An artificial intelligence model for embryo selection in preimplantation DNA methylation screening in assisted reproductive technology.

Autor:	Zhan J; Institute of Biophysics, Chinese Academy of Science, Beijing 100101, China., Chen C; Guangdong Women's and Children's Hospital, Guangzhou 511400, China., Zhang N; Beijing Obstetrics and Gynecology Hospital, Capital Medical University, Beijing Maternal and Child Health Care Hospital, Beijing 100026, China., Zhong S; Dongguan People's Hospital, Dongguan 523059, China., Wang J; Institute of Biophysics, Chinese Academy of Science, Beijing 100101, China.; University of the Chinese Academy of Science, Beijing 101408, China.; School of Future Technology, University of the Chinese Academy of Science, Beijing 100049, China., Hu J; Institute of Biophysics, Chinese Academy of Science, Beijing 100101, China.; University of the Chinese Academy of Science, Beijing 101408, China., Liu J; Institute of Biophysics, Chinese Academy of Science, Beijing 100101, China.; University of the Chinese Academy of Science, Beijing 101408, China.; School of Future Technology, University of the Chinese Academy of Science, Beijing 100049, China.
Jazyk:	angličtina
Zdroj:	Biophysics reports [Biophys Rep] 2023 Dec 31; Vol. 9 (6), pp. 352-361.
DOI:	10.52601/bpr.2023.230035
Abstrakt:	Embryo quality is a critical determinant of clinical outcomes in assisted reproductive technology (ART). A recent clinical trial investigating preimplantation DNA methylation screening (PIMS) revealed that whole genome DNA methylation level is a novel biomarker for assessing ART embryo quality. Here, we reinforced and estimated the clinical efficacy of PIMS. We introduce PIMS-AI, an innovative artificial intelligence (AI) based model, to predict the probability of an embryo producing live birth and subsequently assist ART embryo selection. Our model demonstrated robust performance, achieving an area under the curve (AUC) of 0.90 in cross-validation and 0.80 in independent testing. In simulated embryo selection, PIMS-AI attained an accuracy of 81% in identifying viable embryos for patients. Notably, PIMS-AI offers significant advantages over conventional preimplantation genetic testing for aneuploidy (PGT-A), including enhanced embryo discriminability and the potential to benefit a broader patient population. In conclusion, our approach holds substantial promise for clinical application and has the potential to significantly improve the ART success rate. Competing Interests: Jianhong Zhan, Chuangqi Chen, Na Zhang, Shuhuai Zhong, Jiaming Wang, Jinzhou Hu and Jiang Liu declare that they have no conflict of interest. (© The Author(s) 2023.)
Databáze:	MEDLINE
Externí odkaz:	Zobrazit plný text záznamu