Wang Miaoyan, Xu Dandan, Zhang Lili, Jiang Haoxiang
Department of Radiology, Affiliated Children's Hospital of Jiangnan University, Wuxi 214000, China.
Department of Child Health Care, Affiliated Children's Hospital of Jiangnan University, Wuxi 214000, China.
Diagnostics (Basel). 2023 Sep 22;13(19):3027. doi: 10.3390/diagnostics13193027.
Autism spectrum disorder (ASD) is a neurodevelopmental disorder in children. Early diagnosis and intervention can remodel the neural structure of the brain and improve quality of life but may be inaccurate if based solely on clinical symptoms and assessment scales. Therefore, we aimed to analyze multimodal magnetic resonance imaging (MRI) data from the existing literature and review the abnormal changes in brain structural-functional networks, perfusion, neuronal metabolism, and the glymphatic system in children with ASD, which could help in early diagnosis and precise intervention. Structural MRI revealed morphological differences, abnormal developmental trajectories, and network connectivity changes in the brain at different ages. Functional MRI revealed disruption of functional networks, abnormal perfusion, and neurovascular decoupling associated with core ASD symptoms. Proton magnetic resonance spectroscopy revealed abnormal changes in the neuronal metabolites during different periods. Decreased diffusion tensor imaging signals along the perivascular space index reflected impaired glymphatic system function in children with ASD. Differences in age, subtype, degree of brain damage, and remodeling in children with ASD led to heterogeneity in research results. Multimodal MRI is expected to further assist in early and accurate clinical diagnosis of ASD through deep learning combined with genomics and artificial intelligence.
自闭症谱系障碍(ASD)是一种儿童神经发育障碍。早期诊断和干预可以重塑大脑的神经结构并提高生活质量,但如果仅基于临床症状和评估量表,可能会不准确。因此,我们旨在分析现有文献中的多模态磁共振成像(MRI)数据,并综述ASD儿童脑结构-功能网络、灌注、神经元代谢和类淋巴系统的异常变化,这有助于早期诊断和精准干预。结构MRI显示了不同年龄段大脑的形态差异、异常发育轨迹和网络连接变化。功能MRI显示了功能网络的破坏、异常灌注以及与ASD核心症状相关的神经血管解耦。质子磁共振波谱显示不同时期神经元代谢物的异常变化。沿血管周围间隙指数的扩散张量成像信号降低反映了ASD儿童类淋巴系统功能受损。ASD儿童在年龄、亚型、脑损伤程度和重塑方面的差异导致了研究结果的异质性。多模态MRI有望通过结合基因组学和人工智能的深度学习进一步辅助ASD的早期准确临床诊断。