P-208 Embryo assessment at the click of a button is now possible: evaluation of a deep-learning algorithm integrated directly with the time-lapse platform

Study question

Is the embryo scoring function based on deep learning of specific time-lapse systems clinically useful for classifying human blastocyst?

Summary answer

Blastocyst grading according to iDAScore® is directly associated with conventional morphology and implantation potential, at least in treatments without preimplantation genetic testing for aneuploidy (PGT-A).

What is known already

The conventional approach of embryo evaluation in the time-lapse systems is for embryologists to manually annotate a number of morphological and/or morphokinetic parameters. These values are then used in models of clinical outcome prediction. Embryo selection can be automated by using artificial intelligence (AI) to predict morphokinetic and morphology parameters. In this case, AI is employed in an indirect way to optimize the daily workflow based on existing traditional parameters. Finally, the most innovative approach is the use of AI to directly predict pregnancy, implantation or even live birth by using only time-lapse images.

Study design, size, duration

A retrospective cohort study including 518 patients who underwent IVF treatments and whose embryos (n = 3,406) were cultured in EmbryoScope Plus® time-lapse systems. Blastocysts were routinely evaluated by senior embryologists according to the ASEBIR morphological criteria. Then, embryos were scored using the iDAScore algorithm whose values range from 1 to 9.9.

Participants/materials, setting, methods

Embryo evaluation was performed automatically by iDAScore with the use of deep learning and a neural network. The algorithm was developed considering the entire embryo development to rank embryos according to likelihood of implantation. Embryo score was compared with conventional morphological quality, euploidy rate and the subsequent implantation outcome of 567 single blastocyst transfers. Then, we quantified the contribution of the automatic embryo score to implantation with multivariate logistic regression analysis in different patient populations.

Main results and the role of chance

The comparison between the embryo score provided by the iDAScore and the morphological category (A, B, C or D) assigned by embryologists showed a direct association*. The mean and standard deviation was 9.2 ± 0.4 for A; 8.2 ± 1.2 for B; 6.9 ± 1.6 for C and 4.0 ± 1.8 for D. The euploidy rate increased when embryos showed higher automatic scores*: 45.9% for score ≤ 8.0 (n = 354), 55.6% for score 8.1-8.8 (n = 169) and 62.8% for score >8.8 (n = 180). The implantation rate increased as the embryo score improved*: 37.8% for score ≤ 7.8 (n = 127), 50.9% for score 7.9-8.9 (n = 163), 65.7% for score >8.9 (n = 277). The logistic regression analysis of iDAScore took into account possible confounding factors: oocyte origin (donated vs. autologous); type of embryo transfer (fresh vs. frozen); oocyte age; patient body mass index; PGT-A (tested vs. non-tested embryos) and day of embryo transfer (fifth vs. sixth day of embryo development). iDAScore value was related to the odds of implantation in the oocyte donation program (OR = 1.61; 95%CI [1.19-2.19]; p < 0.001; n = 265) and in conventional treatments with autologous oocytes (OR = 1.52; 95%CI [1.22-1.90]; p < 0.001; n = 192). There was no significant association of embryo score with implantation in treatments involving PGT-A (n = 110).

*p<.05

Limitations, reasons for caution

This study is limited by its retrospective nature. The single-center design should be taken into account when considering the universal application of the model. Although our clinic was not involved in the development of iDAScore, and therefore this study should be considered as an external validation.

Wider implications of the findings

Our findings confirm that embryo evaluation can be performed automatically allowing embryologists to utilize their time more efficiently in other tasks of the IVF process that are more complex and require high precision and attention.

Trial registration number

This research has been funded by a grant from The Ministry of Science, Innovation and Universities FIS (PI21/00283) awarded to M.M.

P-168 Does the concentration of Interleukin-6 (IL-6) in spent embryo culture medium tell us anything? Association with implantation potential after euploid embryo transfer

Study question

Could Interleukin-6 (IL-6) secretion by euploid embryos provide extra information in the prediction of clinical outcomes after human blastocyst transfer?

Summary answer

The concentration of IL-6 in the spent embryo culture medium provides additional and non-redundant information associated with the success of a euploid embryo transfer.

What is known already

Previous studies revealed that the concentration of IL-6 in the culture medium could be useful in selecting the embryo for implantation (Dominguez et al., 2015) and higher concentrations of IL-6 was reported in embryos that reach blastocyst stage than in arrested ones (Lindgren et al., 2018). Recently, proteomic information gained from the analysis of the embryonic secretome have been used to predict the potential of a euploid embryo to lead to a live birth (Bori et al., 2021). Out of 92 proteins measured, IL-6 was one of the most relevant for the prediction of live birth along with blastocyst morphology.

Study design, size, duration

This prospective study included 157 euploid embryos from the preimplantation genetic testing for aneuploidies (PGT-A) program. Embryos were cultured until the blastocyst stage in EmbryoScope systems with single-step medium (Gems, Genea). All of them were routinely assessed by senior embryologists. Morphological quality was based on ASEBIR criteria and morphokinetic parameters were automatically annotated by guided annotations tool. The spent culture medium was collected on day 5/6 of embryo development (day of trophectoderm biopsy).

Participants/materials, setting, methods

Chromosome analysis was performed using next-generation sequence technology. In parallel, 20 µL of spent culture medium from each blastocyst was analyzed with Human IL-6 ELISA Kit. Only euploid embryos were used in the following analysis. We examined the association between IL-6 levels (pg/ul) and embryo morphology and morphokinetics. Out of the total, 77 embryos were selected and transferred according to ASEBIR morphological quality. Pregnancy, implantation and live birth rate were correlated to IL-6 concentration.

Main results and the role of chance

The average concentration of IL-6 in spent embryo culture medium was 1.76±0.93 pg/ul. The protein value was not related to embryo morphology (p = 0.332): 2.35±1.60 pg/ul for embryos graded as A; 1.72±0.95 pg/ul for embryos graded as B and 1.79±0.76 pg/ul for embryos graded as C. Likewise, IL-6 level was not related to morphokinetic parameters. Division time to 2 cells, 3 cells, 4 cells, 5 cells and time to blastulation were not statistically different among the following quartiles of IL-6: ≤ 1.06 pg/ul (n = 41), from 1.07 to 1.66 pg/ul (n = 39), from 1.67 to 2.21 pg/ul (n = 40) and >2.21 pg/ul (n = 37). However, the concentration of IL-6 was higher in those euploid embryos that achieved a clinical pregnancy than in those embryos that failed after transfer. For spent culture media with less than 1.66 pg/ul of IL-6, pregnancy rate was 50%*, implantation rate was 50%* and live birth rate 43.80%. For spent culture media with more than 1.66 pg/ul of IL-6, pregnancy rate was 77.80% *, implantation rate was 75,60%* and live birth rate was 64.40%. *p<0.05

Limitations, reasons for caution

The detection limit in protein quantification and the specific culture medium used that may affect IL-6 concentrations are the main limitations of our study.

Wider implications of the findings

Our findings demonstrated that the concentration of IL-6 in spent culture medium is independent of embryo morphology and morphokinetics, but it is related to the success of a PGT-A treatment. This may provide a promising approach to predict implantation after euploid embryo transfer by measuring the IL-6 protein.

Trial registration number

CDTI (IDI-20191102)

O-073 Artificial intelligence (AI) based triage for preimplantation genetic testing (PGT); an AI model that detects novel features in the embryo associated with ploidy

Study question

Can an AI based triage system noninvasively detect aneuploidy in preimplantation embryos in a precise and valid manner?

Summary answer

Using a feature extraction approach to identify features in time-lapse images, an AI model was validated and found to noninvasively detect ploidy with unprecedented accuracy.

What is known already

Invasive PGT with trophectoderm biopsy is the gold standard for evaluating the genetic integrity of an embryo prior to transfer. Even so, its utility and diagnostic accuracy is debated due to concern of structural damage, sampling bias and viability after vitrification-warming. Though several noninvasive methods for evaluating ploidy have been developed, their main limitations lay in their accuracy. This study reports on the ongoing validation of an AI model that relies on feature extraction and thresholding techniques to distinguish between aneuploid and euploid embryos; the model is intended to be used in clinical settings for PGT triage and preferential transfer.

Study design, size, duration

In this single-center study, we used a retrospective dataset consisting of time-lapse images from 2,502 preimplantation embryos with known ploidy status to train and validate the AI model.

Participants/materials, setting, methods

The model utilized videos captured from time-lapse incubator (Embryoscope) up to 144 hours post-fertilization with chromosome analysis performed using next-generation sequence technology as ground truth labels. The data set was divided using an 70/15/15 training-validation-test split of the data. The AI model included convolutional neural network extracted features alongside spatial features based on several biological and clinical characteristics known to associate with ploidy, embryo behavior, and function. Performances were measured by validation and test-set accuracy.

Main results and the role of chance

Five feature modules were included in the AI model for ploidy evaluation. All modules were analyzed separately and combined: (I) automated detection of abnormal morphokinetic patterns (t2-t8, tM, tSB, tB, tHB) differentiated between the two classes (aneuploid and euploid) to predict aneuploidy with an accuracy of 52%, p < 0.05; (II) previously validated embryo grading classification algorithm demonstrated an association between A and C-grade embryos with euploidy and aneuploidy, respectfully, with an accuracy of 68%, p < 0.05; (III) differential cell division activity and compaction between the two classes predicted aneuploidy with an accuracy of 73%, p < 0.05; (IV): AI-based classification of mitochondrial DNA content, measured as 0.5 micron irregularities in time-lapse images, predicted aneuploidy with an accuracy of 77%, p < 0.05; blastocoelic contractions of more than 8 microns in diameter predicted aneuploidy with 56% accuracy, p < 0.05. Using our AI model, we were able to integrate all 5 features, thereby achieving an unprecedented 90% accuracy. Two features – detection of abnormal morphokinetic patterns and blastocoelic contractions – occur in a minority of embryos (in 3% and 20% of all embryos in the database, respectively). When they do occur, they independently predict aneuploidy with an accuracy of 90% and 82%, demonstrating the robustness of our multi-feature model.

Limitations, reasons for caution

Our AI model needs to be tested on a large, multi-centric dataset to ensure standardization and ability to be replicated in different settings. Even so, given our high degree of demonstrated accuracy, we conclude that our single-center dataset was sufficient for developing the initial validation of the model reported here.

Wider implications of the findings

The ‘explainability’ and implementation of our AI model enables more objective embryo quality assessment and improves the clinics’ ability to prioritize embryos for PGT and preferential transfer using a validated and trusted framework that reduce dramatically the chances of transferring an aneuploid embryo to our patients.

Trial registration number

not applicable

P-224 The sex of the human embryos affects the oxidation profile of the spent culture media

Study question

Is the oxidative status of the spent culture media used in ICSI treatments related to embryo sex and newborn characteristics?

Summary answer

Female embryos produce higher levels of oxidative stress in the culture media than male embryos.

What is known already

Sex-associated differences in embryo development have previously been observed. Studies suggest that male embryos have a faster pre-implantation development, higher morphological grading and lower glucose consumption (Nasiri et al, 2018). The thermochemiluminiscence (TCL) assay quantifies the oxidative status of biological samples by catalyzing an oxidative reaction through heating and counting the photons emitted per second. TCL parameters are directly correlated to the content of oxidant agents in the sample. Previous analysis used TCL assay to relate higher oxidative metabolism in embryos with higher viability. Analysis of spent culture media with TCL could be a potential biomarker for embryo sex prediction.

Study design, size, duration

Prospective observational study over 86 transferred blastocysts (all single embryo transfer) that reached life-birth, belonging to ICSI treatments, including autologous and oocyte donation, performed in a single fertility clinic during three consecutive years. The oxidative status of the spent culture media was analyzed and compared with the characteristics of the newborns.

Participants/materials, setting, methods

Embryo cohorts were cultured in individual wells in an Embryoscope incubator, using single-step Gems culture media (Genea Biomedx). The best embryo of the cohort was selected for transfer using morphologic (ASEBIR) and morphokinetic criteria (KID Score algorithmTM, Vitrolife, (KS)). Spent culture media was analyzed in the Fertissimo TCL Analyzer (Carmel Diagnostics, Israel) and oxidation parameters were compared with the sex, weight and height of the newborns through ANOVA, C2 and Pearsons Correlation coefficient (PCC) tests.

Main results and the role of chance

The sex ratio of the embryos (male to female) resulted 59.3%. The sex ratio was increasingly higher the better morphological classification: C = 16.7%, B = 56.0%, A: 73.3%. KS did not give significantly different scores to the embryos depending on their sex: average KS (female)=6.78 vs average KS (male)=7.03, P = 0.621. No correlation was found between KS or the morphological classification and the weight and height of the babies: PCC (KS-height)=0.158, P = 0.349; PCC (KS-weight)=0.082, P = 0.569; average newborn height: C = 51.67±1.15cm, B = 50.57±3.48cm, A = 50.92±1.95cm, P = 0.791, average newborn weight: C = 3,386.00±459.11g, B = 3,283.35±658.12g, A = 3,229.07±732.13g, P = 0.877. TCL ratio (slope of the time curve of photon emission, representing the level of oxidant agents in the sample) was statistically significantly higher in the culture media of female embryos than of male embryos: Ratio (female)=119.54±13.37 vs Ratio (male)=111.62±15.80, P = 0.017. No statistically significant difference was found in the TCL Ratio between the three morphological classes, although the tendency of the data is towards lower levels with increasing morphological classification: Ratio (C)=120.40±14.43, ratio (B)=116.32±14.39 and ratio (A)=111.27±16.62, P = 0.237. No correlation was found between the TCL parameters and the weight and height of the newborn: PCC (Ratio-height)=-0.173, P = 0.198; PCC (Ratio-weight) 0.036, P = 0.753.

Limitations, reasons for caution

Patient demographics, habits and male sperm characteristics were not considered for the analysis, but might impact embryo characteristics and intrauterine development of the fetus. A larger scale study should be performed to validate results.

Wider implications of the findings

The differential oxidative load embryos exert over the culture medium might be related to a glucose consumption-associated sex dimorphism. Measuring the oxidative status of the culture medium could serve as a non-invasive biomarker for embryo sex selection. This technique could be an interesting option in carriers of sex-linked diseases.

Trial registration number

not applicable

P-277 An artificial intelligence (AI) deselection model for top-quality blastocysts: algorithmic analysis of morphokinetic features for aneuploidy may increase implantation rates

Study question

Can an AI deselection model identify distinct morphokinetic patterns in top-quality blastocyst with unknown ploidy that fail to implant?

Summary answer

An AI based deselection model was able to predict implantation failure based on morphokinetic features previously found to associate with aneuploidy.

What is known already

Aneuploidy is the most common explanation for implantation failure of high-quality blastocysts. Yet, high-quality blastocysts with unknown ploidy that fail to implant are often morphologically indistinguishable from blastocysts that succeed to implant. Our previously published results (ESHRE 2021) demonstrated that aneuploid blastocysts were more likely to reach development events (t2-t8) later, and that the timing between each event was statistically longer (p < 0.001), when compared to euploid embryos. Given that delayed morphokinetic rates are tightly linked to ploidy, we investigated whether similar known morphokinetic features were associated with implantation failure in top-graded embryos.

Study design, size, duration

Time-lapse sequences of 3,259 top-quality blastocysts from fresh single embryo transfer cycles with known implantation outcomes were analyzed using an AI-based algorithm. The algorithm utilized convolutional neural network extracted temporal features based on multiple morphokinetic parameters known to associate with ploidy.

Participants/materials, setting, methods

time-lapse sequences and morphokinetic events were algorithmically analyzed to measure the rate of mitotic division events and compare the number of embryos in each category (implanted/nonimplanted) that reached each developmental event at least one standard deviation (SD) later than the mean for implanted embryos.

Main results and the role of chance

Results showed statistical differences in the following morphokinetic features between the two categories: t2, t3, t4, and t3-t4 (p < 0.05). Implanted top-graded blastocysts were likely to reach t2, t3, and t4 after 25.23 ± 3.8 SD, 36.06 ± 3.4 SD, and 37.14 hours ±3.6 SD, respectively. The time gap between t3 and t4 was found to be 12.25 hours ± 5.31 SD. Given this, we followed the methodology described above to propose cutoff values (in hours) that differentiated between non-implanted and implanted top-graded blastocysts based on their morphokinetic profiles. Implantation failure was found to be associated with the likelihood of reaching t2 after 28.61 hours (OR = 2.36, CI 0.96-5.77), t3 after 39.46 (OR = 3.48, CI 1.62-7.47), and t4 after 40.79 hours (OR = 2.23, CI 1.09- 4.53). A time gap between t3 and t4 of more than 17.56 hours was also associated with implantation failure (OR = 2.48, CI 1.12-5.48), indicating perturbed mitotic activity. The cutoff values proposed here were incorporated into the algorithm for optimized deselection of morphologically similar top-quality blastocysts with delayed morphokinetic profiles.

Limitations, reasons for caution

This study needs to be validated on a larger, multi-centric dataset that takes into account more morphokinetic features associated with ploidy in order to increase the robustness of our algorithm.

Wider implications of the findings

For the first time, our algorithmic model proposed here demonstrates the utility of an AI tool to deselect top-graded blastocysts that would otherwise be selected for transfer based on conventional morphologic assessment alone.

Trial registration number

Not Applicable

O-176 End-to-end deep learning system for recognition of euploid and aneuploid embryos using time-lapse videos

Study question

Can an Artificial Intelligence (AI) system based on a deep learning algorithm analyze time-lapse videos for ploidy status prediction?

Summary answer

Our spatiotemporal model can distinguish aneuploid embryos from euploid embryos using time-lapse videos from 10 to 115 hours post-insemination (hpi) with an accuracy of 71,28%.

What is known already

As the maternal age advances chances of aneuploidy in oocyte also increases and there is a high chance of early termination of pregnancy. Pre-implantation genetic testing for aneuploidy (PGT-A) is a reliable tool for detecting chromosomal status. However, PGT-A is an invasive technique in which protocol requires an embryo biopsy. Continuous monitoring of embryo development led to AI models for the prediction of ploidy based on blastocyst images or morphokinetic parameters. Previous publications showed that euploid embryos reach blastulation earlier than non-euploid embryos. This is the first attempt to predict ploidy by analyzing continuous embryo development through captured time-lapse images.

Study design, size, duration

The present study consisted of a single-center retrospective analysis for the evaluation of ploidy status with a non-invasive method. We developed our models based on a balanced dataset of 940 videos (from 10 to 115 hpi) extracted from the EmbryoScope time-lapse system. All the videos were divided into 90% for training and validating and 10% for testing. The target class for the predicted models was the results of PGT-A on blastocyst by next-generation sequencing.

Participants/materials, setting, methods

We used an end-to-end approach to develop an automated AI system capable of extracting features from images and classifying them considering temporal dependencies. First, a convolutional neural network (CNN) extracted the most relevant features from each frame. We used a deep architecture known as ResNet50.  Second, a bidirectional long short-term memory (LSTM) layer received this information and analyzed temporal dependencies, obtaining a low-dimensional feature vector that defined each video. Finally, a multilayer perceptron classified them.

Main results and the role of chance

Euploid and aneuploid precision was 69% and 75%, respectively. Euploid and aneuploid sensitivity was 79% and 64%, respectively. Euploid and aneuploid F1 score was 73% and 69% respectively. The global accuracy associated with our spatiotemporal model to differentiate between the two classes achieved 71,28% on this dataset. Additionally, we trained models with external information such as maternal age (38,3±3,9 versus 39,1±3,1), but the performance did not improve. Note that we did not apply a prior selection of good quality videos to study more reliably the possible inclusion of an AI model for chromosomal status analysis in clinical practice. 

Limitations, reasons for caution

The main limitation of this study is the single-center retrospective approach and the reduced size of the database, therefore future prospective research would improve model performance. However, the preliminary results showed the high potential of the methods.

Wider implications of the findings

Our results showed potential automation of chromosomic status evaluation. Our findings led to a possible non-invasive method and the research of new unknown key factors for determining ploidy. Further studies with a large number of time-lapse videos could result in a potential translation to clinical use.

Trial registration number

not applicable

P–203 Applying artificial intelligence for ploidy prediction: The concentration of IL–6 in spent culture medium, blastocyst morphological grade and embryo morphokinetics as variables under consideration

Study question

Would it be possible to predict embryo ploidy by taking into account conventional morphological and morphokinetic parameters together with IL–6 concentration in spent culture medium?

Summary answer

Our artificial neural network (ANN) trained with blastocyst morphology, embryo morphokinetics and IL–6 concentration distinguished between euploid/aneuploid embryos in 65% of the testing dataset.

What is known already

The analysis of spent embryo culture media represents the protein and metabolic state of the embryo and could be a non-invasive method of obtaining information about embryo quality. The impact of the presence/absence of several proteins in embryo culture samples over clinical results has been widely studied. The IL–6 is one of the most mentioned protein for its effect on embryo development, implantation and likelihood of achieving a live birth. In this initial attempt, we examined the predictive value for euploidy of a model that took into account the concentration of IL–6 in the spent culture medium.

Study design, size, duration

This prospective study included 319 embryos with PGT-A results. Out of the total, 127 were euploid and 192 aneuploid embryos. Concentration of IL–6 in spent embryo culture media (collected on the day of trophectoderm biopsy-fifth/sixth day of development), morphokinetic parameters (division time to 2 cells-t2; to 3 cells-t3, to 4 cells-t4; to 5 cells-t5 and time of blastocyst formation-tB) and blastocyst morphological grade (according to ASEBIR criteria) were considered to predict the embryo ploidy.

Participants/materials, setting, methods

Embryos were cultured in EmbryoScope. The chromosome analysis was performed using next-generation sequence technology. The concentration of IL–6 was measured in 20µL of spent embryo culture media with ELISA kits. Morphokinetic parameters were automatically annotated and the blastocyst morphology was evaluated by senior embryologists based on blastocele expansion, inner cell mass and trophectoderm quality. All the embryos were divided into 70% for training, 15% for validating and 15% for testing our ANN model with MatLab®.

Main results and the role of chance

The general description for the euploid embryo population was the following: 2% of the embryos were graded as A, 71% were graded as B and 28% were graded as C; the means and standard deviations were 25.32±2.97 hours (h) for t2, 35.33±5.15h for t3, 37.30±5.43h for t4, 48.24±6.62h for t5 and 103.93±12.8h for tB; and the average of IL–6 concentration was 1.51±0.70 pg/ml. The general description for the aneuploid embryo population was the following: 1% of the embryos were graded as A, 48% were graded as B and 51% were graded as C; the means and standard deviations were 26.13±3.51h for t2, 36.70±4.29h for t3, 38.20±4.24h for t4, 49.86±6.89h for t5 and 107.10±8.29h for tB; and the average of IL–6 concentration was 1.47±0.71 pg/ml. Our ANN model showed a higher general success rate as we increased the variables considered in the final prediction of euploid embryos. The accuracy, sensitivity and specificity for the testing dataset were: 0.60, 0.12 and 0.87 with morphokinetic parameters; 0.63, 0.24 and 0.93 with morphokinetics and IL–6 concentration; and 0.65, 0.16 and 0.96 with morphokinetics, IL–6 concentration and blastocyst morphological grade.

Limitations, reasons for caution

The low sensitivity and high specificity achieved in our models indicated that they were more capable of detecting aneuploid than euploid embryos. As this was a preliminary study, the small number of embryos included in the test (n = 48) was also a limitation.

Wider implications of the findings: The results showed that our model tended to classify the embryos as aneuploid. More euploid embryos would be necessary to train our model and achieve better results in the prediction of chromosomally normal embryos. Further studies with large number of embryos and additional variables could improve the non-invasive ploidy prediction.

Trial registration number

Not applicable

O-214 Undisturbed embryo culture under High Humidity atmosphere in a time-lapse system increases pregnancy rates

Study question

Does culture in high relative humidity conditions (HC) improve pregnancy rates when using a time-lapse system (TLS) and single-step (SS) culture medium?

Summary answer

Using an integrated-TLS and SS medium, culture under HC increases the likelihood of embryos to achieve a pregnancy with respect to those cultured in DC.

What is known already

Many variables affect embryo development, and need to be precisely tuned in every IVF laboratory, especially inside the incubators. TLS provide stability during embryo culture, which is a well-known key factor for a proper embryo development. The humidity content of culture atmosphere is especially relevant in order to avoid oscillations in culture media osmolality. It has been previously reported that culture under HC has a significant effect on embryo quality and morphokinetics. However, studies assessing the effect of HC in clinical outcome are rare and inconclusive, mostly due to the variability in the incubator device used and insufficient sample size.

Study design, size, duration

The present is a retrospective study performed over 1624 ICSI treatments from 3 fertility clinics from December 2017 to October 2020. Zygote cohorts were randomly assigned to dry (N = 794) or humid conditions (N = 830). It includes autologous treatments with (N = 555) and without (N = 368) pre-implantation genetic testing (PGT) and egg donation treatments (N = 701). Following selection by combining morphological and morphokinetic criteria, 1611 mostly single embryo transfers (92%) were performed, 779 from DC and 832 from HC.

Participants/materials, setting, methods

Stimulation, oocyte pickup and fertilization were performed according to the standard procedures of the clinic. We used a GERI incubator (Genea Biomedx), with 6 separated chambers for individual patients, 3 of them configured to work in DC, and 3 in HC. Embryos were cultured in specific 16-well GERI trays with single-step Gems® culture medium (Genea Biomedx). The effect of HC in pregnancy rate was assessed by multivariate logistic regression and Pearson Chi Square Test.

Main results and the role of chance

Types of treatment and patient demographics were homogeneously distributed in the two study groups. Mean patient age was 39.88±4.47 years, BMI: 23.54±4.21 Kg/m2 and number of correctly fertilized oocytes: 7.86±3.87. A logistic regression was performed, including other possible affecting factors: ovum age and origin, transfer day, fresh or frozen-warmed embryo transfer, number of transferred embryos and the use of PGT. Said analysis revealed that embryos cultured in HC are more likely to achieve a pregnancy than those cultured in DC (OR = 1.30, 95% CI (1.05-1.59), p=0.014). Pregnancy rate was significantly higher in HC (66.7%) than in DC (60.9%) in the total embryo transfers (p = 0.017). Pregnancy rate was also higher in HC in fresh embryo transfers (68.6% in HC vs 63.2% in DC; p = 0.133) and frozen-thawed transfers (65.2% in HC vs 59.1% in DC; p = 0.062), although differences were not statistically significant due to the reduced sample size. Stratifying the results, the significant difference remained in transfers belonging to autologous cycles (68.4% HC vs 56.5% in DC; p = 0.030) and in treatments in which PGT was performed (67.1% HC vs 56.0% in DC; p = 0.023), but the difference in egg donation procedures was not statistically significant (66.4% in HC vs 64.7% in DC, p = 0.577).

Limitations, reasons for caution

This is a retrospective analysis performed over the clinics’ treatments, so it might be compromised by some bias, although multivariable analysis may overcome them. For further assessing the effect of HC in clinical results a prospective controlled study, with a larger sample size could be performed, also comparing life-birth rates.

Wider implications of the findings

These results, alongside our previous findings (Valera et al. 2020, Albert et al. 2020), support that HC contributes to optimize embryo development and clinical results in undisturbed culture in TLS with single-step medium. To our knowledge, this is the largest study on the matter and the first performing multivariable analysis.

Trial registration number

Not applicable

O-084 Computer vision can distinguish between euploid and aneuploid embryos. A novel artificial intelligence (AI) approach to measure cell division activity associated with chromosomal status

Study question

Can we distinguish between top-grade euploid and aneuploid embryos by AI measurement of cell edges in time-lapse videos?

Summary answer

Aneuploid embryos can be distinguished from euploid embryos by AI determination of a longer time to blastulation and higher cell activity.

What is known already

Continuous monitoring of the embryo development has brought out morphokinetic parameters that are used to predict pre-implantation genetic testing (PGT) results. Previous publications showed that euploid embryos reach blastulation earlier than non-euploid embryos. However, time-lapse data are currently under-utilized in making predictions about embryo chromosomal content. AI and computer vision could take advantage of the massive amount of data embedded in the images of embryo development. This is the first attempt to distinguish between euploid and aneuploid embryos by computer vision in an objective and indirect way based on the measurement of cell edges as a proxy for cell activity.

Study design, size, duration

We performed a retrospective analysis of 1,314 time-lapse videos from embryos cultured to the blastocyst stage with PGT results. This single-center study involved two phases; a comparison of the start time of blastulation between euploid (n = 544) and aneuploid embryos (n = 797). In phase two, we designed a novel methodology to examine whether precise measurement of cell edges over time could reflect cell activity differences in blastulation.

Participants/materials, setting, methods

We assumed that the delay in blastulation is reflected by higher cell activity that could be determined accurately for the first time using computer vision and machine learning to measure the length of the edges (from t2 to t8). We compared computer vision based measurements of cell edges, reflecting cell number and size, in videos of 231 top-grade euploid (n = 111) and aneuploid (n = 120) embryos.

Main results and the role of chance

The mean and standard deviation of blastulation start time was 100.1±6.8 h for euploid embryos and 101.8±8.2 h for aneuploid embryos (p < 0.001). Regarding the measurement of cell activity, a computer vision algorithm identified the edges and provided a certainty score for each edge, higher when the algorithm is more certain that this is a cell edge (as opposed to noise in the images). A threshold was set to distinguish cell edges from noise using this score. The following results for top-grade embryos are shown as the sum of the edge lengths (µm) average of 160 pictures per embryo (frames between t2 and t8). The total length of the cell edges increased from two cells (420±85 µm) to eight cells (861±237 µm), in line with the mitosis events. Both the average total edge measured (450±162 µm for euploid embryos and 489±215 µm for aneuploid embryos, p < 0.01) and the average total of the difference between consecutive frames (135±47 µm for euploid embryos and 153±64 µm for aneuploid embryos, p < 0.01) were higher for aneuploid embryos than for euploid embryos. A regression model to differentiate between the two classes achieved 73% sensitivity and 73% specificity on this dataset.

Limitations, reasons for caution

The main limitation of this study is the difficulty to correlate our findings to other measure of cell activity. A more robust AI function (using not only cell edges lengths) would be required for future analysis to measure the cell activity in cell division up to the blastocyst stage.

Wider implications of the findings

Our results show for the first time that an AI based system can precisely measure microscopic cell edges in the dividing embryo. Using this novel method, we could distinguish between euploid and aneuploid embryos. This non-invasive method could further enhance our knowledge of the developing embryo.

Trial registration number

Not Applicable

P–197 Two different strategies for embryo culture and selection: time-lapse with single-step medium and conventional incubator with sequential media. Are there differences in clinical results?

Study question

Is there a significant difference in the clinical results of embryos cultured in time-lapse systems with single-step medium and conventional benchtop incubators with sequential media?

Summary answer

Embryos cultured in time-lapse systems and single-step media are more likely to achieve an ongoing pregnancy and have higher implantation rates than those cultured otherwise.

What is known already

One of the strategies for embryo culture in IVF consisted in conventional benchtop incubators combined with sequential culture media (CI-Seq). New generation time-lapse systems provide useful information on the morphokinetics of embryo development, but also a stable culture environment where embryos can develop undisturbed until blastocyst stage when paired with single-step culture media (TLS-SS). These features have the potential to improve embryo development and selection. Nonetheless, there is inconclusive evidence of whether this new culture strategy has a significant effect on clinical results of ICSI treatments. Studies on the matter are heterogeneous and reduced in both number and sample size.

Study design, size, duration

Unicentric retrospective cohort study. We compared the results of 11471 blastocyst transferences from 10276 ICSI treatments performed during 4 consecutive years, where embryos were cultured either on CI with sequential media (N = 5255) or a TLS with single-step medium (N = 5021). 3922 of the totals were fresh embryo transfers (ET) and 7549 frozen-thawed ET. We compared the implantation rate (IR) and ongoing pregnancy rate (OGPR) in both study groups, stratifying by ovum origin.

Participants/materials, setting, methods

Three models of TLS were used for embryo culture: EmbryoScope, EmbryoScope Plus (Vitrolife) and GERI (Genea Biomedx), as well as one CI (ASTEC). Sequential media: Cook, Origio, Vitrolife; Single-step media: Gems, Irvine, Life Global. Embryo scoring and selection was performed by ASEBIR criteria in the CI group, and by morphological and morphokinetic assessment for embryos cultured in TLS. Embryos were extracted from the CI only for media change. Statistical analysis: ANOVA tests and Logistic regressions.

Main results and the role of chance

A general Logistic Regression was performed, including egg origin, PGT-A and culture strategy to explain their impact in OGPR. Egg origin (OR = 1,094 (95%CI: 1,015–1,179); P = 0,019) and culture strategy (OR = 1,141 (95%CI: 1,060–1,229); P < 0,001) were statistically significant, which confirms the need for stratification due to the heterogeneity of the groups. The total IR in the TLS-SS group was 54,68±48,84%, significantly higher than that of CI-Seq (49,18±47,91%; P < 0,001). In ovum-donation treatments, a complete Logistic Regression for OGPR, with all typical confounding variables (age, BMI, nº oocytes, fresh/frozen transfer, number and day of ET) resulted in an OR = 1,187 (95%CI: 1,074–1,313; P = 0,001) favoring culture in TL-SS. IR in these treatments were 61,98±47,68% in TL-SS vs 55,08±46,58% in CI-Seq (P < 0,001) in fresh transfers and 51,48±48,91% in TL-SS vs 44,39±47,67% in CI-Seq (P < 0,001) in frozen-thawed ET. In autologous treatments with PGT a similar regression yielded an OR = 1,055 (95%CI: 0,889–1,252; P = 0,542) for culture strategy. The IR of genetically tested ET was not significantly different: 53,08±49,49% for TL-SS, 50,90±49,07% for CI-Seq, P = 0,246. In autologous procedures without PGT, culture strategy was not significant for OGPR (OR = 0,998 (95%CI: 0,835–1,191), P = 0,979) nor IR of fresh (49,75±48,91% TL-SS vs 44,23±47,36% CI-Seq; P = 0,081) nor frozen-thawed transferences (50,77±48,33% TL-SS vs 50,67±47,33% CI-Seq; P = 0,970).

Limitations, reasons for caution

After fertilization check, embryos were evaluated exclusively on D5/6. On D3, embryos cultured in CI were taken out only for a quick media change, but not for evaluation, and all handling was done in isolette cabins with controlled environmental conditions. Being a retrospective study, there is high variability in population.

Wider implications of the findings: A more homogenous prospective study, including comparison in life-birth rates, is necessary to extract final conclusions. However, our results suggest that the introduction of TLS and SS media in IVF laboratories might be a valid strategy to increase clinical results, especially in fresh embryo, thanks to an improved embryo selection.

Trial registration number

Not applicable

P–144 Undisturbed culture in time-lapse systems improves embryo development and quality

Study question

Does culture in integrated time-lapse systems (TLS) improve embryo development and blastocyst quality compared to conventional benchtop incubators (CI), within the same IVF laboratory?

Summary answer

Under similar conditions, culture in TLS resulted in a significant increase in blastocyst rate, top quality blastocyst rate and proportion of biopsied embryos per treatment

What is known already

Integrated TLS have the potential of delivering a stable and undisturbed environment throughout the whole embryo culture, avoiding taking them out for assessment. However, there is still lack of quality evidence of the performance of these incubators compared to CI at supporting embryo culture until blastocyst stage. Studies abording this issue are still scarce, heterogeneous and have a small sample size. Although some authors have reported an improvement in embryo development and quality using TLS, global results are inconsistent. To our knowledge, the present study evaluates the effect of TLS on embryo quality on the largest sample size yet.

Study design, size, duration

Unicentric retrospective cohort study including 14248 ICSI treatments from 2016 to October 2020, with both autologous and donated oocytes. We compared blastocyst rate (BR) and proportion of top-quality blastocysts (TQB=Morphology ASEBIR score A) per treatment between those using TLS (N = 7500) and CI (N = 6748), and the proportion of embryos biopsied (EB) in cycles with pre-implantation genetic testing (PGT-A; N = 2642). We performed a sub-analysis in treatments using single-step culture medium (N-TLS=4398, N-CI=1140) in both types of incubators.

Participants/materials, setting, methods

Embryo cohorts were cultured until blastocyst stage in one of 3 TLS: EmbryoScope, EmbryoScope Plus (Vitrolife,) and Geri (Genea Biomedx), or in a CI (ASTEC). Embryo quality was assessed following ASEBIR morphological criteria. Culture protocols and media changed during the included time period. For that reason, we did a sub-study in the treatments performed since the implementation of Gems® (Genea Biomedx) single-step (SS) culture medium in all incubators. Statistical analysis was done using ANOVA tests.

Main results and the role of chance

Treatments were differently distributed and heterogeneous in terms of number of oocytes obtained per patient, so we stratified the analysis according to ovum origin and compared mean rates per cycle instead of total number of embryos per group. BR was statistically higher (P < 0,001) in the TLS group, in both autologous (62,98±29,37% vs 59,49±31,09% in CI) and oocyte donation treatments (69,25±22,07% vs 66,27±23,28% in CI). Proportion of TQB was also significantly higher in the TLS in both types of cycles (P < 0,001): 3,60±12,29% in TLS vs 2,27±9,71% in CI in autologous cycles, 8,68±15,31% in TLS vs 7,32±14,02% CI in ovum donation cycles. Results were corroborated in the SS media sub-study (P < 0,05): BR was 63,87±29,23% in TLS vs 57,53±30,61% in CI with autologous oocytes, and 70,76±21,63% in TLS vs 67,39±22,68% in CI with donated oocytes; TQB rates were 3,66±12,06% in TLS vs 2,05±9,26% in CI in autologous treatments and 8,81±15,21% in TLS vs 6,84±12,91% in CI in ovum donation treatments. Regarding PGT-A treatments, we found no significant difference in the biopsy rate in the total comparison, although the rate significantly increased in the TLS group since the implementation of single-step medium (52,36±24,69% in TLS vs 48,63±22,56% in CI; P = 0,007)

Limitations, reasons for caution

Not only culture conditions varied over time, but also the number of TLS in the laboratory, which increased lately. Hence, even though the most recent treatments included in the all-SS sub-study are more homogeneous in terms of culture conditions, they are unbalanced regarding the distribution among incubators.

Wider implications of the findings: Our results demonstrate the superiority of TLS coupled with single-step culture media against traditional embryo culture systems at supporting embryo development. The optimal environment provided by TLS enhances embryo development until blastocyst stage as well as their quality, increasing the cumulative chances of getting a life-birth for each patien.

Trial registration number

Not applicable

P–141 Artificial intelligence system for the automation of the blastocyst morphology evaluation in GERI Time-lapse Incubator

Study question

Can an Artificial Intelligence (AI) system (hand-crafted vs. deep learning techniques) based on single embryo image analysis from a GERI time-lapse incubator (TL) evaluate the blastocyst morphology?

Summary answer

Our hand-crafted method trained with blastocyst images from Geri-TL evaluated and classified parameters regarding to embryo quality with a global precision of 63.7% in blind-test.

What is known already

Recent studies have shown that AI can improve automatic grading and embryo selection. The approaches that have been carried out are very different, but all they conclude that there is a great potential (Rad2019, Manoj2020, Thirumalaraju2020). As we know, conventional embryo evaluation is performed manually based on the morphology of the blastocyst, therefore, it should be possible to replicate this process. In this study, we implemented different methods to analyse the behaviour and performance of an AI doing embryology tasks.

Study design, size, duration

Our study consisted of a retrospective analysis for the automatization of embryo evaluation with different approaches. We developed our models based on 715 images extracted from GERI TL Videos (Genea, Australia) from a single IVF center. Database was divided into 3 classes depending on the quality of the embryo according to ASEBIR morphology criteria (high; medium and low-quality). All the images were divided into 70% for training, 15% for validating and 15% for testing.

Participants/materials, setting, methods

We developed an automated AI algorithm to extract and classify features from images at 111,5 hpi of embryos cultured in GERI TL. Hand-crafted features from texture information are extracted to feed the classification algorithm. A statistical analysis is carried out to select the more discriminative variables. Parallelly, a deep neural network was built to compare performance of automatic and hand-crafted features. Additionally, we trained a model to detect embryo in the well.

Main results and the role of chance

High-quality, medium-quality and low-quality sensitivity were 73%, 56% and 72% for hand-crafted method and 76%, 53% and 22% for deep learning approach, respectively. High-quality, medium-quality and low-quality precision were 66%, 56% and 76% for hand-crafted method and 40%, 60% and 55% for deep learning approach, respectively. The global accuracy associated with each method was 64% and 50%. Also, we noticed that results were higher when we applied our embryo masks that avoid irrelevant information. In this initial attempt, our results showed that it is possible to replicate the embryo evaluation process.

Limitations, reasons for caution

The low results obtained in our deep learning model due to the absence of an extent dataset did not allow to obtain a model applicable to the clinic. However, the preliminary study let us to conclude the high potential of the approach.

Wider implications of the findings: Our results showed a potential automatization of the embryo evaluation process in Geri TL where the available software for embryo selection does not provide such option. Our findings leaded to an increase in objectification, a reduction of the workload of the embryologist and the research of new unknown morphological variables.

Trial registration number

Not applicable

P-203 Applying artificial intelligence for ploidy prediction: The concentration of IL-6 in spent culture medium, blastocyst morphological grade and embryo morphokinetics as variables under consideration

Study question

Would it be possible to predict embryo ploidy by taking into account conventional morphological and morphokinetic parameters together with IL-6 concentration in spent culture medium?

Summary answer

Our artificial neural network (ANN) trained with blastocyst morphology, embryo morphokinetics and IL-6 concentration distinguished between euploid/aneuploid embryos in 65% of the testing dataset.

What is known already

The analysis of spent embryo culture media represents the protein and metabolic state of the embryo and could be a non-invasive method of obtaining information about embryo quality. The impact of the presence/absence of several proteins in embryo culture samples over clinical results has been widely studied. The IL-6 is one of the most mentioned protein for its effect on embryo development, implantation and likelihood of achieving a live birth. In this initial attempt, we examined the predictive value for euploidy of a model that took into account the concentration of IL-6 in the spent culture medium.

Study design, size, duration

This prospective study included 319 embryos with PGT-A results. Out of the total, 127 were euploid and 192 aneuploid embryos. Concentration of IL-6 in spent embryo culture media (collected on the day of trophectoderm biopsy-fifth/sixth day of development), morphokinetic parameters (division time to 2 cells-t2; to 3 cells-t3, to 4 cells-t4; to 5 cells-t5 and time of blastocyst formation-tB) and blastocyst morphological grade (according to ASEBIR criteria) were considered to predict the embryo ploidy.

Participants/materials, setting, methods

Embryos were cultured in EmbryoScope. The chromosome analysis was performed using next-generation sequence technology. The concentration of IL-6 was measured in 20µL of spent embryo culture media with ELISA kits. Morphokinetic parameters were automatically annotated and the blastocyst morphology was evaluated by senior embryologists based on blastocele expansion, inner cell mass and trophectoderm quality. All the embryos were divided into 70% for training, 15% for validating and 15% for testing our ANN model with MatLab®.

Main results and the role of chance

The general description for the euploid embryo population was the following: 2% of the embryos were graded as A, 71% were graded as B and 28% were graded as C; the means and standard deviations were 25.32±2.97 hours (h) for t2, 35.33±5.15h for t3, 37.30±5.43h for t4, 48.24±6.62h for t5 and 103.93±12.8h for tB; and the average of IL-6 concentration was 1.51±0.70 pg/ml. The general description for the aneuploid embryo population was the following: 1% of the embryos were graded as A, 48% were graded as B and 51% were graded as C; the means and standard deviations were 26.13±3.51h for t2, 36.70±4.29h for t3, 38.20±4.24h for t4, 49.86±6.89h for t5 and 107.10±8.29h for tB; and the average of IL-6 concentration was 1.47±0.71 pg/ml. Our ANN model showed a higher general success rate as we increased the variables considered in the final prediction of euploid embryos. The accuracy, sensitivity and specificity for the testing dataset were: 0.60, 0.12 and 0.87 with morphokinetic parameters; 0.63, 0.24 and 0.93 with morphokinetics and IL-6 concentration; and 0.65, 0.16 and 0.96 with morphokinetics, IL-6 concentration and blastocyst morphological grade.

Limitations, reasons for caution

The low sensitivity and high specificity achieved in our models indicated that they were more capable of detecting aneuploid than euploid embryos. As this was a preliminary study, the small number of embryos included in the test (n = 48) was also a limitation.

Wider implications of the findings

The results showed that our model tended to classify the embryos as aneuploid. More euploid embryos would be necessary to train our model and achieve better results in the prediction of chromosomally normal embryos. Further studies with large number of embryos and additional variables could improve the non-invasive ploidy prediction.

Trial registration number

not applicable

P–135 Artificial neural networks (ANNs) for live birth prediction in frozen embryo transfers: the strength of post-warmed blastocyst dynamics

Study question

Does the post-warmed blastocyst dynamics have an impact over the likelihood of achieving a live birth?

Summary answer

Variables related to dynamics of vitrified/warmed blastocysts have shown a greater effect on the live birth prediction than only embryo morphological quality through artificial intelligence.

What is known already

Morphological dynamics of vitrified/warmed blastocysts were described by Coello et al., in 2017. The investigated markers were the thickness of zona pellucida (µm) and blastocysts area (µm2) after warming and before transfer, the area of the inner cell mass (µm2), time of initiation of reexpansion (in minutes), and presence of collapse or contraction. They found a correlation between blastocyst reexpansion and implantation rate and developed a hierarchical model for implantation prediction. In our study, we evaluated the post-warmed blastocyst dynamics for live birth prediction by using novel artificial intelligence techniques.

Study design, size, duration

This retrospective analysis included 415 vitrified/warmed blastocysts with known live birth data. Blastocysts after warming were placed in EmbryoScope (Vitrolife) immediately until embryo transfer. Embryo evaluation and selection were performed by senior embryologists according to fresh blastocyst morphology (before vitrification). Then, parameters related to post-warmed blastocyst dynamics were calculated. Finally, these variables and the embryo morphological grade before the vitrification were used as input data for ANNs optimized with genetic algorithm for live birth prediction.

Participants/materials, setting, methods

Blastocysts were vitrified and warmed by the Cryotop method (Kitazato,Biopharma). During the period between the warming procedure and the embryo transfer, the following variables were measured with the drawing tools provided by the EmbryoViewer workstation: zona pellucida thinning (µm), blastocyst expansion (um) and the speed of these two events (µm/h). Finally, multilayer perceptron neural networks were trained with data of 331 embryos by using the backpropagation learning algorithm and tested with data of 84 embryos.

Main results and the role of chance

We trained and tested three architectures of ANNs with different input variables as follows: post-warmed variables (thinning of the zona pellucida, blastocyst expansion, thinning speed and expansion speed) and morphological grade (A, B or C) for ANN1, only post-warmed variables for ANN2 and only morphological grade for ANN3. The highest success rate when ANNs classified embryos as positive and negative live birth (LB+ and LB-) was achieved by combining post-warmed variables and morphological grade before embryo vitrification. The general accuracies for the blind tests were: 73.8% for ANN1, 66.7% for ANN2 and 71.4% for ANN3. Likewise, this combination achieved the highest AUC on test dataset to predict LB- (0.76 for ANN1, 0.74 for ANN2 and 0.67 for ANN3). However, the ANN2 trained with only post-warmed variables showed the best capacity to predict LB+ with an AUC of 0.73 (versus 0.46 for ANN1 and 0.5 for ANN3).

Limitations, reasons for caution

The main limitation is the subjectivity of manual annotations, although only one embryologist participated in this task.

Wider implications of the findings: The dynamics of vitrified/warmed blastocysts prior to embryo transfer could be more relevant variables than the morphological quality on day 5 before the cryopreservation. The analysis of embryo behavior after warming could improve clinical outcomes in frozen embryo transfers.

Trial registration number

none

O-085 In-depth analysis of embryo development: Differences among monosomic, trisomic and chromosomally chaotic embryos compared to euploid embryos

Study question

Is there any visible variation in the development of aneuploid embryos depending on the type of chromosome abnormality?

Summary answer

There were significant visible differences in the development of euploid, monosomic, trisomic and, especially, chaotic embryos.

What is known already

Aneuploidy rates are remarkably high in in vitro fertilized human embryos, with up to 50% of embryos diagnosed as aneuploid based on preimplantation genetic testing for aneuploidies (PGT-A). However, very little is known about the impact of specific aneuploidies during the early human embryo development. A recent publication showed that embryos with single chromosomal gain or loss reached the blastocyst stage later or earlier depending on the chromosome affected (Shahbazi et al., 2020). In our study, we wanted to detect observable differences in embryo behavior between embryos with different chromosomal abnormalities during the entire in vitro development.

Study design, size, duration

This was a retrospective study including 2,500 blastocysts with PGT-A results. Embryos were cultured in EmbryoScope systems until the fifth/sixth day of development (up to the time of trophectoderm biopsy). Automatic-annotations for division times and quality gradings were supervised routinely by senior embryologists using Guided Annotations Tool. Out of the total, 1,000 were euploid embryos used for reference and 1,500 were aneuploid embryos with one or more defects, including monosomic, trisomic and chromosomally chaotic embryos.

Participants/materials, setting, methods

Chromosome analysis was performed using next-generation sequence technology. Then, an in-depth analysis of time-lapse videos and supervised-automatic annotations was performed. We calculated the proportion of embryos, in each aneuploid category, that reached one specific event later than the expected value for euploid embryos plus one standard deviation. Later, we calculated the “relative risk” of an embryo of reaching the milestone late. We did the same for the time between milestones and for pairs of milestones.

Main results and the role of chance

Every aneuploid category was more likely to reach each specific embryo developmental event later than euploid embryos and the time gaps between developmental milestones were also statistically longer in aneuploid embryos (p < 0.0001). The following results were the most interesting relative risks (RR) when we compared the proportion of embryos (in each aneuploid category) to the proportion of euploid embryos (RR for euploid = 1). For reaching the division time to two cells (t2): 1.31 in monosomic embryos, 1.50 in trisomic embryos and 2.43 in chaotic embryos. For the division time to four cells (t4): 1.42 in monosomic embryos, 1.54 in trisomic embryos and 3.07 in chaotic embryos. For the division time to eight cells (t8) and the time of starting blastulation: 1.45 in monosomic embryos, 1.22 in trisomic embryos and 2.74 in chaotic embryos. Combined milestones were stronger indicators than each milestone by itself, the RR were: 1.63 in monosomic embryos, 1.81 in trisomic embryos and 3.35 in chaotic embryos for t2 and t4; 1.50 in monosomic embryos, 1.80 in trisomic embryos and 2.84 in chaotic embryos for t2 and t8; 1.46 in monosomic embryos, 1.90 in trisomic embryos and 3.43 in chaotic embryos for t4 and t8.

Limitations, reasons for caution

At this stage, we did not go down to specific chromosome abnormality as there were very few cases in each fully detailed category. Also, not all the embryos reached every developmental milestone.

Wider implications of the findings

Aneuploid embryos were significantly different from euploid embryos in the first five days of development. A large proportion of aneuploid embryos could be rejected because their developmental milestones falling outside the normal range. This could form part of an automated system for determining euploidy/aneuploidy from observation of embryos in vitro.

Trial registration number

1902-VLC-018-MM

Structural analysis of Drosophila subobscura gypsy elements (gypsyDs)

The study of gypsy elements in Drosophila subobscura (gypsyDs) indicated that they are transcriptionally active and mobile. From the comparative analysis of a complete gypsyDs element with the canonical gypsy sequence from D. melanogaster (gypsyDm) it can be deduced that while the whole structure is maintained, the gypsyDs ORF3 encodes a non-functional Env protein. The PCR amplification and sequencing of the ORF3 from different laboratory strains and H271 clones show that all gypsyDs sequences studied have frame-shifting mutations in this region. These results support that gypsyDs elements lack functional Env proteins and consequently they lack infective ability. In this way, it can be proposed that gypsyDs elements are degenerate forms of insect retroviruses. Heterogeneous results have been obtained in the study of the presence of gypsyDm sequences in different D. subobscura strains indicating that these sequences are unstable in this species.