P-235 An analysis of qualitative and quantitative morphokinetic parameters automatically annotated using CHLOE (Fairtility), an AI-based tool, finds AI score predictive of blastulation and ploidy. (30th June 2022)

• Record Type: Journal Article
• Authors: Gómez, E; Brualla-Mora, A; Almunia, N; Jiménez, R; Hickman, C; Har-vardi, I; Villaquirán, A.M
• Is Part Of: Human reproduction. Volume 37(2022)Supplement 1
• Publication Date: 2022-06-30
• Subjects: Human reproduction -- Periodicals; 618
• DOI: 10.1093/humrep/deac107.225
• Languages: English
• ISSNs: 0268-1161

Abstract

Abstract: Study question: What is the relationship between qualitative and quantitative morphokinetic parameters automatically annotated using CHLOE(Fairtility), an AI-based tool? Summary answer: CHLOE score is associated with ploidy. DUC embryos have lower blastulation, form fewer good blastocysts, have increased fragmentation, slower development, lower implantation than non-DUCs. What is known already: The introduction of time-lapse technologies in IVF has led to the discovery of quantitiative and qualitative morphokinetic parameters which are predictive of embryo viability (ESHRE Workshop group, 2020). The challenges of annotating videos manually remain: (i)operator variation, (ii)time-consuming; (iii)complexity of how to prioritise numerous features when determining which embryos to transfer, freeze or discard. CHLOE (Fairtility) is an AI-based tool designed to automatically capture these parameters from the time-lapse videos, removing the "black box" associated with AI, and, instead, bringing transparency and support to the embryologist responsible for the decision, thus, enhancing personalisation of care down to each individual embryo. Study design, size, duration: Prospective cohort analysis on time-lapse data retrospectively collected at a single private fertility clinic in Spain between 2018-2020. 693 videos were automatically annotated (without training) using the CHLOE Artificial Intelligence (AI) tool for the following quantitative features: tPNa, tPNf, t2, t3, t4, t5, t6, t7, t8, t9, tM, tsB, tB, teB, size of ICM; and the following qualitative parameters: number of pronucleates, morphological quality of Inner Cell Mass and Trophectoderm (CHLOE Morphological scoring), identification of unusual embryo cleavages i.e. Direct Uneven Cleavage (DUCs), amongst other features. Participants/materials, setting, methods: All embryos were cultured using the Embryoscope (Vitrolife) incubator. Using a range of algorithms, CHLOE generated a prediction of blastulation (at 30hpi) and implantation which were compared to outcome (blastocysts vs non-blastocysts; euploids vs Aneuploids&Mosaics; Mosaics vs euploids&aneuploids). Embryos identified as DUCS by CHLOE were compared with non-DUCs in terms of outcomes and in terms of endpoints generated by CHLOE (parametric continuous data assessed using 2-tail t-test, categorical data using chi-square). Main results and the role of chance: Within all cleaved embryos analysed (n = 693), 29% were DUCs. DUC embryos were less likely to blastulate (DUCvsNonDUCs: 25vs50%, p<0.001), had a higher proportion of embryos with severe fragmentation (26% vs 3%, p<0.001), less likely to be suitable for biopsy (23vs87%, p < 0.001) lower blastulation prediction score (0.53vs0.76, p<0.001), lower implantation prediction score (0.21vs0.48, p<0.001) and slower embryo development across the all morphokinetic time-points assessed(p < 0.001), except for t5 (NS); than non-DUCs. DUCs and non-DUCs had similar proportion of 1, 2, 3PNs(5, 83, 5%vs 7, 84, 3%, NS). Within embryos that blastulated (n = 581), 25% were DUCs. DUC blastocysts were less likely to have a good quality ICM (7vs33%, p<0.001) or a good quality trophectoderm (9vs35%, p<0.05), lower implantation score (0.29vs0.52, p<0.05) and slower embryo development across the following morphokinetics time-points than non-DUC blastocysts. DUCs (n = 38) and non-DUC (n = 292) blastocysts had similar euploidy rate (50vs43%, NS), mosaicism rate (8vs11%, NS), and similar ratio of Euploids:Aneuploid:Mosaics (19:16:3vs126:133:33, NS). One DUC embryo was transferred, leading to an ongoing clinical pregnancy. Blastulation score was predictive of blastulation (AUC of 0.91, p < 0.001). Mosaic embryos had similar implantation score to non-mosaics (0.61vs0.67, NS). Euploid embryos had a higher implantation score than aneuploid blastocysts (0.71bs0.62, p < 0.02), so implantation score was predictive of ploidy. Limitations, reasons for caution: This study involved the validation of (i) a specific AI based tool which may not be generalised across other AI tools; (ii) in a single centre. Results obtained did not involve training, suggestive of CHLOE's ability to generalise across clinics. Presenting a framework for responsibly incorporating AI into clinical practice. Wider implications of the findings: CHLOE can simplify the processing of time-lapse data to effectively, consistently, and efficiently quantify parameters that can help explain a comprehensive prediction of embryo viability. This provides a useful tool which will ultimately assist clinicians with selecting the most optimal embryos for transfer and avoid wastage from discarding viable embryos. Trial registration number: not applicable