male and female embryos, and their utilization does not bias towards any neonatal sex.

Impact of letrozole co-treatment during ovarian stimulation on oocyte yield, embryo development, and live birth rate in women with normal ovarian reserve: secondary outcomes from the RIOT trial

STUDY QUESTION

Does letrozole (LZ) co-treatment during ovarian stimulation with gonadotropins for in IVF impact follicle recruitment, oocyte number and quality, embryo quality, or live birth rate (LBR)?

SUMMARY ANSWER

No impact of LZ was found in follicle recruitment, number of oocytes, quality of embryos, or LBR.

WHAT IS KNOWN ALREADY

Multi-follicle stimulation for IVF produces supra-physiological oestradiol levels. LZ is an aromatase inhibitor that lowers serum oestradiol thus reducing negative feedback and increasing the endogenous gonadotropins in both the follicular and the luteal phases, effectively normalizing the endocrine milieu during IVF treatment.

STUDY DESIGN, SIZE, DURATION

Secondary outcomes from a randomized, double-blind placebo-controlled trial (RCT) investigating once-daily 5 mg LZ or placebo during stimulation for IVF with FSH. The RCT was conducted at four fertility clinics at University Hospitals in Denmark from August 2016 to November 2018 and pregnancy outcomes of frozen-thawed embryo transfers (FET) registered until May 2023.

PARTICIPANTS/MATERIALS, SETTING, METHODS

One hundred fifty-nine women with expected normal ovarian reserve (anti-Müllerian hormone 8-32 nmol/l) were randomized to either co-treatment with LZ (n = 80) or placebo (n = 79). In total 1268 oocytes were aspirated developing into 386 embryos, and morphology and morphokinetics were assessed. One hundred twenty-nine embryos were transferred in the fresh cycle and 158 embryos in a subsequent FET cycle. The effect of LZ on cumulative clinical pregnancy rate (CPR), LBR, endometrial thickness in the fresh cycle, and total FSH consumption was reported.

MAIN RESULTS AND THE ROLE OF CHANCE

The proportion of usable embryos of retrieved oocytes was similar in the LZ group and the placebo group with 0.31 vs 0.36 (mean difference (MD) -0.05, 95% CI (-0.12; 0.03), P = 0.65). The size and number of aspirated follicles at oocyte retrieval were similar with 11.8 vs 10.3 follicles per patient (MD 1.5, 95% CI (-0.5; 3.1), P = 0.50), as well as the number of retrieved oocytes with 8.0 vs 7.9 oocytes (MD 0.1, 95% CI (-1.4; 1.6), P = 0.39) in the LZ and placebo groups, respectively. The chance of retrieving an oocyte from the 13 to 16 mm follicles at trigger day was 66% higher (95% CI (24%; 108%), P = 0.002) in the placebo group than in the LZ group, whilst the chance of retrieving an oocyte from the ≥17 mm follicles at trigger day was 50% higher (95% CI (2%; 98%), P = 0.04) in the LZ group than in the placebo group. The proportion of fertilized oocytes with two-pronuclei per retrieved oocytes or per metaphase II oocytes (MII) (the 2PN rates) were similar regardless of fertilization with IVF or ICSI with 0.48 vs 0.57 (MD -0.09, 95% CI (-0.24; 0.04), P = 0.51), and 0.62 vs 0.64 (MD -0.02, 95% CI (-0.13; 0.07), P = 0.78) in the LZ and placebo groups, respectively. However, the MII rate in the ICSI group was significantly lower with 0.75 vs 0.88 in the LZ vs the placebo group (MD -0.14, 95% CI (-0.22; -0.06), P = 0.03). Blastocysts on Day 5 per patient were similar with 1.5 vs 2.0, P = 0.52, as well as vitrified blastocysts per patient Day 5 with 0.8 vs 1.2 in (MD -0.4, 95% CI (-1.0; 0.2), P = 0.52) and vitrified blastocysts per patient Day 6 with 0.6 vs 0.6 (MD 0, 95% CI (-0.3; 0.3), P = 1.00) in the LZ vs placebo group, respectively. Morphologic evaluation of all usable embryos showed a similar distribution in 'Good', 'Fair', and 'Poor', in the LZ vs placebo group, with an odds ratio (OR) of 0.8 95% CI (0.5; 1.3), P = 0.68 of developing a better class embryo. Two hundred and ninety-five of the 386 embryos were cultured in an embryoscope. Morphokinetic annotations showed that the odds of having a high KIDscore™ D3 Day 3 were 1.2 times higher (CI (0.8; 1.9), P = 0.68) in the LZ group vs the placebo group. The CPR per transfer was comparable with 31% vs 39% (risk-difference of 8%, 95% CI (-25%; 11%), P = 0.65) in the LZ and placebo group, respectively, as well as CPR per transfer adjusted for day of transfer, oestradiol and progesterone levels at trigger, progesterone levels mid-luteal, and number of oocytes retrieved (adjusted OR) of 0.8 (95% CI (0.4; 1.6), P = 0.72). Comparable LBR were found per transfer 28% vs 37% (MD -9%, 95% CI (-26%; 9%), P = 0.60) and per randomized women 24% vs 30% (MD of -6%, CI (-22%; 8%), P = 0.60) in the LZ group and placebo group, respectively. Furthermore, 4.8 years since the last oocyte aspiration, a total of 287 of 386 embryos have been transferred in the fresh or a subsequently FET cycle, disclosing the cumulative CPR, which is similar with 38% vs 34% (MD 95% CI (8%; 16%), P = 0.70) in the LZ vs placebo group.

LIMITATIONS, REASONS FOR CAUTION

Both cleavage stage and blastocyst transfer and vitrification were permitted in the protocol, making it necessary to categorize their quality and pool the results. The study was powered to detect hormonal variation but not embryo or pregnancy outcomes.

WIDER IMPLICATIONS OF THE FINDINGS

The similar utilization rate and quality of the embryos support the use of LZ co-treatment for IVF with specific indication as fertility preservation, patients with previous cancer, or poor responders. The effect of LZ on mature oocytes from different follicle sizes and LBRs should be evaluated in a meta-analysis or a larger RCT.

STUDY FUNDING/COMPETING INTEREST(S)

Funding was received from EU Interreg for ReproUnion, Sjaelland University Hospital, Denmark, Ferring Pharmaceuticals, and Gedeon Ricther. Roche Diagnostics contributed with assays. A.P. has received grants from Ferring, Merck Serono, and Gedeon Richter, consulting fees from Preglem, Novo Nordisk, Ferring, Gedeon Richter, Cryos, & Merck A/S, speakers fees from Gedeon Richter, Ferring, Merck A/S, Theramex, & Organon, and travel support from Gedeon Richter. The remaining authors declare that they have no competing interests in the research or publication.

TRIAL REGISTRATION NUMBERS

NCT02939898 and NCT02946684.

Pre-Vitrification and Post-Warming Variables of Vitrified-Warmed Blastocysts That Are Predictable for Implantation

Human IVF embryos that are not used for fresh transfer are cryopreserved by vitrification for later embryo transfers. This study evaluates pre-vitrification and post-warming embryo characteristics that are suitable to predict the chance of clinical pregnancy in single vitrified blastocyst transfer (SVBT) cycles. In a multicenter observational trial (IMBOS trial), embryos were cultured in a time-lapse system before and after vitrification. Associations between clinical pregnancy, morphokinetic parameters, blastocyst collapse, KIDScore D5, pre-vitrification and post-warming Gardner scores, post-warming blastocyst size and re-expansion rates before SVBT were analyzed in 182 SVBTs which resulted in 89 clinical pregnancies. No association was found between clinical pregnancy after SVBT and the number of collapses or the maximal collapse size before vitrification. The multifactorial analysis of pre-vitrification Gardner scores showed a significant association with clinical pregnancy for trophectoderm grading but not for expansion/hatching status and inner cell mass grading. A significant association with clinical pregnancy was found for the time to reach a blastocyst after pronuclear fading (tB-tPNf), KIDScore D5 and post-warming size but not the rate of expansion or maximal expansion size. The selection of blastocysts for SVBT could benefit from using pre-vitrification parameters like tB-tPNf, trophectoderm grading and post-warming blastocyst size.

Making and selecting the best embryo in the laboratory

Over the past 4 decades our ability to maintain a viable human embryo in vitro has improved dramatically, leading to higher implantation rates. This has led to a notable shift to single blastocyst transfer and the ensuing elimination of high order multiple gestations. Future improvements to embryo culture systems will not only come from new improved innovative media formulations (such as the inclusion of antioxidants), but plausibly by moving away from static culture to more dynamic perfusion-based systems now made a reality owing to the breakthroughs in three-dimensional printing technology and micro fabrication. Such an approach has already made it feasible to create high resolution devices for intracytoplasmic sperm injection, culture, and cryopreservation, paving the way not only for improvements in outcomes but also automation of assisted reproductive technology. Although improvements in culture systems can lead to further increases in pregnancy outcomes, the ability to quantitate biomarkers of embryo health and viability will reduce time to pregnancy and decrease pregnancy loss. Currently artificial intelligence is being used to assess embryo development through image analysis, but we predict its power will be realized through the creation of selection algorithms based on the integration of information related to metabolic functions, cell-free DNA, and morphokinetics, thereby using vast amounts of different data types obtained for each embryo to predict outcomes. All of this will not only make assisted reproductive technology more effective, but it will also make it more cost effective, thereby increasing patient access to infertility treatment worldwide.

Comparing performance between clinics of an embryo evaluation algorithm based on time-lapse images and machine learning

PURPOSE

This article aims to assess how differences in maternal age distributions between IVF clinics affect the performance of an artificial intelligence model for embryo viability prediction and proposes a method to account for such differences.

METHODS

Using retrospectively collected data from 4805 fresh and frozen single blastocyst transfers of embryos incubated for 5 to 6 days, the discriminative performance was assessed based on fetal heartbeat outcomes. The data was collected from 4 clinics, and the discrimination was measured in terms of the area under ROC curves (AUC) for each clinic. To account for the different age distributions between clinics, a method for age-standardizing the AUCs was developed in which the clinic-specific AUCs were standardized using weights for each embryo according to the relative frequency of the maternal age in the relevant clinic compared to the age distribution in a common reference population.

RESULTS

There was substantial variation in the clinic-specific AUCs with estimates ranging from 0.58 to 0.69 before standardization. The age-standardization of the AUCs reduced the between-clinic variance by 16%. Most notably, three of the clinics had quite similar AUCs after standardization, while the last clinic had a markedly lower AUC both with and without standardization.

CONCLUSION

The method of using age-standardization of the AUCs that is proposed in this article mitigates some of the variability between clinics. This enables a comparison of clinic-specific AUCs where the difference in age distributions is accounted for.

Cleavage Patterns of 9600 Embryos: The Importance of Irregular Cleavage

This prospective, observational study investigated the incidence of irregular cleavage (IRC) among human embryos and its influence on IVF treatment outcomes. It included 1001 women who underwent 1976 assisted reproduction treatments during 2016-2021 in a single IVF clinic. Embryo morphokinetics were analyzed and evaluated for the association between IRC and women's characteristics, treatment characteristics, and pregnancy outcomes. The incidence of IRC was 17.5% (1689/9632 embryos). Of these, 85% of the embryos had one IRC, 15% had multiple IRC and 35% of IRC events occurred during the embryo's first cell cycle. IRC embryos were found to correlate with male factor (p = 0.01) and higher ICSI rate (p = 0.01). Age, BMI, parity, basal FSH level, stimulation protocol, and number of retrieved oocytes did not differ between groups. Embryos with early IRC or more than one IRC had lower blastulation rates (p = 0.01 for each). Fresh cycles with IRC embryos had a lower clinical pregnancy rate (p = 0.01) and embryos with early IRC had a lower live birth rate (p = 0.04) compared to embryos without IRC. Frozen transfer cycles of blastocyst embryos, with or without IRC, had comparable results. In conclusion, the number of abnormal cleavage events and their timing are important factors in the prognosis of the developing human embryo.

Embryo selection through artificial intelligence versus embryologists: a systematic review

STUDY QUESTION

What is the present performance of artificial intelligence (AI) decision support during embryo selection compared to the standard embryo selection by embryologists?

SUMMARY ANSWER

AI consistently outperformed the clinical teams in all the studies focused on embryo morphology and clinical outcome prediction during embryo selection assessment.

WHAT IS KNOWN ALREADY

The ART success rate is ∼30%, with a worrying trend of increasing female age correlating with considerably worse results. As such, there have been ongoing efforts to address this low success rate through the development of new technologies. With the advent of AI, there is potential for machine learning to be applied in such a manner that areas limited by human subjectivity, such as embryo selection, can be enhanced through increased objectivity. Given the potential of AI to improve IVF success rates, it remains crucial to review the performance between AI and embryologists during embryo selection.

STUDY DESIGN SIZE DURATION

The search was done across PubMed, EMBASE, Ovid Medline, and IEEE Xplore from 1 June 2005 up to and including 7 January 2022. Included articles were also restricted to those written in English. Search terms utilized across all databases for the study were: ('Artificial intelligence' OR 'Machine Learning' OR 'Deep learning' OR 'Neural network') AND ('IVF' OR 'in vitro fertili*' OR 'assisted reproductive techn*' OR 'embryo'), where the character '*' refers the search engine to include any auto completion of the search term.

PARTICIPANTS/MATERIALS SETTING METHODS

A literature search was conducted for literature relating to AI applications to IVF. Primary outcomes of interest were accuracy, sensitivity, and specificity of the embryo morphology grade assessments and the likelihood of clinical outcomes, such as clinical pregnancy after IVF treatments. Risk of bias was assessed using the Modified Down and Black Checklist.

MAIN RESULTS AND THE ROLE OF CHANCE

Twenty articles were included in this review. There was no specific embryo assessment day across the studies-Day 1 until Day 5/6 of embryo development was investigated. The types of input for training AI algorithms were images and time-lapse (10/20), clinical information (6/20), and both images and clinical information (4/20). Each AI model demonstrated promise when compared to an embryologist's visual assessment. On average, the models predicted the likelihood of successful clinical pregnancy with greater accuracy than clinical embryologists, signifying greater reliability when compared to human prediction. The AI models performed at a median accuracy of 75.5% (range 59-94%) on predicting embryo morphology grade. The correct prediction (Ground Truth) was defined through the use of embryo images according to post embryologists' assessment following local respective guidelines. Using blind test datasets, the embryologists' accuracy prediction was 65.4% (range 47-75%) with the same ground truth provided by the original local respective assessment. Similarly, AI models had a median accuracy of 77.8% (range 68-90%) in predicting clinical pregnancy through the use of patient clinical treatment information compared to 64% (range 58-76%) when performed by embryologists. When both images/time-lapse and clinical information inputs were combined, the median accuracy by the AI models was higher at 81.5% (range 67-98%), while clinical embryologists had a median accuracy of 51% (range 43-59%).

LIMITATIONS REASONS FOR CAUTION

The findings of this review are based on studies that have not been prospectively evaluated in a clinical setting. Additionally, a fair comparison of all the studies were deemed unfeasible owing to the heterogeneity of the studies, development of the AI models, database employed and the study design and quality.

WIDER IMPLICATIONS OF THE FINDINGS

AI provides considerable promise to the IVF field and embryo selection. However, there needs to be a shift in developers' perception of the clinical outcome from successful implantation towards ongoing pregnancy or live birth. Additionally, existing models focus on locally generated databases and many lack external validation.

STUDY FUNDING/COMPETING INTERESTS

This study was funded by Monash Data Future Institute. All authors have no conflicts of interest to declare.

REGISTRATION NUMBER

CRD42021256333.

Morphokinetic analysis of early human embryonic development and its relationship to endometriosis resection: a retrospective time-lapse study using the KIDScore™ D3 and D5 implantation data algorithm

RESEARCH QUESTION

Does complete resection of endometriosis improve embryo quality as assessed by morphokinetic parameters using time-lapse microscopy?

DESIGN

For this retrospective study we analysed 237 fertilised, cultured and transferred embryos from 128 fresh IVF and/ or ICSI transfer cycles. Endometriosis was confirmed or excluded by laparoscopy. Patients were stimulated with recombinant FSH using GnRH agonist and antagonist protocols. After fertilisation, a time-lapse incubation system was used for observation. Embryo quality was assessed using the KIDScore™ D3 and D5 implantation data algorithm.

RESULTS

The analysis showed a median KIDScore™ D5 of 2.6 (on a scale of 1 to 9.9) for embryos from patients with endometriosis without complete resection. The control group without endometriosis achieved a score of 6.8 (p = 0.003). The median score for embryos from endometriosis patients with complete resection was 7.2, which was a significant increase compared to embryos from patients without complete resection (p = 0.002). We observed an effect size of r = 0.4 for complete resection versus no resection of endometriosis using the KIDScore™ D5. There were no differences in KIDScore™ D3 between the three patient groups. Pregnancy and miscarriage rates showed the same clinical trends. In three of our four case series of patients who underwent IVF/ ICSI cycles before and after complete resection, we found a marked improvement in embryo quality after complete resection.

CONCLUSIONS

Complete resection of endometriosis could significantly improve the otherwise poor embryo quality of patients undergoing IVF-procedures. The data, therefore, strongly support recommending surgery to patients with endometriosis prior to assisted reproduction.

[Interest of iDAScore (intelligent Data Analysis Score) for embryo selection in routine IVF laboratory practice: Results of a preliminary study]

INTRODUCTION

Embryo selection is a major challenge in ART, especially since the generalization of single embryo transfer, and its optimization could lead to the improvement of clinical results in IVF. Recently, several Artificial Intelligence (AI) models, based on deep-learning such as iDAScore, have been developed. These models, trained on time-lapse videos of embryos with known implantation data, can predict the probability of pregnancy for a given embryo, allowing automatization and standardization in embryo selection.

MATERIAL AND METHODS

In this study, we have compared the hierarchical categorization of 311 D5 blastocysts of iDAScore v1.0 and the embryologists of our unit. These 311 D5 blastocysts have been classified as top (70.1%), good (Q+: 10.6%) and poor (Q-: 19.3%) quality by embryologists according to Gardner classification. Median iDAScores were [9.9-8.4],]8.4-7.5] and]7.5-2.1] for top, good and poor-quality blastocysts respectively.

RESULTS

We observed a significantly concordant categorization between iDAScore and embryologists for top, good and poor-quality blastocysts (respectively, 89.5, 36.4 and 48.3%, P < 10-4). Moreover, the hierarchical categorization of the three best blastocysts between iDAScore and the embryologists was as follow: 1st rank: 71.9%; 2nd rank: 61.6%; 3rd rank: 56.8% (P=0.07). One hundred and fifty-one blastocysts with known implantation data were analyzed. The iDAScore of blastocysts that implanted was significantly higher than those that did not implant (implantation+: 9.10±0.57; implantation-: 8.70±0.95, P=0.003).

CONCLUSION

This preliminary study shows that iDAScore is able to perform a reproducible, reliable and immediate hierarchical classification of blastocysts. Moreover, this tool can identify the blastocysts with the highest implantation potential. If these results confirmed on a larger scale of embryos and patients, IA could revolutionize IVF laboratories by standardizing embryo hierarchical selection.

Delineating the heterogeneity of embryo preimplantation development using automated and accurate morphokinetic annotation

PURPOSE

Our objective was to design an automated deep learning model that extracts the morphokinetic events of embryos that were recorded by time-lapse incubators. Using automated annotation, we set out to characterize the temporal heterogeneity of preimplantation development across a large number of embryos.

METHODS

To perform a retrospective study, we used a dataset of video files of 67,707 embryos from four IVF clinics. A convolutional neural network (CNN) model was trained to assess the developmental states that appear in single frames from 20,253 manually-annotated embryos. Probability-weighted superposition of multiple predicted states was permitted, thus accounting for visual uncertainties. Superimposed embryo states were collapsed onto discrete series of morphokinetic events via monotonic regression of whole-embryo profiles. Unsupervised K-means clustering was applied to define subpopulations of embryos of distinctive morphokinetic profiles.

RESULTS

We perform automated assessment of single-frame embryo states with 97% accuracy and demonstrate whole-embryo morphokinetic annotation with R-square 0.994. High quality embryos that had been valid candidates for transfer were clustered into nine subpopulations, as characterized by distinctive developmental dynamics. Retrospective comparative analysis of transfer versus implantation rates reveals differences between embryo clusters as marked by poor synchronization of the third mitotic cell-cleavage cycle.

CONCLUSIONS

By demonstrating fully automated, accurate, and standardized morphokinetic annotation of time-lapse embryo recordings from IVF clinics, we provide practical means to overcome current limitations that hinder the implementation of morphokinetic decision-support tools within clinical IVF settings due to inter-observer and intra-observer manual annotation variations and workload constrains. Furthermore, our work provides a platform to address embryo heterogeneity using dimensionality-reduced morphokinetic descriptions of preimplantation development.

Ovulatory-cycle frozen embryo transfer: spontaneous or triggered ovulation and the impact of LH elevation at hCG triggering

The effect of the luteinizing hormone (LH) elevation before the human chorionic gonadotropin (hCG) trigger in ovulatory frozen-thawed embryo transfer (Ovu-FET) cycles has not been determined. We aimed to investigate whether triggering ovulation in Ovu-FET cycles affects the live birth rate (LBR), and the contribution of elevated LH at the time of hCG trigger. This retrospective study included Ovu-FET cycles performed in our center from August 2016 to April 2021. Modified Ovu-FET (hCG trigger) and true Ovu-FET (without hCG trigger) were compared. The modified group was divided according to whether hCG was administered, before or after LH increased to > 15 IU/L and was twice the baseline value. The modified (n = 100) and true (n = 246) Ovu-FET groups and both subgroups of the modified Ovu-FET, those who were triggered before (n = 67) or after (n = 33) LH elevation, had comparable characteristics at baseline. Comparison of true vs. modified Ovu-FET outcomes revealed similar LBR (35.4% vs. 32.0%; P = 0.62), respectively. LBR were similar between the modified Ovu-FET subgroups regardless of the hCG trigger timing (31.3% before vs. 33.3% after LH elevation; P = 0.84). In conclusion, LBR of Ovu-FET were not affected by hCG trigger or whether LH was elevated at the time of hCG trigger. These results add reassurance regarding hCG triggering even after LH elevation.

Using the embryo-uterus statistical model to predict pregnancy chances by using cleavage stage morphokinetics and female age: two centre-specific prediction models and mutual validation

BACKGROUND

The predictive capability of time-lapse monitoring (TLM) selection algorithms is influenced by patient characteristics, type and quality of data included in the analysis and the used statistical methods. Previous studies excluded DET cycles of which only one embryo implanted, introducing bias into the data. Therefore, we wanted to develop a TLM prediction model that is able to predict pregnancy chances after both single- and double embryo transfer (SET and DET).

METHODS

This is a retrospective study of couples (n = 1770) undergoing an in vitro fertilization cycle at the Erasmus MC, University Medical Centre Rotterdam (clinic A) or the Reinier de Graaf Hospital (clinic B). This resulted in 2058 transferred embryos with time-lapse and pregnancy outcome information. For each dataset a prediction model was established by using the Embryo-Uterus statistical model with the number of gestational sacs as the outcome variable. This process was followed by cross-validation.

RESULTS

Prediction model A (based on data of clinic A) included female age, t3-t2 and t5-t4, and model B (clinic B) included female age, t2, t3-t2 and t5-t4. Internal validation showed overfitting of model A (calibration slope 0.765 and area under the curve (AUC) 0.60), and minor overfitting of model B (slope 0.915 and AUC 0.65). External validation showed that model A was capable of predicting pregnancy in the dataset of clinic B with an AUC of 0.65 (95% CI: 0.61-0.69; slope 1.223, 95% CI: 0.903-1.561). Model B was less accurate in predicting pregnancy in the dataset of clinic A (AUC 0.60, 95% CI: 0.56-0.65; slope 0.671, 95% CI: 0.422-0.939).

CONCLUSION

Our study demonstrates a novel approach to the development of a TLM prediction model by applying the EU statistical model. With further development and validation in clinical practice, our prediction model approach can aid in embryo selection and decision making for SET or DET.

Development and validation of deep learning based embryo selection across multiple days of transfer

This work describes the development and validation of a fully automated deep learning model, iDAScore v2.0, for the evaluation of human embryos incubated for 2, 3, and 5 or more days. We trained and evaluated the model on an extensive and diverse dataset including 181,428 embryos from 22 IVF clinics across the world. To discriminate the transferred embryos with known outcome, we show areas under the receiver operating curve ranging from 0.621 to 0.707 depending on the day of transfer. Predictive performance increased over time and showed a strong correlation with morphokinetic parameters. The model's performance is equivalent to the KIDScore D3 model on day 3 embryos while it significantly surpasses the performance of KIDScore D5 v3 on day 5+ embryos. This model provides an analysis of time-lapse sequences without the need for user input, and provides a reliable method for ranking embryos for their likelihood of implantation, at both cleavage and blastocyst stages. This greatly improves embryo grading consistency and saves time compared to traditional embryo evaluation methods.

Development of an artificial intelligence based model for predicting the euploidy of blastocysts in PGT-A treatments

The euploidy of embryos is unpredictable before transfer in in vitro fertilisation (IVF) treatments without pre-implantation genetic testing (PGT). Previous studies have suggested that morphokinetic characteristics using an artificial intelligence (AI)-based model in the time-lapse monitoring (TLM) system were correlated with the outcomes of frozen embryo transfer (FET), but the predictive effectiveness of the model for euploidy remains to be perfected. In this study, we combined morphokinetic characteristics, morphological characteristics of blastocysts, and clinical parameters of patients to build a model to predict the euploidy of blastocysts and live births in PGT for aneuploidy treatments. The model was effective in predicting euploidy (AUC = 0.879) but was ineffective in predicting live birth after FET. These results provide a potential method for the selection of embryos for IVF treatments with non-PGT.

Embryo classification beyond pregnancy: early prediction of first trimester miscarriage using machine learning

PURPOSE

First trimester miscarriage is a major concern in IVF-ET treatments, accounting for one out of nine clinical pregnancies and for up to one out of three recognized pregnancies. To develop a machine learning classifier for predicting the risk of cleavage-stage embryos to undergo first trimester miscarriage based on time-lapse images of preimplantation development.

METHODS

Retrospective study of a 4-year multi-center cohort of 391 women undergoing intra-cytoplasmatic sperm injection (ICSI) and fresh single or double embryo transfers. The study included embryos with positive indication of clinical implantation based on gestational sac visualization either with first trimester miscarriage or live-birth outcome. Miscarriage was determined based on negative fetal heartbeat indication during the first trimester. Data were recorded and obtained in hospital setting and research was performed in university setting.

RESULTS

A minimal subset of six non-redundant morphodynamic features were screened that maintained high prediction capacity. Features that account for the distribution of the nucleolus precursor bodies within the small pronucleus and pronuclei dynamics were highly predictive of miscarriage outcome as evaluated using the SHapley Additive exPlanations (SHAP) methodology. Using this feature subset, XGBoost and random forest models were trained following a 100-fold Monte-Carlo cross validation scheme. Miscarriage was predicted with AUC 0.68 to 0.69.

CONCLUSION

We report the development of a decision-support tool for identifying the embryos with high risk of miscarriage. Prioritizing embryos for transfer based on their predicted risk of miscarriage in combination with their predicted implantation potential is expected to improve live-birth rates and shorten time-to-pregnancy.

Detailed analysis of cytoplasmic strings in human blastocysts: new insights

The aim of this study was to determine if there was an association between the presence of cytoplasmic strings (CS) and their characteristics, with blastocyst quality, development and clinical outcome in human blastocysts. This two-centre cohort study was performed between July 2017 and September 2018 and involved a total of 1152 blastocysts from 225 patients undergoing in vitro fertilization (IVF) and intracytoplasmic sperm injection (ICSI). All embryos were cultured in Embryoscope+ and were assessed for CS using time-lapse images. A single assessor examined all blastocysts and reviewed videos using the EmbyroViewer® Software. Blastocyst quality was assessed on day 5 of embryo development. The number of CS, location and duration of their activity was recorded on days 5/6. A positive association between the presence of CS in human blastocysts with blastocyst quality was identified. Blastocysts with a higher number of CS present, were of higher quality and were in the more advanced stages of development. Top quality blastocysts had CS activity present for longer, as well as having a higher number of vesicles present travelling along the CS. Blastocysts that had CS present, had a significantly higher live birth rate. This study has confirmed that a higher number of CS and vesicles in human blastocysts is associated with top quality blastocysts and is not a negative predictor of development. They had a higher number of CS present that appeared earlier in development and, although ceased activity sooner, had a longer duration of activity. Blastocysts with CS had a significant increase in live birth rate.

Non-invasive evaluation of embryos using mid-infrared attenuated total reflection spectrometry of incubation medium: a preliminary study

RESEARCH QUESTION

Can mid-infrared attenuated total reflection (MIR ATR) spectroscopy combined with machine learning methods be used as an additional tool to predict embryo quality and IVF treatment outcomes?

DESIGN

Spent culture media was collected and analysed. MIR ATR absorbance spectra were measured using an ALPHA II spectrometer equipped with an attenuated total reflection (ATR) spectrometry accessory. Patient and treatment data and results were collected and analysed in combination with machine learning techniques to identify possible correlations. The main outcome measures were to define the characteristics of absorbance spectra of spent culture media and to distinguish the difference in absorbance between top- and low-quality embryos, day 3 and day 5 embryos and implanting embryos versus non-implanting embryos.

RESULTS

Spent culture media of 227 embryos was collected and analysed. Absorbance peaks in the culture media were different between day 3 and day 5 embryos. Moreover, significant differences in P-values, spanning from 0.014 to 0.044 in absorbance peaks for day 3 embryos and 0.024 up to 0.04 for day 5 embryos, were seen between implanting and non-implanting embryos. Machine learning techniques offered a pregnancy prediction value of 84.6% for day 3 embryos.

CONCLUSIONS

MIR ATR may offer an additional parameter for better selection of embryos based on the spectrometric absorbance and secretions of metabolites in the culture media.

Non-invasive evaluation of embryo quality for the selection of transferable embryos in human in vitro fertilization-embryo transfer

The ultimate goal of human assisted reproductive technology is to achieve a healthy pregnancy and birth, ideally from the selection and transfer of a single competent embryo. Recently, techniques for efficiently evaluating the state and quality of preimplantation embryos using time-lapse imaging systems have been applied. Artificial intelligence programs based on deep learning technology and big data analysis of time-lapse monitoring system during in vitro culture of preimplantation embryos have also been rapidly developed. In addition, several molecular markers of the secretome have been successfully analyzed in spent embryo culture media, which could easily be obtained during in vitro embryo culture. It is also possible to analyze small amounts of cell-free nucleic acids, mitochondrial nucleic acids, miRNA, and long non-coding RNA derived from embryos using real-time polymerase chain reaction (PCR) or digital PCR, as well as next-generation sequencing. Various efforts are being made to use non-invasive evaluation of embryo quality (NiEEQ) to select the embryo with the best developmental competence. However, each NiEEQ method has some limitations that should be evaluated case by case. Therefore, an integrated analysis strategy fusing several NiEEQ methods should be urgently developed and confirmed by proper clinical trials.

The Future Is Coming: Artificial Intelligence in the Treatment of Infertility Could Improve Assisted Reproduction Outcomes-The Value of Regulatory Frameworks

Infertility is a global health issue affecting women and men of reproductive age with increasing incidence worldwide, in part due to greater awareness and better diagnosis. Assisted reproduction technologies (ART) are considered the ultimate step in the treatment of infertility. Recently, artificial intelligence (AI) has been progressively used in the many fields of medicine, integrating knowledge and computer science through machine learning algorithms. AI has the potential to improve infertility diagnosis and ART outcomes estimated as pregnancy and/or live birth rate, especially with recurrent ART failure. A broad-ranging review has been conducted, focusing on clinical AI applications up until September 2022, which could be estimated in terms of possible applications, such as ultrasound monitoring of folliculogenesis, endometrial receptivity, embryo selection based on quality and viability, and prediction of post implantation embryo development, in order to eliminate potential contributing risk factors. Oocyte morphology assessment is highly relevant in terms of successful fertilization rate, as well as during oocyte freezing for fertility preservation, and substantially valuable in oocyte donation cycles. AI has great implications in the assessment of male infertility, with computerised semen analysis systems already in use and a broad spectrum of possible AI-based applications in environmental and lifestyle evaluation to predict semen quality. In addition, considerable progress has been made in terms of harnessing AI in cases of idiopathic infertility, to improve the stratification of infertile/fertile couples based on their biological and clinical signatures. With AI as a very powerful tool of the future, our review is meant to summarise current AI applications and investigations in contemporary reproduction medicine, mainly focusing on the nonsurgical aspects of it; in addition, the authors have briefly explored the frames of reference and guiding principles for the definition and implementation of legal, regulatory, and ethical standards for AI in healthcare.

Nucleation status of Day 2 pre-implantation embryos, acquired by time-lapse imaging during IVF, is associated with live birth

The primary purpose of this time-lapse data analysis was to identify the association between the nucleation status of a Day 2 preimplantation embryo and live births following in vitro fertilization (IVF). The retrospective data analysis was based on 2769 transferred embryos from 1966 treatment cycles and utilised only Known Implantation Data (KID) for live births. Nucleation errors (NE) such as micronucleation, binucleation, multinucleation and minor error groups, were annotated in the time-lapse images which were taken every 15 minutes for a minimum of 44 hours post insemination. Further, factors that may impact NE and the relationship of early morphological attributes and morphokinetic variables with NE occurrence were explored. The frequency of NE among the transferred embryos was 23.8%. The reversibility of NE evidenced by their presence at the two-cell stage, but absence at the four-cell stage was 89.6%. Embryos exhibiting nucleation errors at the two-cell stage had significantly lower live birth rates compared to embryos with no nucleation errors, constituting a significant predictor. A Generalized Additive Mixed Model was used to control for confounders and for controlling clustering effects from dual embryo transfers. Increased incidences of NE were observed with increasing age, with delayed occurrence of cell divisions and in oocytes inseminated with surgically retrieved spermatozoa. NE assessment and their impact on live birth provides valuable markers for early preimplantation embryo selection. In addition, the high incidence of reversibility of NE and their possible impact on live birth suggest that incorporating two-cell nuclear status annotations in embryo selection, alongside morphology and morphokinetics, is of value.

Morphological and morphokinetic associations with aneuploidy: a systematic review and meta-analysis

BACKGROUND

A time lapse system (TLS) is utilized in some fertility clinics with the aim of predicting embryo viability and chance of live birth during IVF. It has been hypothesized that aneuploid embryos display altered morphokinetics as a consequence of their abnormal chromosome complement. Since aneuploidy is one of the fundamental reasons for IVF failure and miscarriage, attention has focused on utilizing morphokinetics to develop models to non-invasively risk stratify embryos for ploidy status. This could avoid or reduce the costs associated with pre-implantation genetic testing for aneuploidy (PGT-A). Furthermore, TLS have provided an understanding of the true prevalence of other dysmorphisms. Hypothetically, the incorporation of morphological features into a model could act synergistically, improving a model's discriminative ability to predict ploidy status.

OBJECTIVE AND RATIONALE

The aim of this systematic review and meta-analysis was to investigate associations between ploidy status and morphokinetic or morphological features commonly denoted on a TLS. This will determine the feasibility of a prediction model for euploidy and summarize the most useful prognostic markers to be included in model development.

SEARCH METHODS

Five separate searches were conducted in Medline, Embase, PubMed and Cinahl from inception to 1 July 2021. Search terms and word variants included, among others, PGT-A, ploidy, morphokinetics and time lapse, and the latter were successively substituted for the following morphological parameters: fragmentation, multinucleation, abnormal cleavage and contraction. Studies were limited to human studies.

OUTCOMES

Overall, 58 studies were included incorporating over 40 000 embryos. All except one study had a moderate risk of bias in at least one domain when assessed by the quality in prognostic studies tool. Ten morphokinetic variables were significantly delayed in aneuploid embryos. When excluding studies using less reliable genetic technologies, the most notable variables were: time to eight cells (t8, 1.13 h, 95% CI: 0.21-2.05; three studies; n = 742; I2 = 0%), t9 (2.27 h, 95% CI: 0.5-4.03; two studies; n = 671; I2 = 33%), time to formation of a full blastocyst (tB, 1.99 h, 95% CI 0.15-3.81; four studies; n = 1640; I2 = 76%) and time to expanded blastocyst (tEB, 2.35 h, 95% CI: 0.06-4.63; four studies; n = 1640; I2 = 83%). There is potentially some prognostic potential in the degree of fragmentation, multinucleation persisting to the four-cell stage and frequency of embryo contractions. Reverse cleavage was associated with euploidy in this meta-analysis; however, this article argues that these are likely spurious results requiring further investigation. There was no association with direct unequal cleavage in an embryo that progressed to a blastocyst, or with multinucleation assessed on Day 2 or at the two-cell stage. However, owing to heterogeneous results and poor-quality evidence, associations between these morphological components needs to be investigated further before conclusions can be reliably drawn.

WIDER IMPLICATIONS

This first systematic review and meta-analysis of morphological and morphokinetic associations with ploidy status demonstrates the most useful morphokinetic variables, namely t8, t9 and tEB to be included in future model development. There is considerable variability within aneuploid and euploid embryos making definitively classifying them impossible; however, it is feasible that embryos could be prioritized for biopsy. Furthermore, these results support the mechanism by which algorithms for live birth may have predictive ability, suggesting aneuploidy causes delayed cytokinesis. We highlight significant heterogeneity in our results secondary to local conditions and diverse patient populations, therefore calling for future models to be robustly developed and tested in-house. If successful, such a model would constitute a meaningful breakthrough when accessing PGT-A is unsuitable for couples.

Embryologist agreement when assessing blastocyst implantation probability: is data-driven prediction the solution to embryo assessment subjectivity?

STUDY QUESTION

What is the accuracy and agreement of embryologists when assessing the implantation probability of blastocysts using time-lapse imaging (TLI), and can it be improved with a data-driven algorithm?

SUMMARY ANSWER

The overall interobserver agreement of a large panel of embryologists was moderate and prediction accuracy was modest, while the purpose-built artificial intelligence model generally resulted in higher performance metrics.

WHAT IS KNOWN ALREADY

Previous studies have demonstrated significant interobserver variability amongst embryologists when assessing embryo quality. However, data concerning embryologists' ability to predict implantation probability using TLI is still lacking. Emerging technologies based on data-driven tools have shown great promise for improving embryo selection and predicting clinical outcomes.

STUDY DESIGN, SIZE, DURATION

TLI video files of 136 embryos with known implantation data were retrospectively collected from two clinical sites between 2018 and 2019 for the performance assessment of 36 embryologists and comparison with a deep neural network (DNN).

PARTICIPANTS/MATERIALS, SETTING, METHODS

We recruited 39 embryologists from 13 different countries. All participants were blinded to clinical outcomes. A total of 136 TLI videos of embryos that reached the blastocyst stage were used for this experiment. Each embryo's likelihood of successfully implanting was assessed by 36 embryologists, providing implantation probability grades (IPGs) from 1 to 5, where 1 indicates a very low likelihood of implantation and 5 indicates a very high likelihood. Subsequently, three embryologists with over 5 years of experience provided Gardner scores. All 136 blastocysts were categorized into three quality groups based on their Gardner scores. Embryologist predictions were then converted into predictions of implantation (IPG ≥ 3) and no implantation (IPG ≤ 2). Embryologists' performance and agreement were assessed using Fleiss kappa coefficient. A 10-fold cross-validation DNN was developed to provide IPGs for TLI video files. The model's performance was compared to that of the embryologists.

MAIN RESULTS AND THE ROLE OF CHANCE

Logistic regression was employed for the following confounding variables: country of residence, academic level, embryo scoring system, log years of experience and experience using TLI. None were found to have a statistically significant impact on embryologist performance at α = 0.05. The average implantation prediction accuracy for the embryologists was 51.9% for all embryos (N = 136). The average accuracy of the embryologists when assessing top quality and poor quality embryos (according to the Gardner score categorizations) was 57.5% and 57.4%, respectively, and 44.6% for fair quality embryos. Overall interobserver agreement was moderate (κ = 0.56, N = 136). The best agreement was achieved in the poor + top quality group (κ = 0.65, N = 77), while the agreement in the fair quality group was lower (κ = 0.25, N = 59). The DNN showed an overall accuracy rate of 62.5%, with accuracies of 62.2%, 61% and 65.6% for the poor, fair and top quality groups, respectively. The AUC for the DNN was higher than that of the embryologists overall (0.70 DNN vs 0.61 embryologists) as well as in all of the Gardner groups (DNN vs embryologists-Poor: 0.69 vs 0.62; Fair: 0.67 vs 0.53; Top: 0.77 vs 0.54).

LIMITATIONS, REASONS FOR CAUTION

Blastocyst assessment was performed using video files acquired from time-lapse incubators, where each video contained data from a single focal plane. Clinical data regarding the underlying cause of infertility and endometrial thickness before the transfer was not available, yet may explain implantation failure and lower accuracy of IPGs. Implantation was defined as the presence of a gestational sac, whereas the detection of fetal heartbeat is a more robust marker of embryo viability. The raw data were anonymized to the extent that it was not possible to quantify the number of unique patients and cycles included in the study, potentially masking the effect of bias from a limited patient pool. Furthermore, the lack of demographic data makes it difficult to draw conclusions on how representative the dataset was of the wider population. Finally, embryologists were required to assess the implantation potential, not embryo quality. Although this is not the traditional approach to embryo evaluation, morphology/morphokinetics as a means of assessing embryo quality is believed to be strongly correlated with viability and, for some methods, implantation potential.

WIDER IMPLICATIONS OF THE FINDINGS

Embryo selection is a key element in IVF success and continues to be a challenge. Improving the predictive ability could assist in optimizing implantation success rates and other clinical outcomes and could minimize the financial and emotional burden on the patient. This study demonstrates moderate agreement rates between embryologists, likely due to the subjective nature of embryo assessment. In particular, we found that average embryologist accuracy and agreement were significantly lower for fair quality embryos when compared with that for top and poor quality embryos. Using data-driven algorithms as an assistive tool may help IVF professionals increase success rates and promote much needed standardization in the IVF clinic. Our results indicate a need for further research regarding technological advancement in this field.

STUDY FUNDING/COMPETING INTEREST(S)

Embryonics Ltd is an Israel-based company. Funding for the study was partially provided by the Israeli Innovation Authority, grant #74556.

TRIAL REGISTRATION NUMBER

N/A.

Current trends in artificial intelligence in reproductive endocrinology

PURPOSE OF REVIEW

Artificial Intelligence, a tool that integrates computer science and machine learning to mimic human decision-making processes, is transforming the world and changing the way we live. Recently, the healthcare industry has gradually adopted artificial intelligence in many applications and obtained some degree of success. In this review, we summarize the current applications of artificial intelligence in Reproductive Endocrinology, in both laboratory and clinical settings.

RECENT FINDINGS

Artificial Intelligence has been used to select the embryos with high implantation potential, proper ploidy status, to predict later embryo development, and to increase pregnancy and live birth rates. Some studies also suggested that artificial intelligence can help improve infertility diagnosis and patient management. Recently, it has been demonstrated that artificial intelligence also plays a role in effective laboratory quality control and performance.

SUMMARY

In this review, we discuss various applications of artificial intelligence in different areas of reproductive medicine. We summarize the current findings with their potentials and limitations, and also discuss the future direction for research and clinical applications.

Faster Fertilization and Cleavage Kinetics Reflect Competence to Achieve a Live Birth: Data from Single-Embryo Transfer Cycles

The aim of this study was to assess the relationship between early developmental kinetics and the competence to result in a live birth as well as the impact of maternal age and the number of retrieved oocytes. This retrospective cohort study included 3,021 single-embryo transfer cycles and assessed live birth outcomes paired with morphokinetic data; 1,412 transfers resulted in live births (LB), and 1,609 did not (NLB). Early morphokinetic parameters between LB and NLB embryos were compared from patients stratified into four age groups (20-25, 26-30, 31-36, and ≥37 years) and between embryos in the same competence groups within the age groups. Early morphokinetic parameters were also compared between LB and NLB embryos from patients stratified into four groups based on the number of oocytes harvested (≤7, 8-14, 15-21, and ≥22). The association between morphokinetic parameters and LB was tested using univariate and multivariate analyses. This study indicated that embryos resulting in LB generally exhibit faster developmental dynamic parameters than embryos that do not. However, this difference decreased in the younger (20-25 years) and older (≥37 years) age groups. In addition, when the number of harvested oocytes was low (≤7) or high (≥22), this difference was less obvious. The morphokinetic parameters of embryonic cleavage are an effective reference value for embryo selection strategies aimed at increasing live birth rates, especially for patients aged 26–36 years, with 8–21 harvested oocytes.

Validation of Non-Invasive Preimplantation Genetic Screening Using a Routine IVF Laboratory Workflow

Embryo selection is needed to optimize the chances of pregnancy in assisted reproduction technology. This study aimed to validate non-invasive preimplantation genetic testing for aneuploidy (niPGT-A) using a routine IVF laboratory workflow. Can niPGT-A combined with time-lapse morphokinetics provide a better embryo-selection strategy? A total of 118 spent culture mediums (SCMs) from 32 couples were collected. A total of 40 SCMs and 40 corresponding trophectoderm (TE) biopsy samples (n = 29) or arrested embryos (n = 11) were assessed for concordance. All embryos were cultured to the blastocyst stage (day 5 or 6) in a single-embryo culture time-lapse incubator. The modified multiple annealing and looping-based amplification cycle (MALBAC) single-cell whole genome amplification method was used to amplify cell-free DNA (cfDNA) from the SCM, which was then sequenced on the Illumina MiSeq system. The majority of insemination methods were conventional IVF. Low cfDNA concentrations were noted in this study. The amplification niPGT-A and conventional PGT-A was 67.7%. Based on this study, performing niPGT-A without altering the daily laboratory procedures cannot provide a precise diagnosis. However, niPGT-A can be applied in clinical IVF, enabling the addition of blastocysts with a better prediction of euploidy for transfer.

Asynchronous division at 4–8-cell stage of preimplantation embryos affects live birth through ICM/TE differentiation

To improve the performance of assisted reproductive technology, it is necessary to find an indicator that can identify and select embryos that will be born or be aborted. We searched for indicators of embryo selection by comparing born/abort mouse embryos. We found that asynchronous embryos during the 4–8-cell stage were predisposed to be aborted. In asynchronous mouse embryos, the nuclear translocation of YAP1 in some blastomeres and compaction were delayed, and the number of ICMs was reduced. Hence, it is possible that asynchronous embryos have abnormal differentiation. When the synchrony of human embryos was observed, it was confirmed that embryos that did not reach clinical pregnancy had asynchrony as in mice. This could make synchrony a universal indicator common to all animal species.

Maternal underweight does not adversely affect the outcomes of IVF/ICSI and frozen embryo transfer cycles or early embryo development

OBJECTIVE

To compare assisted reproductive technology (ART) outcomes and preimplantation embryo development between underweight and normal-weight women.

METHODS

This retrospective cohort study included 26 underweight women (body mass index [BMI] < 18.50 kg/m²) and 104 normal-weight women (BMI >20 and <24.9 kg/m²) who underwent a total of 204 in vitro fertilization/intracytoplasmic sperm injection (IVF/ICSI) cycles and 358 fresh/frozen embryo transfers (ET) in our institution between January 2016 and December 2018. Statistical analyses compared selected ART outcomes (ovarian stimulation, fertilization, and pregnancy) between both weight groups. Morphokinetic and morphological parameters were also compared between 346 and 1467 embryos of underweight and normal-weight women, respectively.

RESULTS

The mean ± standard deviation age of the underweight and normal-weight women was similar (31.6 ± 4.17 vs 32.4 ± 3.59 years; p = .323). There were no differences in the peak estradiol levels, the number of retrieved oocytes, the number of metaphase II oocytes, and the oocyte maturity rates between the two groups. The IVF/ICSI fertilization rates and the number of embryos suitable for transfer or cryopreservation were similar for both groups. All morphokinetic parameters that were evaluated by means of time-lapse imaging as well as the morphological characteristics were comparable between low and normal BMI categories. There were no significant differences in pregnancy achievement, clinical pregnancy, live births, and miscarriage rates between the suboptimal and optimal weight women.

CONCLUSION

Underweight status has no adverse impacts on the outcomes of IVF/ICSI with either fresh or frozen ET or on preimplantation embryo development and quality.

Development of a dynamic machine learning algorithm to predict clinical pregnancy and live birth rate with embryo morphokinetics

Objective

Design

Setting

Patient(s)

Intervention(s)

Main Outcome Measure(s)

Result(s)

Conclusion(s)

Standardization of Post-Vitrification Human Blastocyst Expansion as a Tool for Implantation Prediction

The increased use of vitrified blastocysts has encouraged the development of various criteria for selecting the embryo most likely to implant. Post-thaw assessment methods and timetables vary among investigators. We investigated the predictive value of well-defined measurements of human blastocyst re-expansion, following a fixed incubation period. Post-thaw measurements were taken exactly at 0 and 120 ± 15 min. Minimum and maximum cross-sectional axes were measured. Three groups were defined: Group 1: embryos that continued to shrink by 10 µm or more; group 2: embryos that ranged from −9 to +9 µm; and group 3: re-expansion of 10 µm or more. Patient and morphokinetic data were collected and integrated into the analysis. A total of 115 cases were included. The clinical pregnancy rate for group 1 was 18.9%; group 2, 27%; and group 3, 51.2% (p = 0.007). Pre-thaw morphologic grading and morphokinetic scores of the study groups did not reveal differences. p-values were 0.17 for the pre-thaw morphologic score, 0.54 for KID3, and 0.37 for KID5. The patients’ demographic and clinical data were similar. The clinical pregnancy rate correlated with the degree of thawed blastocyst re-expansion measured 2 h after incubation. This standardized measure is suggested as a tool to predict the potential of treatment success before embryo transfer.

The Impact of Culture Medium on Morphokinetics of Cleavage Stage Embryos: An Observational Study

To study the impact of culture media on preimplantation morphokinetics used for predicting clinical outcomes. All IVF and ICSI cycles performed between 2012 and 2017 with time-lapse information available were included. In November 2014, culture medium was changed from Vitrolife G-1 PLUS to SAGE 1-Step. Each embryo was retrospectively assigned a morphokinetic-based KIDScore for prediction of implantation. Clinical outcomes were retrieved from medical records. Linear mixed models were used to study differences in morphokinetic parameters, a proportional odds model for KIDScore ranking and logistic regression for differences in clinical outcomes. All analyses were adjusted for patient and treatment characteristics. In 253 (63.1%) cycles, embryos (n = 671) were cultured in Vitrolife, and in 148 (36.9%) cycles, embryos (n = 517) were cultured in SAGE. All cleavage divisions occurred earlier for SAGE embryos than for Vitrolife embryos (2-cell: -2.28 (95%CI: -3.66, -0.89), 3-cell: -2.34 (95%CI: -4.00, -0.64), 4-cell: -2.41 (95%CI: -4.11, -0.71), 5-cell: -2.54 (95%CI: -4.90, -0.18), 6-cell: -3.58 (95%CI: -6.08, -1.08), 7-cell: -5.62 (95%CI: -8.80, -2.45) and 8-cell: -5.32 (95%CI: -9.21, -1.42) hours, respectively). Significantly more embryos cultured in SAGE classified for the highest KIDScore compared to embryos cultured in Vitrolife (p < 0.001). No differences were observed in clinical outcomes. Our results demonstrate an impact of culture medium on preimplantation embryo developmental kinetics, which affects classification within the KIDScore algorithm, while pregnancy outcomes were comparable between the groups. This study underscores the need to include the type of culture medium in the development of morphokinetic-based embryo selection tools.

Does conventional morphological evaluation still play a role in predicting blastocyst formation?

BACKGROUND

Advanced models including time-lapse imaging and artificial intelligence technologies have been used to predict blastocyst formation. However, the conventional morphological evaluation of embryos is still widely used. The purpose of the present study was to evaluate the predictive power of conventional morphological evaluation regarding blastocyst formation.

METHODS

Retrospective evaluation of data from 15,613 patients receiving blastocyst culture from January 2013 through December 2020 in our institution were reviewed. Generalized estimating equations (GEE) were used to establish the morphology-based model. To estimate whether including more features regarding patient characteristics and cycle parameters improve the predicting power, we also establish models including 27 more features with either LASSO regression or XGbosst. The predicted number of blastocyst were associated with the observed number of the blastocyst and were used to predict the blastocyst transfer cancellation either in fresh or frozen cycles.

RESULTS

Based on early cleavage and routine observed morphological parameters (cell number, fragmentation, and symmetry), the GEE model predicted blastocyst formation with an AUC of 0.779(95%CI: 0.77-0.787) and an accuracy of 74.7%(95%CI: 73.9%-75.5%) in the validation set. LASSO regression model and XGboost model based on the combination of cycle characteristics and embryo morphology yielded similar predicting power with AUCs of 0.78(95%CI: 0.771-0.789) and 0.754(95%CI: 0.745-0.763), respectively. For per-cycle blastocyst yield, the predicted number of blastocysts using morphological parameters alone strongly correlated with observed blastocyst number (r = 0.897, P < 0.0001) and predicted blastocyst transfer cancel with an AUC of 0.926((95%CI: 0.911-0.94).

CONCLUSION

The data suggested that routine morphology observation remained a feasible tool to support an informed decision regarding the day of transfer. However, models based on the combination of cycle characteristics and embryo morphology do not increase the predicting power significantly.

The KIDScore™ D3 scoring system contributes to the prediction of embryonic development potential: A promising tool for screening high-quality embryos

Using the KIDScoreTM D3 (KID3) scoring system, day 3 embryos observed by time-lapse imaging (TLI) were scored to explore the predictive value of the KID scoring system on the developmental potential of embryos. The kinetic parameters of 477 normal fertilized embryos from 77 patients who underwent TLI in our hospital from January 2019 to June 2020 were evaluated by KID3, and the embryos were divided into five groups according to the scores for retrospective analysis of blastocyst formation. Additionally, the high-quality blastocyst formation rate, pregnancy rate and early abortion rate were analyzed via KID3 and traditional morphological assessments, and comparisons of differences among different ages were also performed. In the KID3 estimate, the blastocyst or high-quality blastocyst formation rate in the score 5 group was markedly higher than that in the score 1–4 groups. Blastocyst or high-quality blastocyst formation rates in the A group (the results of two evaluation tools indicated they were excellent embryos) and the B group (KID3: excellent embryos, traditional evaluation: not excellent embryos) were evidently increased in comparison with the C or D group (KID3: not excellent embryos, traditional evaluation: excellent embryo or not, respectively). Furthermore, the percentages of score 5 embryos, blastocyst and high-quality blastocyst formation rates for patients ≥ 35 years old were markedly decreased compared with those for patients < 34 years old, while the trends of nondiploid cleavage, multinucleation and asymmetric division were the opposite. Collectively, the KID3 scoring system may be a promising predictive tool for screening embryos with better developmental potential.