Selecting embryos with the highest implantation potential using data mining and decision tree based on classical embryo morphology and morphokinetics

Artificial intelligence and porcine breeding

Livestock management is evolving into a new era, characterized by the analysis of vast quantities of data (Big Data) collected from both traditional breeding methods and new technologies such as sensors, automated monitoring system, and advanced analytics. Artificial intelligence (A-In), which refers to the capability of machines to mimic human intelligence, including subfields like machine learning and deep learning, is playing a pivotal role in this transformation. A wide array of A-In techniques, successfully employed in various industrial and scientific contexts, are now being integrated into mainstream livestock management practices. In the case of swine breeding, while traditional methods have yielded considerable success, the increasing amount of information requires the adoption of new technologies such as A-In to drive productivity, enhance animal welfare, and reduce environmental impact. Current findings suggest that these techniques have the potential to match or exceed the performance of traditional methods, often being more scalable in terms of efficiency and sustainability within the breeding industry. This review provides insights into the application of A-In in porcine breeding, from the perspectives of both sows (including welfare and reproductive management) and boars (including semen quality and health), and explores new approaches which are already being applied in other species.

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.

Knowledge-embedded spatio-temporal analysis for euploidy embryos identification in couples with chromosomal rearrangements

BACKGROUND

The goal of the assisted reproductive treatment is to transfer one euploid blastocyst and to help infertile women giving birth one healthy neonate. Some algorithms have been used to assess the ploidy status of embryos derived from couples with normal chromosome, who subjected to preimplantation genetic testing for aneuploidy (PGT-A) treatment. However, it is currently unknown whether artificial intelligence model can be used to assess the euploidy status of blastocyst derived from populations with chromosomal rearrangement.

METHODS

From February 2020 to May 2021, we collected the whole raw time-lapse videos at multiple focal planes from in vitro cultured embryos, the clinical information of couples, and the comprehensive chromosome screening results of those blastocysts that had received PGT treatment. Initially, we developed a novel deep learning model called the Attentive Multi-Focus Selection Network (AMSNet) to analyze time-lapse videos in real time and predict blastocyst formation. Building upon AMSNet, we integrated additional clinically predictive variables and created a second deep learning model, the Attentive Multi-Focus Video and Clinical Information Fusion Network (AMCFNet), to assess the euploidy status of embryos. The efficacy of the AMCFNet was further tested in embryos with parental chromosomal rearrangements. The receiver operating characteristic curve (ROC) was used to evaluate the superiority of the model.

RESULTS

A total of 4112 embryos with complete time-lapse videos were enrolled for the blastocyst formation prediction task, and 1422 qualified blastocysts received PGT-A ( n = 589) or PGT for chromosomal structural rearrangement (PGT-SR, n = 833) were enrolled for the euploidy assessment task in this study. The AMSNet model using seven focal raw time-lapse videos has the best real-time accuracy. The real-time accuracy for AMSNet to predict blastocyst formation reached above 70% on the day 2 of embryo culture, and then increased to 80% on the day 4 of embryo culture. Combing with 4 clinical features of couples, the AUC of AMCFNet with 7 focal points increased to 0.729 in blastocysts derived from couples with chromosomal rearrangement.

CONCLUSION

Integrating seven focal raw time-lapse images of embryos and parental clinical information, AMCFNet model have the capability of assessing euploidy status in blastocysts derived from couples with chromosomal rearrangement.

Altered morphokinetics and differential reproductive outcomes associated with cell exclusion events in human embryos

RESEARCH QUESTION

Can embryos harbouring cell exclusion and their reproductive outcomes be classified based on morphokinetic profiles?

DESIGN

A total of 469 time-lapse videos of embryos transferred between 2013 and 2019 from a single clinic were analysed. Videos were assessed and grouped according to the presence or absence of one or more excluded cells before compaction. Cell division timings, intervals between subsequent cell divisions and dynamic intervals were analysed to determine the morphokinetic profiles of embryos with cell exclusion (CE+), compared with fully compacted embryos without cell exclusion or extrusion (CE-).

RESULTS

Transfer of CE+ embryos resulted in lower proportions of fetal heartbeat (FHB) and live birth compared with CE- embryos (both, P < 0.001). CE+ embryos were associated with delays in t2 (P = 0.030), t6 (P = 0.018), t7 (P < 0.001), t8 (P = 0.001), tSC (P < 0.001) and tM (P < 0.001). Earlier timings for t3 (P = 0.014) and t5 (P < 0.001) were positively associated with CE+; CE+ embryos indicated prolonged S2, S3, ECC3, cc2 and cc4. Logistic regression analysis revealed that t5, tM, S2 and ECC3 were the strongest predictive indicators of cell exclusion. Timings for S2 and ECC3 were useful in identifying increased odds of FHB when a cell exclusion event was present.

CONCLUSION

Embryos harbouring cell exclusion indicated altered morphokinetic profiles. Their overall lower reproductive success was associated with two morphokinetic parameters. Morphokinetic profiles could be used as adjunct indicators for reproductive success during cycles producing few, low-quality embryos. This may allow more objective identification of cell exclusion and refinement of embryo ranking procedures before transfer.

Embryo ploidy status classification through computer-assisted morphology assessment

BACKGROUND

Preimplantation genetic testing for aneuploidy has been proven to be effective in determining the embryo's chromosomal or ploidy status. The test requires a biopsy of embryonic cells on day 3, 5, or 6 from which complete information on the chromosomes would be obtained. The main drawbacks of preimplantation genetic testing for aneuploidy include its relatively invasive approach and the lack of research studies on the long-term effects of preimplantation genetic testing for aneuploidy.

OBJECTIVE

Computer-assisted predictive modeling through machine learning and deep learning algorithms has been proposed to minimize the use of invasive preimplantation genetic testing for aneuploidy. The capability to predict morphologic characteristics of embryo ploidy status creates a meaningful support system for decision-making before further treatment.

STUDY DESIGN

Image processing is a component in developing a predictive model specialized in image classification through which a model is able to differentiate images based on unique features. Image processing is obtained through image augmentation to capture segmented embryos and perform feature extraction. Furthermore, multiple machine learning and deep learning algorithms were used to create prediction-based modeling, and all of the prediction models undergo similar model performance assessments to determine the best model prediction algorithm.

RESULTS

An efficient artificial intelligence model that can predict embryo ploidy status was developed using image processing through a histogram of oriented gradient and then followed by principal component analysis. The gradient boosting algorithm showed an advantage against other algorithms and yielded an accuracy of 0.74, an aneuploid precision of 0.83, and an aneuploid predictive value (recall) of 0.84.

CONCLUSION

This research study proved that machine-assisted technology perceives the embryo differently than human observation and determined that further research on in vitro fertilization is needed. The study finding serves as a basis for developing a better computer-assisted prediction model.

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.

New frontiers in embryo selection

Human infertility is a major global public health issue estimated to affect one out of six couples, while the number of assisted reproduction cycles grows impressively year over year. Efforts to alleviate infertility using advanced technology are gaining traction rapidly as infertility has an enormous impact on couples and the potential to destabilize entire societies if replacement birthrates are not achieved. Artificial intelligence (AI) technologies, leveraged by the highly advanced assisted reproductive technology (ART) industry, are a promising addition to the armamentarium of tools available to combat global infertility. This review provides a background for current methodologies in embryo selection, which is a manual, time-consuming, and poorly reproducible task. AI has the potential to improve this process (among many others) in both the clinician's office and the IVF laboratory. Embryo selection is evolving through digital methodologies into an automated procedure, with superior reliability and reproducibility, that is likely to result in higher pregnancy rates for patients. There is an emerging body of data demonstrating the utility of AI applications in multiple areas in the IVF laboratory. AI platforms have been developed to evaluate individual embryologist performance; to provide quality assurance for culture systems; to correlate embryologist's assessments and AI systems; to predict embryo ploidy, implantation, fetal heartbeat, and live birth outcome; and to replace the current "analogue" system of embryo selection with a digital paradigm. AI capability will distinguish high performing, high profit margin, low-cost, and highly successful IVF clinic business models. We think it will become the standard, "new normal" in IVF labs, as rapidly and thoroughly as vitrification, blastocyst culture, and intracytoplasmic sperm injection replaced their predecessor technologies. At the time of this review, the AI technology to automate embryo evaluation and selection has robustly matured, and therefore, it is the main focus of this review.

Mitochondrial DNA copy number in cumulus granulosa cells as a predictor for embryo morphokinetics and chromosome status

While morphokinetic evaluation of embryos has become the most commonly used technique in IVF to select embryos for transfer, studies have demonstrated that mitochondrial DNA (mtDNA) copy number is correlated with embryo viability and transfer outcomes. Correspondingly, this cohort study aims to evaluate the association between the mtDNA copy number in cumulus granulosa cells (CGCs) with embryo morphokinetic parameters and chromosomal status. Real-time PCR was employed to measure the mtDNA copy number of the 129 CGCs in samples obtained from 30 patients undergoing the IVF-IMSI program at Morula IVF Jakarta between July and October 2020. Bivariate and multiple analyses were utilized to determine its relationship with embryo morphokinetics, blastocyst yield, and chromosomal status. According to the analysis, there was a significant correlation between the mtDNA copy number and the blastocyst status after adjusting for the maternal age and sperm morphology (coefficient 0.832, p value = 0.032, RR value 2.299). Moreover, a significant link was observed between mtDNA copy number in CGC and early embryo developmental phase M1 (t2-t8), using the equation of M1 is 5.702-0.271 mtDNA copy number of CGCs + 0.017 maternal age + 0.013 sperm motility -0.115 sperm morphology (p value = 0.032). However, no correlation was found between the mtDNA copy number in CGCs with the other morphokinetic parameters (M2: tC-tEB, M3: t2-tEB, DC, RC, MN with p > 0.05), or the chromosomal status of the embryos (euploid: 139.44 ± 133.12, aneuploid: 142.40 ± 111.30, p = 0.806). In conclusion, our study suggests that mtDNA copy number in CGCs can serve as a useful biomarker for blastocyst status and early embryo developmental phase but not for chromosomal status.

Embryo Morphokinetic Activity Evident in Short Videos of In Vitro Bovine Embryos

Embryo transfer (ET) and in vitro fertilization (IVF) are increasing in use by dairy producers as a means to breed their animals as these assisted reproductive techniques can optimize the genetics of the dairy breed or enable “beef on dairy” programs to increase the profitability of the dairy. Due to the advantages of ET and IVF, it is anticipated that their use will continue to increase despite the status of underwhelmingly low pregnancy outcomes. Pregnancy rates of bovine ET/IVF remain below 56%, with many dairy producers implementing beef on dairy programs reporting pregnancy to be lower than 23%. The inability to objectively evaluate embryo health prior to transfer into a recipient is a contributing factor to this problem as 20% of transferred embryos are inviable at the time of transfer and have little chance of establishing a pregnancy. The objective of this research was to evaluate bovine embryo real-time morphokinetic activity based on 30 s video recordings of day 7.5 morulas and correlate morphokinetic activity to developmental outcomes. Eighty-eight embryos were recorded in standard embryo culture conditions with an SMZ-1000 Stereo zoom microscope and TE-300 Nikon inverted microscope. The difference in the embryo’s morphokinetic activity was measured frame-by-frame and correlated to embryo hatching outcomes. It was found that embryos with lower morphokinetic activity demonstrated higher hatching rates and developmental outcomes, suggesting measurement of embryo morphokinetic activity is a noninvasive and non-subjective method to evaluate embryo competency prior to transfer and can be used to improve the reproductive efficiency and profitability of IVF/ET of dairy cattle.

PTEN expression in human cumulus cells is associated with embryo development competence

Embryo quality determines the success of in vitro fertilization and embryo transfer (IVF-ET) treatment. Biomarkers for the evaluation of embryo quality have some limitations. Apoptosis in cumulus cells (CCs) is important for ovarian function. PTEN (phosphatase and tensin homolog) is a well known tumour suppressor gene that functions as a mediator of apoptosis and is crucial for mammalian reproduction. In the present study, we analyzed the expression level of PTEN in human CCs and aimed to investigate its association with embryo developmental competence in IVF treatment cycles. The PTEN mRNA level in CCs was measured using real-time fluorescence quantitative PCR. The association of the differential expression of PTEN with embryo quality was analyzed. Our data showed that PTEN mRNA levels were significantly decreased in CCs surrounding mature oocytes compared with immature oocytes. Similar changes were found in the analysis of fertilization and blastocyst formation. The speculation that the measurement of PTEN mRNA levels in human CCs would provide a useful tool for selecting oocytes with greater chances to implant into the uterus needs to be further verified through single-embryo transfer in the future. The proapoptotic mechanism of PTEN in human reproduction needs to be further studied.

Prediction of embryo implantation rate using a sole parameter of timing of starting blastulation

A time-lapse monitoring system provides a complete picture of the dynamic embryonic development process and simultaneously supplies extensive morphokinetic data. The objective of this study was to investigate whether the use of the morphokinetic parameter of time of starting blastulation (tSB) can improve the implantation rate of day-5 transferred blastocyst selected based on morphological parameters. In this retrospective study we analyzed the morphokinetics of 196 day-5 transferred blastocysts, selected solely based on morphological parameters. The interval time from intracytoplasmic sperm injection (ICSI) to time of starting blastocyst formation (tSB) was calculated for each embryo. The overall implantation rate of transferred blastocyst, selected based only on morphological parameters, was 49.2%. Implantation rate, determined retrospectively, was significantly higher (58.8% versus 42.6%, P = 0.02) for embryos with a short interval time to tSB (78-95.9 h) compared with embryos with a longer timeframe (96-114 h). Time of expanded blastocyst (tEB) post-ICSI was also significantly associated with implantation; however, this parameter was not available for all the embryos at time of transfer. When we tested only high ranked KIDScore day-3 sub-group embryos, the implantation rate was significantly higher in short interval time embryos compared with longer interval time embryos (62.2% vs. 45.5%, respectively, P = 0.02).These observations emphasize the importance of the timing of starting blastulation over blastocyst morphological parameters and may provide a preferable criterion for good morphology day-5 blastocyst selection.

Silencing mark H3K27me3 is differently reprogrammed in bovine embryos with distinct kinetics of development

The kinetics of the first cleavages is a predictor of blastocyst development and implantation. For bovine embryos, this attribute was previously related to distinct metabolic, molecular and epigenetic profiles, including DNA and histone modifications. In the present work, we described the dynamics of trimethylation of lysine 27 on histone H3 (H3K27me3) in fast and slow developing embryos and verified if this epigenetic mark was also influenced by the speed of the first cleavages. In vitro-produced bovine embryos were classified as fast (4 or more cells) or slow (2 cells) at 40 hr post fertilization (hpf) and either collected or cultured until 96 hpf or 186 hpf. Immunofluorescence analysis was performed in these three time points and showed that although both groups presented the same levels of H3K27me3 at 40 hpf, slow embryos presented a pronounced increase in this mark at 186 hpf when compared to fast embryos, resulting in blastocysts with remarkable differences in H3K27me3 levels. In conclusion, the increased levels of this repressive histone post-translation modification (PTM) might be an attempt of slow embryos to promote gene expression control and chromatin integrity, since it was already reported that these embryos present reduced levels of other epigenetic repressive marks as DNA methylation and trimethylation of lysine 9 on histone H3 (H3K9me3).

Artificial intelligence in the embryology laboratory: a review

The goal of an IVF cycle is a healthy live-born baby. Despite the many advances in the field of assisted reproductive technologies, accurately predicting the outcome of an IVF cycle has yet to be achieved. One reason for this is the method of selecting an embryo for transfer. Morphological assessment of embryos is the traditional method of evaluating embryo quality and selecting which embryo to transfer. However, this subjective method of assessing embryos leads to inter- and intra-observer variability, resulting in less than optimal IVF success rates. To overcome this, it is common practice to transfer more than one embryo, potentially resulting in high-risk multiple pregnancies. Although time-lapse incubators and preimplantation genetic testing for aneuploidy have been introduced to help increase the chances of live birth, the outcomes remain less than ideal. Utilization of artificial intelligence (AI) has become increasingly popular in the medical field and is increasingly being leveraged in the embryology laboratory to help improve IVF outcomes. Many studies have been published investigating the use of AI as an unbiased, automated approach to embryo assessment. This review summarizes recent AI advancements in the embryology laboratory.

Ionophore application for artificial oocyte activation and its potential effect on morphokinetics: a sibling oocyte study

PURPOSE

To evaluate whether ionophore application at the oocyte stage changes the morphokinetics of the associated embryos in cases of artificial oocyte activation.

METHODS

In a prospective sibling oocyte approach, 78 ICSI patients with suspected fertilization problems had half of their MII-oocytes treated with a ready-to-use ionophore (calcimycin) immediately following ICSI (study group). Untreated ICSI eggs served as the control group. Primary analyses focused on morphokinetic behavior and the presence of irregular cleavages. The rates of fertilization, utilization, pregnancy, and live birth rate were also evaluated.

RESULTS

Ionophore-treated oocytes showed a significantly earlier formation of pronuclei (t2PNa) and a better synchronized third cell cycle (s3) (P < .05). The rate of irregular cleavage was unaffected (P > .05). Ionophore treatment significantly improved the overall rates of fertilization (P < .01) and blastocyst utilization (P < .05).

CONCLUSION

Ionophore application does not negatively affect cleavage timing nor is it associated with irregular cleavage.

Change in the Strategy of Embryo Selection with Time-Lapse System Implementation-Impact on Clinical Pregnancy Rates

Time-lapse systems (TLS) and associated algorithms are interesting tools to improve embryo selection. This study aimed to evaluate how TLS and KIDScore™ algorithm changed our practices of embryo selection, as compared to a conventional morphological evaluation, and improved clinical pregnancy rates (CPR). In the study group (year 2020, n = 303 transfers), embryos were cultured in an EmbryoScope+ time-lapse incubator. A first team observed embryos conventionally once a day, while a second team selected the embryos for transfer based on time-lapse recordings. In the control group (year 2019, n = 279 transfers), embryos were selected using the conventional method, and CPR were recorded. In 2020, disagreement between TLS and the conventional method occurred in 32.1% of transfers, more often for early embryos (34.7%) than for blastocysts (20.5%). Irregular morphokinetic events (direct or reverse cleavage, multinucleation, abnormal pronuclei) were detected in 54.9% of the discordant embryos. When it was available, KIDScore™ was decreased for 73.2% of the deselected embryos. Discordant blastocysts mainly corresponded with a decrease in KIDScore™ (90.9%), whereas discordant Day 3 embryos resulted from a decreased KIDScore™ and/or an irregular morphokinetic event. CPR was significantly improved in the TLS group (2020), as compared to the conventional group (2019) (32.3% vs. 21.9%, p = 0.005), even after multivariate analysis. In conclusion, TLS is useful to highlight some embryo development abnormalities and identify embryos with the highest potential for pregnancy.

A machine learning system with reinforcement capacity for predicting the fate of an ART embryo

The aim of this work was to construct a score issued from a machine learning system with self-improvement capacity able to predict the fate of an ART embryo incubated in a time lapse monitoring (TLM) system. A retrospective study was performed. For the training data group, 110 couples were included and, 891 embryos were cultured. For the global setting data group, 201 couples were included, and 1186 embryos were cultured. No image analysis was used; morphokinetic parameters from the first three days of embryo culture were used to perform a logistic regression between the cell number and time. A score named DynScore was constructed, the prediction power of the DynScore on blastocyst formation and the baby delivery were tested via the area under the curve (AUC) obtained from the receiver operating characteristic (ROC). In the training data group, the DynScore allowed the blastocyst formation prediction (AUC = 0.634, p < 0.001), this approach was the higher among the set of the tested scores. Similar results were found with the global setting data group (AUC = 0.638, p < 0.001) and it was possible to increase the AUC of the DynScore with a regular update of the prediction system by reinforcement, with an AUC able to reach a value above 0.9. As only the best blastocysts were transferred, none of the tested scores was able to predict delivery. In conclusion, the DynScore seems to be able to predict the fate of an embryo. The reinforcement of the prediction system allows maintaining the predictive capacity of DynScore irrespective of the various events that may occur during the ART process. The DynScore could be implemented in any TLM system and adapted by itself to the data of any ART center.Abbreviations: ART: assisted reproduction technology; TLM: time lapse monitoring system; AUC: area under the curve; ROC: receiver operating characteristic; eSET: elective single embryo transfer; AIS: artificial intelligence system; KID: known implantation data; AMH: anti-Müllerian hormone; BMI: body mass index; WHO: World Health Organization; c-IVF: conventional in-vitro fertilization; ICSI: intracytoplasmic sperm injection; PNf: pronuclear formation; D3: day 3; D5: day 5; D6: day 6; GnRH: gonadotrophin releasing hormone; FSH: follicle stimulating hormone; LH: luteinizing hormone; hCG: human chorionic gonadotropin; PVP: polyvinyl pyrrolidone; PNf: time of pronuclear fading; tx: time of cleavage to x blastomeres embryo; ICM: inner cell mass; TE: trophectoderm; NbCell_t: number of cells at t time; FIFO: first in first out; TD: training data group; SD: setting data group; R: real world.

The optimal number of embryo cells for effective pregnancy and decrease of multiple pregnancy rate in frozen-thawed embryo transfer

To investigate the effect of the number of embryo cells on the clinical outcome of frozen-thawed embryo transfer and explore the optimal policy for decreases of multiple pregnancy rate, patients who experienced day 3 vitrified double frozen-thawed embryo transfer were retrospectively analyzed. According to the number of embryonic cells in each pre-frozen embryo, the patients were divided into six groups: 8C₂ (two 8-cell embryos), 8C₁- < 8C₁ (one 8-cell embryo and one under-8-cell embryo), 8C₁- > 8C₁ (one 8-cell embryo and one over-8-cell embryo), < 8C₂ (two under-8-cell embryos), < 8C₁- > 8C₁ (one under-8-cell embryo and one over-8-cell embryo), and > 8C₂ (two over-8-cell embryos). The clinical data were analyzed. The classification decision tree was used to analyze the optimal transfer strategy. A total of 2184 cycles of day 3 vitrified double frozen-thawed embryo transfer were enrolled. In day 3 double frozen-thawed embryo cycles, the 8C₂ group and 8C₁- > 8C₁ group had significantly (P < 0.05) higher pregnancy and multiple pregnancy rates than the other groups. No significant (P > 0.05) difference existed in the pregnancy rate and live birth rate between the 8C₁- < 8C₁ group, 8C₂ group and 8C₁- > 8C₁ group, but the implantation rate and multiple pregnancy rate in the 8C₁- < 8C₁ group were significantly (P < 0.05) lower than in the other two groups. Compared with the multiple pregnancy rate of all cycles, the cycles in two branches showed significantly (P < 0.05) higher multiple pregnancy rates (≤ 29 years old: 8C₂ / 8C₁- > 8C₁; 29 < age ≤ 36 years for the first transfer: 8C₂ / 8C₁- < 8C₁ / 8C₁- > 8C₁, one branch showed similar rate (≤ 29 years old: 8C₂ / 8C₁- > 8C₁) for the first transfer, and the remaining four branches demonstrated significantly (P < 0.05) lower rates. The clinical pregnancy rates before and after optimization were 51.0% vs 50.5%, and the multiple pregnancy rates were 38.5% vs 16.9%. In conclusion, the number of pre-frozen embryonic cells is an important factor affecting the clinical outcome of frozen-thawed embryo transfer in day 3 double good embryos frozen-thawed cycles. The age of patient, number of embryo cells, and the first time of transfer are the most valuable parameters for prediction. For women ≤ 29 years old, the single embryo transfer (SET) strategy was to choose an embryo ≥ 8 cells, and for women with < 29 age ≤ 36 years old, the SET strategy in the first transfer was to choose an embryo ≥ 8 cells.

Morphokinetics of embryos after IMSI versus ICSI in couples with sub-optimal sperm quality: A time-lapse study

An investigation was conducted to determine the influence of two sperm selection modalities, IMSI and ICSI, on the morphokinetics, dynamic development and ploidy status of embryos derived from males with sub-optimal sperm profiles during IVF program. A total of 209 PGTA-tested top-quality blastocysts (IMSI = 129, ICSI = 80) from 84 couples (IMSI = 51, ICSI = 33) were assessed retrospectively. This study found that both IMSI and ICSI yielded comparable embryo morphokinetics, except for the T7, TEB and CC3 parameters (p < 0.05). A significant lower incidence of multinucleation was observed in the IMSI group when compared to the ICSI group (48.8% vs. 71.3%, p = 0.002), while other parameters of embryo development such as direct cleavage, distorted cytoplasmic movement, reverse cleavage and vacuole(s) appearance did not differ (p > 0.05). No differences were noticed in the proportion of generating chromosomally euploid embryos (44.2% vs. 51.3%, p = 0.394, respectively, for IMSI and ICSI). The implementation of IMSI or ICSI in couples with sub-optimal sperm profiles resulted in embryos with comparatively similar morphokinetics. Furthermore, the incidence of multinucleation at the two- to four-cell stage was lower following the practice of IMSI, although the method did not improve the proportion of gaining euploid embryos.

Association between early embryo morphokinetics plus transcript levels of sperm apoptotic genes and clinical outcomes in IMSI and ICSI cycles of male factor patients

PURPOSE

The aim was to assess the correlation of sperm apoptotic transcript levels with cleavage stage embryokinetic and pregnancy outcomes of intracytoplasmic morphologically selected sperm injection (IMSI) and ICSI methods in patients with male factor infertility.

MATERIAL AND METHODS

Eighty male factor cases were divided into ICSI and IMSI groups. ICSI was done routinely, and for IMSI, sperm was selected at high magnification and injected. On day 3, time-lapse parameters were evaluated, and the best embryos were transferred and followed to delivery. In addition, sperm DNA fragmentation and apoptotic transcript levels were quantified using reverse transcription Q-PCR between the groups.

RESULTS

IMSI selected spermatozoa had lower DNA fragmentation and apoptotic transcript levels compared with ICSI (p < 0.0001). Moreover, all cytokinetic variables and cleavage abnormalities were noticeably different between groups (p < 0.0001); the rates of clinical outcomes were higher in the IMSI group. The transcript levels of Caspase 3 showed a moderate negative correlation with s2 and s3 (rs = - 0.57, P = 0.008 and rs = - 0.51, p = 0.021, respectively) in the IMSI group. However, there was no relationship between sperm apoptotic transcript levels and clinical outcomes in two groups.

CONCLUSIONS

Sperms selected at high magnification showed lower DNA fragmentation and apoptosis genes transcript. Also, better embryo kinetics and clinical outcomes were confirmed in IMSI than ICSI groups. Some time-lapse parameters may be associated with transcript levels of apoptosis genes. Therefore, these noninvasive techniques may be unique in assisting couples with male factor infertility.

TRIAL REGISTRATION

This trial retrospectively registered on 4 July 2020 (IRCT20180130038561N1).

Can novel early non-invasive biomarkers of embryo quality be identified with time-lapse imaging to predict live birth?

STUDY QUESTION

Can time-lapse imaging systems make it possible to identify novel early non-invasive biomarkers to predict live birth?

SUMMARY ANSWER

From mostly high-grade embryos, out of 35 morphometric, morphologic and morphokinetic variables, only pronuclei (PN) position at time of PN juxtaposition and the absence of multinucleated blastomeres at the 2-cell stage (MNB2cell), were potentially associated with live birth.

WHAT IS KNOWN ALREADY

Previous studies indicate that some kinetic markers may be predictive of blastocyst development and embryonic implantation. Certain teams have suggested including some of them in decisional algorithms for embryo transfers.

STUDY DESIGN, SIZE, DURATION

Using a time-lapse incubator (EmbryoScope, Unisense FertiliTech), we retrospectively explored the associations between the morphometric, morphologic and morphokinetic parameters of oocytes, zygotes and embryos, and their associations with live birth. This study assessed 232 embryos from single embryo transfers after ICSI cycles performed between January 2014 and December 2017.

PARTICIPANTS/MATERIALS, SETTING, METHODS

The morphometric, morphologic and morphokinetic parameters (18, 4 and 13, respectively) of oocytes, zygotes and early embryos were studied retrospectively. The associations between these parameters were examined using a Spearman's correlation, Mann-Whitney or chi-squared test as appropriate. We examined whether these parameters were associated with outcomes in univariate and multivariate logistic regression analyses.

MAIN RESULTS AND THE ROLE OF CHANCE

Central PN juxtaposition was associated with a 2-fold increase in the odds of live birth (OR = 2.20; 95% CI, [1.26-3.89]; P = 0.006), while the presence of MNB2cell was associated with half the odds of live birth (OR = 0.51; 95% CI, [0.27-0.95]; P = 0.035). These two parameters were independent of embryo kinetics. The 33 remaining parameters had no significant association with the capacity of transferred embryos to develop to term.

LIMITATIONS, REASONS FOR CAUTION

Even though the population size was relatively small, our analyses were based on homogeneous cycles, i.e. young women whose transferred embryos were found to be high-grade according to conventional morphology evaluation. In addition, our conclusions were established from a specific, highly selected population, so other study populations, such as women in an older age bracket, may yield different results. Finally, because we assessed day 2/3 transfers, our findings cannot be generalized to embryos cultured up to the blastocyst stage.

WIDER IMPLICATIONS OF THE FINDINGS

It would be interesting to explore, prospectively, whether PN localisation is a relevant measure to predict embryo development when added into further algorithms and whether this parameter could be suitable for use in other IVF clinics. Further studies are needed, notably to explore the added value of timing evaluation in cohorts of embryos with low or intermediate morphology grade, as well as in other maternal populations (i.e. older women).

STUDY FUNDING/COMPETING INTEREST(S)

No external funding was used for this study. P. Sagot received funding from the following commercial companies: Merck Serono, Finox Biotech, Ferring, MSD France SAS, Teva Sante ́ SAS, Allergan France, Gedeon Richter France, Effik S.A., Karl Storz Endoscopie France, GE Medical Systems SCS, Laboratoires Genevrier, H.A.C. Pharma and Ipsen.All the authors confirm that none of this funding was used to support the research in this study. There are no patents, products in development or marketed products to declare. This does not alter the authors' adherence to all the journal policies on sharing data and materials.

Generation of viable blastocysts from discarded human cleavage embryos

Background

While a relationship between embryo morphology, developmental ability, and genetic integrity exists, the selection of embryos with higher implantation potential remains a major challenge in assisted reproductive technology (ART). This study investigated blastocyst developmental competence and euploidy status in human embryos that had been classed as too poor quality to transfer (ET) or cryopreserve at the cleavage stage.

Embryos were divided into three groups. Group 1 (n = 41) included good quality embryos from candidates of preimplantation genetic testing for aneuploidy (PGT-A). Groups II and III were the “rejected” supernumerary embryos, defined as suboptimal for ET or vitrification after morphological examination, with embryos randomly divided between the groups. Group II embryos (n = 31) were cultured up to the day 3 cleavage stage, when they were biopsied and fixed. Group III embryos (n = 27) were cultured up to the day 5 blastocyst stage, when they were evaluated for morphology and chromosomal status. Chromosomal status in all groups was assessed by multi-color fluorescence in situ hybridization (FISH) for chromosomes 13, 18, 21, X, and Y.

Results

Euploidy rates in groups I, II, and III were 56.1%, 38.7%, and 55.5 %, respectively. Among the blastocysts that developed from “rejected” embryos, 59.3% were classed as good quality. The most frequent chromosomal aneuploidy was related to the sex chromosome (22.2%). The mosaicism rate was not significantly different between the group II and III embryos (25.8% vs. 37.0%, p = 0.28).

Conclusion

In conclusion, surplus poor-quality embryos rejected from clinical utilization at the cleavage stage may develop into viable blastocysts with normal chromosomal status for at least 5 chromosomes. Recovery of euploidy during poor-quality embryo transition from cleavage stage to blastocyst could provide an alternative choice for ET.

Morphokinetics and in vitro developmental potential of monopronucleated ICSI zygotes until the blastocyst stage

The aim of this study was to provide a more comprehensive understanding of 1PN intracytoplasmic sperm injection (ICSI) zygotes. To achieve this objective, we assessed whether all 1PN-derived embryos showed a similar morphokinetic pattern, and if the morphokinetic behaviour of 1PN-derived embryos was comparable with that of 2PN-derived embryos. In total, 149 1PN ICSI zygotes (study group) and 195 2PN ICSI zygotes (control group) were included in the study. Embryo development potential was evaluated in terms of blastocyst rate. Morphokinetic parameters, including the pronucleus diameter and kinetics of in vitro development, were also analyzed. Embryos derived from 1PN ICSI zygotes showed impaired development compared with 2PN-derived embryos, with blastocyst rates of 28.9% and 67.2%, respectively. The diameter of the pronucleus of 1PN zygotes was larger than that of 2PN zygotes. When compared with 2PN-derived embryos, those derived from 1PN zygotes had a visible pronucleus for a shorter time, in addition to a longer syngamy time and slower kinetic behaviour from two to nine cells. When 1PN-derived blastocysts and 2PN-derived blastocysts were compared, the developmental kinetics were similar in both groups, except for a delayed and longer duration of the compaction phase in 1PN-derived embryos. In conclusion, monopronucleated ICSI zygotes present differences in developmental capacity and morphokinetic behaviour compared with 2PN ICSI zygotes, showing particular morphokinetic parameters related to pronucleus formation. Only the 1PN ICSI-derived embryos that reached the blastocyst stage have similar morphokinetic development to blastocysts from 2PN zygotes.

Deconstructing the myth of poor prognosis for fast-cleaving embryos on day 3. Is it time to change the consensus?

PURPOSE

To determine the developmental competence of fast-cleaving D3 embryos.

METHODS

Retrospective study including 4028 embryos from 513 PGT-A cycles performed between July 2014 and June 2017. Embryos were cultured in time-lapse incubators and biopsied at blastocyst stage. Embryos were classified in groups according to the number of cells on D3 (from 2-cell to ≥13 -cell and compacted). A generalized linear mixed model adjusted for confounding factors was performed to assess the chance to give rise to an euploid blastocyst in each group compared with the chance of 8-cell embryos. Implantation and live birth rates were also analyzed.

RESULTS

The statistical analysis showed that embryos with 9 to 11 cells had a slightly lower euploid blastocyst rate than 8-cell embryos (OR (95% CI) 0.77 (0.61-0.96)) while embryos with more than 11 cells were found to be just as likely to give rise to an euploid blastocyst as the 8-cell embryos (OR (95% CI) 1.20 (0.92-1.56)). Conversely, slow-cleaving embryos had a significantly lower euploid blastocyst rate than 8-cell embryos (OR (95% CI) 0.31 (0.24-0.39)). Moreover, euploid blastocysts derived from fast-cleaving embryos and from 8-cell embryos exhibit similar live birth rates. No significant differences were found in the chance to give rise a live birth between 8-cell and 9- to 11-cell embryos (OR (95% CI) 1.23 (0.70-2.15)) and > 11-cell embryos (OR (95% CI) 1.09 (0.57-2.09)).

CONCLUSIONS

Embryos with more than 11 cells exhibit similar developmental competence to 8-cell embryos. Their poor prognosis should be reconsidered.

Artificial intelligence in reproductive medicine

Artificial intelligence (AI) has experienced rapid growth over the past few years, moving from the experimental to the implementation phase in various fields, including medicine. Advances in learning algorithms and theories, the availability of large datasets and improvements in computing power have contributed to breakthroughs in current AI applications. Machine learning (ML), a subset of AI, allows computers to detect patterns from large complex datasets automatically and uses these patterns to make predictions. AI is proving to be increasingly applicable to healthcare, and multiple machine learning techniques have been used to improve the performance of assisted reproductive technology (ART). Despite various challenges, the integration of AI and reproductive medicine is bound to give an essential direction to medical development in the future. In this review, we discuss the basic aspects of AI and machine learning, and we address the applications, potential limitations and challenges of AI. We also highlight the prospects and future directions in the context of reproductive medicine.

Deconstructing the myth of poor prognosis for fast-cleaving embryos on day 3. Is it time to change the consensus?

PURPOSE

To determine the developmental competence of fast-cleaving D3 embryos.

METHODS

Retrospective study including 4028 embryos from 513 PGT-A cycles performed between July 2014 and June 2017. Embryos were cultured in time-lapse incubators and biopsied at blastocyst stage. Embryos were classified in groups according to the number of cells on D3 (from 2-cell to ≥13 -cell and compacted). A generalized linear mixed model adjusted for confounding factors was performed to assess the chance to give rise to an euploid blastocyst in each group compared with the chance of 8-cell embryos. Implantation and live birth rates were also analyzed.

RESULTS

The statistical analysis showed that embryos with 9 to 11 cells had a slightly lower euploid blastocyst rate than 8-cell embryos (OR (95% CI) 0.77 (0.61-0.96)) while embryos with more than 11 cells were found to be just as likely to give rise to an euploid blastocyst as the 8-cell embryos (OR (95% CI) 1.20 (0.92-1.56)). Conversely, slow-cleaving embryos had a significantly lower euploid blastocyst rate than 8-cell embryos (OR (95% CI) 0.31 (0.24-0.39)). Moreover, euploid blastocysts derived from fast-cleaving embryos and from 8-cell embryos exhibit similar live birth rates. No significant differences were found in the chance to give rise a live birth between 8-cell and 9- to 11-cell embryos (OR (95% CI) 1.23 (0.70-2.15)) and > 11-cell embryos (OR (95% CI) 1.09 (0.57-2.09)).

CONCLUSIONS

Embryos with more than 11 cells exhibit similar developmental competence to 8-cell embryos. Their poor prognosis should be reconsidered.

Does polycystic ovary syndrome affect morphokinetics or abnormalities in early embryonic development?

OBJECTIVES

This study aimed to investigate whether oocyte retrieval from PCOS patients affects the morphokinetics or the incidence of abnormalities in early embryonic development, using time-lapse imaging analysis.

METHODS

This was a prospective study in total of 39 PCOS patients and 67 women with normal ovarian function, underwent a GnRH antagonist protocol of controlled ovarian stimulation and fertilization by ICSI. 402 zygotes from the PCOS group and 449 zygotes from the control group were observed by time-lapse monitoring for 48 h following sperm injection.

RESULTS

Patients with PCOS showed a significantly higher number of retrieved oocytes, and a significantly higher number of metaphase II oocytes per cycle than that of the non-PCOS group (18.85 ± 9.41 vs. 11.48 ± 5.51 and 14.97 ± 7.43 vs. 9.51 ± 4.7, respectively). However, oocyte maturation rate and morphologically assessed embryo quality did not differ between two groups. After 48 h of the embryo culture using time-lapse video recording, most of the embryos in both groups had reached the 4-cell stage (353/449 vs. 314/402 embryos). There were no significant differences between the control and PCOS group regarding the time-points of the successive events in early embryonic development from the appearance of 2 polar bodies to the 6-cell stage. However, the percentage of t2 stages which fell in "optimal range" (>24 h and ≤28 h) was significantly lower in the PCOS group than in the control group (37.8% vs. 48.1%, P = 0.004). The proportion of embryos manifesting abnormal fertility, multinucleation, direct cleavage and reverse cleavage were not significantly different between the two groups.

CONCLUSION

Our data indicated that PCOS does not affect the morphokinetics or incidence of abnormalities in early embryonic development.

Are computational applications the "crystal ball" in the IVF laboratory? The evolution from mathematics to artificial intelligence

Mathematics rules the world of science. Innovative technologies based on mathematics have paved the way for implementation of novel strategies in assisted reproduction. Ascertaining efficient embryo selection in order to secure optimal pregnancy rates remains the focus of the in vitro fertilization scientific community and the strongest driver behind innovative approaches. This scoping review aims to describe and analyze complex models based on mathematics for embryo selection, devices, and software most widely employed in the IVF laboratory and algorithms in the service of the cutting-edge technology of artificial intelligence. Despite their promising nature, the practicing embryologist is the one ultimately responsible for the success of the IVF laboratory and thus the one to approve embracing pioneering technologies in routine practice. Applied mathematics and computational biology have already provided significant insight into the selection of the most competent preimplantation embryo. This review describes the leap of evolution from basic mathematics to bioinformatics and investigates the possibility that computational applications may be the means to foretell a promising future for the IVF clinical practice.

Predictive factors for live birth after in vitro maturation of oocytes in women with polycystic ovary syndrome

OBJECTIVE

In vitro maturation (IVM) of human oocytes can be an alternative treatment option to conventional in vitro fertilization. Women with polycystic ovary syndrome (PCOS) are considered the classical candidates for IVM because of the associated ovarian morphology and because IVM diminishes the risk of developing ovarian hyperstimulation syndrome. The objective of this study was to identify predictive factors for live birth in a cohort of women with PCOS who underwent IVM.

METHODS

This retrospective study included 159 patients with PCOS who had IVM cycles in which single or double embryo transfer was performed. The IVM protocol included three days of gonadotropin ovarian stimulation and hCG priming when the leading follicle size was 10-12 mm. Collected cumulus-oocyte complexes were cultured for 24 h for maturation. Intracytoplasmic sperm injection (ICSI) was used for fertilization. Embryo transfer was performed two days after fertilization. Demographic and clinical parameters were analyzed with logistic regression to identify predictors for live birth.

RESULTS

The women's mean age was 27.4 years, the mean number of retrieved oocytes was 14, and the live birth rate was 34.6%. The logistic regression revealed the following significant factors for live birth: infertility duration (OR 0.9; 95% CI, 0.82-0.98), number of collected oocytes (OR 1.56; 95% CI, 1.01-3.2), embryo cell number (OR 2.1; 95% CI, 1.4-3.5), and embryo grade (OR 1.84; 95% CI, 1.13-4.2).

CONCLUSION

Infertility duration, oocyte number, embryo cell number, and embryo grade were the most significant predictors for live birth after IVM in PCOS patients. These prognostic factors can be used when planning treatment or counselling patients.