Minasi Maria Giulia, Greco Pierfrancesco, Varricchio Maria Teresa, Barillari Paolo, Greco Ermanno
Center for Reproductive Medicine, Villa Mafalda, Via Monte delle Gioie 5, Rome 00199, Italy.
Center for Reproductive Medicine, Villa Mafalda, Rome, Italy.
Ther Adv Reprod Health. 2020 Dec 7;14:2633494120976921. doi: 10.1177/2633494120976921. eCollection 2020 Jan-Dec.
A major challenge in the assisted reproduction laboratory is to set up reproducible and efficient criteria to identify the embryo with the highest developmental potential. Over the years, several methods have been used worldwide with this purpose. Initially, standard morphology assessment was the only available strategy. It is now universally recognized that besides being a very subjective embryo selection strategy, morphology evaluation alone has a very poor prognostic value. More recently, the availability of time-lapse incubators allowed a continuous monitoring of human embryo development. This technology has spread quickly and many fertility clinics over the world produced a remarkable amount of data. To date, however, a general consensus on which variables, or combination of variables, should play a central role in embryo selection is still lacking. Many confounding factors, concerning both patient features and clinical and biological procedures, have been observed to influence embryo development. In addition, several studies have reported unexpected positive outcomes, even in the presence of abnormal developmental criteria. While it does not seem that time-lapse technology is ready to entirely replace the more invasive preimplantation genetic testing in identifying the embryo with the highest implantation potential, it is certainly true that its application is rapidly growing, becoming progressively more accurate. Studies involving artificial intelligence and deep-learning models as well as combining morphokinetic with other non-invasive markers of embryo development, are currently ongoing, raising hopes for its successful applicability for clinical purpose in the near future. The present review mainly focuses on data published starting from the first decade of 2000, when time-lapse technology was introduced as a routine clinical practice in the infertility centers.
辅助生殖实验室面临的一个主要挑战是建立可重复且高效的标准，以识别具有最高发育潜力的胚胎。多年来，世界各地已为此目的采用了多种方法。最初，标准形态学评估是唯一可用的策略。现在人们普遍认识到，形态学评估不仅是一种非常主观的胚胎选择策略，而且单独进行形态学评估的预后价值非常低。最近，延时培养箱的出现使得对人类胚胎发育进行连续监测成为可能。这项技术迅速普及，世界各地的许多生育诊所都产生了大量数据。然而，迄今为止，对于哪些变量或变量组合应在胚胎选择中发挥核心作用，仍未达成普遍共识。人们观察到，许多与患者特征以及临床和生物学程序相关的混杂因素都会影响胚胎发育。此外，一些研究报告了意外的积极结果，即使存在异常发育标准。虽然延时技术似乎还未准备好完全取代侵入性更强的植入前基因检测来识别具有最高着床潜力的胚胎，但它的应用肯定在迅速增长，并且越来越准确。目前正在进行涉及人工智能和深度学习模型以及将形态动力学与胚胎发育的其他非侵入性标记相结合的研究，这让人们对其在不久的将来成功应用于临床充满希望。本综述主要关注从21世纪第一个十年开始发表的数据，当时延时技术在不孕不育中心被引入作为常规临床实践。
