A comparison of morphokinetic markers predicting blastocyst formation and implantation potential from two large clinical data sets

Metabolic imaging of human embryos is predictive of ploidy status but is not associated with clinical pregnancy outcomes: a pilot trial

STUDY QUESTION

Does fluorescence lifetime imaging microscopy (FLIM)-based metabolic imaging assessment of human blastocysts prior to frozen transfer correlate with pregnancy outcomes?

SUMMARY ANSWER

FLIM failed to distinguish consistent patterns in mitochondrial metabolism between blastocysts leading to pregnancy compared to those that did not.

WHAT IS KNOWN ALREADY

FLIM measurements provide quantitative information on NAD(P)H and flavin adenine dinucleotide (FAD+) concentrations. The metabolism of embryos has long been linked to their viability, suggesting the potential utility of metabolic measurements to aid in selection.

STUDY DESIGN, SIZE, DURATION

This was a pilot trial enrolling 121 IVF couples who consented to have their frozen blastocyst measured using non-invasive metabolic imaging. After being warmed, 105 couples' good-quality blastocysts underwent a 6-min scan in a controlled temperature and gas environment. FLIM-assessed blastocysts were then transferred without any intervention in management.

PARTICIPANTS/MATERIALS, SETTING, METHODS

Eight metabolic parameters were obtained from each blastocyst (4 for NAD(P)H and 4 for FAD): short and long fluorescence lifetime, fluorescence intensity, and fraction of the molecule engaged with enzyme. The redox ratio (intensity of NAD(P)H)/(intensity of FAD) was also calculated. FLIM data were combined with known metadata and analyzed to quantify the ability of metabolic imaging to differentiate embryos that resulted in pregnancy from embryos that did not. De-identified discarded aneuploid human embryos (n = 158) were also measured to quantify correlations with ploidy status and other factors. Statistical comparisons were performed using logistic regression and receiver operating characteristic (ROC) curves with 5-fold cross-validation averaged over 100 repeats with random sampling. AUC values were used to quantify the ability to distinguish between classes.

MAIN RESULTS AND THE ROLE OF CHANCE

No metabolic imaging parameters showed significant differences between good-quality blastocysts resulting in pregnancy versus those that did not. A logistic regression using metabolic data and metadata produced an ROC AUC of 0.58. In contrast, robust AUCs were obtained when classifying other factors such as comparison of Day 5 (n = 64) versus Day 6 (n = 41) blastocysts (AUC = 0.78), inner cell mass versus trophectoderm (n = 105: AUC = 0.88) and aneuploid (n = 158) versus euploid and positive pregnancy embryos (n = 108) (AUC = 0.82).

LIMITATIONS, REASONS FOR CAUTION

The study protocol did not select which embryo to transfer and the cohort of 105 included blastocysts were all high quality. The study was also limited in number of participants and study sites. Increased power and performing the trial in more sites may have provided a stronger conclusion regarding the merits of the use of FLIM clinically.

WIDER IMPLICATIONS OF THE FINDINGS

FLIM failed to distinguish consistent patterns in mitochondrial metabolism between good-quality blastocysts leading to pregnancy compared to those that did not. Blastocyst ploidy status was, however, highly distinguishable. In addition, embryo regions and embryo day were consistently revealed by FLIM. While metabolic imaging detects mitochondrial metabolic features in human blastocysts, this pilot trial indicates it does not have the potential to serve as an effective embryo viability detection tool. This may be because mitochondrial metabolism plays an alternative role post-implantation.

STUDY FUNDING/COMPETING INTEREST(S)

This study was sponsored by Optiva Fertility, Inc. Boston IVF contributed to the clinical site and services. Becker Hickl, GmbH, provided the FLIM system on loan. T.S. was the founder and held stock in Optiva Fertility, Inc., and D.S. and E.S. had options with Optiva Fertility, Inc., during this study.

TRIAL REGISTRATION NUMBER

The study was approved by WCG Connexus IRB (Study Number 1298156).

Application of artificial intelligence in gametes and embryos selection

Gamete and embryo quality are critical to the success rate of Assisted Reproductive Technology (ART) cycles, but there remains a lack of methods to accurately measure the quality of sperm, oocytes and embryos. The ability of Artificial Intelligence (AI) technology to analyze large amounts of data, especially video and images, is particularly useful in gamete and embryo assessment and selection. The well-trained model has fast calculation speed and high accuracy, which can help embryologists to perform more objective gamete and embryo selection. Various artificial intelligence models have been developed for gamete and embryo assessment, some of which exhibit good performance. In this review, we summarize the latest applications of AI technology in semen analysis, as well as selection for sperm, oocyte and embryo, and discuss the existing problems and development directions of artificial intelligence in this field.

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.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSION

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

The effects of temperature variation treatments on embryonic development: a mouse study

Since the development of ART, embryos have been cultured at 37 °C in an attempt to mimic the in vivo conditions and the average body temperature of an adult. However, a gradient of temperatures within the reproductive tract has been demonstrated in humans and several other mammalian species. Therefore, the aim of this study was to evaluate the effects of temperature variation treatments on mouse embryo quality through morphokinetic events, blastocyst morphology, the relative gene expression of Igf2, Bax, Bcl2 and Apaf1 and the metabolomics of individual culture media. Study groups consisted of 2 circadian treatments, T1 with embryos being cultured at 37 °C during the day and 35.5 °C during the night, T2 with 38.5 °C during the day and 37 °C during the night and a control group with constant 37 °C. Our main findings are that the lower-temperature group (T1) showed a consistent negative effect on mouse embryo development with “slow” cleaving embryos, poor-quality blastocysts, a higher expression of the apoptotic gene Apaf1, and a significantly different set of amino acids representing a more stressed metabolism. On the other hand, our higher-temperature group (T2) showed similar results to the control group, with no adverse effects on blastocyst viability.

Focus on time-lapse analysis: blastocyst collapse and morphometric assessment as new features of embryo viability

The main goal of assisted reproductive technology (ART) is to achieve a healthy singleton live birth after the transfer of one embryo. A major objective of IVF scientists has always been to use adequate criteria for selecting the embryo for transfer according to its implantation potential. Indeed, embryo quality is usually assessed by evaluating visual morphology, which relies on the removal of the embryo from the incubator and might include inter- and intra-evaluator variation among embryologists. Recently, an advancement in embryo culture has taken place with the introduction of a new type of incubator with an integrated time-lapse monitoring system, which enables embryologists to analyse the dynamic events of embryo development from fertilization to blastocyst formation. This novel practice is rapidly growing and has been used in many IVF centres worldwide. Therefore, the main aim of this review is to present the benefits of time-lapse monitoring in a modern embryology laboratory; in particular, we discuss blastocyst collapse and morphometric blastocyst assessment, and analyse their association with embryo viability and implantation potential. In addition, we highlight preliminary studies involving artificial intelligence and machine learning models as non-invasive markers of clinical pregnancy.

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.

Comparing prediction of ongoing pregnancy and live birth outcomes in patients with advanced and younger maternal age patients using KIDScore™ day 5: a large-cohort retrospective study with single vitrified-warmed blastocyst transfer

BACKGROUND

The KIDScore™ Day 5 (KS-D5) model, version 3, is a general morphokinetic prediction model (Vitrolife, Sweden) for fetal heartbeat prediction after embryo transfer that was developed based on a large data set that included implantation results from a range of clinics with different patient populations, culture conditions and clinical practices. However, there was no study to comparing their pregnancy and live birth prediction ability among different maternal age. The aim of this study is to analyze the performance of KS-D5 in predicting pregnancy and live birth in various maternal age groups after single vitrified-warmed blastocyst transfer (SVBT).

METHODS

A total of 2486 single vitrified-warmed blastocyst transfer (SVBT) cycles were analyzed retrospectively. Confirmed fetal heartbeat positive (FHB+) and live birth (LB+) rates were stratified by Society for Assisted Reproductive Technology (SART) maternal age criteria (< 35, 35-37, 38-40, 41-42 and ≥ 43 years of age). Within each age group, the performance of the prediction model was calculated using the AUC, and the results were compared across the age groups.

RESULTS

In all age groups, the FHB+ rates decreased as the KIDScore decreased (P <  0.05). Conversely, the AUCs increased as the maternal age increased. The AUC of the < 35 age group (0.589) was significantly lower than the AUCs of the 41-42 age group (0.673) and the ≥43 age group (0.737), respectively (P <  0.05). In all age groups, the LB+ rates decreased as the KIDScore decreased (P <  0.05). Conversely, the AUCs increased as the maternal age increased. The AUC of the ≥43 age group (0.768) was significantly higher than the AUCs of other age groups (P <  0.05; < 35 age group = 0.596, 35-37 age group = 0.640, 38-40 age group = 0.646, 41-42 age group = 0.679).

CONCLUSIONS

In the present study, we determined that the KIDScore model worked well for prediction of pregnancy and live birth outcomes in advanced age patients.

Artificial intelligence in human in vitro fertilization and embryology

Embryo evaluation and selection embody the aggregate manifestation of the entire in vitro fertilization (IVF) process. It aims to choose the "best" embryos from the larger cohort of fertilized oocytes, the majority of which will be determined to be not viable either as a result of abnormal development or due to chromosomal imbalances. Indeed, it is generally acknowledged that even after embryo selection based on morphology, time-lapse microscopic photography, or embryo biopsy with preimplantation genetic testing, implantation rates in the human are difficult to predict. Our pursuit of enhancing embryo evaluation and selection, as well as increasing live birth rates, will require the adoption of novel technologies. Recently, several artificial intelligence (AI)-based methods have emerged as objective, standardized, and efficient tools for evaluating human embryos. Moreover, AI-based methods can be implemented for other clinical aspects of IVF, such as assessing patient reproductive potential and individualizing gonadotropin stimulation protocols. As AI has the capability to analyze "big" data, the ultimate goal will be to apply AI tools to the analysis of all embryological, clinical, and genetic data in an effort to provide patient-tailored treatments. In this chapter, we present an overview of existing AI technologies in reproductive medicine and envision their potential future applications in the field.

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.

Biomechanics of Early Life in the Female Reproductive Tract

Early human life that starts at the onset of fertilization and ends with implantation of the embryo in the uterine wall is the foundation for a successful pregnancy. The different stages during this period require biomechanical mechanisms, which are mostly unknown due to difficulties to conduct in vivo studies in humans.

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.

The dynamics between in vitro culture and metabolism: embryonic adaptation to environmental changes

Previous studies have discussed the importance of an optimal range of metabolic activity during preimplantation development. To avoid factors than can trigger an undesirable trajectory, it is important to learn how nutrients and metabolites interact to help launching the correct developmental program of the embryo, and how much the in vitro culture system can impair this process. Here, using the bovine model, we describe a factorial experimental design used to investigate the biochemical and molecular signature of embryos in response to different combinations of morphological features—i.e. speed of development—and external stimuli during in vitro culture—i.e. different oxygen tensions and glucose supplementation. Our analyses demonstrate that the embryos present heterogeneous metabolic responses depending on early morphological phenotypes and the composition of their surroundings. However, despite the contribution of each single stimulus for the embryo phenotype, oxygen tension is determinant for such differences. The lower oxygen environment boosts the metabolism of embryos with faster kinetics, in particular those cultured in lower glucose concentrations.

Tricarboxylic Acid Cycle Metabolites as Mediators of DNA Methylation Reprogramming in Bovine Preimplantation Embryos

In many cell types, epigenetic changes are partially regulated by the availability of metabolites involved in the activity of chromatin-modifying enzymes. Even so, the association between metabolism and the typical epigenetic reprogramming that occurs during preimplantation embryo development remains poorly understood. In this work, we explore the link between energy metabolism, more specifically the tricarboxylic acid cycle (TCA), and epigenetic regulation in bovine preimplantation embryos. Using a morphokinetics model of embryonic development (fast- and slow-developing embryos), we show that DNA methylation (5mC) and hydroxymethylation (5hmC) are dynamically regulated and altered by the speed of the first cleavages. More specifically, slow-developing embryos fail to perform the typical reprogramming that is necessary to ensure the generation of blastocysts with higher ability to establish specific cell lineages. Transcriptome analysis revealed that such differences were mainly associated with enzymes involved in the TCA cycle rather than specific writers/erasers of DNA methylation marks. This relationship was later confirmed by disturbing the embryonic metabolism through changes in α-ketoglutarate or succinate availability in culture media. This was sufficient to interfere with the DNA methylation dynamics despite the fact that blastocyst rates and total cell number were not quite affected. These results provide the first evidence of a relationship between epigenetic reprogramming and energy metabolism in bovine embryos. Likewise, levels of metabolites in culture media may be crucial for precise epigenetic reprogramming, with possible further consequences in the molecular control and differentiation of cells.

Faster fertilization and cleavage kinetics reflect competence to achieve a live birth after intracytoplasmic sperm injection, but this association fades with maternal age

OBJECTIVE

To assess the relationship of early developmental kinetics with competence to provide a live birth and the impact of maternal age in this context.

DESIGN

Retrospective cohort study including 4,915 embryos, of which 1,390 were transferred and provided a clinical outcome paired with morphokinetic data; 168 of them resulted in a live birth (LB), and 1,222 did not (NLB). Early morphokinetic parameters were compared between LB and NLB embryos from patients stratified into two age groups (<37 and ≥37 years), and between embryos at the same competence group from patients aged <37 and ≥37 years. The association of morphokinetic parameters with live birth was tested by univariate and multivariate analyses.

SETTING

Fertility clinic.

PATIENT(S)

The study population included 1,066 patients undergoing autologous intracytoplasmic sperm injection cycles with fresh single (SET), double (DET) or triple (TET) embryo transfers on day 2 or 3. Of them, 669 patients produced NLB embryos and 134 produced LB embryos.

INTERVENTION(S)

None.

MAIN OUTCOME MEASURE(S)

Fertilization and cleavage morphokinetic parameters and live birth.

RESULT(S)

In the total patient population, all morphokinetic parameters were achieved earlier in LB compared with NLB embryos. The same was observed in patients aged <37 years (P<.015), but not ≥37 years. Except for the t8 (time at which an 8-blastomere embryo was identified), all morphokinetic parameters were reached earlier in LB embryos from patients aged <37 years compared with LB embryos from patients aged ≥37 years. Univariate analysis revealed that earlier occurrence of all morphokinetic parameters was associated with live birth, although only earlier t2 (time at which two separate and distinct cells were identified) was associated with live birth independently from maternal age in the multivariate analysis.

CONCLUSION(S)

Despite its retrospective nature and performance in a single IVF center, this study presents novel data indicating that embryos competent to provide a live birth display overall faster early developmental kinetics compared with embryos that do not achieve a live birth after transfer, a difference that, however, narrows as maternal age advances. The findings suggest that fertilization and cleavage morphokinetic parameters may constitute valuable references for embryo selection strategies aiming to improve live birth rates, specifically before advanced maternal age while holding limited usefulness in advanced maternal age.