Screening Human Embryos for Polygenic Traits Has Limited Utility.

The increasing proportion of variance in human complex traits explained by polygenic scores, along with progress in preimplantation genetic diagnosis, suggests the possibility of screening embryos for traits such as height or cognitive ability. However, the expected outcomes of embryo screening are unclear, which undermines discussion of associated ethical concerns. Here, we use theory, simulations, and real data to evaluate the potential gain of embryo screening, defined as the difference in trait value between the top-scoring embryo and the average embryo. The gain increases very slowly with the number of embryos but more rapidly with the variance explained by the score. Given current technology, the average gain due to screening would be ≈2.5 cm for height and ≈2.5 IQ points for cognitive ability. These mean values are accompanied by wide prediction intervals, and indeed, in large nuclear families, the majority of children top-scoring for height are not the tallest.

A comparison of morphokinetic models and morphological selection for prioritizing euploid embryos: a multicentre cohort study.

STUDY QUESTION: Are morphokinetic models better at prioritizing a euploid embryo for transfer over morphological selection by an embryologist? SUMMARY ANSWER: Morphokinetic algorithms lead to an improved prioritization of euploid embryos when compared to embryologist selection. WHAT IS KNOWN ALREADY: PREFER (predicting euploidy for embryos in reproductive medicine) is a previously published morphokinetic model associated with live birth and miscarriage. The second model uses live birth as the target outcome (LB model). STUDY DESIGN, SIZE, DURATION: Data for this cohort study were obtained from 1958 biopsied blastocysts at nine IVF clinics across the UK from January 2021 to December 2022. PARTICIPANTS/MATERIALS, SETTING, METHODS: The ability of the PREFER and LB models to prioritize a euploid embryo was compared against arbitrary selection and the prediction of four embryologists using the timelapse video, blinded to the morphokinetic time stamp. The comparisons were made using calculated percentages and normalized discounted cumulative gain (NDCG), whereby an NDCG score of 1 would equate to all euploid embryos being ranked first. In arbitrary selection, the ploidy status was randomly assigned within each cycle and the NDGC calculated, and this was then repeated 100 times and the mean obtained. MAIN RESULTS AND THE ROLE OF CHANCE: Arbitrary embryo selection would rank a euploid embryo first 37% of the time, embryologist selection 39%, and the LB and PREFER ploidy morphokinetic models 46% and 47% of the time, respectively. The AUC for LB and PREFER model was 0.62 and 0.63, respectively. Morphological selection did not significantly improve the performance of both morphokinetic models when used in combination. There was a significant difference between the NDGC metric of the PREFER model versus embryologist selection at 0.96 and 0.87, respectively (t = 14.1, P < 0.001). Similarly, there was a significant difference between the LB model and embryologist selection with an NDGC metric of 0.95 and 0.87, respectively (t = 12.0, P < 0.001). All four embryologists ranked embryos similarly, with an intraclass coefficient of 0.91 (95% CI 0.82-0.95, P < 0.001). LIMITATIONS, REASONS FOR CAUTION: Aside from the retrospective study design, limitations include allowing the embryologist to watch the time lapse video, potentially providing more information than a truly static morphological assessment. Furthermore, the embryologists at the participating centres were familiar with the significant variables in time lapse, which could bias the results. WIDER IMPLICATIONS OF THE FINDINGS: The present study shows that the use of morphokinetic models, namely PREFER and LB, translates into improved euploid embryo selection. STUDY FUNDING/COMPETING INTEREST(S): This study received no specific grant funding from any funding agency in the public, commercial or not-for-profit sectors. Dr Alison Campbell is minor share holder of Care Fertility. All other authors have no conflicts of interest to declare. Time lapse is a technology for which patients are charged extra at participating centres. TRIAL REGISTRATION NUMBER: N/A.

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.

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

PURPOSE: The introduction of the time-lapse monitoring system (TMS) and the development of predictive algorithms could contribute to the optimal embryos selection for transfer. Therefore, the present study aims at investigating the efficiency of KIDScore and iDAScore systems for blastocyst stage embryos in predicting live birth events. METHODS: The present retrospective study was conducted in a private IVF Unit setting throughout a 10-month period from October 2021 to July 2022, and included the analysis of 429 embryos deriving from 91 IVF/ICSI cycles conducted due to infertility of various etiologies. Embryos incubated at the Embryoscope+ timelapse incubator were analyzed through the established scoring systems: KIDScore and iDAScore®. The main outcome measure was the comparison of the two scoring systems in terms of live birth prediction. Embryos with the higher scores at day 5 (KID5 score/iDA5 score) were transferred or cryopreserved for later use. RESULTS: Embryos with high KID5 and iDA5 scores positively correlated with the probability of successful live birth, with KID5 score yielding a higher efficiency in predicting a successful reproductive outcome compared to a proportionally high iDA5 score. KID5 demonstrated conservative performance in successfully predicting live birth compared to iDA5 score, indicating that an efficient prediction can be either provided by a relatively lower KID5 score or a relatively higher iDA5 score. CONCLUSION: The developed artificial intelligence tools should be implemented in clinical practice in conjunction with the conventional morphological assessment for the conduction of optimized embryo transfer in terms of a successful live birth.

Clinical outcomes of single blastocyst transfer with machine learning guided noninvasive chromosome screening grading system in infertile patients.

BACKGROUND: Prospective observational studies have demonstrated that the machine learning (ML) -guided noninvasive chromosome screening (NICS) grading system, which we called the noninvasive chromosome screening-artificial intelligence (NICS-AI) grading system, can be used embryo selection. The current prospective interventional clinical study was conducted to investigate whether this NICS-AI grading system can be used as a powerful tool for embryo selection. METHODS: Patients who visited our centre between October 2018 and December 2021 were recruited. Grade A and B embryos with a high probability of euploidy were transferred in the NICS group. The patients in the control group selected the embryos according to the traditional morphological grading. Finally, 90 patients in the NICS group and 161 patients in the control group were compared statistically for their clinical outcomes. RESULTS: In the NICS group, the clinical pregnancy rate (70.0% vs. 54.0%, p < 0.001), the ongoing pregnancy rate (58.9% vs. 44.7%, p = 0.001), and the live birth rate (56.7% vs. 42.9%, p = 0.001) were significantly higher than those of the control group. When the female was ≥ 35 years old, the clinical pregnancy rate (67.7% vs. 32.1%, p < 0.001), ongoing pregnancy rate (56.5% vs. 25.0%, p = 0.001), and live birth rate (54.8% vs. 25.0%, p = 0.001) in the NICS group were significantly higher than those of the control group. Regardless of whether the patients had a previous record of early spontaneous abortion or not, the live birth rate of the NICS group was higher than that of the control group (61.0% vs. 46.9%; 57.9% vs. 34.8%; 33.3% vs. 0%) but the differences were not statistically significant. CONCLUSIONS: NICS-AI was able to improve embryo utilisation rate, and the live birth rate, especially for those ≥ 35 years old, with transfer of Grade A embryos being preferred, followed by Grade B embryos. NICS-AI can be used as an effective tool for embryo selection in the future.

Formation of the first plane of division relative to the pronuclear axis predicts embryonic ploidy.

RESEARCH QUESTION: Is there a relationship between the pronuclear axis and the first cleavage plane formation in human pronuclear-stage embryos, and what are the effects on ploidy and clinical pregnancy rates? DESIGN: Transferred embryos were followed up until their prognoses. A total of 762 embryos formed two cells and reached the blastocyst stage after normal fertilization in a time-lapse incubator. Embryos were classified into three groups: group A: embryos in which the first plane of division was formed parallel to the axis of the pronucleus; group B: embryos in which cases of oblique formation were observed; and group C: embryos in which cases of perpendicular formation were observed. RESULTS: The euploidy rate was significantly higher in groups A and B than those in group C (P < 0.01), whereas the aneuploidy rate was significantly higher in group C (P < 0.01) than in groups A and B. No differences were found between the three groups in frequency of positive HCG-based pregnancy tests, frequency of clinical pregnancies, miscarriage rates or delivery rates. CONCLUSIONS: The formation pattern of the first plane of division relative to the pronuclear axis was a predictor of embryonic ploidy, with a reduced rate of euploidy and a high probability of aneuploidy observed when the first plane of division was perpendicular to the pronuclear axis.

Beyond black-box models: explainable AI for embryo ploidy prediction and patient-centric consultation.

PURPOSE: To determine if an explainable artificial intelligence (XAI) model enhances the accuracy and transparency of predicting embryo ploidy status based on embryonic characteristics and clinical data. METHODS: This retrospective study utilized a dataset of 1908 blastocyst embryos. The dataset includes ploidy status, morphokinetic features, morphology grades, and 11 clinical variables. Six machine learning (ML) models including Random Forest (RF), Linear Discriminant Analysis (LDA), Logistic Regression (LR), Support Vector Machine (SVM), AdaBoost (ADA), and Light Gradient-Boosting Machine (LGBM) were trained to predict ploidy status probabilities across three distinct datasets: high-grade embryos (HGE, n = 1107), low-grade embryos (LGE, n = 364), and all-grade embryos (AGE, n = 1471). The model's performance was interpreted using XAI, including SHapley Additive exPlanations (SHAP) and Local Interpretable Model-agnostic Explanations (LIME) techniques. RESULTS: The mean maternal age was 38.5 ± 3.85 years. The Random Forest (RF) model exhibited superior performance compared to the other five ML models, achieving an accuracy of 0.749 and an AUC of 0.808 for AGE. In the external test set, the RF model achieved an accuracy of 0.714 and an AUC of 0.750 (95% CI, 0.702-0.796). SHAP's feature impact analysis highlighted that maternal age, paternal age, time to blastocyst (tB), and day 5 morphology grade significantly impacted the predictive model. In addition, LIME offered specific case-ploidy prediction probabilities, revealing the model's assigned values for each variable within a finite range. CONCLUSION: The model highlights the potential of using XAI algorithms to enhance ploidy prediction, optimize embryo selection as patient-centric consultation, and provides reliability and transparent insights into the decision-making process.

Time-lapse imaging of morula compaction for selecting high-quality blastocysts: a retrospective cohort study.

PURPOSE: Before blastocyst development, embryos undergo morphological and metabolic changes crucial for their subsequent growth. This study aimed to investigate the relationship between morula compaction and blastocyst formation and the subsequent chromosomal status of the embryos. METHODS: This retrospective cohort study evaluated embryo development (n = 371) using time-lapse imaging; 94 blastocysts underwent preimplantation genetic testing for aneuploidy (PGT-A). RESULTS: The embryos were classified as fully (Group 1, n = 194) or partially (Group 2, n = 177) compacted. Group 1 had significantly higher proportions of good- and average-quality blastocysts than Group 2 (21.6% vs. 3.4%, p = 0.001; 47.9% vs. 26.6%, p = 0.001, respectively). The time from the morula stage to the beginning and completion of compaction and blastocyst formation was significantly shorter in Group 1 than in Group 2 (78.6 vs. 82.4 h, p = 0.001; 87.0 vs. 92.2 h, p = 0.001; 100.2 vs. 103.7 h, p = 0.017, respectively). Group 1 embryos had larger surface areas than Group 2 embryos at various time points following blastocyst formation. Group 1 blastocysts had significantly higher average expansion rates than Group 2 blastocysts (653.6 vs. 499.2 µm2/h, p = 0.001). PGT-A revealed a higher proportion of euploid embryos in Group 1 than in Group 2 (47.2% vs. 36.6%, p = 0.303). CONCLUSION: Time-lapse microscopy uncovered a positive relationship between compaction and blastocyst quality and its association with embryo ploidy. Hence, compaction evaluation should be prioritized before blastocyst selection for transfer or cryopreservation.

Detection of Interleukin-1 ß (IL-1ß) in Single Human Blastocyst-Conditioned Medium Using Ultrasensitive Bead-Based Digital Microfluidic Chip and Its Relationship with Embryonic Implantation Potential.

The implantation of human embryos is a complex process involving various cytokines and receptors expressed by both endometrium and embryos. However, the role of cytokines produced by a single embryo in successful implantation is largely unknown. This study aimed to investigate the role of IL-1ß expressed in a single-embryo-conditioned medium (ECM) in embryo implantation. Seventy samples of single ECM were analyzed by a specially designed magnetic-beads-based microfluidic chip from 15 women. We discovered that IL-1ß level increased as the embryo developed, and the difference was significant. In addition, receiver operator characteristic (ROC) curves analysis showed a higher chance of pregnancy when the IL-1ß level on day 5 ECM was below 79.37 pg/mL and the difference between day 5 and day 3 was below 24.90 pg/mL. Our study discovered a possible association between embryonic proteomic expression and successful implantation, which might facilitate single-embryo transfer in the future by helping clinicians identify the embryo with the greatest implantation potential.

Developmental perturbation in human embryos: Clinical and biological significance learned from time-lapse images.

Background: Time-lapse technology (TLT) has gained widespread adoption worldwide. In addition to facilitating the undisturbed culture of embryos, TLT offers the unique capability of continuously monitoring embryos to detect spatiotemporal changes. Although these observed phenomena play a role in optimal embryo selection/deselection, the clinical advantages of introducing TLT remain unclear. However, manual annotation of embryo perturbation could facilitate a comprehensive assessment of developmental competence. This process requires a thorough understanding of embryo observation and the biological significance associated with developmental dogma and variation. This review elucidates the typical behavior and variation of each phenomenon, exploring their clinical significance and research perspectives. Methods: The MEDLINE database was searched using PubMed for peer-reviewed English-language original articles concerning human embryo development. Main findings: TLT allows the observation of consecutive changes in embryo morphology, serving as potential biomarkers for embryo assessment. In assisted reproductive technology laboratories, several phenomena have not revealed their mechanism, posing difficulties such as fertilization deficiency and morula arrest. Conclusion: A profound understanding of the biological mechanisms and significance of each phenomenon is crucial. Further collaborative efforts between the clinical and molecular fields following translational studies are required to advance embryonic outcomes and assessment.

Clinical validation of an automatic classification algorithm applied on cleavage stage embryos: analysis for blastulation, euploidy, implantation, and live-birth potential.

STUDY QUESTION: Is a commercially available embryo assessment algorithm for early embryo evaluation based on the automatic annotation of morphokinetic timings a useful tool for embryo selection in IVF cycles? SUMMARY ANSWER: The classification provided by the algorithm was shown to be significantly predictive, especially when combined with conventional morphological evaluation, for development to blastocyst, implantation, and live birth, but not for euploidy. WHAT IS KNOWN ALREADY: The gold standard for embryo selection is still morphological evaluation conducted by embryologists. Since the introduction of time-lapse technology to embryo culture, many algorithms for embryo selection have been developed based on embryo morphokinetics, providing complementary information to morphological evaluation. However, manual annotations of developmental events and application of algorithms can be time-consuming and subjective processes. The introduction of automation to morphokinetic annotations is a promising approach that can potentially reduce subjectivity in the embryo selection process and improve the workflow in IVF laboratories. STUDY DESIGN, SIZE, DURATION: This observational, retrospective cohort study was performed in a single IVF clinic between 2018 and 2021 and included 3736 embryos from oocyte donation cycles (423 cycles) and 1291 embryos from autologous cycles with preimplantation genetic testing for aneuploidies (PGT-A, 185 cycles). Embryos were classified on Day 3 with a score from 1 (best) to 5 (worst) by the automatic embryo assessment algorithm. The performance of the embryo classification model for blastocyst development, implantation, live birth, and euploidy prediction was assessed. PARTICIPANTS/MATERIALS, SETTING, METHODS: All embryos were monitored by a time-lapse system with an automatic cell-tracking and embryo assessment software during culture. The embryo assessment algorithm was applied on Day 3, resulting in embryo classification from 1 to 5 (from highest to lowest developmental potential) depending on four parameters: P2 (t3-t2), P3 (t4-t3), oocyte age, and number of cells. There were 959 embryos selected for transfer on Day 5 or 6 based on conventional morphological evaluation. The blastocyst development, implantation, live birth, and euploidy rates (for embryos subjected to PGT-A) were compared between the different scores. The correlation of the algorithm scoring with the occurrence of those outcomes was quantified by generalized estimating equations (GEEs). Finally, the performance of the GEE model using the embryo assessment algorithm as the predictor was compared to that using conventional morphological evaluation, as well as to a model using a combination of both classification systems. MAIN RESULTS AND THE ROLE OF CHANCE: The blastocyst rate was higher with lower the scores generated by the embryo assessment algorithm. A GEE model confirmed the positive association between lower embryo score and higher odds of blastulation (odds ratio (OR) (1 vs 5 score) = 15.849; P < 0.001). This association was consistent in both oocyte donation and autologous embryos subjected to PGT-A. The automatic embryo classification results were also statistically associated with implantation and live birth. The OR of Score 1 vs 5 was 2.920 (95% CI 1.440-5.925; P = 0.003; E = 2.81) for implantation and 3.317 (95% CI 1.615-6.814; P = 0.001; E = 3.04) for live birth. However, this association was not found in embryos subjected to PGT-A. The highest performance was achieved when combining the automatic embryo scoring and traditional morphological classification (AUC for implantation potential = 0.629; AUC for live-birth potential = 0.636). Again, no association was found between the embryo classification and euploidy status in embryos subjected to PGT-A (OR (1 vs 5) = 0.755 (95% CI 0.255-0.981); P = 0.489; E = 1.57). LIMITATIONS, REASONS FOR CAUTION: The retrospective nature of this study may be a reason for caution, although the large sample size reinforced the ability of the model for embryo selection. WIDER IMPLICATIONS OF THE FINDINGS: Time-lapse technology with automated embryo assessment can be used together with conventional morphological evaluation to increase the accuracy of embryo selection process and improve the success rates of assisted reproduction cycles. To our knowledge, this is the largest embryo dataset analysed with this embryo assessment algorithm. STUDY FUNDING/COMPETING INTEREST(S): This research was supported by Agencia Valenciana de Innovació and European Social Fund (ACIF/2019/264 and CIBEFP/2021/13). In the last 5 years, M.M. received speaker fees from Vitrolife, Merck, Ferring, Gideon Richter, Angelini, and Theramex, and B.A.-R. received speaker fees from Merck. The remaining authors have no competing interests to declare. TRIAL REGISTRATION NUMBER: N/A.

A balancing act: sex selection after pre-implantation genetic testing for aneuploidy for first versus second baby.

STUDY QUESTION: How often do patients undergoing frozen embryo transfer (FET) after preimplantation genetic testing for aneuploidy (PGT-A) choose to select for sex and do sex selection rates differ before and after successful delivery of a first baby? SUMMARY ANSWER: When a choice was available between male and female embryos, patients selected the sex more frequently when trying to conceive the second child (62%) as compared to the first child (32.4%) and most commonly selected for the opposite sex of the first child. WHAT IS KNOWN ALREADY: Sex selection is widely available in US fertility clinics. However, the rate of sex selection for patients undergoing FET after PGT-A is unknown. STUDY DESIGN, SIZE, DURATION: This is a retrospective cohort study of 585 patients that took place between January 2013 and February 2021. PARTICIPANTS/MATERIALS, SETTING, METHODS: The study took place at a single, urban academic fertility center in the USA. Patients were included if they had a live birth after single euploid FET and returned for at least one subsequent euploid FET. The primary outcomes were the rates of sex selection for first versus second baby. Secondary outcomes were rate of selection for same versus opposite sex as first live birth and overall rate of selection for males versus females. MAIN RESULTS AND THE ROLE OF CHANCE: Five hundred and eighty-five patients underwent a total of 1560 single euploid FETs resulting in either one or two live births. A choice between male and female euploid embryos was available for 919 FETs (first child: 67.5% (519/769) versus second child: 50.6% (400/791), P < 0.01). When a choice was available, patients selected the sex more frequently when trying to conceive the second child (first child: 32.4% (168/519) versus second child: 62.0% (248/400), P < 0.01). When sex was selected after first live birth, the opposite sex of the first child was selected 81.8% (203/248 FETs) of the time. Of transfers that involved sex selection, rates of male and female selection were similar for the first child, but selection for females was greater for the second child (first child: 51.2% (86/168) male versus 48.9% (82/168) female, second child: 41.1% (102/248) male versus 58.9% (146/248) female, P < 0.04). LIMITATIONS, REASONS FOR CAUTION: The study was performed at one urban academic medical center in the Northeastern US, which may limit generalizability to other settings where PGT-A may be performed less frequently, or sex selection may be limited or not permitted. In addition, we could not reliably account for whether patients or their partners had prior children and if so, of what sex. WIDER IMPLICATIONS OF THE FINDINGS: Patients undergoing PGT-A with both male and female euploid embryos were more likely to select for sex when attempting a second child and usually selected for the opposite sex of their first child. These findings highlight the potential for family balancing for patients who undergo PGT-A in settings where sex selection is permitted. STUDY FUNDING/COMPETING INTEREST(S): This study received no funding. The authors have no conflicts of interest to declare. TRIAL REGISTRATION NUMBER: N/A.

Noninvasive metabolic profiling of cumulus cells, oocytes, and embryos via fluorescence lifetime imaging microscopy: a mini-review.

A major challenge in ART is to select high-quality oocytes and embryos. The metabolism of oocytes and embryos has long been linked to their viability, suggesting the potential utility of metabolic measurements to aid in selection. Here, we review recent work on noninvasive metabolic imaging of cumulus cells, oocytes, and embryos. We focus our discussion on fluorescence lifetime imaging microscopy (FLIM) of the autofluorescent coenzymes NAD(P)H and flavine adenine dinucleotide (FAD+), which play central roles in many metabolic pathways. FLIM measurements provide quantitative information on NAD(P)H and FAD+ concentrations and engagement with enzymes, leading to a robust means of characterizing the metabolic state of cells. We argue that FLIM is a promising approach to aid in oocyte and embryo selection.

Predicting the likelihood of live birth: an objective and user-friendly blastocyst grading system.

RESEARCH QUESTION: Can day-5 blastocysts be ranked according to their likelihood of live birth using an objective and user-friendly grading system? DESIGN: A retrospective multicentre study conducted between 2017 and 2019, including 1044 day-5 blastocysts. Blastocyst expansion degree, trophectoderm and inner cell mass quality were assessed morphologically and morphometrically. Several analyses were conducted: the association between the qualitative and quantitative assessment for the blastocyst expansion degree and the number of trophectoderm cells; the effect of the embryo quality on day 3 and the contribution of the three blastocyst parameters to live birth, with logistic regression; and a decision tree with the most significant variables to create the new scoring system. RESULTS: Cut-off points were found to discriminate between expanding and expanded blastocysts (165 µm for blastocyst diameter) and between trophectoderm grades (A: ≥14 cells; B: 11-13 cells; C: ≤10 cells). When the embryos reached the blastocyst stage, their quality on day 3 did not add predictive value for implantation and live birth. In the logistic regression analysis, the only parameter capable of significantly predicting the live birth likelihood was the trophectoderm grade: A versus C (OR 1.95, 95% CI 1.26 to 3.0); B versus C (OR 1.71, 95% CI 1.22 to 2.4). The decision tree supported the finding that the trophectoderm grade had the highest predictive value for a live birth, followed by the blastocyst expansion degree in a second step. CONCLUSIONS: This new method makes objective blastocyst assessment feasible, allowing for standardization and exportation to other laboratories worldwide.

Does embryo categorization by existing artificial intelligence, morphokinetic or morphological embryo selection models correlate with blastocyst euploidy rates?

RESEARCH QUESTION: Does embryo categorization by existing artificial intelligence (AI), morphokinetic or morphological embryo selection models correlate with blastocyst euploidy? DESIGN: A total of 834 patients (mean maternal age 40.5 ± 3.4 years) who underwent preimplantation genetic testing for aneuploidies (PGT-A) on a total of 3573 tested blastocysts were included in this retrospective study. The cycles were stratified into five maternal age groups according to the Society for Assisted Reproductive Technology age groups (<35, 35-37, 38-40, 41-42 and >42 years). The main outcome of this study was the correlation of euploidy rates in stratified maternal age groups and an automated AI model (iDAScore® v1.0), a morphokinetic embryo selection model (KIDScore Day 5 ver 3, KS-D5) and a traditional morphological grading model (Gardner criteria), respectively. RESULTS: Euploidy rates were significantly correlated with iDAScore (P = 0.0035 to <0.001) in all age groups, and expect for the youngest age group, with KS-D5 and Gardner criteria (all P < 0.0001). Additionally, multivariate logistic regression analysis showed that for all models, higher scores were significantly correlated with euploidy (all P < 0.0001). CONCLUSION: These results show that existing blastocyst scoring models correlate with ploidy status. However, as these models were developed to indicate implantation potential, they cannot accurately diagnose if an embryo is euploid or aneuploid. Instead, they may be used to support the decision of how many and which blastocysts to biopsy, thus potentially reducing patient costs.

Correlations between a deep learning-based algorithm for embryo evaluation with cleavage-stage cell numbers and fragmentation.

RESEARCH QUESTION: Do cell numbers and degree of fragmentation in cleavage-stage embryos, assessed manually, correlate with evaluations made by deep learning algorithm model iDAScore v2.0? DESIGN: Retrospective observational study (n = 5040 embryos; 1786 treatments) conducted at two Swedish assisted reproductive technology centres between 2016 and 2021. Fresh single embryo transfer was carried out on days 2 or 3 after fertilization. Embryo evaluation using iDAScore v2.0 was compared with manual assessment of numbers of cells and grade of fragmentation, analysed by video sequences. RESULTS: Data from embryos transferred on days 2 and 3 showed that having three or fewer cells compared with four or fewer cells on day 2, and six or fewer cells versus seven to eight cells on day 3, correlated significantly with a difference in iDAScore (medians 2.4 versus 4.0 and 2.6 versus 4.6 respectively; both P < 0.001). The iDAScore for 0-10% fragmentation was significantly higher compared with the groups with higher fragmentation (P < 0.001). When combining cell numbers and fragmentation, iDAScore values decreased as fragmentation increased, regardless of cell number. iDAScore discriminated between embryos that resulted in live birth or no live birth (AUC of 0.627 and 0.607), compared with the morphological model (AUC of 0.618 and 0.585) for day 2 and day 3, respectively. CONCLUSIONS: The iDAScore v2.0 values correlated significantly with cell numbers and fragmentation scored manually for cleavage-stage embryos on days 2 and 3. iDAScore had some predictive value for live birth, conditional that embryo selection was based on morphology.

Interpretable artificial intelligence-assisted embryo selection improved single-blastocyst transfer outcomes: a prospective cohort study.

RESEARCH QUESTION: What is the pregnancy and neonatal outcomes of an interpretable artificial intelligence (AI) model for embryo selection in a prospective clinical trial? DESIGN: This single-centre prospective cohort study was carried out from October 2021 to March 2022. A total of 330 eligible patients were assigned to their preferred groups, with 250 patients undergoing a fresh single-blastocyst transfer cycle after the exclusion criteria had been applied. For the AI-assisted group (AAG), embryologists selected the embryos for transfer based on the ranking recommendations provided by an interpretable AI system, while with the manual group, embryologists used the Gardner grading system to make their decisions. RESULTS: The implantation rate was significantly higher in the AAG than the manual group (80.87% versus 68.15%, P = 0.022). No significant difference was found in terms of monozygotic twin rate, miscarriage rate, live birth rate and ectopic pregnancy rate between the groups. Furthermore, there was no significant difference in terms of neonatal outcomes, including gestational weeks, premature birth rate, birth height, birthweight, sex ratio at birth and newborn malformation rate. The consensus rate between the AI and retrospective analysis by the embryologists was significantly higher for good-quality embryos (i.e. grade 4BB or higher) versus poor-quality embryos (i.e. less than 4BB) (84.71% versus 25%, P < 0.001). CONCLUSIONS: These prospective trial results suggest that the proposed AI system could effectively help embryologists to improve the implantation rate with single-blastocyst transfer compared with traditional manual evaluation methods.

Novel image analyser-assisted morphometric methodology offer unique opportunity for selection of embryos with potential for implantation.

BACKGROUND: Previous studies looked into the connections between pregnancy and the Zona Pellucida (ZP) thickness and Zona Pellucida Thickness Variation (ZPTV), as well as the embryo's radius, circumference, perimeter and global symmetry. However, no research has linked embryo implantation and pregnancy to the percentage of ZP thinning, the reduction in ooplasm volume, and the increase in perivitelline space (PVS) volume. Our objective is to correlate the percentage of ZP thinning, the percentage of ooplasm volume shrinkage and the percentage of PVS increase to the implantation. These data will be used for embryo selection as well as it can be put into a software that will assist embryo selection. MATERIALS AND METHODS: Retrospective study included 281 patients, all of them had 2 embryos transferred, 149 patients got pregnant with two gestation sacs and 132 patients did not get pregnant. All of the transferred embryos had the ZP thickness measured several times from time of ICSI till Embryo Transfer (ET), the ooplasm volume was calculated from time of ICSI till two Pronuclei (2PN) fading and the PVS was calculated from the ICSI time till the 2PN fading. RESULTS: The first characteristic is the change in the average ZP thickness that decreased by 32.7% + 5.3% at 70 h for the implanted embryos (Group 1) versus 23.6% + 4.8% for non-implanted embryos (Group 2) p = 0.000. The second characteristic is the average reduction in the volume of the ooplasm which is 20.5% + 4.3% in Group 1 versus 15.1% + 5.2% in Group 2, p = 0.000. The third characteristic is the increase in the volume of the PVS which was 38.1% + 7.6% in Group 1 versus 31.6% + 9.7% in Group 2 p = 0.000. CONCLUSION: The implanted embryos showed higher percent of ZP thinning, higher percent of ooplasm reduction and higher percent of PVS increase.

Comparison of clinical outcomes for different morphological scores of D5 and D6 blastocysts in the frozen-thawed cycle.

BACKGROUND: Both embryo development speed and embryo morphology score played a significant role in frozen-thawed embryo transfer cycle (FET) outcomes. Most of the literature indicates that D5 embryos performed better than D6 embryos, although a few also indicate that there is no difference in clinical outcomes between D5 and D6 embryos. Clinically, D5 embryos are preferred for equal morphological scores. But how to choose embryos when the morphological score of D6 embryos is better than D5? METHODS: A retrospective study including 8199 frozen-thawed embryo transfers (FETs) was conducted to analyze patients who underwent IVF-FET from January 2018 to December 2020. Patients were divided into 8 groups according to the rate of embryonic development and morphological scores to compare pregnancy outcomes. We further compared clinical pregnancy outcomes and neonatal outcomes between BC embryos on day 5 (D5) and BA/BB embryos on day 6 (D6). RESULTS: Our study found no difference in clinical pregnancy rate (CPR) and live birth rate (LBR) between AA/AB blastocysts in D5 or D6 frozen blastocysts. However, for BA/BB/BC blastocysts, embryonic pregnancy outcome was significantly better in D5 than in D6. In our further analysis and comparison of BC embryos in D5 and BA/BB embryos in D6, we found no difference in clinical pregnancy outcomes and neonatal outcomes, but D6 BA/BB embryos had a higher rate of miscarriage. After adjusting for confounding factors, none of the indicators differed between groups. CONCLUSION: Our study provides suggestions for embryo selection: AA/AB embryos are preferred, regardless of the embryo development day, and the second choice is BA or BB embryos on D5. BA/BB embryos in D6 had a higher miscarriage rate than BC embryos in D5 but were not statistically significant after adjusting for confounding factors.

Time-lapse monitoring technologies for the selection of bovine in vitro fertilized embryos with high implantation potential.

Over the years, the utilization of in vitro fertilization (IVF) in bovine embryo production has increased globally to accelerate the selection of cows with high genetic values. The selection of embryos with high implantation potential is a critical factor in establishing pregnancy. Time-lapse monitoring (TLM) has emerged as a new technique that allows frequent and non-invasive imaging of developing embryos. TLM is considered to have several advantages over the conventional morphological evaluation of embryos, which has been widely used in bovine embryo production. Establishing a novel embryo selection algorithm specifically for bovine IVF embryos is a critical challenge, but information on the association between morphokinetic data obtained using TLM and the implantation potential of embryos is still limited. This review outlines the potential application of TLM technology to improve the fertility of bovine IVF embryos, focusing on the results of human and bovine TLM studies that can be applied to select bovine embryos with high implantation potential. First, the progress of the TLM technology in bovine embryo production is summarized. The association between kinetic and morphological parameters and the developmental and implantation potential of human and bovine embryos is outlined. Finally, the benefits of evaluating blastocyst collapse and re-expansion as indicators of bovine embryo viability and the possible application of TLM to detect chromosomal abnormalities and determine embryo sex will be discussed.