O-102 Comparing the efficacy of two commercially available AI-based embryo assessment tools in a large clinical laboratory

Abstract

Abstract Study question Are artificial intelligence (AI) systems an effective tool to aid in assessment of embryo viability, that can be implemented in a busy clinical laboratory setting? Summary answer LW and iDA scores both have value in predicting embryo potential, however iDA was a significantly stronger indicator of clinical pregnancy and live birth rates. What is known already Embryologist assessment of blastocysts can be variable, influenced by a range of factors including fatigue, experience, emotional bias, workload, and time pressures. An advantage of AI technologies is the consistent and objective assessment of embryos, along with the potential to observe variations not detectable by the human eye. Both AI systems have been demonstrated by their developers to have a degree of effectiveness, however there is less data to show how this translates to routine clinical use in a laboratory not involved in the development of either system. Study design, size, duration Embryos were cultured in EmbryoScope+ using Vitrolife sequential media at 6% CO2 and 5% O2. All single embryo transfers of blastocyst stage embryos during 2020 (n = 806) were assessed by two independent commercially available AI-based systems, Life Whisperer (LW) by Presagen and Intelligent Data Analysis (iDA) by Vitrolife. Both systems assessed embryos independently of embryologist assessment. Scores from LW and iDA were analysed against clinical pregnancy and birth outcomes. Participants/materials, setting, methods LW and iDA independently assigned each embryo a score from 0-10 based on prediction of embryo viability. LW scores were calculated by analysing a static 2D image of a blastocyst, input by the embryologist. iDA scores were generated from Embryoscope+ timelapse footage after a minimum of 112 hours in culture. Clinical pregnancy was defined as presence of a gestational sac, and pregnancy loss as any clinical pregnancy that did not result in live birth. Main results and the role of chance This cohort had a mean patient age of 36.9 years and had undertaken a mean of 3.2 prior cycles. The overall clinical pregnancy rate was 45.3%. Of these pregnancies, 79.2% resulted in live birth, thus the pregnancy loss rate was 20.8%. Scores at the extremes of each scale, <5 and ≥9, resulted in a statistically significant difference in clinical pregnancy rates from both iDA scores (24.0% and 59.3% respectively, p = 0.0001) and LW scores (38.0% and 53.1% respectively, p = 0.0031), with this difference being more pronounced in iDA assessments. When stratifying scores into five categories, a linear relationship was observed between increasing score and pregnancy rate. This relationship was consistent whether assessing by raw score, as generated by the AI program, or by allocating a designated proportion of the cohort to each category. Interestingly, pregnancy loss significantly decreased with increasing iDA scores (iDA<5: 50% and iDA≥9: 13.7%, p = 0.0066). Although a similar trend was seen with LW scores, this was less pronounced and not statistically significant (LW < 5: 28.6% and LW ≥ 9: 18.3%, p = 0.1124). This demonstrates that iDA score was both more representative of the chance of establishing a clinical pregnancy and of that pregnancy resulting in a live birth. Limitations, reasons for caution This study was conducted at a single clinical laboratory and results may not necessarily be applicable to all settings. Variables such as differing culture conditions, the transfer of multiple embryos, or transfer of embryos prior to the blastocyst stage, may impact these findings. Wider implications of the findings AI technologies may aid embryologists in the selection of embryos and reduce variability between scientists. More effective ranking of embryos may reduce the number of cycles required to achieve a pregnancy and potentially reduce pregnancy loss. This is particularly valuable to patients who have many embryos available for transfer. Trial registration number NA