[Interest of iDAScore (intelligent Data Analysis Score) for embryo selection in routine IVF laboratory practice: results of a preliminary study.].

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Abstract

Embryo selection is a major challenge in ART, especially since the generalization of single embryo transfer, and its optimization could lead to the improvement of clinical results in IVF. Recently, several Artificial Intelligence (AI) models, based on deep-learning such as iDAScore, have been developed. These models, trained on time-lapse videos of embryos with known implantation data, can predict the probability of pregnancy for a given embryo, allowing automatization and standardization in embryo selection.In this study, we have compared the hierarchical categorization of 311 D5 blastocysts of iDAScore v1.0 and the embryologists of our unit. These 311 D5 blastocysts have been classified as top (70.1%), good (Q+: 10.6%) and poor (Q-: 19.3%) quality by embryologists according to Gardner classification. Median iDAScores were [9.9-8.4], ]8.4-7.5] and ]7.5-2.1] for top, good and poor-quality blastocysts respectively.We observed a significantly concordant categorization between iDAScore and embryologists for top, good and poor-quality blastocysts (respectively, 89.5%, 36.4% and 48.3%, p <10-4). Moreover, the hierarchical categorization of the three best blastocysts between iDAScore and the embryologists was as follow: 1st rank: 71.9 %; 2nd rank: 61.6%; 3rd rank: 56.8%, (p = 0.07). 151 blastocysts with known implantation data were analyzed. The iDAScore of blastocysts that implanted was significantly higher than those that did not implant. (implantation +: 9.10 ± 0.57; implantation -: 8.70 ± 0.95, p = 0.003).This preliminary study shows that iDAScore is able to perform a reproducible, reliable and immediate hierarchical classification of blastocysts. Moreover, this tool can identify the blastocysts with the highest implantation potential. If these results confirmed on a larger scale of embryos and patients, IA could revolutionize IVF laboratories by standardizing embryo hierarchical selection.Copyright © 2023 Elsevier Masson SAS. All rights reserved.