Enhancing Embryo Selection With AiVF: A Major Advancement in ART - A Retrospective Study
试验速览
- 阶段
- 不适用
- 状态
- 已完成
- 发起方
- 入组人数
- 333
- 试验地点
- 1
- 主要终点
- Comparison of artificial intelligence (AI) Score and Laboratory Embryo Classification
研究概览
简要总结
In assisted reproductive technology (ART), selecting the most viable embryos from a large number of fertilized eggs is crucial. While techniques like morphological assessment, time-lapse monitoring systems, and pre-implantation genetic testing have improved the process, implantation success rates remain limited. The introduction of artificial intelligence in embryo evaluation, such as automated systems like EMA by AIVFTM, provides a promising alternative to enhance the accuracy and effectiveness of embryo selection. This study aims to assess the performance of the EMA system compared to traditional methods by examining its ability to rank embryos based on their potential for successful implantation, with the goal of increasing the chances of a successful pregnancy. This is the first clinical evaluation of this platform in France, offering new opportunities to improve decision-making in in-vitro fertilization.
详细描述
This monocentric study analyzes 420 ART cycles from the Clermont-Ferrand University Hospital, conducted between January 2022 and December 2023. It includes IVF/ICSI cycles with embryos cultured in a Time-Lapse Incubator (Geri) and both fresh and frozen blastocyst transfers. A total of 1211 embryos were analyzed, with 619 used to train algorithms for predicting reproductive outcomes. This included 551 single and 34 double embryo transfer cycles, divided into 274 fresh and 345 frozen blastocyst transfers. For all blastocyst-stage embryos, the Geri score, Gardner classification, and EMA score based on time-lapse video were recorded for statistical analysis and evaluation of reproductive outcome predictions
研究设计
- 研究类型
- Observational
- 观察模型
- Cohort
- 时间视角
- Retrospective
入排标准
- 年龄范围
- 18 Years 至 60 Years（Adult）
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •IVF or ICSI treatment between January 2022 and December 2023
- •Fresh or frozen sperm from the partner or a donor
- •Embryo culture up to the 105th hour
- •Fresh or frozen embryo transfer on Day 5
- •Known implantation data (clinical pregnancy assessed by the presence of cardiac activity at 6 weeks via ultrasound)
排除标准
- •Epididymal or testicular sperm
- •Embryo culture with transfer on Day 2 or Day 3
- •ICSI with oocyte donation or the use of thawed oocytes
- •Transfer of two embryos resulting in a singleton pregnancy
- •No blastocyst obtained on Day 5
结局指标
主要结局
Comparison of artificial intelligence (AI) Score and Laboratory Embryo Classification
时间窗: 01/01/2022-31/12/2023
The study aims to compare the EMA score assigned by the EMA platform (AiVFTM), an artificial intelligence-based tool, with the manual embryo classification performed by embryologists in the laboratory. This manual classification includes morphological assessment using the Gardner grading system and morphokinetic evaluation through the GERI score. The goal is to determine the level of concordance between the AI-generated scores and traditional embryologist assessments, and to evaluate the relationship and possible variability between the EMA score and the manual scoring methods.
次要结局
- To determine the association between EMA Score and implantation and live birth rates(01/01/2022-31/12/2023)
- To evaluate the optimal EMA score threshold for maximizing live birth rates(01/01/2022-31/12/2023)