ArticleReproductive biology and endocrinology : RB&E2022
Does conventional morphological evaluation still play a role in predicting blastocyst formation?
Article in Reproductive biology and endocrinology : RB&E, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- Effect of acupuncture for poor ovarian response: a multicenter randomized controlled trial.Frontiers in endocrinology · 2026Trial
- First cleavage signatures define a temporal trade-off and predict embryo fitness.Scientific reports · 2026Article
- Correlation between artificial intelligence-based IDAScore and embryo morphokinetic parameters: a retrospective cohort study.BMC pregnancy and childbirth · 2026Article
- Non-invasive biomarkers in assisted reproductive technologies, current evidence, clinical utility and future perspectives.Frontiers in reproductive health · 2026Review
- Non-invasive assessment of embryo development and ploidy: morphokinetics predict blastulation, and exploratory metabolomics identifies candidate metabolic signatures for euploidy.Frontiers in cell and developmental biology · 2026Article
- Prediction of blastocyst development using cleavage-stage embryo metrics and maternal age.Scientific reports · 2025Article
- Development and validation of machine learning models for predicting blastocyst yield in IVF cycles.Scientific reports · 2025Article
- Cleavage-stage embryo segmentation using SAM-based dual branch pipeline: development and evaluation with the CleavageEmbryo dataset.Bioinformatics (Oxford, England) · 2025Article
- Frozen-thawed double cleavage-stage or frozen-thawed single day 6 blastocyst stage embryo transfer: which is preferable for patients younger than 35 without day 5 blastocyst formation?Frontiers in endocrinology · 2025Observational
- Unraveling the mysteries of early embryonic arrest: genetic factors and molecular mechanisms.Journal of assisted reproduction and genetics · 2024Review
- Which transfer day results in the highest live birth rate for PCOS patients undergoing in vitro fertilization?BMC pregnancy and childbirth · 2023Article
- Prediction model for day 3 embryo implantation potential based on metabolites in spent embryo culture medium.BMC pregnancy and childbirth · 2023Article
- Predicting the unexpected total fertilization failure in conventionalFrontiers in cell and developmental biology · 2023Article
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Authors and funding
10 authors.
Funding
Abstract
backgroundAdvanced models including time-lapse imaging and artificial intelligence technologies have been used to predict blastocyst formation. However, the conventional morphological evaluation of embryos is still widely used. The purpose of the present study was to evaluate the predictive power of conventional morphological evaluation regarding blastocyst formation.
methodsRetrospective evaluation of data from 15,613 patients receiving blastocyst culture from January 2013 through December 2020 in our institution were reviewed. Generalized estimating equations (GEE) were used to establish the morphology-based model. To estimate whether including more features regarding patient characteristics and cycle parameters improve the predicting power, we also establish models including 27 more features with either LASSO regression or XGbosst. The predicted number of blastocyst were associated with the observed number of the blastocyst and were used to predict the blastocyst transfer cancellation either in fresh or frozen cycles.
resultsBased on early cleavage and routine observed morphological parameters (cell number, fragmentation, and symmetry), the GEE model predicted blastocyst formation with an AUC of 0.779(95%CI: 0.77-0.787) and an accuracy of 74.7%(95%CI: 73.9%-75.5%) in the validation set. LASSO regression model and XGboost model based on the combination of cycle characteristics and embryo morphology yielded similar predicting power with AUCs of 0.78(95%CI: 0.771-0.789) and 0.754(95%CI: 0.745-0.763), respectively. For per-cycle blastocyst yield, the predicted number of blastocysts using morphological parameters alone strongly correlated with observed blastocyst number (r = 0.897, P < 0.0001) and predicted blastocyst transfer cancel with an AUC of 0.926((95%CI: 0.911-0.94).
conclusionThe data suggested that routine morphology observation remained a feasible tool to support an informed decision regarding the day of transfer. However, models based on the combination of cycle characteristics and embryo morphology do not increase the predicting power significantly.
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