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ORIGINAL RESEARCH article

Front. Endocrinol.
Sec. Reproduction
Volume 15 - 2024 | doi: 10.3389/fendo.2024.1449035
This article is part of the Research Topic Advances in the Study of the Developmental Process and Gene State of Gametes and Embryos View all articles

Can Time-Lapse Culture Combined with Artificial Intelligence Improve Ongoing Pregnancy Rates in Fresh Transfer Cycles of Single Cleavage Stage Embryos?

Provisionally accepted
Xiao Wang Xiao Wang 1Qipeng Wei Qipeng Wei 2Weiyu Huang Weiyu Huang 1Lanlan Yin Lanlan Yin 1Tianzhong Ma Tianzhong Ma 1*
  • 1 Affiliated Hospital of Guangdong Medical University, Zhanjiang, China
  • 2 Xiangyang Central Hospital, Affiliated Hospital of Hubei University of Arts and Science, Xiangyang, China

The final, formatted version of the article will be published soon.

    With the rapid advancement of time-lapse culture and artificial intelligence (AI) technologies for embryo screening, pregnancy rates in assisted reproductive technology (ART) have significantly improved. However, clinical pregnancy rates in fresh cycles remain dependent on the number and type of embryos transferred. The selection of embryos with the highest implantation potential is critical for embryologists and influences transfer strategies in fertility centers. The superiority of AI over traditional morphological scoring for ranking cleavage-stage embryos based on their implantation potential remains controversial. Methods This retrospective study analyzed 105 fresh embryo transfer cycles at the Centre for Reproductive Medicine from August 2023 to March 2024, following IVF/ICSI treatment at the cleavage stage. All embryos were cultured using time-lapse technology and scored using an automated AI model (iDAScore V2.0). Embryos were categorized into three groups based on the iDAScore V2.0: Group A (8 cells, iDA: 1.0-5.7); Group B (8 cells, iDA: 5.8-8.0); and Group C (>8 cells, iDA: 5.8-8.0). Clinical treatment outcomes, embryonic development, and pregnancy outcomes were analyzed and compared across the groups. Results Baseline characteristics such as patient age, AMH levels, AFC, and basal sex hormones showed no significant differences among the three groups (p > 0.05). The iDAscores were significantly higher in Group C (7.3 ± 0.5) compared to Group B (6.7 ± 0.5) and the iDAscores were significantly higher in Group B (6.7 ± 0.5) compared to Group A (4.8 ± 1.0) (p < 0.001). The mean number of high-quality embryos was highest in Group C (4.7 ± 3.0), followed by Group B (3.6 ± 1.7) and Group A (2.1 ± 1.2) (p < 0.001). There was no statistical difference (p = 0.392) in the ongoing pregnancy rate for single cleavage-stage transfers between Group B (54.5%, 30/55) and Group A (38.1%, 8/21), although there was a tendency for Group B to be higher. Conclusion Combining time-lapse culture with AI scoring may enhance ongoing pregnancy rates in single cleavage-stage fresh transfer cycles. Keywords time-lapse culture, AI, single cleavage stage embryo transfer, fresh cycle

    Keywords: Time-lapse culture, artificial intelligence, single cleavage stage embryo transfer, Fresh Cycle Transfer, iDAscores

    Received: 14 Jun 2024; Accepted: 12 Aug 2024.

    Copyright: © 2024 Wang, Wei, Huang, Yin and Ma. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Tianzhong Ma, Affiliated Hospital of Guangdong Medical University, Zhanjiang, China

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