Improving embryo selection using a computer-automated time-lapse image analysis test plus day 3 morphology: results from a prospective multicenter trial

A novel machine-learning framework based on early embryo morphokinetics identifies a feature signature associated with blastocyst development

BACKGROUND

Artificial Intelligence entails the application of computer algorithms to the huge and heterogeneous amount of morphodynamic data produced by Time-Lapse Technology. In this context, Machine Learning (ML) methods were developed in order to assist embryologists with automatized and objective predictive models able to standardize human embryo assessment. In this study, we aimed at developing a novel ML-based strategy to identify relevant patterns associated with the prediction of blastocyst development stage on day 5.

METHODS

We retrospectively analysed the morphokinetics of 575 embryos obtained from 80 women who underwent IVF at our Unit. Embryo morphokinetics was registered using the Geri plus® time-lapse system. Overall, 30 clinical, morphological and morphokinetic variables related to women and embryos were recorded and combined. Some embryos reached the expanded blastocyst stage on day 5 (BL Group, n = 210), some others did not (nBL Group, n = 365).

RESULTS

The novel EmbryoMLSelection framework was developed following four-steps: Feature Selection, Rules Extraction, Rules Selection and Rules Evaluation. Six rules composed by a combination of 8 variables were finally selected, and provided a predictive power described by an AUC of 0.84 and an accuracy of 81%.

CONCLUSIONS

We provided herein a new feature-signature able to identify with an high performance embryos with the best developmental competence to reach the expanded blastocyst stage on day 5. Clear and clinically relevant cut-offs were identified for each considered variable, providing an objective tool for early embryo developmental assessment.

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

PURPOSE

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

METHODS

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

RESULTS

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

CONCLUSION

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

A clinical consensus-compliant deep learning approach to quantitatively evaluate human in vitro fertilization early embryonic development with optical microscope images

The selection of embryos is a key for the success of in vitro fertilization (IVF). However, automatic quality assessment on human IVF embryos with optical microscope images is still challenging. In this study, we developed a clinical consensus-compliant deep learning approach, named Esava (Embryo Segmentation and Viability Assessment), to quantitatively evaluate the development of IVF embryos using optical microscope images. In total 551 optical microscope images of human IVF embryos of day-2 to day-3 were collected, preprocessed, and annotated. Using the Faster R-CNN model as baseline, our Esava model was constructed, refined, trained, and validated for precise and robust blastomere detection. A novel algorithm Crowd-NMS was proposed and employed in Esava to enhance the object detection and to precisely quantify the embryonic cells and their size uniformity. Additionally, an innovative GrabCut-based unsupervised module was integrated for the segmentation of blastomeres and embryos. Independently tested on 94 embryo images for blastomere detection, Esava obtained the high rates of 0.9940, 0.9121, and 0.9531 for precision, recall, and mAP respectively, and gained significant advances compared with previous computational methods. Intraclass correlation coefficients indicated the consistency between Esava and three experienced embryologists. Another test on 51 extra images demonstrated that Esava surpassed other tools significantly, achieving the highest average precision 0.9025. Moreover, it also accurately identified the borders of blastomeres with mIoU over 0.88 on the independent testing dataset. Esava is compliant with the Istanbul clinical consensus and compatible to senior embryologists. Taken together, Esava improves the accuracy and efficiency of embryonic development assessment with optical microscope images.

Association of early cleavage, morula compaction and blastocysts ploidy of IVF embryos cultured in a time-lapse system and biopsied for genetic test for aneuploidy

IVF embryos have historically been evaluated by morphological characteristics. The time-lapse system (TLS) has become a promising tool, providing an uninterrupted evaluation of morphological and dynamic parameters of embryo development. Furthermore, TLS sheds light on unknown phenomena such as direct cleavage and incomplete morula compaction. We retrospectively analyzed the morphology (Gardner Score) and morphokinetics (KIDScore) of 835 blastocysts grown in a TLS incubator (Embryoscope+), which were biopsied for preimplantation genetic testing for aneuploidy (PGT-A). Only the embryos that reached the blastocyst stage were included in this study and time-lapse videos were retrospectively reanalysed. According to the pattern of initial cleavages and morula compaction, the embryos were classified as: normal (NC) or abnormal (AC) cleavage, and fully (FCM) or partially compacted (PCM) morulae. No difference was found in early cleavage types or morula compaction patterns between female age groups (< 38, 38-40 and > 40 yo). Most of NC embryos resulted in FCM (≅ 60%), while no embryos with AC resulted in FCM. Aneuploidy rate of AC-PCM group did not differ from that of NC-FCM group in women < 38 yo, but aneuploidy was significantly higher in AC-PCM compared to NC-FCM of women > 40 yo. However, the quality of embryos was lower in AC-PCM blastocysts in women of all age ranges. Morphological and morphokinetic scores declined with increasing age, in the NC-PCM and AC-PCM groups, compared to the NC-FCM. Similar aneuploidy rates among NC-FCM and AC-PCM groups support the hypothesis that PCM in anomalous-cleaved embryos can represent a potential correction mechanism, even though lower morphological/morphokinetic scores are seen on AC-PCM. Therefore, both morphological and morphokinetic assessment should consider these embryonic development phenomena.

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

AIM

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

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

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

Research progress of time-lapse imaging technology and embryonic development potential: A review

Cultivation and selection of high-quality human embryos are critical for the success of in vitro fertilization-embryo transfer. Time-lapse imaging technology (TLI) provides a stable culture environment for embryos, which can continuously observe and record the development process of early embryos, so that doctors can record embryo development time parameters more accurately. In this study, we review the current observation and research on the main embryo dynamics parameters in TLI and discusses their significance and development for embryo development potential. To analysis and summary, the application and research situation of TLI, we searched PubMed, Web of Science, and China National Knowledge Infrastructure, using TLI, embryo dynamics parameters, embryo development potential as Keywords, cited 50 out of the initial 89 selected literatures and summarized. With comparative analysis and research, we found that the embryo dynamic parameters provided by TLI has been intensively studied in clinical empirical and observational research, extensive experimental data verified its effectiveness and advantages in embryo development potential assessment. TLI provides technical support of embryo dynamic parameters, which may become the quantitative indicators for superior embryos and pregnancy prediction as well. Existing studies have shown that certain kinetic parameters provided by TLI culture can predict embryo implantation, but no parameter has been confirmed as the absolute correlation biological indicators yet. In this review we believe that further research is needed to verify these preliminary and sometimes contradictory results, and explore the predictive significance of various embryo kinetic parameters relying on TLI technology for embryo development potential.

Non-Coding RNAs as Biomarkers for Embryo Quality and Pregnancy Outcomes: A Systematic Review and Meta-Analysis

Despite advances in in vitro fertilization (IVF), there is still a lack of non-invasive and reliable biomarkers for selecting embryos with the highest developmental and implantation potential. Recently, small non-coding RNAs (sncRNAs) have been identified in biological fluids, and extracellular sncRNAs are explored as diagnostic biomarkers in the prediction of IVF outcomes. To determine the predictive role of sncRNAs in embryo quality and IVF outcomes, a systematic review and meta-analysis was performed. Articles were retrieved from PubMed, EMBASE, and Web of Science from 1990 to 31 July 2022. Eighteen studies that met the selection criteria were analyzed. In total, 22 and 47 different sncRNAs were found to be dysregulated in follicular fluid (FF) and embryo spent culture medium (SCM), respectively. MiR-663b, miR-454 and miR-320a in FF and miR-20a in SCM showed consistent dysregulation in two different studies. The meta-analysis indicated the potential predictive performance of sncRNAs as non-invasive biomarkers, with a pooled area under curve (AUC) value of 0.81 (95% CI 0.78, 0.844), a sensitivity of 0.79 (95% CI 0.72, 0.85), a specificity of 0.67 (95% CI 0.52, 0.79) and a diagnostic odds ratio (DOR) of 8 (95% CI 5, 12). Significant heterogeneity was identified among studies in sensitivity (I2  =  46.11%) and specificity (I2  =  89.73%). This study demonstrates that sncRNAs may distinguish embryos with higher developmental and implantation potentials. They can be promising non-invasive biomarkers for embryo selection in ART. However, the significant heterogeneity among studies highlights the demand for prospective multicenter studies with optimized methods and adequate sample sizes in the future.

Cutting-edge techniques provide insights regarding repeated implantation failure patients

RESEARCH QUESTION

Can time-lapse parameters and the transcriptional profile of cumulus cells be used to achieve a more stringent and non-invasive method of embryo assessment and to identify possible factors affecting the embryo's ability to implant in repeated implantation failure (RIF) patients?

DESIGN

A total of 190 embryos from 18 oocyte donors and 145 embryos from 15 RIF patients were evaluated based on time-lapse parameters. Three morphokinetic parameters including T5 (time to reach five cells), T3 (time to reach three cells) and CC2 (time to two to three cells) were recorded for all embryos. Embryos that had all three parameters in the normal range were graded as high quality and comparison between these parameters were compared in high-quality embryos between two groups. The transcriptional profile of cumulus cells related to high-quality embryos of both groups were analysed by RNA sequencing and compared. Finally, the possible relationship between differentially expressed genes and time-lapse parameters was examined.

RESULTS

T5 was significantly lower in the RIF group than the donor group (P = 0.011). The cumulus cell transcriptome analysis showed 193 genes were down-regulated and 222 genes up-regulated. The mammalian target of rapamycin and the transforming growth factor beta pathways were significantly increased in the RIF group compared to the donor group (P = 0.007 and 0.01, respectively). Vitamin B12 and fatty acid beta-oxidation pathways were also significantly reduced in the RIF group compared to the donor group (P = 0.006 and 0.01, respectively).

CONCLUSIONS

Differences in the transcriptomic profiles of cumulus cells and some morphokinetic parameters may be one of the main factors contributing to unexplained RIF.

A proof of concept for a deep learning system that can aid embryologists in predicting blastocyst survival after thaw

The ability to understand whether embryos survive the thaw process is crucial to transferring competent embryos that can lead to pregnancy. The objective of this study was to develop a proof of concept deep learning model capable of assisting embryologist assessment of survival of thawed blastocysts prior to embryo transfer. A deep learning model was developed using 652 labeled time-lapse videos of freeze-thaw blastocysts. The model was evaluated against and along embryologists on a test set of 99 freeze-thaw blastocysts, using images obtained at 0.5 h increments from 0 to 3 h post-thaw. The model achieved AUCs of 0.869 (95% CI 0.789, 0.934) and 0.807 (95% CI 0.717, 0.886) and the embryologists achieved average AUCs of 0.829 (95% CI 0.747, 0.896) and 0.850 (95% CI 0.773, 0.908) at 2 h and 3 h, respectively. Combining embryologist predictions with model predictions resulted in a significant increase in AUC of 0.051 (95% CI 0.021, 0.083) at 2 h, and an equivalent increase in AUC of 0.010 (95% CI -0.018, 0.037) at 3 h. This study suggests that a deep learning model can predict in vitro blastocyst survival after thaw in aneuploid embryos. After correlation with clinical outcomes of transferred embryos, this model may help embryologists ascertain which embryos may have failed to survive the thaw process and increase the likelihood of pregnancy by preventing the transfer of non-viable embryos.

LWMA-Net: Light-weighted morphology attention learning for human embryo grading

Visual inspection of embryo morphology is routinely used in embryo assessment and selection. However, due to the complexity of morphologies and large inter- and intra-observer variances among embryologists, manual evaluations remain to be subjective and time-consuming. Thus, we proposed a light-weighted morphology attention learning network (LWMA-Net) for automatic assistance on embryo grading. The LWMA-Net integrated a morphology attention module (MAM) to seek the informative features and their locations and a multiscale fusion module (MFM) to increase the features flowing in the model. The LWMA-Net was trained with a primary set of 3599 embryos from 2318 couples that were clinically enrolled between Sep. 2016 and Dec. 2018, and generated area under the receiver operating characteristic curves (AUCs) of 96.88% and 97.58% on 4- and 3-category gradings, respectively. An independent test set comprises 691 embryos from 321 couples between Jan. 2019 and Jan. 2021 were used to test the assisted fertility values on the embryo grading. Five experienced embryologists were invited to regrade the embryos in the independent set with and without the aid of the LWMA-Net three months apart. Embryologists aided by our LWMA-Net significantly improved their grading capabilities with average AUCs improved by 4.98%-5.32% on 4- and 3-category grading tasks, respectively, which suggests good potential of our LWMA-Net on assisted human reproduction.

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

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

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.

Association between the morphokinetics of in-vitro-derived bovine embryos and the transcriptomic profile of the derived blastocysts

The time-lapse system is a non-invasive method that enables a continuous evaluation through embryo development. Here, we examined the association between the morphokinetics of the developing embryo and the transcriptomic profile of the formed blastocysts. Bovine oocytes were matured and fertilized in vitro; then, the putative zygotes were cultured in an incubator equipped with a time-lapse system. Based on the first-cleavage pattern, embryos were categorized as normal or abnormal (68.5±2.2 and 31.6±2.3%, respectively; P<0.001). A cleaved embryo was defined as normal when it first cleaved into two equal blastomeres; it was classified as synchronous or asynchronous according to its subsequent cleavages. An abnormal pattern was defined as direct, unequal, or reverse cleavage. Direct cleavage was classified as division from one cell directly into three or more blastomeres; unequal cleavage was classified as division that resulted in asymmetrically sized blastomeres; and reverse cleavage of the first division was classified as reduced number of blastomeres from two to one. Of the normally cleaving embryos, 60.2±3.1% underwent synchronous cleavage into 4, 8, and 16 blastomeres, and 39.7±3.1% cleaved asynchronously (P<0.001). The blastocyte formation rate was lower for the synchronously vs. the asynchronously cleaved embryos (P<0.03). The abnormally cleaved embryos showed low competence to develop to blastocysts, relative to the normally cleaved embryos (P<0.001). Microarray analysis revealed 895 and 643 differentially expressed genes in blastocysts that developed from synchronously and asynchronously cleaved embryos, respectively, relative to those that developed from directly cleaved embryos. The genes were related to the cell cycle, cell differentiation, metabolism, and apoptosis. About 180 differentially expressed genes were found between the synchronously vs. the asynchronously cleaved embryos, related to metabolism and the apoptosis mechanism. We provide the first evidence indicating that an embryo's morphokinetics is associated with the transcriptome profile of the derived blastocyst, which might be practically relevant for the embryo transfer program.

Current trends in artificial intelligence in reproductive endocrinology

PURPOSE OF REVIEW

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

RECENT FINDINGS

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

SUMMARY

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

Marginal differences in preimplantation morphokinetics between conventional IVF and ICSI in patients with preimplantation genetic testing for aneuploidy (PGT-A): A sibling oocyte study

Objective

This study aimed to analyze the morphokinetic behaviour between conventional IVF and ICSI, in cycles with preimplantation genetic testing for aneuploidies (PGT-A).

Materials

A randomized controlled trial (NCT03708991) was conducted in a private fertility center. Thirty couples with non-male factor infertility were recruited between November 2018 and April 2019. A total of 568 sibling cumulus oocyte complexes were randomly inseminated with conventional IVF and ICSI and cultured in an Embryoscope time-lapse system. The morphokinetic behaviour of IVF/ICSI sibling oocytes was analysed as primary endpoint. As secondary endpoints, morphokinetic parameters that predict blastocysts that will be biopsied, the day of biopsy, gender and euploid outcome was assessed.

Results

When comparing IVF to ICSI, only the time to reach the 2-cell stage (t2) was significantly delayed for IVF embryos: OR: 1.282 [1.020–1.612], p = 0.033. After standardizing for tPNf (ct parameters), only Blast(tStartBlastulation-t2) remained significant: OR: 0.803 [0.648–0.994], p = 0.044. For the analysis of zygotes that will be biopsied on day 5/6 versus zygotes without biopsy, only early morphokinetic parameters were considered. All parameters were different in the multivariate model: ct2: OR: 0.840 [0.709–0.996], p = 0.045; ct6: OR: 0.943 [0.890–0.998], p = 0.043; cc2(t3-t2): OR: 1.148 [1.044–1.263], p = 0.004; cc3(t5-t3): OR: 1.177 [1.107–1.251], p<0.0001. When comparing the development between blastocysts biopsied on day 5 versus day 6, only three morphokinetic parameters were significant: cc2(t3-t2): OR: 1.394 [1.010–1.926], p = 0.044; ctBlastocyst: OR: 0.613 [0.489–0.768], p<0.0001 and ctExpandedBlastocyst: OR: 0.913 [0.868–0.960], p = 0.0004. Multivariate analysis of gender and ploidy did not reveal differences in morphokinetic behaviour.

Conclusion

Minor morphokinetic differences are observed between IVF and ICSI. Early in the development, distinct cleavage patterns are observed between embryos that will be biopsied or not.

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

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

Robust and generalizable embryo selection based on artificial intelligence and time-lapse image sequences

Assessing and selecting the most viable embryos for transfer is an essential part of in vitro fertilization (IVF). In recent years, several approaches have been made to improve and automate the procedure using artificial intelligence (AI) and deep learning. Based on images of embryos with known implantation data (KID), AI models have been trained to automatically score embryos related to their chance of achieving a successful implantation. However, as of now, only limited research has been conducted to evaluate how embryo selection models generalize to new clinics and how they perform in subgroup analyses across various conditions. In this paper, we investigate how a deep learning-based embryo selection model using only time-lapse image sequences performs across different patient ages and clinical conditions, and how it correlates with traditional morphokinetic parameters. The model was trained and evaluated based on a large dataset from 18 IVF centers consisting of 115,832 embryos, of which 14,644 embryos were transferred KID embryos. In an independent test set, the AI model sorted KID embryos with an area under the curve (AUC) of a receiver operating characteristic curve of 0.67 and all embryos with an AUC of 0.95. A clinic hold-out test showed that the model generalized to new clinics with an AUC range of 0.60–0.75 for KID embryos. Across different subgroups of age, insemination method, incubation time, and transfer protocol, the AUC ranged between 0.63 and 0.69. Furthermore, model predictions correlated positively with blastocyst grading and negatively with direct cleavages. The fully automated iDAScore v1.0 model was shown to perform at least as good as a state-of-the-art manual embryo selection model. Moreover, full automatization of embryo scoring implies fewer manual evaluations and eliminates biases due to inter- and intraobserver variation.

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.

Oocyte quality and embryo selection strategies: a review for the embryologists, by the embryologists

With the advance of assisted reproduction techniques, and the trend towards blastocyst culture and single embryo transfer, gamete and embryo assessment have gained greater importance in ART treatment. Embryo quality depends mainly on gamete quality and culture conditions. Oocyte maturity identification is necessary in order to plan fertilization timing. Mature oocytes at the metaphase II stage show a higher fertilization rate compared to immature oocytes. Morphology assessment is a critical yet challenging task that may serve as a good prognostic tool for future development and implantation potential if done effectively. Various grading systems have been suggested to assess embryos at pronuclear, cleavage, and blastocyst stages. By identifying the embryo with the highest implantation potential, it is possible to reduce the number of embryos transferred without compromising the chances of a successful pregnancy. Apart from the conventional morphology assessment, there are several invasive or non-invasive methods for embryo selection such as preimplantation genetic testing, morphokinetics, proteomics, metabolomics, oxygen consumption, and measurement of oxidative stress in culture medium. Morphokinetics is a method based on time-lapse technology and continuous monitoring of embryos. In this review, we aim to describe and compare the most effective and widely used methods for gamete and embryo assessment as well as embryo selection.

Time-Lapse Systems: A Comprehensive Analysis on Effectiveness

Time-lapse systems have quickly become a common feature of in vitro fertilization laboratories all over the world. Since being introduced over a decade ago, the alleged benefits of time-lapse technology have continued to grow, from undisturbed culture conditions and round the clock, noninvasive observations to more recent computer-assisted selection of embryos through the development of algorithms. Despite the global uptake of time-lapse technology, its real impact on clinical outcomes is still controversial. This review aims to explore the different features offered by time-lapse technology, discussing incubation, algorithms, artificial intelligence and the regulation of nonessential treatment interventions, while assessing evidence on whether any benefit is offered over conventional technology.

OUP accepted manuscript

STUDY QUESTION

Can use of a commercially available time-lapse algorithm for Day 5 blastocyst selection improve pregnancy rates compared with morphology alone?

SUMMARY ANSWER

The use of a time-lapse selection model to choose blastocysts for fresh single embryo transfer on Day 5 did not improve ongoing pregnancy rate compared to morphology alone.

WHAT IS KNOWN ALREADY

Evidence from time-lapse monitoring suggests correlations between timing of key developmental events and embryo viability. No good quality evidence exists to support improved pregnancy rates following time-lapse selection.

STUDY DESIGN, SIZE, DURATION

A prospective multicenter randomized controlled trial including 776 randomized patients was performed between 2018 and 2021. Patients with at least two good quality blastocysts on Day 5 were allocated by a computer randomization program in a proportion of 1:1 into either the control group, whereby single blastocysts were selected for transfer by morphology alone, or the intervention group whereby final selection was decided by a commercially available time-lapse model. The embryologists at the time of blastocyst morphological scoring were blinded to which study group the patients would be randomized, and the physician and patients were blind to which group they were allocated until after the primary outcome was known. The primary outcome was number of ongoing pregnancies in the two groups.

PARTICIPANTS/MATERIALS, SETTING, METHODS

From 10 Nordic IVF clinics, 776 patients with a minimum of two good quality blastocysts on Day 5 (D5) were randomized into one of the two study groups. A commercial time-lapse model decided the final selection of blastocysts for 387 patients in the intervention (time-lapse) group, and blastocysts with the highest morphological score were transferred for 389 patients in the control group. Only single embryo transfers in fresh cycles were performed.

MAIN RESULTS AND THE ROLE OF CHANCE

In the full analysis set, the ongoing pregnancy rate for the time-lapse group was 47.4% (175/369) and 48.1% (181/376) in the control group. No statistically significant difference was found between the two groups: mean difference −0.7% (95% CI −8.2, 6.7, P = 0.90). Pregnancy rate (60.2% versus 59.0%, mean difference 1.1%, 95% CI −6.2, 8.4, P = 0.81) and early pregnancy loss (21.2% versus 18.5%, mean difference 2.7%, 95% CI −5.2, 10.6, P = 0.55) were the same for the time-lapse and the control group. Subgroup analyses showed that patient and treatment characteristics did not significantly affect the commercial time-lapse model D5 performance. In the time-lapse group, the choice of best blastocyst changed on 42% of occasions (154/369, 95% CI 36.9, 47.2) after the algorithm was applied, and this rate was similar for most treatment clinics.

LIMITATIONS, REASONS FOR CAUTION

During 2020, the patient recruitment rate slowed down at participating clinics owing to coronavirus disease-19 restrictions, so the target sample size was not achieved as planned and it was decided to stop the trial prematurely. The study only investigated embryo selection at the blastocyst stage on D5 in fresh IVF transfer cycles. In addition, only blastocysts of good morphological quality were considered for transfer, limiting the number of embryos for selection in both groups: also, it could be argued that this manual preselection of blastocysts limits the theoretical selection power of time-lapse, as well as restricting the results mainly to a good prognosis patient group. Most patients were aimed for blastocyst stage transfer when a minimum of five zygotes were available for extended culture. Finally, the primary clinical outcome evaluated was pregnancy to only 6–8 weeks.

WIDER IMPLICATIONS OF THE FINDINGS

The study suggests that time-lapse selection with a commercially available time-lapse model does not increase chance of ongoing pregnancy after single blastocyst transfer on Day 5 compared to morphology alone.

STUDY FUNDING/COMPETING INTEREST(S)

The study was financed by a grant from the Swedish state under the ALF-agreement between the Swedish government and the county councils (ALFGBG-723141). Vitrolife supported the study with embryo culture dishes and culture media. During the study period, T.H. changed his employment from Livio AB to Vitrolife AB. All other authors have no conflicts of interests to disclose.

TRIAL REGISTRATION NUMBER

ClinicalTrials.gov registration number NCT03445923.

TRIAL REGISTRATION DATE

26 February 2018.

DATE OF FIRST PATIENT’S ENROLMENT

11 June 2018.

Shallow artificial networks with morphokinetic time‐lapse parameters coupled to ART data allow to predict live birth

Purpose

The purpose of this work was to construct shallow neural networks (SNN) using time‐lapse technology (TLT) from morphokinetic parameters coupled to assisted reproductive technology (ART) parameters in order to assist the choice of embryo(s) to be transferred with the highest probability of achieving a live birth (LB).

Methods

A retrospective observational single‐center study was performed, 654 cycles were included. Three SNN: multilayers perceptron (MLP), simple recurrent neuronal network (simple RNN) and long short term memory RNN (LSTM‐RNN) were trained with K‐fold cross‐validation to avoid sampling bias. The predictive power of SNNs was measured using performance scores as AUC (area under curve), accuracy, precision, Recall and F1 score.

Results

In the training data group, MLP and simple RNN provide the best performance scores; however, all AUCs were above 0.8. In the validating data group, all networks were equivalent with no performance scores difference and all AUC values were above 0.8.

Conclusion

Coupling morphokinetic parameters with ART parameters allows to SNNs to predict the probability of LB, and all SNNs seems to be efficient according to the performance scores. An automatic time recognition system coupled to one of these SNNs could allow a complete automation to choose the blastocyst(s) to be transferred.

The Association of Kinetic Variables with Blastocyst Development and Ploidy Status

Background:

Despite a plethora of studies conducted so far, a debate is still unresolved as to whether TLM can identify predictive kinetic biomarkers or algorithms universally applicable. Therefore, this study aimed to elucidate if there is a relationship between kinetic variables and ploidy status of human embryos or blastocyst developmental potential.

Methods:

For conducting this retrospective cohort study, the normal distribution of data was verified using Kolmogorov-Smirnov test with the Lilliefors’ amendment and the Shapiro-Wilk test. Kinetic variables were expressed as median and quartiles (Q1, Q2, Q3, Q4). Mann-Whitney U-test was used to compare the median values of parameters. Univariate and multiple logistic regression models were used to assess relationship between blastocyst developmental potential or ploidy status and kinetics. Several confounding factors were also assessed.

Results:

Blastocyst developmental potential was positively correlated with the t4-t3 interval (s2) (OR=1.417, 95% CI of 1.288–1.560). s2 median value was significantly different between high- and low-quality blastocysts (0.50 and 1.33 hours post-insemination, hpi, respectively; p=0.003). In addition, timing of pronuclear appearance (tPNa) (OR=1.287; 95% CI of 1.131–1.463) had a significant relationship with ploidy changes. The median value of tPNa was statistically different (p=0.03) between euploid and aneuploid blastocysts (Euploid blastocysts=8.9 hpi; aneuploid blastocysts=10.3 hpi).

Conclusion:

The present findings are in line with the study hypothesis that kinetic analysis may reveal associations between cleavage patterns and embryo development to the blastocyst stage and ploidy status.

An artificial intelligence model (euploid prediction algorithm) can predict embryo ploidy status based on time-lapse data

BACKGROUND

For the association between time-lapse technology (TLT) and embryo ploidy status, there has not yet been fully understood. TLT has the characteristics of large amount of data and non-invasiveness. If we want to accurately predict embryo ploidy status from TLT, artificial intelligence (AI) technology is a good choice. However, the current work of AI in this field needs to be strengthened.

METHODS

A total of 469 preimplantation genetic testing (PGT) cycles and 1803 blastocysts from April 2018 to November 2019 were included in the study. All embryo images are captured during 5 or 6 days after fertilization before biopsy by time-lapse microscope system. All euploid embryos or aneuploid embryos are used as data sets. The data set is divided into training set, validation set and test set. The training set is mainly used for model training, the validation set is mainly used to adjust the hyperparameters of the model and the preliminary evaluation of the model, and the test set is used to evaluate the generalization ability of the model. For better verification, we used data other than the training data for external verification. A total of 155 PGT cycles from December 2019 to December 2020 and 523 blastocysts were included in the verification process.

RESULTS

The euploid prediction algorithm (EPA) was able to predict euploid on the testing dataset with an area under curve (AUC) of 0.80.

CONCLUSIONS

The TLT incubator has gradually become the choice of reproductive centers. Our AI model named EPA that can predict embryo ploidy well based on TLT data. We hope that this system can serve all in vitro fertilization and embryo transfer (IVF-ET) patients in the future, allowing embryologists to have more non-invasive aids when selecting the best embryo to transfer.

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.

Blastocyst Prediction of Day-3 Cleavage-Stage Embryos Using Machine Learning

Background: Embryo selection plays an important role in the success of in vitro fertilization (IVF). However, morphological embryo assessment has a number of limitations, including the time required, lack of accuracy, and inconsistency. This study determined whether a machine learning-based model could predict blastocyst formation using day-3 embryo images.

Methods: Day-3 embryo images from IVF/intracytoplasmic sperm injection (ICSI) cycles performed at My Duc Phu Nhuan Hospital between August 2018 and June 2019 were retrospectively analyzed to inform model development. Day-3 embryo images derived from two-pronuclear (2PN) zygotes with known blastocyst formation data were extracted from the CCM-iBIS time-lapse incubator (Astec, Japan) at 67 hours post ICSI, and labeled as blastocyst/non-blastocyst based on results at 116 hours post ICSI. Images were used as the input dataset to train (85%) and validate (15%) the convolutional neural network (CNN) model, then model accuracy was determined using the training and validation dataset. The performance of 13 experienced embryologists for predicting blastocyst formation based on 100 day-3 embryo images was also evaluated.

Results: A total of 1,135 images were allocated into training ([Formula: see text] 967) and validation ([Formula: see text] 168) sets, with an even distribution for blastocyst formation outcome. The accuracy of the final model for blastocyst formation was 97.72% in the training dataset and 76.19% in the validation dataset. The final model predicted blastocyst formation from day-3 embryo images in the validation dataset with an area under the curve of 0.75 (95% confidence interval [CI] 0.69–0.81). Embryologists predicted blastocyst formation with the accuracy of 70.07% (95% CI 68.12%–72.03%), sensitivity of 87.04% (95% CI 82.56%–91.52%), and specificity of 30.93% (95% CI 29.35%–32.51%).

Conclusions: The CNN-based machine learning model using day-3 embryo images predicted blastocyst formation more accurately than experienced embryologists. The CNN-based model is a potential tool to predict additional IVF outcomes.

Back to the future: optimised microwell culture of individual human preimplantation stage embryos

Although in vitro culture of human embryos is a crucial step in assisted reproduction, the lack of focused research hampers worldwide standardisation and consistent outcomes. Only 1.2% of research papers published in five leading journals in human reproduction in 2019 focused on in vitro culture conditions, creating the impression that the optimisation process has approached its limits. On the other hand, in vitro culture of mammalian embryos is based on old principles, while there is no consensus on basic issues as density, time, medium change, gas atmosphere and small technical details including the way of drop preparation. This opinion paper aims to highlight and analyse the slow advancement in this field and stimulate research for simple and affordable solutions to meet the current requirements. A possible way for advancement is discussed in detail. Selection of embryos with the highest developmental competence requires individual culture and modification of the widely used "drop under oil" approach. Current use of three-dimensional surfaces instead of large flat bottoms is restricted to time-lapse systems, but these wells are designed for optical clarity, not for the needs of embryos. The size and shape of the original microwells (Well of the Well; WOW) offer a practical and straightforward solution to combine the benefits of communal and individual incubation and improve the overall quality of cultured embryos.

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.

Comparison of pregnancy outcomes using a time-lapse monitoring system for embryo incubation versus a conventional incubator in in vitro fertilization: An age-stratification analysis

OBJECTIVE

The aim of this study was to compare the pregnancy outcomes of in vitro fertilization with embryo transfer between embryos cultured in a time-lapse monitoring system (TLS) and those cultured in a conventional incubator (CI).

METHODS

The medical records of 250 fertilized embryos from 141 patients undergoing infertility treatment with assisted reproductive technology at a tertiary hospital from June 2018 to May 2020 were reviewed. The study population was divided into TLS and CI groups at a 1 to 1 ratio (125 embryos per group). The primary outcome was the live birth rate.

RESULTS

The TLS group had a significantly higher clinical pregnancy rate (46.4% vs. 27.2%, p=0.002), implantation rate (27.1% vs. 12.0%, p=0.004), and live birth rate (32.0% vs. 18.4%, p=0.013) than the CI group. Furthermore, subgroup analyses of the clinical pregnancy rate and live birth rate in the different age groups favored the TLS group. However, this difference only reached statistical significance in the live birth rate in women aged over 40 years and the clinical pregnancy rate in women aged 35-40 years (p=0.048 and p=0.031, respectively). The miscarriage rate, cleavage rate, and blastocyst rate were comparable.

CONCLUSION

TLS application improved the live birth rate, implantation rate, and clinical pregnancy rate, particularly in the advanced age group in this study, while the other reproductive outcomes were comparable. Large randomized controlled trials are needed to further explore the ramifications of these findings, especially in different age groups.

A novel embryo quality scoring system to compare groups of embryos at different developmental stages

PURPOSE

To construct a new embryonic quality scoring system to compare groups of embryos at different developmental stages.

METHODS

Based on a hypothesis that the implantation potential of any embryo in an ovum pickup (OPU) cycle remains the same at any stage of development, be it day 2, 3, or 5, a new embryo quality scoring (EQS) system was designed. It was based on the analysis of the clinical results of 1610 single embryo transfers. We validated this scoring system in the comparison of embryonic quality between groups by evaluating the mean scores calculated at day 2, day 3, and day 5 for 957 embryos (150 cycles) from 3 different groups. We then compared EQSs of patients with pregnancy favorable factors (group A) such as young age and high AMH levels, with the patients with contra features (group B).

RESULTS

We confirmed that each mean EQS assessed at different stages of embryonic development within the same group was similar. The mean EQSs on day 3 and day 5 in group A were significantly higher than the mean EQSs on days 2, 3, and 5 in group B.

CONCLUSION

The novel EQS system proposed by us enables embryonic quality comparison between groups of embryos at different developmental stages.

Improving embryo selection by the development of a laboratory-adapted time-lapse model

OBJECTIVE

To study whether a powerful, in-house, embryo-selection model can be developed for a specific in vitro fertilization (IVF) laboratory where embryos were already selected for transfer using general models.

DESIGN

In total, 12,944 fertilized oocytes were incubated in an EmbryoScope (Vitrolife, Göteborg, Sweden) at our laboratory. Embryos were selected for transfer or freezing using general models. There were 1,879 embryos with known implantation data (KID), of which 425 had positive KIDs. For the outcome, we set 3 endpoints for KID's definition: gestational sac, clinical pregnancy, and live birth. Results of a comparison between KID-positive and -negative embryos for cell division timings were analyzed separately for intracytoplasmic sperm injection (ICSI) and IVF embryos in patients aged 18-41 years.

SETTING

IVF center.

PATIENTS

The study included 1,075 women undergoing IVF or ICSI treatment between June 2013 and February 2019.

INTERVENTION(S)

None.

MAIN OUTCOME MEASURE(S)

The KID-positive and -negative embryos were analyzed for statistical differences in cell division timing and cell cycle intervals. We used the EmbryoScope Stats software (Unisense FertiliTech, Aarhus, Denmark) for model development. The statistically different timing parameters were tested for their contribution to scoring in the model. The algorithms were tested for area under the receiver operating characteristic curve (AUC) in the KID embryos for developing day-2, -3, and -5 embryo-selection models. The validation of these algorithms was performed using calibration/validation procedures.

RESULTS

Because significant differences in morphokinetics were found between the KID-positive and KID-negative embryos in our laboratory, it was possible to use our specific KID data to develop an in-house model. The algorithms were developed for embryo selection on days 2, 3, and 5 in the ICSI embryos. In most cases, AUC was >0.65, which indicated that these models were valid in our laboratory. In addition, these AUC values were obtained from all gestational sac, clinical pregnancy, and live birth KID embryo databases tested. An increase in the predictability of the models was observed from days 2-3 to day 5 models. The AUC test results ranged between 0.657 and 0.673 for day 2 and day 3, respectively, and 0.803 for the day 5 model.

CONCLUSION

A model based on laboratory-specific morphokinetics was found to be complementary to general models and an important additive tool for improving single embryo selection. Developing an in-house laboratory-specific model requires many stages of sorting and characterization. Many insights were drawn about the model developing process. These may facilitate and improve the process in other laboratories.

The effect of Day 3 cell number on pregnancy outcomes in vitrified-thawed single blastocyst transfer cycles

STUDY QUESTION

Does cell number on Day 3 have an impact on pregnancy outcomes in vitrified-thawed single blastocyst transfer cycles?

SUMMARY ANSWER

A low Day 3 cell number (≤5 cells) was independently associated with decreased live birth rate (LBR) during single blastocyst transfer cycles in young women.

WHAT IS KNOWN ALREADY

Day 3 cell number is an effective predictor of IVF success rates when transferring cleavage stage embryos. However, the association between Day 3 blastomere number and pregnancy outcomes after blastocyst transfer is still unknown.

STUDY DESIGN, SIZE, DURATION

A retrospective cohort study of 3543 patients who underwent frozen-thawed single blastocyst transfers from January 2013 to June 2018 at a tertiary-care academic medical center.

PARTICIPANTS/MATERIALS, SETTING, METHODS

Patients were grouped into six groups according to the Day 3 cell number: ≤4 cells, 5 cells, 6 cells, 7 cells, 8 cells and >8 cells. The primary outcome measure was LBR. A logistic regression analysis was performed to explore the independent association between Day 3 blastomere number and LBR after adjustment for some potential confounders.

MAIN RESULTS AND THE ROLE OF CHANCE

In women <35 years old, the LBR varied significantly according to Day 3 cell number, with the rate of 31.2%, 34.4%, 41.9%, 45.1%, 48.1% and 48.2% for the ≤4-cell, 5-cell, 6-cell, 7-cell, 8-cell and >8-cell groups, respectively (P < 0.001). This significant difference was also observed in the high- and low-quality blastocyst subgroups of young women. However, for women ≥35 years old, the rate of live birth was similar between groups. Furthermore, after accounting for confounding factors, the LBR was significantly decreased in the ≤4-cell (adjusted odds ratio (aOR): 0.62, 95% CI: 0.48-0.80, P < 0.001) and 5-cell (aOR: 0.73, 95% CI: 0.57-0.92, P = 0.009) groups as compared to the 8-cell group. Likewise, the blastocysts arising from ≤4-cell (aOR: 0.73, 95% CI: 0.57-0.93, P = 0.010) or 5-cell (aOR: 0.77, 95% CI: 0.61-0.97, P = 0.024) embryos were associated with lower clinical pregnancy rate than those from 8-cell embryos. No significant differences were observed in biochemical pregnancy rate and miscarriage rate.

LIMITATIONS, REASONS FOR CAUTION

A limitation of the current study was its retrospective design. Future prospective studies are needed to confirm our findings.

WIDER IMPLICATIONS OF THE FINDINGS

Our observations suggested that a low Day 3 cell number was related to decreased LBR after blastocyst transfer in young women, which provided vital information for clinicians in selecting blastocyst during IVF treatment.

STUDY FUNDING/COMPETING INTEREST(S)

This study was supported by the National Natural Science Foundation of China (NSFC) (31770989 to Y.W.; 81671520 to Q.C.) and the Shanghai Ninth People's Hospital Foundation of China (JYLJ030 to Y.W.). The authors have no conflicts of interest to declare.

TRIAL REGISTRATION NUMBER

N/A.

Outcome of in vitro fertilization cycles with automatic time-lapse instrumentation combined with the early embryo viability assessment score

AIM

To evaluate whether embryo selection using the early embryo viability assessment (EEVA) score increases the ongoing pregnancy rate of in vitro fertilization and intracytoplasmic sperm injection patients.

METHODS

One hundred eighty-one patients whose serum anti mullerian hormone (AMH) level was greater than 0.5 ng/μL were enrolled in the study. All patients received oocyte retrieval repeatedly from June 2017 to January 2019. Transferred embryos were selected using the EEVA score and Veeck's criteria. We investigated the blastocyst rate according to the EEVA score and Veeck's criteria and also evaluated the clinical outcome following embryo transfer of the blastocysts.

RESULTS

Blastocyst development rate (48.7%) and high-quality blastocyst (42.4%) of Veeck 1 was statistically higher than others. The blastocyst rate (71.4%) and high-quality blastocyst rate (60.0%) for EEVA 1 was the highest, and a correlation between the EEVA score and the blastocyst rate was also identified in cases younger than 40 years. Blastocyst rate of EEVA 1 + 2 (69.8% 208/298) was statistically higher than that of Veeck 1 + 2 (40.1% 317/791) (p < 0.05) and high-quality blastocyst rate of EEVA 1 + 2 (50.0% 104/208) was also higher than that of Veeck 1 + 2 (36.6% 117/320) (p < 0.05). However, there was a significant correlation between EEVA and the pregnancy rate and pregnancy rate of EEVA 1 + 2 showed no statistical difference compared with Veeck 1 + 2.

CONCLUSIONS

Although it remains to be answered whether a computer can substitute Veeck's classification, the EEVA score could be a viable alternative to predict the blastocyst rate and to select those high-potential embryos that improve the pregnancy rate.

Back to the future: optimised microwell culture of individual human preimplantation stage embryos

Although in vitro culture of human embryos is a crucial step in assisted reproduction, the lack of focused research hampers worldwide standardisation and consistent outcomes. Only 1.2% of research papers published in five leading journals in human reproduction in 2019 focused on in vitro culture conditions, creating the impression that the optimisation process has approached its limits. On the other hand, in vitro culture of mammalian embryos is based on old principles, while there is no consensus on basic issues as density, time, medium change, gas atmosphere and small technical details including the way of drop preparation. This opinion paper aims to highlight and analyse the slow advancement in this field and stimulate research for simple and affordable solutions to meet the current requirements. A possible way for advancement is discussed in detail. Selection of embryos with the highest developmental competence requires individual culture and modification of the widely used "drop under oil" approach. Current use of three-dimensional surfaces instead of large flat bottoms is restricted to time-lapse systems, but these wells are designed for optical clarity, not for the needs of embryos. The size and shape of the original microwells (Well of the Well; WOW) offer a practical and straightforward solution to combine the benefits of communal and individual incubation and improve the overall quality of cultured embryos.

Expression Level of ADAMTS1 in Granulosa Cells of PCOS Patients Is Related to Granulosa Cell Function, Oocyte Quality, and Embryo Development

A disintegrin and metalloproteinase with thrombospondin motifs 1 (ADAMTS1) is an extracellular matrix metalloproteinase that plays an important role in the process of ovulation. According to previous studies, the expression level of ADAMTS1 in the granulosa cells of polycystic ovarian syndrome (PCOS) patients and the mechanism for regulating oocyte quality and embryonic development potential are still unclear. Our research clarified that ADAMTS1 was significantly increased in granulosa cells of PCOS patients as compared to ovulatory controls. After silencing ADAMTS1 in granulosa cells, cell proliferation and E₂ secretion were significantly inhibited, which may be related to the down-regulation of B-cell lymphoma 2 (Bcl2) family genes and key genes involved in E₂ synthesis. Through retrospective analysis of the clinical data, it was found that the expression level of ADAMTS1 was significantly positively correlated to the oocyte maturation rate and good-quality embryo rate in PCOS patients. The downregulation of ADAMTS1 in primary granulosa cells lead to the changes in the expression of marker genes for oocyte and embryonic quality. By using immunofluorescence staining, it was found ADAMTS1 was expressed in various stages of pre-implantation embryo but its expression level gradually decreases with the development of the embryo. In addition, the silence of ADAMTS1 in 3PN zygotes significantly prolonged the development time of the zygote to the morula stage. This is, to our knowledge, the first time to explored the mechanism by which ADAMST1 is involved in affecting the quality of oocytes and embryonic development potential, which will provide new evidence for further understanding of the follicular microenvironment and embryo development.

Embryo morphokinetic score is associated with biomarkers of developmental competence and implantation

PURPOSE

To study embryo morphokinetics in relation to release in spent media of molecules with possible roles in development and implantation (miR-20a, miR-30c, and sHLA-G).

METHODS

Data were obtained from embryos generated in standard IVF and ICSI cycles. The Eeva system was used for embryo assessment, based on early morphokinetic parameters and producing a score (1-5, best-worst) corresponding to higher/medium/lower chances of development to blastocyst. miRNAs - mm miR-20a-5p and miR-30c-5p - and sHLA-G were quantified in 25 μl of spent blastocyst media (SBM) collected before vitrification or transfer. Statistical analyses were performed applying Kolmogorov-Smirnov, Shapiro-Wilk, and Spearman's correlation coefficient tests, where appropriate.

RESULTS

SBM were collected from a total of 172 viable blastocysts. Their analysis showed that concentration of miR-20a was progressively lower as Eeva score increased and probability of development to blastocyst decreased (P = 0.016). The opposite trend was observed in the case of miR-30c, i.e., concentration was higher as score increased and chances of development to blastocyst decreased (P = 0.004). Analysis of sHLA-G revealed a negative correlation with Eeva score, i.e., levels were progressively lower as Eeva score increased and probability of development to blastocyst decreased (R = - 0.388, N = 141, P = 0.001).

CONCLUSION

Our data suggest that morphokinetic algorithms that predict development to blastocyst stage, in fact, also identify embryos with molecular and cellular profiles more consistent with developmental functions.

Development of deep learning algorithms for predicting blastocyst formation and quality by time-lapse monitoring

Approaches to reliably predict the developmental potential of embryos and select suitable embryos for blastocyst culture are needed. The development of time-lapse monitoring (TLM) and artificial intelligence (AI) may help solve this problem. Here, we report deep learning models that can accurately predict blastocyst formation and usable blastocysts using TLM videos of the embryo’s first three days. The DenseNet201 network, focal loss, long short-term memory (LSTM) network and gradient boosting classifier were mainly employed, and video preparation algorithms, spatial stream and temporal stream models were developed into ensemble prediction models called STEM and STEM⁺. STEM exhibited 78.2% accuracy and 0.82 AUC in predicting blastocyst formation, and STEM⁺ achieved 71.9% accuracy and 0.79 AUC in predicting usable blastocysts. We believe the models are beneficial for blastocyst formation prediction and embryo selection in clinical practice, and our modeling methods will provide valuable information for analyzing medical videos with continuous appearance variation.

Liao et al. propose a deep learning model to predict blastocyst formation using TLM videos following the first three days of embryogenesis. The authors develop an ensemble prediction model, STEM and STEM⁺, which were found to exhibit 78.2% and 71.9% accuracy at predicting blastocyst formation and useable blastocysts respectively.

Evaluation of deep convolutional neural networks in classifying human embryo images based on their morphological quality

A critical factor that influences the success of an in-vitro fertilization (IVF) treatment cycle is the quality of the transferred embryo. Embryo morphology assessments, conventionally performed through manual microscopic analysis suffer from disparities in practice, selection criteria, and subjectivity due to the experience of the embryologist. Convolutional neural networks (CNNs) are powerful, promising algorithms with significant potential for accurate classifications across many object categories. Network architectures and hyper-parameters affect the efficiency of CNNs for any given task. Here, we evaluate multi-layered CNNs developed from scratch and popular deep-learning architectures such as Inception v3, ResNET-50, Inception-ResNET-v2, NASNetLarge, ResNeXt-101, ResNeXt-50, and Xception in differentiating between embryos based on their morphological quality at 113 h post insemination (hpi). Xception performed the best in differentiating between the embryos based on their morphological quality.

Fertility technologies and how to optimize laboratory performance to support the shortening of time to birth of a healthy singleton: a Delphi consensus

PURPOSE

To explore how the assisted reproductive technology (ART) laboratories can be optimized and standardized to enhance embryo culture and selection, to bridge the gap between standard practice and the new concept of shortening time to healthy singleton birth.

METHODS

A Delphi consensus was conducted (January to July 2018) to assess how the ART laboratory could be optimized, in conjunction with existing guidelines, to reduce the time to a healthy singleton birth. Eight experts plus the coordinator discussed and refined statements proposed by the coordinator. The statements were distributed via an online survey to 29 participants (including the eight experts from step 1), who voted on their agreement/disagreement with each statement. Consensus was reached if ≥ 66% of participants agreed/disagreed with a statement. If consensus was not achieved for any statement, that statement was revised and the process repeated until consensus was achieved. Details of statements achieving consensus were communicated to the participants.

RESULTS

Consensus was achieved for all 13 statements, which underlined the need for professional guidelines and standardization of lab processes to increase laboratory competency and quality. The most important points identified were the improvement of embryo culture and embryo assessment to shorten time to live birth through the availability of more high-quality embryos, priority selection of the most viable embryos and improved cryosurvival.

CONCLUSION

The efficiency of the ART laboratory can be improved through professional guidelines on standardized practices and optimized embryo culture environment, assessment, selection and cryopreservation methodologies, thereby reducing the time to a healthy singleton delivery.

Assisted oocyte activation effects on the morphokinetic pattern of derived embryos

OBJECTIVE

Assisted oocyte activation (AOA) can restore fertilization rates after IVF/ICSI cycles with fertilization failure. AOA is an experimental technique, and its downstream effects remain poorly characterized. Clarifying the relationship between AOA and embryo, morphokinetics could offer complementary insights into the quality and viability of the embryos obtained with this technique. The aim of this study is to compare the preimplantation morphokinetic development of embryos derived from ICSI-AOA (experimental group) vs. ICSI cycles (control group).

METHODS

A retrospective cohort study was carried out with 141 embryos from fresh oocyte donation cycles performed between 2013 and 2017; 41 embryos were derived from 7 ICSI-AOA cycles and 100 embryos from 18 ICSI cycles. Morphokinetic development of all embryos was followed using a time-lapse system.

RESULTS

We show that embryos from both groups develop similarly for most milestones, with the exception of the time of second polar body extrusion (tPB2) and the time to second cell division (t3).

CONCLUSIONS

We conclude that ionomycin mediated AOA does not seem to affect the morphokinetic pattern of preimplantation embryo development, despite the alterations found in tPB2 and t3, which could directly reflect the use of a Ca²⁺ ionophore as a transient and quick non-physiologic increase of free intracytoplasmic Ca²⁺.

Cytoplasmic movements of the early human embryo: imaging and artificial intelligence to predict blastocyst development

RESEARCH QUESTION

Can artificial intelligence and advanced image analysis extract and harness novel information derived from cytoplasmic movements of the early human embryo to predict development to blastocyst?

DESIGN

In a proof-of-principle study, 230 human preimplantation embryos were retrospectively assessed using an artificial neural network. After intracytoplasmic sperm injection, embryos underwent time-lapse monitoring for 44 h. For comparison, standard embryo assessment of each embryo by a single embryologist was carried out to predict development to blastocyst stage based on a single picture frame taken at 42 h of development. In the experimental approach, in embryos that developed to blastocyst or destined to arrest, cytoplasm movement velocity was recorded by time-lapse monitoring during the first 44 h of culture and analysed with a Particle Image Velocimetry algorithm to extract quantitative information. Three main artificial intelligence approaches, the k-Nearest Neighbour, the Long-Short Term Memory Neural Network and the hybrid ensemble classifier were used to classify the embryos.

RESULTS

Blind operator assessment classified each embryo in terms of ability to develop to blastocyst, with 75.4% accuracy, 76.5% sensitivity, 74.3% specificity, 74.3% precision and 75.4% F1 score. Integration of results from artificial intelligence models with the blind operator classification, resulted in 82.6% accuracy, 79.4% sensitivity, 85.7% specificity, 84.4% precision and 81.8% F1 score.

CONCLUSIONS

The present study suggests the possibility of predicting human blastocyst development at early cleavage stages by detection of cytoplasm movement velocity and artificial intelligence analysis. This indicates the importance of the dynamics of the cytoplasm as a novel and valuable source of data to assess embryo viability.

The clinical use of time-lapse in human-assisted reproduction

A major challenge in the assisted reproduction laboratory is to set up reproducible and efficient criteria to identify the embryo with the highest developmental potential. Over the years, several methods have been used worldwide with this purpose. Initially, standard morphology assessment was the only available strategy. It is now universally recognized that besides being a very subjective embryo selection strategy, morphology evaluation alone has a very poor prognostic value. More recently, the availability of time-lapse incubators allowed a continuous monitoring of human embryo development. This technology has spread quickly and many fertility clinics over the world produced a remarkable amount of data. To date, however, a general consensus on which variables, or combination of variables, should play a central role in embryo selection is still lacking. Many confounding factors, concerning both patient features and clinical and biological procedures, have been observed to influence embryo development. In addition, several studies have reported unexpected positive outcomes, even in the presence of abnormal developmental criteria. While it does not seem that time-lapse technology is ready to entirely replace the more invasive preimplantation genetic testing in identifying the embryo with the highest implantation potential, it is certainly true that its application is rapidly growing, becoming progressively more accurate. Studies involving artificial intelligence and deep-learning models as well as combining morphokinetic with other non-invasive markers of embryo development, are currently ongoing, raising hopes for its successful applicability for clinical purpose in the near future. The present review mainly focuses on data published starting from the first decade of 2000, when time-lapse technology was introduced as a routine clinical practice in the infertility centers.

A matched propensity score study of embryo morphokinetics following gonadotropin-releasing hormone agonist versus human chorionic gonadotropin trigger

PURPOSE

To compare morphokinetic parameters and quality of embryos derived from GnRH antagonist ICSI cycles triggered either with GnRH agonist or standard hCG between matched groups of patients.

METHODS

Morphokinetic parameters of embryos derived from matched first GnRH antagonist ICSI cycles triggered by GnRH agonist or standard hCG between 2013 and 2016 were compared. Matching was performed for maternal age, peak estradiol levels, and number of oocytes retrieved. Outcome measures were: time to pronucleus fading (tPNf), cleavage timings (t2-t8), synchrony of the second and third cycles (S2 and S3), duration of the second and third cycle (CC2 and CC3), optimal cell cycle division parameters, and known implantation data (KID) scoring for embryo quality. Multivariate linear and logistic regression analyses were performed for confounding factors.

RESULTS

We analyzed 824 embryos from 84 GnRH agonist trigger cycles and 746 embryos from 84 matched hCG trigger cycles. Embryos derived from the cycles triggered with hCG triggering cleaved faster than those deriving from GnRH agonist trigger. The differences were significant throughout most stages of embryo development (t3-t6), and a shorter second cell cycle duration of the hCG trigger embryos was observed. There was no difference in synchrony of the second and third cell cycles and the optimal cell cycle division parameters between the two groups, but there was a higher percentage of embryos without multinucleation in the hCG trigger group (27.8% vs. 21.6%, p < 0.001).

CONCLUSION

The type of trigger in matched antagonist ICSI cycles was found to affect early embryo cleavage times but not embryo quality.