Probabilistic maps of white matter hyperintensity in a Chinese aging cohort and application for clinical diagnosis.

Journal: European radiology
Published Date: Oct 25, 2025

Abstract

OBJECTIVES: White matter hyperintensities (WMH) are abnormalities in brain imaging that contribute to cognitive decline and diseases. This study aimed to build WMH probability maps (WPMs) and normative data of WMH volume from a Chinese aging cohort, to offer valuable insights for diagnosis. MATERIALS AND METHODS: We developed WPMs from a comprehensive dataset across six age groups (20-29, 30-39, 40-49, 50-59, 60-69, and 70-79 years), encompassing 735 participants. WMH segmentation was performed with a deep learning approach, and the resulting masks were registered to the standard space for WPM construction. We explored how WMH volume changed with age and established normative data for different age groups. Additionally, we examined whether WMH volume moderates the relationship between aging and cognitive decline. The practical utility of WPMs was then validated with a separate patient cohort with mild cognitive impairment and Alzheimer's disease. RESULTS: WPMs and the normative data of WMH volume were constructed for six age groups. As age increased, both the likelihood and spatial coverage of WMH grew. All types of WMH (total, periventricular, and deep white matter hyperintensities) quadratically increased with age. Deep white matter hyperintensities moderated the decline of general cognitive abilities related to aging. The two patient groups had significantly higher ratios of abnormal WMH than typical aging adults. CONCLUSION: We successfully built WPMs and WMH normative data for Chinese adults and demonstrated their clinical diagnostic values. KEY POINTS: Question Current diagnostic tools lack population-specific references for white matter hyperintensities (WMH)in Chinese aging adults, limiting accurate discrimination between pathological neurodegeneration and typical aging patterns. Findings These Chinese WMH probability maps show quadratic age-related growth, with deep WMH moderating cognitive decline. Mild cognitive impairment/Alzheimer's Disease (MCI/AD) patients exhibited significantly higher WMH volumes. Clinical relevance These population-specific WMH references enable clinicians to quantitatively identify abnormal aging and early neurodegeneration in Chinese patients, addressing the critical need for ethnically tailored diagnostic tools in Alzheimer's disease and vascular cognitive impairment.

Authors

  • Xinyi Cai
    School of Biomedical Engineering & State Key Laboratory of Advanced Medical Materials and Devices, ShanghaiTech University, 393 Middle Huaxia Road, Shanghai 20030, PR China.
  • Xiao Luo
    Department of Spine Surgery, The Third Hospital of Mianyang, Sichuan Mental Health Center, Mianyang, China.
  • Lianghu Guo
    School of Biomedical Engineering, ShanghaiTech University, Shanghai, China.
  • Yi Gu
    Department of Electrical and Computer Engineering, University of California, San Diego, California.
  • Qing Yang
    School of Nursing, Chengdu Medical College, Chengdu, China.
  • Yao Li
    Center of Robotics and Intelligent Machine, Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Science, No. 266 Fangzhen Road, Beibei District, Chongqing, 400714, China.
  • Minming Zhang
    Department of Radiology, the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310009, China. [email protected].
  • Jinsong Wu
    Department of Neurosurgery, Huashan Hospital, Fudan University, Shanghai, China.
  • Qiang He
    College of Biomass Science and Engineering, Healthy Food Evaluation Research Center, Sichuan University, Chengdu 610065, China.
  • Xu Zhang
    China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China.
  • Peiyu Huang
    Department of Radiology, the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
  • Han Zhang
    Johns Hopkins University, Baltimore, MD, USA.

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