通过使用双AI系统预测植入,其中包括三维胚胎囊图像和传统胚胎评估参数-试点研究
Yasunari Miyagi1, Toshihiro Habara2, Rei Hirata2
1Medical Data Labo Okayama City Okayama Prefecture Japan.
Reproductive medicine and biology
|October 1, 2024
概括
一个新的双人工智能 (AI) 系统有效地预测了使用3D成像和传统胚胎评估的胚胎植入成功. 这种人工智能工具显示出改善临床试管婴儿结果的前景.
科学领域:
- 生殖医学是一种生殖医学.
- 医疗保健中的人工智能
- 胚胎学 胚胎学
背景情况:
- 辅助生殖技术 (ART) 依赖于精确的胚胎评估来成功植入胚胎.
- 传统的胚胎评估 (CEE) 参数在预测试管婴儿成功方面存在局限性.
- 像3D重建这样的先进成像技术为胚胎分析提供了新的可能性.
研究的目的:
- 评估双人工智能 (AI) 系统用于预测胚胎细胞植入的有效性.
- 将3D重建图像与CEE参数集成,以提高预测准确度.
- 评估开发的双AI系统的临床可行性.
主要方法:
- 开发了一种双重的人工智能系统:第一个人工智能处理了从断层扫描胚胎细胞图像中删除背景,第二个人工智能预测了植入成功.
- 数据包括2022年6月至2023年7月期间收集的977例 (458例植入,519例非植入) 的10747张断层脑囊细胞图像.
- 人工智能系统使用了3D重建图像和传统胚胎评估 (CEE) 参数,包括母亲的年龄.
主要成果:
- 双AI系统实现了0.774 ± 0.033.3的特征曲线下的面积.
- 敏感性,特异性,正预测值,负预测值和准确性分别为0.727,0.719,0.727,0.719和0.723.
- 这些结果证明了该系统在处理3D数据和CEE信息以进行植入预测方面的能力.
结论:
- 双人工智能系统在预测胚胎细胞植入成功方面证明是有用的.
- 人工智能系统整合3D成像和CEE数据显示出巨大的潜力.
- 双AI系统代表了在试管婴儿实践中临床应用的可行选择.
相关概念视频
Cleavage and Blastulation
44.8K
After a large-single-celled zygote is produced via fertilization, the process of cleavage occurs while zygotes travel through the uterine tube. Cleavage is a mitotic cell division that does not result in growth. With each round of successive cell division, daughter cells get increasingly smaller.
44.8K
In Vitro Fertilization
229
In vitro fertilization (IVF) is a form of assisted reproductive technology where an egg is fertilized with sperm in a controlled laboratory environment before transferring the resulting embryo into the uterus. This process is designed to help individuals and couples experiencing difficulties conceiving.
The IVF process begins with ovarian stimulation, during which reproductive endocrinologists prescribe hormonal medications to stimulate the ovaries to produce multiple eggs instead of the single...
The IVF process begins with ovarian stimulation, during which reproductive endocrinologists prescribe hormonal medications to stimulate the ovaries to produce multiple eggs instead of the single...
229


