Advances in Early Monitoring and Prognostic Evaluation of Neonatal Hypoxic-Ischemic Encephalopathy

新生儿缺氧缺血性脑病(hypoxic-ischemic encephalopathy, HIE)是导致新生儿远期神经功能障碍的重要原因，其遗留的认知缺陷、运动障碍等后遗症对患儿生活质量及家庭社会负担造成深远影响。近年来，围产期监护技术显著提升了HIE的早期识别能力，为判断助产及剖宫产时机及启动神经保护干预争取了关键时间窗。在预后评估领域，多模态监测策略结合深度学习驱动的影像组学技术，可有效预测神经发育结局，进而指导个体化康复方案。本文综述了HIE早期监测与预后评估领域的技术进展，探讨了人工智能算法整合多模态监测数据的未来应用。Hypoxic-ischemic encephalopathy (HIE) is an important cause of neonatal long-term neurological dysfunction, and its sequelae such as cognitive deficits and dyskinesia have a profound impact on children’s quality of life and family social burden. In recent years, perinatal monitoring technology has significantly improved the early identification ability of HIE, and has won a key time window for judging the timing of midwifery and cesarean section and starting neuroprotective intervention. In the field of prognosis evaluation, multimodal monitoring strategy combined with deep learning-driven imaging technology can effectively predict the outcome of neurological development, and then guide individualized rehabilitation programs. This paper summarizes the technical progress in the field of early monitoring and prognosis evaluation of HIE, and discusses the future application of artificial intelligence algorithm to integrate multimodal monitoring data.