Inter- and intra-observer variability of time-lapse annotations

The density of the inner cell mass is a new indicator of the quality of a human blastocyst: a valid supplement to the Gardner scoring system

STUDY QUESTION

Can the density of the inner cell mass (ICM) be a new indicator of the quality of the human blastocyst?

SUMMARY ANSWER

The densification index (DI) developed in this study can quantify ICM density and provide positive guidance for ploidy, pregnancy, and live birth.

WHAT IS KNOWN ALREADY

In evaluating the quality of ICM, reproductive care clinics still use size indicators without further evaluation. The main disadvantage of this current method is that the evaluation of blastocyst ICM is relatively rough and cannot meet the needs of clinical embryologists, especially when multiple blastocysts have the same ICM score, which makes them difficult to evaluate further.

STUDY DESIGN, SIZE, DURATION

This observational study included data from 2272 blastocysts in 1991 frozen-thawed embryo transfer (FET) cycles between January 2018 to November 2021 and 1105 blastocysts in 430 preimplantation genetic testing cycles between January 2019 and February 2023.

PARTICIPANTS/MATERIALS, SETTING, METHODS

FET, ICSI, blastocyst culture, trophectoderm biopsy, time-lapse (TL) monitoring, and next-generation sequencing were performed. After preliminary sample size selection, the 11 focal plane images captured by the TL system were normalized and the spatial frequency was used to construct the DI of the ICM.

MAIN RESULTS AND THE ROLE OF CHANCE

This study successfully constructed a quantitative indicator DI that can reflect the degree of ICM density in terms of fusion and texture features. The higher the DI value, the better the density of the blastocyst ICM, and the higher the chances that the blastocyst was euploid (P < 0.001) and that pregnancy (P < 0.001) and live birth (P = 0.005) were reached. In blastocysts with ICM graded B and blastocysts graded 4BB, DI was also positively associated with ploidy, pregnancy, and live birth (P < 0.05). ROC analysis showed that combining the Gardner scoring system with DI can more effectively predict pregnancy and live births, when compared to using the Gardner scoring system alone.

LIMITATIONS, REASONS FOR CAUTION

Accurate calculation of the DI value places high demands on image quality, requiring manual selection of the clearest focal plane and exposure control. Images with the ICM not completely within the field of view cannot be used. The association between the density of ICM and chromosomal mosaicism was not evaluated. The associations between the density of ICM and different assisted reproductive technologies and different culture conditions in embryo laboratories were also not evaluated. Prospective studies are needed to further investigate the impact of ICM density on clinical outcomes.

WIDER IMPLICATIONS OF THE FINDINGS

ICM density assessment is a new direction in blastocyst assessment. This study explores new ways of assessing blastocyst ICM density and develops quantitative indicators and a corresponding qualitative evaluation scheme for ICM density. The DI of the blastocyst ICM developed in this study is easy to calculate and requires only TL equipment and image processing, providing positive guidance for clinical outcomes. The qualitative evaluation scheme of ICM density can assist embryologists without TL equipment to manually evaluate ICM density. ICM density is a simple indicator that can be used in practice and is a good complement to the blastocyst scoring systems currently used in most centers.

STUDY FUNDING/COMPETING INTEREST(S)

This work was supported by the National Key Research & Development Program of China (2021YFC2700603). The authors report no financial or commercial conflicts of interest.

TRIAL REGISTRATION NUMBER

N/A.

Embryo multinucleation: detection, possible origins, and implications for treatment

Cell cycle regulation is crucial to assure expansion of a cell population, while preserving genome integrity. This notion is especially relevant to fertilization and early embryo development, a time when the cell cycle transforms from meiotic into mitotic cycles. Zygote-to-embryo transition is acutely error-prone, causing major developmental perturbations, including cleavage delays, tri- and multi-chotomous cleavages, and cell fragmentation. Another such alteration is bi- and multinucleation, consisting of the simultaneous formation of two or more nuclei at interphase. Indeed, multinucleation affects a large proportion of early human embryos, typically at the two-cell stage. Mechanistically, several factors, including spindle dysfunction, failed cleavage, and cell fusion, may generate this cell anomaly. In assisted reproduction treatment, multinucleation is associated with reduced developmental rates and lower implantation rates in Days 2-3 embryo transfers. However, many multinucleated embryos can develop to the blastocyst stage. In blastocyst transfers, the current evidence does not suggest a major impact of a previous history of multinucleation on the odds of euploidy or successful treatment outcomes. Human embryo multinucleation remains a not-fully-understood but developmentally relevant and intriguing phenomenon which requires further research of its generative mechanisms and clinical implications.

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

RESEARCH QUESTION

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

DESIGN

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

RESULTS

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

CONCLUSIONS

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

Towards an Objective Measurement Tool for ADHD-like Traits in Family Dogs: A Comprehensive Test Battery

Family dogs exhibit neuropsychological deficits similar to attention-deficit/hyperactivity disorder (ADHD) symptoms in humans. Questionnaire methods have mostly been used to assess ADHD-like behaviours in dogs. In addition to our validated questionnaire (Dog ADHD and Functionality Rating Scale-DAFRS; 2024), we developed a simple behavioural test battery covering the ADHD symptom domains (i.e., inattention, hyperactivity, and impulsivity) in dogs. Our main aim was (i) to provide a final external validation step to the DAFRS by examining its associations with the test variables (N = 59); and (ii) to compare owner- and trainer-rated factor scores' associations with the test variables (n = 38). We developed four tests covering the ADHD symptom domains: the attention test (inattention), the plush dog test (impulsivity), the leash test, and the sit test (hyperactivity). All four behavioural variables correlated with their respective questionnaire scores, i.e., the strongest for hyperactivity, and the least strong for inattention. Both owner- and trainer-rated scores (n = 38) correlated with the relevant test variables in an expected direction. Dogs' training status was linked only to the sit test results. Test-retest analyses (n = 34) indicated moderate-to-excellent agreement across all behavioural variables. Our findings support the validity of our novel human-analogue questionnaire for dogs as the behavioural tests strongly correlate with the relevant questionnaire scores, indicating that the two constructs together can effectively assess inattention, hyperactivity, and impulsivity in dogs.

Evaluation of the Clinical Efficacy and Trust in AI-Assisted Embryo Ranking: Survey-Based Prospective Study

BACKGROUND

Current embryo assessment methods for in vitro fertilization depend on subjective morphological assessments. Recently, artificial intelligence (AI) has emerged as a promising tool for embryo assessment; however, its clinical efficacy and trustworthiness remain unproven. Simulation studies may provide additional evidence, provided that they are meticulously designed to mitigate bias and variance.

OBJECTIVE

The primary objective of this study was to evaluate the benefits of an AI model for predicting clinical pregnancy through well-designed simulations. The secondary objective was to identify the characteristics of and potential bias in the subgroups of embryologists with varying degrees of experience.

METHODS

This simulation study involved a questionnaire-based survey conducted on 61 embryologists with varying levels of experience from 12 in vitro fertilization clinics. The survey was conducted via Google Forms (Google Inc) in three phases: (1) phase 1, an initial assessment (December 23, 2022, to January 22, 2023); (2) phase 2, a validation assessment (March 6, 2023, to April 5, 2023); and (3) phase 3 an AI-guided assessment (March 6, 2023, to April 5, 2023). Inter- and intraobserver assessments and the accuracy of embryo selection from 360 day-5 embryos before and after AI guidance were analyzed for all embryologists and subgroups of senior and junior embryologists.

RESULTS

With AI guidance, the interobserver agreement increased from 0.355 to 0.527 and from 0.440 to 0.524 for junior and senior embryologists, respectively, thus reaching similar levels of agreement. In a test of accurate embryo selection with 90 questions, the numbers of correct responses by the embryologists only, embryologists with AI guidance, and AI only were 34 (38%), 45 (50%), and 59 (66%), respectively. Without AI, the average score (accuracy) of the junior group was 33.516 (37%), while that of the senior group was 35.967 (40%), with P<.001 in the t test. With AI guidance, the average score (accuracy) of the junior group increased to 46.581 (52%), reaching a level similar to that of the senior embryologists of 44.833 (50%), with P=.34. Junior embryologists had a higher level of trust in the AI score.

CONCLUSIONS

This study demonstrates the potential benefits of AI in selecting embryos with high chances of pregnancy, particularly for embryologists with 5 years or less of experience, possibly due to their trust in AI. Thus, using AI as an auxiliary tool in clinical practice has the potential to improve embryo assessment and increase the probability of a successful pregnancy.

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

STUDY QUESTION

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

SUMMARY ANSWER

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

WHAT IS KNOWN ALREADY?

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

STUDY DESIGN, SIZE, DURATION

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

PARTICIPANTS/MATERIALS, SETTING, METHODS

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

MAIN RESULTS AND THE ROLE OF CHANCE

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

LIMITATIONS, REASONS FOR CAUTION

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

WIDER IMPLICATIONS OF THE FINDINGS

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

STUDY FUNDING/COMPETTING INTEREST(S)

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

TRIAL REGISTRATION NUMBER

N/A.

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.

Microfluidic chip as a promising evaluation method in assisted reproduction: A systematic review

The aim of assisted reproductive technology (ART) is to select the high-quality sperm, oocytes, and embryos, and finally achieve a successful pregnancy. However, functional evaluation is hindered by intra- and inter-operator variability. Microfluidic chips emerge as the one of the most powerful tools to analyze biological samples for reduced size, precise control, and flexible extension. Herein, a systematic search was conducted in PubMed, Scopus, Web of Science, ScienceDirect, and IEEE Xplore databases until March 2023. We displayed and prospected all detection strategies based on microfluidics in the ART field. After full-text screening, 71 studies were identified as eligible for inclusion. The percentages of human and mouse studies equaled with 31.5%. The prominent country in terms of publication number was the USA (n = 13). Polydimethylsiloxane (n = 49) and soft lithography (n = 28) were the most commonly used material and fabrication method, respectively. All articles were classified into three types: sperm (n = 38), oocytes (n = 20), and embryos (n = 13). The assessment contents included motility, counting, mechanics, permeability, impedance, secretion, oxygen consumption, and metabolism. Collectively, the microfluidic chip technology facilitates more efficient, accurate, and objective evaluation in ART. It can even be combined with artificial intelligence to assist the daily activities of embryologists. More well-designed clinical studies and affordable integrated microfluidic chips are needed to validate the safety, efficacy, and reproducibility. Trial registration: The protocol was registered in the Open Science Frame REGISTRIES (identification: osf.io/6rv4a).

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

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

Development of a human-analogue, 3-symptom domain Dog ADHD and Functionality Rating Scale (DAFRS)

The family dog, in its natural environment, exhibits neuropsychological deficits redolent of human psychiatric disorders, including behaviours that are similar to human attention-deficit/hyperactivity disorder (ADHD) symptoms. Based on standard questionnaire methods in humans, we aimed to develop and validate a detailed, psychometrically improved tool to assess owner views on relevant dog behaviours. We modified available questionnaires by adding items that allow for separate analysis of impulsivity, and items on functional impairment. We collected data from 1168 owners for different validation steps of the new questionnaire and, similarly to assessment of humans where teachers also evaluate as an expert control, we collected data from dog trainers. Exploratory and confirmatory factor analysis revealed 3 factors: inattention (IA), hyperactivity (H) and impulsivity (I), corresponding to all three human symptom dimensions in dogs. Test-retest analyses showed excellent agreement between measurements for all factors. Similarly to findings with humans, trainer-owner rating comparisons showed fair (IA) to moderate (H, I) agreement. As in humans, greater ADHD scores were associated with greater functional impairment scores. We suggest that in dogs, similarly to humans, parallel examination of (extreme) ADHD and functional impairment scores could help distinguish diagnosable individuals, after further validation of the questionnaire using a relevant behaviour test.

Beyond appearance: Can morphologically low-grade euploid blastocysts yield successful pregnancies?

Purpose

The primary objective of this investigation is to evaluate how morphological quality affects the pregnancy outcomes in euploid embryos determined by preimplantation genetic testing for aneuploidies (PGT-A). Concurrently, as a secondary objective, we aim to identify which specific aspects of morphological evaluation exert the most significant impact on these outcomes.

Methods

A retrospective analysis of 451 single euploid embryo transfer cycles at our clinic was conducted. Embryos were evaluated based on the degree of blastocyst expansion, inner cell mass (ICM), trophectoderm (TE) morphology, and the day of blastocyst vitrification. Outcomes between morphologically low-grade and high-grade embryos were compared. Additionally, the study analyzed which morphological factors most influenced pregnancy outcomes.

Results

Pregnancy outcomes were significantly lower in morphologically low-grade blastocysts compared to high-grade ones. Among the morphological evaluations, the ICM assessment was significantly associated with the live birth rate.

Conclusion

Our study indicates that the morphological quality of euploid embryos, particularly the evaluation of the ICM, plays a crucial role in IVF-ET success.

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.

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.

An artificial intelligence algorithm for automated blastocyst morphometric parameters demonstrates a positive association with implantation potential

Blastocyst selection is primarily based on morphological scoring systems and morphokinetic data. These methods involve subjective grading and time-consuming techniques. Artificial intelligence allows for objective and quick blastocyst selection. In this study, 608 blastocysts were selected for transfer using morphokinetics and Gardner criteria. Retrospectively, morphometric parameters of blastocyst size, inner cell mass (ICM) size, ICM-to-blastocyst size ratio, and ICM shape were automatically measured by a semantic segmentation neural network model. The model was trained on 1506 videos with 102 videos for validation with no overlap between the ICM and trophectoderm models. Univariable logistic analysis found blastocyst size and ICM-to-blastocyst size ratio to be significantly associated with implantation potential. Multivariable regression analysis, adjusted for woman age, found blastocyst size to be significantly associated with implantation potential. The odds of implantation increased by 1.74 for embryos with a blastocyst size greater than the mean (147 ± 19.1 μm). The performance of the algorithm was represented by an area under the curve of 0.70 (p < 0.01). In conclusion, this study supports the association of a large blastocyst size with higher implantation potential and suggests that automatically measured blastocyst morphometrics can be used as a precise, consistent, and time-saving tool for improving blastocyst selection.

Embryo selection through artificial intelligence versus embryologists: a systematic review

STUDY QUESTION

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

SUMMARY ANSWER

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

WHAT IS KNOWN ALREADY

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

STUDY DESIGN SIZE DURATION

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

PARTICIPANTS/MATERIALS SETTING METHODS

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

MAIN RESULTS AND THE ROLE OF CHANCE

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

LIMITATIONS REASONS FOR CAUTION

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

WIDER IMPLICATIONS OF THE FINDINGS

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

STUDY FUNDING/COMPETING INTERESTS

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

REGISTRATION NUMBER

CRD42021256333.

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

PURPOSE

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Maternal age affects pronuclear and chromatin dynamics, morula compaction and cell polarity, and blastulation of human embryos

STUDY QUESTION

Does maternal ageing impact early and late morphokinetic and cellular processes of human blastocyst formation?

SUMMARY ANSWER

Maternal ageing significantly affects pronuclear size and intra- and extra-nuclear dynamics during fertilization, dysregulates cell polarity during compaction, and reduces blastocoel expansion.

WHAT IS KNOWN ALREADY

In ART, advanced maternal age (AMA) affects oocyte yield, fertilization, and overall developmental competence. However, with the exception of chromosome segregation errors occurring during oocyte meiosis, the molecular and biochemical mechanisms responsible for AMA-related subfertility and reduced embryo developmental competence remain unclear. In particular, studies reporting morphokinetics and cellular alterations during the fertilization and pre-implantation period in women of AMA remain limited.

STUDY DESIGN, SIZE, DURATION

A total of 2058 fertilized oocytes were stratified by maternal age according to the Society for Assisted Reproductive Technology classification (<35, 35-37, 38-40, 41-42, and >42 years) and retrospectively analysed. AMA effects were assessed in relation to: embryo morphokinetics and morphological alterations; and the presence and distribution of cell polarity markers-Yes-associated protein (YAP) and protein kinase C-ζ (PKC-ζ)-involved in blastocyst morphogenesis.

PARTICIPANTS/MATERIALS, SETTING, METHODS

A total of 1050 cycles from 1050 patients met the inclusion criteria and were analysed. Microinjected oocytes were assessed using a time-lapse culture system. Immature oocytes at oocyte retrieval and mature oocytes not suitable for time-lapse monitoring, owing to an excess of residual corona cells or inadequate orientation for correct observation, were not analysed. Phenomena relevant to meiotic resumption, pronuclear dynamics, cytoplasmic/cortical modifications, cleavage patterns and embryo quality were annotated and compared among groups. Furthermore, 20 human embryos donated for research by consenting couples were used for immunofluorescence.

MAIN RESULTS AND THE ROLE OF CHANCE

Static microscopic observation revealed that blastocyst formation and expansion were impaired in the 41-42 and >42-year groups (P < 0.0001). The morphological grades of the inner cell mass and trophectoderm were poorer in the >42-year group than those in the <35-year group (P = 0.0022 and P < 0.0001, respectively). Time-lapse microscopic observation revealed a reduction in nucleolus precursor body alignment in female pronuclei in the 41-42 and >42-year groups (P = 0.0010). Female pronuclear area decreased and asynchronous pronuclear breakdown increased in the >42-year group (P = 0.0027 and P < 0.0122, respectively). Developmental speed at cleavage stage, incidence of irregularity of first cleavage, type and duration of blastomere movement, and number of multinucleated cells were comparable among age groups. Delayed embryonic compaction and an increased number of extruded blastomeres were observed in the >42-year group (P = 0.0002 and P = 0.0047, respectively). Blastulation and blastocyst expansion were also delayed in the 41-42 and >42-year groups (P < 0.0001 for both). YAP positivity rate in the outer cells of morulae and embryo PKC-ζ immunoflourescence decreased in the >42-year group (P < 0.0001 for both).

LIMITATIONS, REASONS FOR CAUTION

At the cellular level, the investigation was limited to cell polarity markers. Cell components of other developmental pathways should be studied in relation to AMA.

WIDER IMPLICATIONS OF THE FINDINGS

The study indicates that maternal ageing affects the key functions of embryo morphogenesis, irrespective of the well-established influence on the fidelity of oocyte meiosis.

STUDY FUNDING/COMPETING INTEREST(S)

This study was supported by the participating institutions. The authors have no conflicts of interest to declare.

TRIAL REGISTRATION NUMBER

N/A.

Neural responsiveness to reward and suicidal ideation in social anxiety and major depression before and after psychotherapy

Suicidality is prevalent in Social Anxiety Disorder (SAD) and Major Depressive Disorder (MDD). Limited data indicate the reward positivity (RewP), a neurophysiological index of reward responsivity, and subjective capacity for pleasure may serve as brain and behavioral assays for suicide risk though this has yet to be examined in SAD or MDD in the context of psychotherapy. Therefore, the current study tested whether suicidal ideation (SI) relates to RewP and subjective capacity for anticipatory and consummatory pleasure at baseline and whether Cognitive Behavioral Therapy (CBT) impacts these measures. Participants with SAD (n = 55) or MDD (n = 54) completed a monetary reward task (gains vs. losses) during electroencephalogram (EEG) before being randomized to CBT or supportive therapy (ST), a comparator common factors arm. EEG and SI data were collected at baseline, mid-treatment, and post-treatment; capacity for pleasure was collected at baseline and post-treatment. Baseline results showed participants with SAD or MDD were comparable in SI, RewP, and capacity for pleasure. When controlling for symptom severity, SI negatively corresponded with RewP following gains and SI positively corresponded with RewP following losses at baseline. Yet, SI did not relate to subjective capacity for pleasure. Evidence of a distinct SI-RewP association suggests RewP may serve as a transdiagnositic brain-based marker of SI. Treatment outcome revealed that among participants with SI at baseline, SI significantly decreased regardless of treatment arm; also, consummatory, but not anticipatory, pleasure increased across participants regardless of treatment arm. RewP was stable following treatment, which has been reported in other clinical trial studies.

A non-invasive artificial intelligence approach for the prediction of human blastocyst ploidy: a retrospective model development and validation study

BACKGROUND

One challenge in the field of in-vitro fertilisation is the selection of the most viable embryos for transfer. Morphological quality assessment and morphokinetic analysis both have the disadvantage of intra-observer and inter-observer variability. A third method, preimplantation genetic testing for aneuploidy (PGT-A), has limitations too, including its invasiveness and cost. We hypothesised that differences in aneuploid and euploid embryos that allow for model-based classification are reflected in morphology, morphokinetics, and associated clinical information.

METHODS

In this retrospective study, we used machine-learning and deep-learning approaches to develop STORK-A, a non-invasive and automated method of embryo evaluation that uses artificial intelligence to predict embryo ploidy status. Our method used a dataset of 10 378 embryos that consisted of static images captured at 110 h after intracytoplasmic sperm injection, morphokinetic parameters, blastocyst morphological assessments, maternal age, and ploidy status. Independent and external datasets, Weill Cornell Medicine EmbryoScope+ (WCM-ES+; Weill Cornell Medicine Center of Reproductive Medicine, NY, USA) and IVI Valencia (IVI Valencia, Health Research Institute la Fe, Valencia, Spain) were used to test the generalisability of STORK-A and were compared measuring accuracy and area under the receiver operating characteristic curve (AUC).

FINDINGS

Analysis and model development included the use of 10 378 embryos, all with PGT-A results, from 1385 patients (maternal age range 21-48 years; mean age 36·98 years [SD 4·62]). STORK-A predicted aneuploid versus euploid embryos with an accuracy of 69·3% (95% CI 66·9-71·5; AUC 0·761; positive predictive value [PPV] 76·1%; negative predictive value [NPV] 62·1%) when using images, maternal age, morphokinetics, and blastocyst score. A second classification task trained to predict complex aneuploidy versus euploidy and single aneuploidy produced an accuracy of 74·0% (95% CI 71·7-76·1; AUC 0·760; PPV 54·9%; NPV 87·6%) using an image, maternal age, morphokinetic parameters, and blastocyst grade. A third classification task trained to predict complex aneuploidy versus euploidy had an accuracy of 77·6% (95% CI 75·0-80·0; AUC 0·847; PPV 76·7%; NPV 78·0%). STORK-A reported accuracies of 63·4% (AUC 0·702) on the WCM-ES+ dataset and 65·7% (AUC 0·715) on the IVI Valencia dataset, when using an image, maternal age, and morphokinetic parameters, similar to the STORK-A test dataset accuracy of 67·8% (AUC 0·737), showing generalisability.

INTERPRETATION

As a proof of concept, STORK-A shows an ability to predict embryo ploidy in a non-invasive manner and shows future potential as a standardised supplementation to traditional methods of embryo selection and prioritisation for implantation or recommendation for PGT-A.

FUNDING

US National Institutes of Health.

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.

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.

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

STUDY QUESTION

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

SUMMARY ANSWER

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

WHAT IS KNOWN ALREADY

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

STUDY DESIGN, SIZE, DURATION

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

PARTICIPANTS/MATERIALS, SETTING, METHODS

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

MAIN RESULTS AND THE ROLE OF CHANCE

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

LIMITATIONS, REASONS FOR CAUTION

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

WIDER IMPLICATIONS OF THE FINDINGS

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

STUDY FUNDING/COMPETING INTEREST(S)

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

TRIAL REGISTRATION NUMBER

N/A.

Human blastocyst spontaneous collapse is associated with worse morphological quality and higher degeneration and aneuploidy rates: a comprehensive analysis standardized through artificial intelligence

STUDY QUESTION

What are the factors associated with human blastocyst spontaneous collapse and the consequences of this event?

SUMMARY ANSWER

Approximately 50% of blastocysts collapsed, especially when non-viable, morphologically poor and/or aneuploid.

WHAT IS KNOWN ALREADY

Time-lapse microscopy (TLM) is a powerful tool to observe preimplantation development dynamics. Lately, artificial intelligence (AI) has been harnessed to automate and standardize such observations. Here, we adopted AI to comprehensively portray blastocyst spontaneous collapse, namely the phenomenon of reduction in size of the embryo accompanied by efflux of blastocoel fluid and the detachment of the trophectoderm (TE) from the zona pellucida (ZP). Although the underlying causes are unknown, blastocyst spontaneous collapse deserves attention as a possible marker of reduced competence.

STUDY DESIGN, SIZE, DURATION

An observational study was carried out, including 2348 TLM videos recorded during preimplantation genetic testing for aneuploidies (PGT-A, n = 720) cycles performed between January 2013 and December 2020. All embryos in the analysis at least reached the time of starting blastulation (tSB), 1943 of them reached full expansion, and were biopsied and then vitrified.

PARTICIPANTS/MATERIALS, SETTING, METHODS

ICSI, blastocyst culture, TE biopsy without Day 3 ZP drilling, comprehensive chromosome testing and vitrification were performed. The AI software automatically registered tSB and time of expanding blastocyst (tEB), start and end time of each collapse, time between consecutive collapses, embryo proper area, percentage of shrinkage, embryo:ZP ratio at embryo collapse, time of biopsy (t-biopsy) and related area of the fully (re-)expanded blastocyst before biopsy, time between the last collapse and biopsy. Blastocyst morphological quality was defined according to both Gardner's criteria and an AI-generated implantation score. Euploidy rate per biopsied blastocyst and live birth rate (LBR) per euploid single embryo transfer (SET) were the main outcomes. All significant associations were confirmed through regression analyses. All couple, cycle and embryo main features were also investigated for possible associations with blastocyst spontaneous collapse.

MAIN RESULTS AND THE ROLE OF CHANCE

At least one collapsing embryo (either viable or subsequently undergoing degeneration) was recorded in 559 cycles (77.6%) and in 498 cycles (69.2%) if considering only viable blastocysts. The prevalence of blastocyst spontaneous collapse after the tSB, but before the achievement of full expansion, was 50% (N = 1168/2348), irrespective of cycle and/or couple characteristics. Blastocyst degeneration was 13% among non-collapsing embryos, while it was 18%, 20%, 26% and 39% among embryos collapsing once, twice, three times or ≥4 times, respectively. The results showed that 47.3% (N = 918/1943) of the viable blastocysts experienced at least one spontaneous collapse (ranging from 1 up to 9). Although starting from similar tSB, the number of spontaneous collapses was associated with a delay in both tEB and time of biopsy. Of note, the worse the quality of a blastocyst, the more and the longer its spontaneous collapses. Blastocyst spontaneous collapse was significantly associated with lower euploidy rates (47% in non-collapsing and 38%, 32%, 31% and 20% in blastocysts collapsing once, twice, three times or ≥4 times, respectively; multivariate odds ratio 0.78, 95%CI 0.62-0.98, adjusted P = 0.03). The difference in the LBR after euploid vitrified-warmed SET was not significant (46% and 39% in non-collapsing and collapsing blastocysts, respectively).

LIMITATIONS, REASONS FOR CAUTION

An association between chromosomal mosaicism and blastocyst collapse cannot be reliably assessed on a single TE biopsy. Gestational and perinatal outcomes were not evaluated. Other culture strategies and media should be tested for their association with blastocyst spontaneous collapse. Future studies with a larger sample size are needed to investigate putative impacts on clinical outcomes after euploid transfers.

WIDER IMPLICATIONS OF THE FINDINGS

These results demonstrate the synergistic power of TLM and AI to increase the throughput of embryo preimplantation development observation. They also highlight the transition from compaction to full blastocyst as a delicate morphogenetic process. Blastocyst spontaneous collapse is common and associates with inherently lower competence, but additional data are required to deepen our knowledge on its causes and consequences.

STUDY FUNDING/COMPETING INTEREST(S)

There is no external funding to report. I.E., A.B.-M., I.H.-V. and B.K. are Fairtility employees. I.E. and B.K. also have stock or stock options of Fairtility.

TRIAL REGISTRATION NUMBER

N/A.

Brain response to emotional faces in anxiety and depression: neural predictors of cognitive behavioral therapy outcome and predictor-based subgroups following therapy

BACKGROUND

Neuroimaging studies have shown variance in brain response to emotional faces predicts cognitive behavioral therapy (CBT) outcome. An important next step is to determine if individual differences in neural predictors of CBT response represent distinct patient groups.

METHODS

In total, 90 patients with internalizing disorders completed a face-matching task during functional magnetic resonance imaging before and after 12 weeks of CBT and 45 healthy controls completed the task before and after 12 weeks. Patients exhibiting a pre-to-post CBT >50% reduction in symptom severity on two measures were considered treatment responders. Regions of interest (ROIs) for angry, fearful, and happy faces were submitted to receiver operating characteristic (ROC) curve analysis. Significant ROIs were then submitted to decision tree analysis to classify responder/non-responder subgroups. Psychophysiological interactions (PPI) were used to explore functional connectivity in the region(s) that delineated subgroups.

RESULTS

A total of 51 patients were treatment responders and ROC curve results were significant for all face types though specific regions varied. Decision tree results revealed superior occipital response to angry faces identified patient subgroups such that the subgroup with 'high' occipital activity had more responders than the 'low' occipital subgroup. Following CBT, the high, relative to low, occipital subgroup was less symptomatic. Controls exhibited stable superior occipital activation over time. Whole-brain PPI showed reduced baseline superior occipital-postcentral gyrus functional connectivity in responders compared to non-responders.

CONCLUSIONS

Preliminary findings indicate patients characterized by relatively more pre-treatment superior occipital gyrus engagement to angry faces and reduced superior occipital-postcentral gyrus connectivity, relative to non-responders, may represent a phenotype likely to benefit from CBT.

Zygote Diameter and Total Cytoplasmic Volume as Useful Predictive Tools of Blastocyst Quality

Introduction According to the Embryo Protection Act, the selection of embryos with the greatest potential for successful implantation in Germany must be performed in the pronucleus stage. The main aim of this study was to identify morphokinetic parameters that could serve as noninvasive biomarkers of blastocyst quality in countries with restrictive reproductive medicine laws. Materials and Methods The sample comprised 191 embryos from 40 patients undergoing antagonist cycles for intracytoplasmic sperm injection. Blastocysts were cultured in an EmbryoScope chamber and video records were validated to determine the post-injection timing of various developmental stages, cleavage stages, and blastocyst formation. The Gardner and Schoolcraft scoring system was used to characterize blastocyst quality. Results Morphokinetic data showed that the zygote diameter and total cytoplasmic volume were significantly different between good and poor blastocysts quality groups, where zygotes, which formed better blastocyst quality, had smaller diameter and smaller total cytoplasmic volume. Zygotes with more rapid pronuclear disappearance developed in better-quality blastocysts. Differences between good- and poor-quality blastocysts were also observed for late-stage parameters and for the spatial arrangement of blastomere where tetrahedral embryos more frequently forming good-quality blastocyst compare to the non-tetrahedral. Conclusions The study findings could be used to enhance embryo selection, especially in countries with strict Embryo Law Regulations. Further studies, including those in which the implantation potential and pregnancy rate are considered, are warranted to confirm these preliminary results.

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

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

Evaluating ADHD Assessment for Dogs: A Replication Study

The family dog, in its natural environment, exhibits neuropsychological deficits redolent of human psychiatric disorders, including behaviours similar to human Attention-Deficit/Hyperactivity Disorder (ADHD) symptoms. For dogs, Vas and colleagues developed a 13-item questionnaire to measure inattention and hyperactivity/impulsivity (Dog ARS; 2007). We re-assessed, in a large sample of dogs (N = 319), psychometric properties of the Dog ARS, to identify possible limitations as a basis for further development. We examined the cross-study stability of factor structure and 40-day temporal stability of item and subscale scores and compared owner-report with expert (dog trainer)-report (n = 86), paralleling human parent/teacher assessments. To identify ambiguous items, we administered a modified version (including “I don’t know” options, N = 520) to a different sample. We could replicate the factor structure with evidence of good internal consistency and test–retest reliability of both subscales. Agreement between owner and trainer ratings was fair (inattention) and moderate (hyperactivity/impulsivity). Three ambiguous items were identified. Overall, we claim that the Dog ARS is a reliable tool to assess ADHD-like behaviour in dogs, but in its current form, it is not suitable to detect diagnosable individuals, as it does not comprise items assessing functional impairment, and also, the inclusion of owner-expert ratings in the evaluation process would be necessary.

Deep Learning-Enabled Technologies for Bioimage Analysis

Deep learning (DL) is a subfield of machine learning (ML), which has recently demonstrated its potency to significantly improve the quantification and classification workflows in biomedical and clinical applications. Among the end applications profoundly benefitting from DL, cellular morphology quantification is one of the pioneers. Here, we first briefly explain fundamental concepts in DL and then we review some of the emerging DL-enabled applications in cell morphology quantification in the fields of embryology, point-of-care ovulation testing, as a predictive tool for fetal heart pregnancy, cancer diagnostics via classification of cancer histology images, autosomal polycystic kidney disease, and chronic kidney diseases.

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.

Time Series Prediction of Viable Embryo and Automatic Grading in IVF using Deep Learning

Background:

The process of In Vitro Fertilization (IVF) involves collecting multiple samples of mature eggs that are fertilized with sperms in the IVF laboratory. They are eventually graded, and the most viable embryo out of all the samples is selected for transfer in the mother’s womb for a healthy pregnancy. Currently, the process of grading and selecting the healthiest embryo is performed by visual morphology, and manual records are maintained by embryologists.

Objectives:

Maintaining manual records makes the process very tedious, time-consuming, and error-prone. The absence of a universal grading leads to high subjectivity and low success rate of pregnancy. To improve the chances of pregnancy, multiple embryos are transferred in the womb elevating the risk of multiple pregnancies. In this paper, we propose a deep learning-based method to perform the automatic grading of the embryos using time series prediction with Long Short Term Memory (LSTM) and Convolutional Neural Network (CNN).

Methods:

CNN extracts the features of the images of embryos, and a sequence of such features is fed to LSTM for time series prediction, which gives the final grade.

Results:

Our model gave an ideal accuracy of 100% on training and validation. A comparison of obtained results is made with those obtained from a GRU model as well as other pre-trained models.

Conclusion:

The automated process is robust and eliminates subjectivity. The days-long hard work can now be replaced with our model, which gives the grading within 8 seconds with a GPU.

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.

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

PURPOSE

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

METHODS

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

RESULTS

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

CONCLUSION

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

Inter-centre reliability in embryo grading across several IVF clinics is limited: implications for embryo selection

RESEARCH QUESTION

What is the intra- and inter-centre reliability in embryo grading performed according to the Istanbul Consensus across several IVF clinics?

DESIGN

Forty Day 3 embryos and 40 blastocysts were photographed on three focal planes. Senior and junior embryologists from 65 clinics were invited to grade them according to the Istanbul Consensus (Study Phase I). All participants then attended interactive training where a panel of experts graded the same embryos (Study Phase II). Finally, a second set of pictures was sent to both embryologists and experts for a blinded evaluation (Study Phase III). Intra-centre reliability was reported for Study Phase I as Cohen's kappa between senior and junior embryologists; inter-centre reliability was instead calculated between senior/junior embryologists and experts in Study Phase I versus III to outline improvements after training (i.e. upgrade of Cohen's kappa category according to Landis and Koch).

RESULTS

Thirty-six embryologists from 18 centres participated (28% participation rate). The intra-centre reliability was (i) substantial (0.63) for blastomere symmetry (range -0.02 to 1.0), (ii) substantial (0.72) for fragmentation (range 0.29-1.0), (iii) substantial (0.66) for blastocyst expansion (range 0.19-1.0), (iv) moderate (0.59) for inner cell mass quality (range 0.07-0.92), (v) moderate (0.56) for trophectoderm quality (range 0.01-0.97). The inter-centre reliability showed an overall improvement from Study Phase I to III, from fair (0.21-0.4) to moderate (0.41-0.6) for all parameters under analysis, except for blastomere fragmentation among senior embryologists, which was already moderate before training.

CONCLUSIONS

Intra-centre reliability was generally moderate/substantial, while inter-centre reliability was just fair. The interactive training improved it to moderate, hence this workflow was deemed helpful. The establishment of external quality assessment services (e.g. UK NEQAS) and the avant-garde of artificial intelligence might further improve the reliability of this key practice for embryo selection.

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.

Artificial intelligence in the fertility clinic: status, pitfalls and possibilities

In recent years, the amount of data produced in the field of ART has increased exponentially. The diversity of data is large, ranging from videos to tabular data. At the same time, artificial intelligence (AI) is progressively used in medical practice and may become a promising tool to improve success rates with ART. AI models may compensate for the lack of objectivity in several critical procedures in fertility clinics, especially embryo and sperm assessments. Various models have been developed, and even though several of them show promising performance, there are still many challenges to overcome. In this review, we present recent research on AI in the context of ART. We discuss the strengths and weaknesses of the presented methods, especially regarding clinical relevance. We also address the pitfalls hampering successful use of AI in the clinic and discuss future possibilities and important aspects to make AI truly useful for ART.

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.

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.

Early embryo morphokinetics is a better predictor of post-ICSI live birth than embryo morphology: speed is more important than beauty at the cleavage stage

Given the importance of embryo developmental competence assessment in reproductive medicine and biology, the aim of this study was to compare the performance of fertilization and cleavage morphokinetics with embryo morphology to predict post-ICSI live birth. Data from embryos cultured in a time-lapse microscopy (TLM) incubator and with known live birth outcomes (LB: embryos achieving live birth, n = 168; NLB: embryos not achieving live birth, n = 1633) were used to generate receiver operating characteristic (ROC) curves based on morphokinetic or morphological scores, and the respective areas under the curve (AUC) were compared. The association between live birth and 12 combinations of four morphokinetic quality degrees (A-D) with three morphological quality degrees (A-C) was assessed using multivariate analysis. Morphokinetic parameters from tPNa to t8 were reached earlier in LB compared with NLB embryos. The ROC curve analysis indicated that morphokinetic information is more accurate than conventional morphology to predict live birth [AUC = 0.64 (95% CI 0.58-0.70) versus AUC = 0.58 (95% CI 0.51-0.65)]. The multivariate analysis was in line with AUCs, revealing that embryos with poor morphokinetics, independently of their morphology, provide lower live birth rates (P < 0.001). A considerable percentage of embryos with top morphology presented poor morphokinetics (20.10%), accompanied by a severely reduced live birth rate in comparison with embryos with top morphology and morphokinetics (P < 0.001). In conclusion, TLM-derived early morphokinetic parameters were more predictive of live-birth achievement following ICSI than conventional morphology.

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.

Use of time-lapse monitoring in medically assisted reproduction treatments: a mini-review

During human in vitro culture, a morphological microscope analysis is normally performed to select the best embryo to transfer, with the hope of obtaining a successful pregnancy. The morphological evaluation may combine number and size of blastomeres, fragmentation, multinucleation, blastocyst expansion, inner-cell mass and trophectoderm appearance. However, standard microscopy evaluation involves the removal of the embryos from the incubator, exposing them to changes in pH, temperature, and oxygen level. Additionally, morphological assessments might include high inter-observer variability. Recently, continuous embryo culture using time-lapse monitoring (TLM) has allowed embryologists to analyse the dynamic and morphokinetic events of embryo development and, based on that, the embryologist is able to scrutinize the complete sequence of embryonic evolution, from fertilization to the blastocyst formation. Therefore, TLM allows an uninterrupted culture condition, reducing the need to remove embryos from the incubator. The monitoring system is normally composed of a standard incubator with an integrated microscope coupled to a digital camera, which is able to collect images at regular times, and subsequently processed into video. These data can be annotated and analyzed using an integrated software, therefore this allows embryologists to facilitate the process of embryo selection for transfer. The main aim of this paper is to discuss the potential benefits and uses of the TLM in the embryology laboratory.

Time-lapse imaging derived morphokinetic variables reveal association with implantation and live birth following in vitro fertilization: A retrospective study using data from transferred human embryos

The purpose of this retrospective time-lapse data analysis from transferred preimplantation human embryos was to identify early morphokinetic cleavage variables that are related to implantation and live birth following in vitro fertilization (IVF). All embryos were monitored from fertilization check until embryo transfer for a minimum of 44 hours. The study was designed to assess the association between day 2 embryo morphokinetic variables with implantation and live birth based on Known Implantation Data (KID). The kinetic variables were subjected to quartile-based analysis. The predictive ability for implantation and live birth was studied using receiver operator characteristic (ROC) curves. Three morphokinetic variables, time to 2-cells (t2), duration of second cell cycle (cc2) below one threshold and cc2 above another threshold had the highest predictive value with regards to implantation and live birth following IVF treatment. The predictive pre-transfer information has little divergence between fetal heartbeat and live birth data and therefore, at least for early morphokinetic variables up to the four-cell stage (t4), conclusions and models based on fetal heartbeat data can be expected to be valid for live birth datasets as well. The three above mentioned variables (t2, cc2 below one threshold and cc2 above another threshold) may supplement morphological evaluation in embryo selection and thereby improve the outcome of in vitro fertilization treatments.

An artificial intelligence model based on the proteomic profile of euploid embryos and blastocyst morphology: a preliminary study

RESEARCH QUESTION

The study aimed to develop an artificial intelligence model based on artificial neural networks (ANNs) to predict the likelihood of achieving a live birth using the proteomic profile of spent culture media and blastocyst morphology.

DESIGN

This retrospective cohort study included 212 patients who underwent single blastocyst transfer at IVI Valencia. A single image of each of 186 embryos was studied, and the protein profile was analysed in 81 samples of spent embryo culture medium from patients included in the preimplantation genetic testing programme. The information extracted from the analyses was used as input data for the ANN. The multilayer perceptron and the back-propagation learning method were used to train the ANN. Finally, predictive power was measured using the area under the curve (AUC) of the receiver operating characteristic curve.

RESULTS

Three ANN architectures classified most of the embryos correctly as leading (LB+) or not leading (LB-) to a live birth: 100.0% for ANN1 (morphological variables and two proteins), 85.7% for ANN2 (morphological variables and seven proteins), and 83.3% for ANN3 (morphological variables and 25 proteins). The artificial intelligence model using information extracted from blastocyst image analysis and concentrations of interleukin-6 and matrix metalloproteinase-1 was able to predict live birth with an AUC of 1.0.

CONCLUSIONS

The model proposed in this preliminary report may provide a promising tool to select the embryo most likely to lead to a live birth in a euploid cohort. The accuracy of prediction demonstrated by this software may improve the efficacy of an assisted reproduction treatment by reducing the number of transfers per patient. Prospective studies are, however, needed.

Mining of variables from embryo morphokinetics, blastocyst's morphology and patient parameters: an approach to predict the live birth in the assisted reproduction service

Based on growing demand for assisted reproduction technology, improved predictive models are required to optimize in vitro fertilization/intracytoplasmatic sperm injection strategies, prioritizing single embryo transfer. There are still several obstacles to overcome for the purpose of improving assisted reproductive success, such as intra- and inter-observer subjectivity in embryonic selection, high occurrence of multiple pregnancies, maternal and neonatal complications. Here, we compare studies that used several variables that impact the success of assisted reproduction, such as blastocyst morphology and morphokinetic aspects of embryo development as well as characteristics of the patients submitted to assisted reproduction, in order to predict embryo quality, implantation or live birth. Thereby, we emphasize the proposal of an artificial intelligence-based platform for a more objective method to predict live birth.

Assessing equine embryo developmental competency by time-lapse image analysis

The timing of early mitotic events during preimplantation embryo development is important for subsequent embryogenesis in many mammalian species, including mouse and human, but, to date, no study has closely examined mitotic timing in equine embryos from oocytes obtained by ovum pick-up. Here, cumulus-oocyte complexes were collected by transvaginal follicular aspiration, matured invitro and fertilised via intracytoplasmic sperm injection. Each fertilised oocyte was cultured up to the blastocyst stage and monitored by time-lapse imaging for the measurement of cell cycle intervals and identification of morphological criteria indicative of developmental potential. Of the 56 fertilised oocytes, 35 initiated mitosis and 11 progressed to the blastocyst stage. Analysis of the first three mitotic divisions in embryos that formed blastocysts determined that typical blastocyst timing (median±IQR) is 30.0±17.5min, 8.8±1.7h and 0.6±1.4h respectively. Frequent cellular fragmentation, multipolar divisions and blastomere exclusion suggested that equine embryos likely contend with a high incidence of chromosomal missegregation. Indeed, chromosome-containing micronuclei and multinuclei with extensive DNA damage were observed throughout preimplantation embryogenesis. This indicates that time-lapse image analysis may be used as a non-invasive method to assess equine embryo quality in future studies.

Novel and conventional embryo parameters as input data for artificial neural networks: an artificial intelligence model applied for prediction of the implantation potential

OBJECTIVE

To describe novel embryo features capable of predicting implantation potential as input data for an artificial neural network (ANN) model.

DESIGN

Retrospective cohort study.

SETTING

University-affiliated private IVF center.

PATIENT(S)

This study included 637 patients from the oocyte donation program who underwent single-blastocyst transfer during two consecutive years.

INTERVENTION(S)

None.

MAIN OUTCOME MEASURE(S)

The research was divided into two phases. Phase 1 consisted of the description and analysis of the following embryo features in implanted and nonimplanted embryos: distance and speed of pronuclear migration, blastocyst expanded diameter, inner cell mass area, and trophectoderm cell cycle length. Phase 2 consisted of the development of an ANN algorithm for implantation prediction. Results were obtained for four models fed with different input data. The predictive power was measured with the use of the area under the receiver operating characteristic curve (AUC).

RESULT(S)

Out of the five novel described parameters, blastocyst expanded diameter and trophectoderm cell cycle length had statistically different values in implanted and nonimplanted embryos. After the ANN models were trained and validated using fivefold cross-validation, they were capable of predicting implantation on testing data with AUCs of 0.64 for ANN1 (conventional morphokinetics), 0.73 for ANN2 (novel morphodynamics), 0.77 for ANN3 (conventional morphokinetics + novel morphodynamics), and 0.68 for ANN4 (discriminatory variables from statistical test).

CONCLUSION(S)

The novel proposed embryo features affect the implantation potential, and their combination with conventional morphokinetic parameters is effective as input data for a predictive model based on artificial intelligence.

Time-lapse imaging: the state of the art†

The introduction of time-lapse imaging to clinical in vitro fertilization practice enabled the undisturbed monitoring of embryos throughout the entire culture period. Initially, the main objective was to achieve a better embryo development. However, this technology also provided an insight into the novel concept of morphokinetics, parameters regarding embryo cell dynamics. The vast amount of data obtained defined the optimal ranges in the cell-cycle lengths at different stages of embryo development. This added valuable information to embryo assessment prior to transfer. Kinetic markers became part of embryo evaluation strategies with the potential to increase the chances of clinical success. However, none of them has been established as an international standard. The present work aims at describing new approaches into time-lapse: progress to date, challenges, and possible future directions.