Nicolielo Mariana, Jacobs Catherine Kuhn, Lourenço Bruna, Maffeis Murilo Costa, Chéles Dóris Spinosa, Duarte Matheus Búbola, Mendes Bruno Araújo, Moraes Vinícius Casado, Chehin Maurício Barbour, Alegretti José Roberto, da Motta Eduardo Leme Alves, Lorenzon Aline Rodrigues, Nogueira Marcelo Fábio Gouveia, Rocha José Celso
Embryology Department, Huntington Reproductive Medicine-Eugin Group, São Paulo, SP, Brazil.
Laboratory of Applied Mathematics, Department of Biological Sciences, São Paulo State University (UNESP), Assis, SP, Brazil.
Sci Rep. 2025 Sep 2;15(1):32273. doi: 10.1038/s41598-025-17755-y.
The need to reduce the number of embryos transferred in assisted reproductive care to prevent multiple gestations has led to a stronger emphasis on selecting embryos with the highest morphological quality. Although this evaluation has traditionally been performed by trained embryologists, the increasing use of time-lapse incubators has introduced a greater volume of data and subjectivity in decision-making. Artificial intelligence (AI)-based tools can support embryologists by offering objective, standardized embryo assessments.In Brazil, like other countries, where imported embryo selection technologies may not account for local demographic and ethnic profiles, an AI model - Morphological Artificial Intelligence Assistance (MAIA) - was developed through a collaboration between a university and a private fertility clinic in São Paulo. The model was trained using 1,015 embryo images and prospectively tested in a clinical setting on 200 single embryo transfers. In clinical testing, MAIA achieved an overall accuracy of 66.5%. In elective embryo transfers, where there were more than one embryo eligible for transfer, MAIA achieved 70.1% accuracy for predicting clinical pregnancy. Designed with a user-friendly interface tailored by embryologists, MAIA provides real-time embryo evaluations to support decision-making in routine care.
为了减少辅助生殖治疗中移植的胚胎数量以防止多胎妊娠,人们更加注重选择形态质量最高的胚胎。传统上,这种评估由训练有素的胚胎学家进行,但延时培养箱的使用日益增加,使得决策过程中的数据量更大且主观性更强。基于人工智能(AI)的工具可以通过提供客观、标准化的胚胎评估来支持胚胎学家。在巴西,与其他国家一样,进口的胚胎选择技术可能无法考虑当地的人口和种族特征,因此一所大学与圣保罗的一家私立生育诊所合作开发了一种人工智能模型——形态学人工智能辅助(MAIA)。该模型使用1015张胚胎图像进行训练,并在临床环境中对200例单胚胎移植进行了前瞻性测试。在临床试验中,MAIA的总体准确率达到了66.5%。在有多个胚胎适合移植的选择性胚胎移植中,MAIA预测临床妊娠的准确率达到了70.1%。MAIA设计了由胚胎学家定制的用户友好界面,可以提供实时胚胎评估,以支持常规护理中的决策。