Use of time-lapse technology and artificial intelligence in the embryology laboratory: an updated review.

IF 1.9 Q3 OBSTETRICS & GYNECOLOGY
Romualdo Sciorio, Luca Tramontano, Giuseppe Gullo
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引用次数: 0

Abstract

During human in-vitro culture, morphological microscope analysis is routinely used to select embryos with the highest implantation potential for transfer, aiming for successful pregnancy and healthy live birth. This evaluation includes blastomere number, size, fragmentation, multinucleation, blastocyst (BL) expansion, and the inner-cell mass and trophectoderm appearance. However, this method requires removing embryos from the incubator, exposing them to non-physiological conditions such as fluctuations in pH, temperature, gases concentrations, as well as significant inter-observer variability. Continuous embryo culture using time-lapse monitoring (TLM) has revolutionized embryo evaluation by allowing continuous, real-time tracking of embryo development from fertilisation to blastocyst formation. This reduces the need to remove embryos from the incubator and helps maintain stable culture conditions. The monitoring system typically includes a standard incubator with an integrated microscope coupled to a digital camera, capturing images at regular intervals that are processed into a video for analysis. Despite its advantages, accurately predicting implantation rates in humans remains challenging. Recently, artificial intelligence (AI) has emerged as promising tool to objectively evaluate human embryos. AI can analyse large datasets, including embryological, clinical, and genetic information, and assist in individualizing treatment protocols. Integrating AI with TLM could improve embryo selection and enhance overall success rates. This paper explores the potential benefits of combining TLM and AI in reproductive and embryology laboratories, highlighting their potential to improve the outcomes of human ART.

胚胎学实验室中延时技术和人工智能的应用:最新综述。
在人体外培养过程中,通常使用形态显微镜分析来选择植入潜力最大的胚胎进行移植,以成功妊娠和健康活产为目标。这种评价包括卵裂球的数量、大小、破碎、多核、囊胚(BL)的扩张、内细胞团块和滋养外胚层的外观。然而,这种方法需要将胚胎从培养箱中取出,将其暴露在非生理条件下,如pH值、温度、气体浓度的波动,以及观察者之间的显著差异。使用延时监测(TLM)的连续胚胎培养已经彻底改变了胚胎评估,允许从受精到囊胚形成的胚胎发育的连续、实时跟踪。这减少了从培养箱中取出胚胎的需要,并有助于保持稳定的培养条件。监控系统通常包括一个标准的培养箱,上面有一个集成的显微镜和一个数码相机,定期捕捉图像,然后处理成视频进行分析。尽管有其优势,但准确预测人类的着床率仍然具有挑战性。最近,人工智能(AI)已经成为客观评估人类胚胎的有前途的工具。人工智能可以分析大型数据集,包括胚胎学、临床和遗传信息,并协助制定个性化的治疗方案。人工智能与TLM相结合可以提高胚胎选择效率,提高整体成功率。本文探讨了在生殖和胚胎学实验室中将TLM和AI结合的潜在益处,强调了它们改善人类ART结果的潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
3.30
自引率
6.70%
发文量
56
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