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Estimated Brain Age in Healthy Aging and Across Multiple Neurological Disorders

  • Li Chai
  • , Jun Sun
  • , Zhizheng Zhuo
  • , Ren Wei
  • , Xiaolu Xu
  • , Yunyun Duan
  • , Decai Tian
  • , Yutong Bai
  • , Ningnannan Zhang
  • , Haiqing Li
  • , Yuxin Li
  • , Yongmei Li
  • , Fuqing Zhou
  • , Jun Xu
  • , James H. Cole
  • , Frederik Barkhof
  • , Jianguo Zhang
  • , Huaguang Zheng
  • , Yaou Liu*
  • *Corresponding author for this work
  • Capital Medical University
  • Tianjin Medical University
  • Fudan University
  • The First Affiliated Hospital of Chongqing Medical University
  • Nanchang University
  • University College London
  • Amsterdam UMC - Vrije Universiteit Amsterdam

Research output: Contribution to journalArticleAcademicpeer-review

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Abstract

Background: The brain aging in the general population and patients with neurological disorders is not well understood. Purpose: To characterize brain aging in the above conditions and its clinical relevance. Study Type: Retrospective. Population: A total of 2913 healthy controls (HC), with 1395 females; 331 multiple sclerosis (MS); 189 neuromyelitis optica spectrum disorder (NMOSD); 239 Alzheimer's disease (AD); 244 Parkinson's disease (PD); and 338 cerebral small vessel disease (cSVD). Field Strength/Sequence: 3.0 T/Three-dimensional (3D) T1-weighted images. Assessment: The brain age was estimated by our previously developed model, using a 3D convolutional neural network trained on 9794 3D T1-weighted images of healthy individuals. Brain age gap (BAG), the difference between chronological age and estimated brain age, was calculated to represent accelerated and resilient brain conditions. We compared MRI metrics between individuals with accelerated (BAG ≥ 5 years) and resilient brain age (BAG ≤ −5 years) in HC, and correlated BAG with MRI metrics, and cognitive and physical measures across neurological disorders. Statistical Tests: Student's t test, Wilcoxon test, chi-square test or Fisher's exact test, and correlation analysis. P < 0.05 was considered statistically significant. Results: In HC, individuals with accelerated brain age exhibited significantly higher white matter hyperintensity (WMH) and lower regional brain volumes than those with resilient brain age. BAG was significantly higher in MS (10.30 ± 12.6 years), NMOSD (2.96 ± 7.8 years), AD (6.50 ± 6.6 years), PD (4.24 ± 4.8 years), and cSVD (3.24 ± 5.9 years) compared to HC. Increased BAG was significantly associated with regional brain atrophy, WMH burden, and cognitive impairment across neurological disorders. Increased BAG was significantly correlated with physical disability in MS (r = 0.17). Data Conclusion: Healthy individuals with accelerated brain age show high WMH burden and regional volume reduction. Neurological disorders exhibit distinct accelerated brain aging, correlated with impaired cognitive and physical function. Level of Evidence: 4. Technical Efficacy: Stage 2.

Original languageEnglish
JournalJournal of magnetic resonance imaging
Early online date2024
DOIs
Publication statusE-pub ahead of print - 2024

Keywords

  • MRI
  • brain age
  • brain aging
  • neurological disorders

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