Ma Bing-Xin, Zhou Feng, Zhao Guang-Nian, Jin Lei, Huang Bo
Reproductive Medicine Center, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430074, China.
Department of Infection Control, Renmin Hospital of Wuhan University, Wuhan 430060, China.
Biomedicines. 2025 Jul 15;13(7):1734. doi: 10.3390/biomedicines13071734.
With the development of artificial intelligence technology in medicine, an intelligent deep learning-based embryo scoring system (iDAScore) has been developed on full-time lapse sequences of embryos. It automatically ranks embryos according to the likelihood of achieving a fetal heartbeat with no manual input from embryologists. To ensure its performance, external validation studies should be performed at multiple clinics. : A total of 6291 single vitrified-thawed blastocyst transfer cycles from 2018 to 2021 at the Reproductive Medicine Center, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology were retrospectively analyzed by the iDAScore model. Patients with two or more blastocysts transferred and blastocysts that were not cultured in a time-lapse incubator were excluded. Blastocysts were divided into four comparably sized groups by first sorting their iDAScore values in ascending order and then compared with the clinical, perinatal, and neonatal outcomes. Our results showed that clinical pregnancy, miscarriage, and live birth significantly correlated with iDAScore ( < 0.001). For perinatal and neonatal outcomes, no significant difference was shown in four iDAScore groups, except sex ratio. Uni- and multivariable logistic regressions showed that iDAScore was significantly positively correlated with live birth rate ( < 0.05). : In conclusion, the objective ranking can prioritize embryos reliably and rapidly for transfer, which could allow embryologists more time for processes requiring hands-on procedures.
随着人工智能技术在医学领域的发展，基于智能深度学习的胚胎评分系统（iDAScore）已在胚胎的全时程延时序列上开发出来。它无需胚胎学家手动输入，就能根据实现胎心的可能性自动对胚胎进行排名。为确保其性能，应在多家诊所进行外部验证研究。：华中科技大学同济医学院附属同济医院生殖医学中心对2018年至2021年的6291个单冻融囊胚移植周期进行了回顾性分析，采用iDAScore模型。排除移植两个或更多囊胚的患者以及未在延时培养箱中培养的囊胚。首先按iDAScore值升序对囊胚进行排序，然后将其分为四个大小相当的组，并与临床、围产期和新生儿结局进行比较。我们的结果表明，临床妊娠、流产和活产与iDAScore显著相关（<0.001）。对于围产期和新生儿结局，除性别比例外，四个iDAScore组未显示出显著差异。单变量和多变量逻辑回归显示，iDAScore与活产率显著正相关（<0.05）。总之，客观排名可以可靠且快速地对胚胎进行排序以便移植，这可以让胚胎学家有更多时间用于需要动手操作的流程。
