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Updated: Aug 5, 2026
Semiconductor Sequencing for Preimplantation Genetic Testing for Aneuploidy
Published on: August 25, 2019
Artificial intelligence-based embryo ranking can match or improve traditional assessments but cannot predict an
Danilo Cimadomo1, Marilena Taggi2, Federica Innocenti2
1Department of Biology and Biotechnology "Lazzaro Spallanzani", University of Pavia, Pavia, Italy; IVIRMA Global Research Alliance, IVIRMA Italia, Rome, Italy.
Objective:
To evaluate whether artificial intelligence (AI)-based blastocyst ranking tools can outperform traditional noninvasive assessments in prioritizing euploid embryos for transfer.
Design:
Retrospective single-center cohort study.
Subjects:
The study included 786 preimplantation genetic testing for aneuploidy cycles performed between 2013 and 2020 after embryo culture in a time-lapse incubator (TLI). The analysis focused on 279 cycles producing ≥3 blastocysts, of which ≥1 was euploid and ≥1 aneuploid embryo.
Exposure:
Blastocyst ranking was conducted through: static morphology on the basis of Gardner's score (control; embryologists-assigned scores from 1 [AA] to 9 [CC]); random guessing; Gardner's score plus morphodynamic parameters (time of expanding blastocyst [tEB] and embryo area at tEB in μm2); and two versions of a commercially-available AI model. The coefficient of variation (CV = SD/mean) within each cohort of blastocysts was then calculated to estimate the morphological variability perceived by each method among sibling embryos, and its association with ranking accuracy was investigated.
Main Outcome Measures:
Accuracy in prioritizing euploid blastocysts within cohorts of sibling embryos, assessed by the proportion of cycles in which a euploid embryo was ranked first, and association between intracohort CV and ranking performance.
Results:
The AI model version-2 showed the highest rate of correctly prioritized euploid blastocysts (68%), followed by morphodynamic assessment (64%), AI model version-1 (62%), Gardner's score (58%), and random guessing (44%). Larger intracohort CVs for Gardner's scores were positively associated with prioritization of euploid embryos. No such associations were observed with AI-based CVs.
Conclusion:
The AI-powered tools can match or slightly improve traditional noninvasive assessments. However, no blastocyst ranking strategy on the basis of morphology/morphodynamics may prevent aneuploid embryos from being prioritized, even in the presence of euploid siblings.
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