METHODS: This retrospective study was approved by the Institutional Review Board of Chung Sun Medical University, Taichung, Taiwan. Patients undergoing SET cycles (n = 482) following PGT-A at a single reproductive center between January 2017 and June 2021. The blastocyst morphology and morphokinetics of all embryos were evaluated using a time-lapse system. The blastocysts were ranked based on the scores generated by iDAScore, which were defined as AI scores, or by KIDScore D5 (version 3.2) following the manufacturer\'s protocols. A single blastocyst without aneuploidy was transferred after examining the embryonic ploidy status using a next-generation sequencing-based PGT-A platform. Logistic regression analysis with generalized estimating equations was conducted to assess whether AI scores are associated with the probability of live birth (LB) while considering confounding factors.
RESULTS: Logistic regression analysis revealed that AI score was significantly associated with LB probability (adjusted odds ratio [OR] = 2.037, 95% confidence interval [CI]: 1.632-2.542) when pulsatility index (PI) level and types of chromosomal abnormalities were controlled. Blastocysts were divided into quartiles in accordance with their AI score (group 1: 3.0-7.8; group 2: 7.9-8.6; group 3: 8.7-8.9; and group 4: 9.0-9.5). Group 1 had a lower LB rate (34.6% vs. 59.8-72.3%) and a higher rate of pregnancy loss (26% vs. 4.7-8.9%) compared with the other groups (p < 0.05). The receiver operating characteristic curve analysis verified that the iDAScore had a significant but limited ability to predict LB (area under the curve [AUC] = 0.64); this ability was significantly weaker than that of the combination of iDAScore, type of chromosomal abnormalities, and PI level (AUC = 0.67). In the comparison of the LB groups with the non-LB groups, the AI scores were significantly lower in the non-LB groups, both for euploid (median: 8.6 vs. 8.8) and mosaic (median: 8.0 vs. 8.6) SETs.
CONCLUSIONS: Although its predictive ability can be further enhanced, the AI score was significantly associated with LB probability in SET cycles. Euploid or mosaic blastocysts with low AI scores (≤ 7.8) were associated with a lower LB rate, indicating the potential of this annotation-free AI system as a decision-support tool for deselecting embryos with poor pregnancy outcomes following PGT-A.
方法:这项回顾性研究得到了重阳医科大学机构审查委员会的批准,台中,台湾。在2017年1月至2021年6月期间,在单个生殖中心接受PGT-A后进行SET周期(n=482)的患者。使用延时系统评估所有胚胎的胚泡形态和形态动力学。根据iDAScore产生的分数对胚泡进行排名,定义为AI分数,或通过KIDScoreD5(版本3.2)遵循制造商的协议。在使用基于下一代测序的PGT-A平台检查胚胎倍性状态后,转移了没有非整倍性的单个胚泡。使用广义估计方程进行Logistic回归分析,以评估AI得分是否与活产概率(LB)相关,同时考虑混杂因素。
结果:Logistic回归分析显示,当控制搏动指数(PI)水平和染色体异常类型时,AI得分与LB概率(调整后比值比[OR]=2.037,95%置信区间[CI]:1.632-2.542)显着相关。根据AI评分将囊胚分为四分位数(第1组:3.0-7.8;第2组:7.9-8.6;第3组:8.7-8.9;第4组:9.0-9.5)。第1组的LB率较低(34.6%vs.59.8-72.3%)和更高的妊娠损失率(26%vs.4.7-8.9%)与其他组相比(p<0.05)。受试者工作特征曲线分析证实,iDAScore具有显著但有限的预测LB的能力(曲线下面积[AUC]=0.64);这种能力明显弱于iDAScore的组合,染色体异常的类型,和PI水平(AUC=0.67)。在LB组和非LB组的比较中,非LB组的AI得分明显较低,均为整倍体(中位数:8.6vs.8.8)和马赛克(中位数:8.0vs.8.6)SET。
结论:虽然其预测能力可以进一步提高,在SET周期中,AI评分与LB概率显著相关.低AI评分(≤7.8)的Euploid或镶嵌胚泡与较低的LB率相关,表明这种无注释的AI系统作为决策支持工具的潜力,用于取消选择PGT-A后妊娠结局不良的胚胎。