Cytoplasmic strings between ICM and mTE are a positive predictor of clinical pregnancy and live birth outcomes: A time-lapse study

Enhancing clinical utility: deep learning-based embryo scoring model for non-invasive aneuploidy prediction

BACKGROUND

The best method for selecting embryos ploidy is preimplantation genetic testing for aneuploidies (PGT-A). However, it takes more labour, money, and experience. As such, more approachable, non- invasive techniques were still needed. Analyses driven by artificial intelligence have been presented recently to automate and objectify picture assessments.

METHODS

In present retrospective study, a total of 3448 biopsied blastocysts from 979 Time-lapse (TL)-PGT cycles were retrospectively analyzed. The "intelligent data analysis (iDA) Score" as a deep learning algorithm was used in TL incubators and assigned each blastocyst with a score between 1.0 and 9.9.

RESULTS

Significant differences were observed in iDAScore among blastocysts with different ploidy. Additionally, multivariate logistic regression analysis showed that higher scores were significantly correlated with euploidy (p < 0.001). The Area Under the Curve (AUC) of iDAScore alone for predicting euploidy embryo is 0.612, but rose to 0.688 by adding clinical and embryonic characteristics.

CONCLUSIONS

This study provided additional information to strengthen the clinical applicability of iDAScore. This may provide a non-invasive and inexpensive alternative for patients who have no available blastocyst for biopsy or who are economically disadvantaged. However, the accuracy of embryo ploidy is still dependent on the results of next-generation sequencing technology (NGS) analysis.

Development and validation of a nomogram for predicting ongoing pregnancy in single vitrified-warmed blastocyst embryo transfer cycles

Introduction

The global adoption of the "freeze-all strategy" has led to a continuous increase in utilization of single vitrified-warmed blastocyst embryo transfer (SVBT) owing to its clinical effectiveness. Accurate prediction of clinical pregnancy is crucial from a patient-centered perspective. However, this remains challenging, with inherent limitations due to the absence of precise and user-friendly prediction tools. Thus, this study primarily aimed to develop and assess a nomogram based on quantitative clinical data to optimize the efficacy of personalized prognosis assessment.

Materials and methods

We conducted a retrospective cohort analysis of ongoing pregnancy data from 658 patients with infertility who underwent SVBT at our center between October 17, 2017, and December 18, 2021. Patients were randomly assigned to the training (n=461) or validation (n=197) cohort for nomogram development and testing, respectively. A nomogram was constructed using the results of the multivariable logistic regression (MLR), which included clinical covariates that were assessed for their association with ongoing pregnancy.

Results

The MLR identified eight significant variables that independently predicted ongoing pregnancy outcomes in the study population. These predictors encompassed maternal physiology, including maternal age at oocyte retrieval and serum anti-Müllerian hormone levels; uterine factors, such as adenomyosis; and various embryo assessment parameters, including the number of fertilized embryos, blastocyst morphology, blastulation day, blastocyst re-expansion speed, and presence of embryo string. The area under the receiver operating characteristic curve in our prediction model was 0.675 (95% confidence interval [CI], 0.622-0.729) and 0.656 (95% CI, 0.573-0.739) in the training and validation cohorts, respectively, indicating good discrimination performance in both cohorts.

Conclusions

Our individualized nomogram is a practical and user-friendly tool that can provide accurate and useful SVBT information for patients and clinicians. By offering this model to patients, clinical stakeholders can alleviate uncertainty and confusion about fertility treatment options and enhance patients' confidence in making informed decisions.

Human embryo live imaging reveals nuclear DNA shedding during blastocyst expansion and biopsy

Proper preimplantation development is essential to assemble a blastocyst capable of implantation. Live imaging has uncovered major events driving early development in mouse embryos; yet, studies in humans have been limited by restrictions on genetic manipulation and lack of imaging approaches. We have overcome this barrier by combining fluorescent dyes with live imaging to reveal the dynamics of chromosome segregation, compaction, polarization, blastocyst formation, and hatching in the human embryo. We also show that blastocyst expansion mechanically constrains trophectoderm cells, causing nuclear budding and DNA shedding into the cytoplasm. Furthermore, cells with lower perinuclear keratin levels are more prone to undergo DNA loss. Moreover, applying trophectoderm biopsy, a mechanical procedure performed clinically for genetic testing, increases DNA shedding. Thus, our work reveals distinct processes underlying human development compared with mouse and suggests that aneuploidies in human embryos may not only originate from chromosome segregation errors during mitosis but also from nuclear DNA shedding.

Detailed analysis of cytoplasmic strings in human blastocysts: new insights

The aim of this study was to determine if there was an association between the presence of cytoplasmic strings (CS) and their characteristics, with blastocyst quality, development and clinical outcome in human blastocysts. This two-centre cohort study was performed between July 2017 and September 2018 and involved a total of 1152 blastocysts from 225 patients undergoing in vitro fertilization (IVF) and intracytoplasmic sperm injection (ICSI). All embryos were cultured in Embryoscope+ and were assessed for CS using time-lapse images. A single assessor examined all blastocysts and reviewed videos using the EmbyroViewer® Software. Blastocyst quality was assessed on day 5 of embryo development. The number of CS, location and duration of their activity was recorded on days 5/6. A positive association between the presence of CS in human blastocysts with blastocyst quality was identified. Blastocysts with a higher number of CS present, were of higher quality and were in the more advanced stages of development. Top quality blastocysts had CS activity present for longer, as well as having a higher number of vesicles present travelling along the CS. Blastocysts that had CS present, had a significantly higher live birth rate. This study has confirmed that a higher number of CS and vesicles in human blastocysts is associated with top quality blastocysts and is not a negative predictor of development. They had a higher number of CS present that appeared earlier in development and, although ceased activity sooner, had a longer duration of activity. Blastocysts with CS had a significant increase in live birth rate.