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Correlation between artificial intelligence-based IDAScore and embryo morphokinetic parameters: a retrospective
Lanxiang He1, Qiulei Ke1,2, Huizhen Li1
1Reproductive Medicine Center, Affiliated Hospital of Guangdong Medical University, 57 Renmin Avenue South, Zhanjiang, Guangdong Province, 524001, P. R. China.
BMC Pregnancy and Childbirth
|July 17, 2026
Summary
Artificial intelligence (AI) embryo scoring, like IDAScore, correlates with embryo development speed and quality. Higher IDAScore values in time-lapse imaging predict better implantation potential, offering a scientific basis for AI-driven embryo selection in assisted reproductive technologies.
Area of Science:
- Reproductive Medicine and Embryology
- Artificial Intelligence in Healthcare
- Bioinformatics and Computational Biology
Background:
- Artificial intelligence (AI) and time-lapse (TL) imaging enhance assisted reproductive technologies (ART) outcomes.
- The IDAScore AI model for embryo evaluation lacks transparency in assessing internal embryonic processes.
- Limited interpretability of AI-driven embryo assessment necessitates further investigation into its underlying mechanisms.
Purpose of the Study:
- To investigate the correlation between the IDAScore AI model and embryonic morphological kinetics.
- To provide a scientific explanation for AI-driven embryo assessment and selection processes.
- To validate the utility of IDAScore in predicting embryo developmental potential and clinical outcomes.
Main Methods:
- Retrospective analysis of 102 cleavage-stage and 210 blastocyst transfer cycles using time-lapse imaging and IDAScore V2.0.
- Embryos were stratified into high and low IDAScore groups for comparative analysis.
- Comparison of clinical characteristics, ovarian stimulation parameters, embryonic kinetic data, and pregnancy outcomes across groups.
Main Results:
- Higher IDAScore groups exhibited significantly faster embryonic development kinetics (e.g., time to 8 cells, time to full blastocyst expansion) and improved morphological quality.
- Logistic regression identified specific kinetic parameters (cc2 interval for cleavage, time to full blastocyst expansion for blastocysts) as significant predictors of IDAScore.
- Higher IDAScore was associated with increased rates of high-quality embryos, blastocyst formation, and clinical pregnancy, along with a lower miscarriage rate.
Conclusions:
- A significant correlation exists between IDAScore values and key embryonic morphological and kinetic parameters.
- Embryos with faster developmental kinetics, reflected by higher IDAScore, demonstrate enhanced implantation potential.
- These findings establish a scientific rationale for employing IDAScore in embryo selection protocols within ART.
