红外与毫米波学报2025，Vol.44Issue(5)：752-761,10.DOI:10.11972/j.issn.1001-9014.2025.05.013
基于fNIRS脑激活特征的中枢性性早熟分类模型研究
Research on the classification model of central precocious puberty based on brain activation features from functional near-infrared spectroscopy
摘要
Abstract
Central precocious puberty(CPP)is mainly caused by the premature activation of the hypothalamic-pituitary-gonadal axis,which leads to abnormal hormone levels and triggers structural and functional changes in the brain,mak-ing the neurovascular coupling mechanisms of children with CPP different from those of normal children in the task state.Addressing current limitations of clinical diagnosis,such as false negatives,interference from obesity,and physi-ological discomfort,this study utilized functional near-infrared spectroscopy(fNIRS)to analyze task-related brain acti-vation characteristics in 167 children from Tianjin Hospital,including 85 normal children and 82 children with CPP.An auxiliary diagnostic model for CPP was established based on these analyses.It was found that the prefrontal activation areas during mental arithmetic(MA)were more in the normal group than in the CPP group,and the activation areas were more in females than in males.By selecting mean,variance,kurtosis,and skewness from the two channels with the highest frequency of correlation and the highest magnitude of negative correlation as input features,the constructed classification model achieved an accuracy rate of 79.1%.This study provides a new and important reference for the rap-id screening and pathogenesis study of CPP.关键词
功能性近红外光谱成像/辅助诊断分类模型/激活特征/中枢性性早熟Key words
functional near-infrared spectroscopy/auxiliary diagnostic classification model/activation feature/central precocious puberty分类
数理科学引用本文复制引用
李泽英,贾丽芳,邹映雪,高峰,刘东远..基于fNIRS脑激活特征的中枢性性早熟分类模型研究[J].红外与毫米波学报,2025,44(5):752-761,10.基金项目
国家自然科学基金(62205239,81971656,62075156) （62205239,81971656,62075156）
中国博士后自然科学基金(2023M732600)Supported by the National Natural Science Foundation of China(62205239,81971656,62075156) （2023M732600）
China Postdoctoral Science Foundation(2023M732600) （2023M732600）
