Wang Hao, Zhang Tao, Ruan Jing, Zheng Xi, Zheng Shuwei, Liu Qiqi, He Fen, Sun Bo, Zhang Qi, Zhu Yuanfang, Chen Xiaoyan
Maternal-Fetal Medicine Institute, Department of Obstetrics and Gynecology, Shenzhen Baoan Women's and Children's Hospital, Shenzhen, China.
Department of Obstetrics and Gynaecology, The Chinese University of Hong Kong, Shatin, Hong Kong, China.
Placenta. 2025 May 9. doi: 10.1016/j.placenta.2025.05.004.
The placenta is a vital organ that supports fetal growth and pregnancy maintenance. Its dysfunction is associated with severe complications, including preeclampsia, fetal growth restriction, and placenta accreta spectrum disorders. Traditional approaches to placental research have provided valuable insights but are limited in capturing the complexity of this dynamic organ. In recent years, multimodal approaches-integrating advanced imaging, single-cell and spatial omics, and artificial intelligence (AI)-have enabled comprehensive analyses of placental development and disease. These strategies offer improved diagnostic accuracy, deeper molecular understanding, and real-time assessment of placental function. This review summarizes recent advances in multimodal placental research, highlighting key technologies such as ultrasound and MRI, single-cell transcriptomics, spatial profiling, and AI-based prediction models. Particular emphasis is placed on contributions from Chinese research teams, who have developed novel platforms, atlases, and clinically relevant tools. We also discuss ongoing challenges, including data standardization, interpretability of AI models, and ethical considerations. Looking ahead, the integration of multimodal data with AI and wearable technologies holds promise for precision obstetrics and individualized pregnancy care. Together, these innovations are advancing both scientific understanding and clinical management of placenta-related disorders.
胎盘是一个支持胎儿生长和维持妊娠的重要器官。其功能障碍与严重并发症相关，包括子痫前期、胎儿生长受限和胎盘植入谱系障碍。传统的胎盘研究方法提供了有价值的见解，但在捕捉这个动态器官的复杂性方面存在局限性。近年来，整合先进成像、单细胞和空间组学以及人工智能（AI）的多模态方法，使得对胎盘发育和疾病的全面分析成为可能。这些策略提高了诊断准确性，加深了对分子的理解，并实现了对胎盘功能的实时评估。本综述总结了多模态胎盘研究的最新进展，重点介绍了超声和磁共振成像、单细胞转录组学、空间分析以及基于人工智能的预测模型等关键技术。特别强调了中国研究团队的贡献，他们开发了新颖的平台、图谱和临床相关工具。我们还讨论了当前面临的挑战，包括数据标准化、人工智能模型的可解释性以及伦理考量。展望未来，多模态数据与人工智能和可穿戴技术的整合有望实现精准产科和个性化孕期护理。这些创新共同推动了对胎盘相关疾病的科学认识和临床管理。
