P-554 Artificial intelligence (AI) for embryo genetic risk assessment: a novel form of preimplantation genetic screening
Authors: Gilboa D , Tauber Y , Sayegh I , Shapiro M , Seidman D 
Published: July 2024

Study question

Can an AI-based embryo ploidy screening tool effectively provide a genetic risk assessment on Day 5 embryos?

Summary answer

AI screening results showed strong predictive value for early detection of at-risk embryos warranting confirmatory diagnostic testing, based only on time lapse video assessment.

What is known already

Euploid embryo transfer is the dogma of IVF success. Embryo evaluation relies extensively on diagnostic preimplantation genetic testing for aneuploidy (PGT-A) by means of trophectoderm biopsy. Though pivotal, this presents substantial practical and financial limitations. There is demand for an alternative genetic screening method that provides a quantitative embryo genetic risk assessment for patients who opt out of invasive diagnostic testing, or who intend to undergo fresh transfer. These results can provide information for understanding your aneuploidy risk for more precise prognosis counseling and testing. This is important since diagnostic tests may incur excess financial burden, inconclusive outcomes, and time-to-results.

Study design, size, duration

Time lapse videos (N = 5,000) were used for AI training. The AI core architecture was a video transformer model for spatio-temporal video sampling. Known ploidy and live-birth results were used as ground truth, with maternal age and embryo quality scores incorporated as input parameters during calibrated logistic regression. A blind test dataset (N = 708 embryos; euploid=352; aneuploid=356; mean ± SD patient age: 35.9 ± 5.4 years) was used to evaluate predictive accuracy.

Participants/materials, setting, methods

The AI outputs a scalar (1-99) that associates with euploidy likelihood. The AI’s screening value was determined by its specificity (correct prediction of aneuploid), sensitivity (correct prediction of euploid), false positive, and false negative rate. We determined optimal AI score thresholds that identified high aneuploidy and euploidy risk categories (AI score &lt;33; AI score &gt;66, respectively).

Main results and the role of chance

Specificity of the AI screening test was 83.0%, with a sensitivity of 56.0%. The false positive rate was 26.7% and the false negative rate was 29.3%. The AI’s high specificity relative to its sensitivity shows its clinical value to deselect embryos with the strongest risk of genetic abnormality, and for the prioritization of embryos for confirmatory PGT. Boxplot visualization of the full AI score distribution showed successful discrimination between aneuploid and euploid embryos (mean AI score for aneuploid and euploid were 51.3 and 43.5, respectively) with appropriately minimized overlapping of the interquartile range. The optimal AI score thresholds for detecting embryos with the highest and lowest likelihoods of euploidy were &gt;66 /&lt;33, respectively, representing 71% likelihood of euploidy for the &gt;66 group and 72% aneuploidy for the &lt;33 group.

Limitations, reasons for caution

The screening does not provide diagnostic genetic testing on the chromosome level. The influence of mosaicism on the false positive/negative rates was not assessed.

Wider implications of the findings

Results support the use of an AI ploidy screening test for effective decision-making and triage of at-risk embryos for transfer or confirmatory diagnostic testing via PGT-A.

Trial registration number

Not applicable