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Related Concept Videos

Improving Translational Accuracy02:07

Improving Translational Accuracy

Base complementarity between the three base pairs of mRNA codon and the tRNA anticodon is not a failsafe mechanism. Inaccuracies can range from a single mismatch to no correct base pairing at all. The free energy difference between the correct and nearly correct base pairs can be as small as 3 kcal/ mol. With complementarity being the only proofreading step, the estimated error frequency would be one wrong amino acid in every 100 amino acids incorporated. However, error frequencies observed in...
Improving Translational Accuracy02:07

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Decoding embryo development: the effect of clinical variables in morphokinetics and artificial intelligence quality

Jorge Ten1, M Carmen Tio1, Pedro Pini2

  • 1Instituto Bernabeu, Alicante, Spain.

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|May 30, 2025
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Summary

Artificial intelligence (AI) effectively assesses embryo quality, linking morphokinetic events (MKS) and patient factors to pregnancy outcomes. Higher embryo scores significantly increase clinical and ongoing pregnancy rates.

Keywords:
AIembryo quality scoreeuploid Ratesmorphokineticspregnancy/live birth rates

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Area of Science:

  • Reproductive Medicine
  • Embryology
  • Artificial Intelligence in Healthcare

Background:

  • Embryo quality is crucial for successful IVF outcomes.
  • Morphokinetic events (MKS) and patient parameters are known to influence embryo development.
  • Evaluating these factors comprehensively can optimize assisted reproductive technology (ART) success rates.

Purpose of the Study:

  • To investigate if MKS and patient parameters affect embryo quality scores.
  • To determine the relationship between AI-assessed embryo quality and pregnancy outcomes.
  • To explore the impact of morphokinetics on ploidy and clinical results.

Main Methods:

  • Retrospective analysis of 6024 embryos from 1355 cycles using a time-lapse AI system (CHLOE EQ™).
  • Assessed patient age, oocyte source (autologous vs. donor), and oocyte status (fresh vs. frozen).
  • Analyzed 23 MKS and their correlation with embryo quality score and ploidy.

Main Results:

  • AI embryo quality score strongly correlated with time to expanded blastocyst (tEB; -0.816).
  • Increased patient age, frozen oocytes, and autologous oocytes were associated with longer tEB and lower embryo quality.
  • Higher embryo quality scores significantly increased odds of clinical pregnancy (21.7%) and ongoing pregnancy/live birth (18.5%).

Conclusions:

  • AI can accurately evaluate embryo quality and aid embryologist decision-making.
  • AI models can elucidate the impact of clinical factors on ART outcomes.
  • Morphokinetic analysis integrated with AI provides valuable insights into embryo potential and patient-specific factors.