STUDY QUESTION Can more reliable time cut-offs of embryo developmental incompetence be generated by combining time-lapse technology (TLT), artificial intelligence, and preimplantation genetics screening for aneuploidy (PGT-A)? SUMMARY ANSWER Embryo developmental incompetence can be better predicted by time cut-offs at multiple developmental stages and for different ranges of maternal age. WHAT IS KNOWN ALREADY TLT is instrumental for the continual and undisturbed observation of embryo development. It has produced morphokinetic algorithms aimed at selecting embryos able to generate a viable pregnancy, however, such efforts have had limited success. Regardless, the potential of this technology for improving multiple aspects of the IVF process remains considerable. Specifically, TLT could be harnessed to discriminate developmentally incompetent embryos: i.e. those unable to develop to the blastocyst stage or affected by full-chromosome meiotic aneuploidies. If proven valuable, this application would prevent the non-productive use of such embryos, thereby improving laboratory and clinical efficiency and reducing patient stress and costs due to unnecessary embryo transfer and cryopreservation. STUDY DESIGN, SIZE, DURATION The training dataset involved embryos of PGT-A cycles cultured in Embryoscope with a single media (836 euploid and 1179 aneuploid blastocysts and 1874 arrested embryos; 2013–2020). Selection criteria were ejaculated sperm, own (not donated) fresh oocytes, trophectoderm biopsy and comprehensive-chromosome-testing to diagnose uniform aneuploidies. Out-of-sample (30% of training), internal (299 euploid and 490 aneuploid blastocysts and 680 arrested embryos; 2021–2022) and external (97 euploid, 110 aneuploid and 603 untested blastocysts and 514 arrested embryos, 2018 to early 2022) validations were conducted. PARTICIPANTS/MATERIALS, SETTING, METHODS A training dataset (70%) was used to define thresholds. Several models were generated by fitting outcomes to each timing (tPNa-t8) and maternal age. ROC curves pinpointed in-sample classification values associated with 95%, 99% and 99.99% true-positive rate for predicting incompetence. These values were integrated with upper limits of maternal age ranges (<35, 35-37, 38–40, 41–42, and >42 years) in logit functions to identify time cut-offs, whose accuracy was tested on the validation datasets through confusion matrices. MAIN RESULTS AND THE ROLE OF CHANCE For developmental (in)competence, the best performing (i) tPNa cut-offs were 27.8 hpi (error-rate: 0/743), 32.6 hpi (error rate: 0/934), 26.8 hpi (error rate: 0/1178), 22.9 hpi (error-rate: 1/654, 0.1%) and 17.2 hpi (error rate: 4/423, 0.9%) in the <35, 35–37, 38–40, 41–42, and >42 years groups, respectively; (ii) tPNf cut-offs were 36.7 hpi (error rate: 0/738), 47.9 hpi (error rate: 0/921), 45.6 hpi (error rate: 1/1156, 0.1%), 44.1 hpi (error rate: 0/647) and 41.8 hpi (error rate: 0/417); (iii) t2 cut-offs were 50.9 hpi (error rate: 0/724), 49 hpi (error rate: 0/915), 47.1 hpi (error rate: 0/1146), 45.8 hpi (error rate: 0/636) and 43.9 hpi (error rate: 0/416); (iv) t4 cut-offs were 66.9 hpi (error rate: 0/683), 80.7 hpi (error rate: 0/836), 77.1 hpi (error rate: 0/1063), 74.7 hpi (error rate: 0/590) and 71.2 hpi (error rate: 0/389); and (v) t8 cut-offs were 118.1 hpi (error rate: 0/619), 110.6 hpi (error rate: 0/772), 140 hpi (error rate: 0/969), 135 hpi (error rate: 0/533) and 127.5 hpi (error rate: 0/355). tPNf and t2 showed a significant association with chromosomal (in)competence, also when adjusted for maternal age. Nevertheless, the relevant cut-offs were found to perform less well and were redundant compared with the blastocyst development cut-offs. LIMITATIONS, REASONS FOR CAUTION Study limits are its retrospective design and the datasets being unbalanced towards advanced maternal age cases. The potential effects of abnormal cleavage patterns were not assessed. Larger sample sizes and external validations in other clinical settings are warranted. WIDER IMPLICATIONS OF THE FINDINGS If confirmed by independent studies, this approach could significantly improve the efficiency of ART, by reducing the workload and patient impacts (extended culture and cleavage stage cryopreservation or transfer) associated with embryos that ultimately are developmentally incompetent and should not be considered for treatment. Pending validation, these data might be applied also in static embryo observation settings. STUDY FUNDING/COMPETING INTEREST(S) This study was supported by the participating institutions. The authors have no conflicts of interest to declare TRIAL REGISTRATION NUMBER N/A.

中文翻译：

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时间会证明一切：延时技术和人工智能设定表明胚胎无能的截止时间


研究问题 能否通过结合延时技术 （TLT）、人工智能和非整倍体植入前遗传学筛选 （PGT-A） 来产生更可靠的胚胎发育无能时间截止？摘要答案 胚胎发育功能不全可以通过多个发育阶段和不同产妇年龄范围的时间截止来更好地预测。众所周知，TLT 有助于持续和不受干扰地观察胚胎发育。它已经产生了旨在选择能够产生有效妊娠的胚胎的形态动力学算法，然而，这种努力收效甚微。无论如何，这项技术在改善 IVF 过程的多个方面的潜力仍然相当大。具体来说，TLT 可用于区分发育无能的胚胎：即那些无法发育到囊胚阶段或受全染色体减数分裂非整倍体影响的胚胎。如果证明有价值，此应用程序将防止此类胚胎的非生产性使用，从而提高实验室和临床效率，并减少因不必要的胚胎移植和冷冻保存而导致的患者压力和成本。研究设计、规模、持续时间 训练数据集涉及在 Embryoscope 中使用单一培养基培养的 PGT-A 周期胚胎（836 个整倍体和 1179 个非整倍体囊胚和 1874 个停滞胚胎;2013-2020 年）。选择标准是射精的精子、拥有（未捐赠的）新鲜卵母细胞、滋养外胚层活检和综合染色体检测，以诊断均匀的非整倍体。 样本外（30% 的训练）、内部（299 个整倍体和 490 个非整倍体囊胚和 680 个停滞胚胎;2021-2022 年）和外部（97 个整倍体、110 个非整倍体和 603 个未经测试的囊胚和 514 个停滞胚胎，2018 年至 2022 年初）进行了验证。参与者/材料、设置、方法 使用培训数据集 （70%） 来定义阈值。通过将结果拟合到每个时间 （tPNa-t8） 和产妇年龄来生成几个模型。ROC 曲线精确定位了与 95% 、 99% 和 99.99% 真阳性率相关的样本内分类值，用于预测无能。这些值与 logit 函数中产妇年龄范围的上限 （<35、35-37、38-40、41-42 和 >42 岁） 相结合，以确定时间截止时间，其准确性通过混淆矩阵在验证数据集上进行测试。主要结果和机会的作用 对于发育（非）能力，表现最好的 （i） tPNa 临界值为 27.8 hpi（错误率：0/743）、32.6 hpi（错误率：0/934）、26.8 hpi（错误率：0/1178）、22.9 hpi（错误率：1/654,0.1%）和 17.2 hpi（错误率：4/423,0.9%）在 <35、35-37、38-40、41-42 和 >42 岁组中， 分别;（ii） tPNf 临界值为 36.7 hPi（误差率：0/738）、47.9 hPi（误差率：0/921）、45.6 hPi（误差率：1/1156,0.1%）、44.1 hPi（误差率：0/647）和 41.8 hPi（误差率：0/417）;（iii） T2 临界值为 50.9 HPI （误差率： 0/724）、49 HPI （误差率： 0/915）、47.1 HPI （误差率： 0/1146）、45.8 HPI （误差率： 0/636） 和 43.9 HPI （误差率： 0/416）;（iv） T4 临界值为 66.9 HPI （错误率： 0/683）、80.7 HPI （错误率： 0/836）、77.1 HPI （错误率： 0/1063）、74.7 HPI （错误率： 0/590） 和 71.2 HPI （错误率： 0/389）;（v） T8 临界值为 118.1 hPi（错误率：0/619），110。6 hPi（错误率：0/772）、140 hPi（错误率：0/969）、135 hPi（错误率：0/533）和 127.5 hPi（错误率：0/355）。tPNf 和 t2 显示与染色体 （in） 能能性显着相关，即使根据产妇年龄进行调整也是如此。然而，与囊胚发育临界值相比，相关临界值的表现较差，并且是多余的。局限性，谨慎的原因 研究的局限性在于其回顾性设计和数据集对高龄产妇病例的不平衡。未评估异常卵裂模式的潜在影响。需要更大的样本量和其他临床环境中的外部验证。研究结果的更广泛意义 如果得到独立研究的证实，这种方法可以通过减少与最终发育无能且不应考虑治疗的胚胎相关的工作量和患者影响（延长培养和卵裂期冷冻保存或转移），从而显着提高 ART 的效率。在等待验证之前，这些数据也可能应用于静态胚胎观察设置。研究资金/竞争利益 本研究得到了参与机构的支持。作者声明试验注册号 N/A 没有利益冲突。