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
{"title":"健康老龄化和多种神经系统疾病的估计脑龄。","authors":"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","doi":"10.1002/jmri.29667","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>The brain aging in the general population and patients with neurological disorders is not well understood.</p><p><strong>Purpose: </strong>To characterize brain aging in the above conditions and its clinical relevance.</p><p><strong>Study type: </strong>Retrospective.</p><p><strong>Population: </strong>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).</p><p><strong>Field strength/sequence: </strong>3.0 T/Three-dimensional (3D) T1-weighted images.</p><p><strong>Assessment: </strong>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.</p><p><strong>Statistical tests: </strong>Student's t test, Wilcoxon test, chi-square test or Fisher's exact test, and correlation analysis. P < 0.05 was considered statistically significant.</p><p><strong>Results: </strong>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).</p><p><strong>Data conclusion: </strong>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.</p><p><strong>Level of evidence: </strong>4 TECHNICAL EFFICACY: Stage 2.</p>","PeriodicalId":16140,"journal":{"name":"Journal of Magnetic Resonance Imaging","volume":" ","pages":""},"PeriodicalIF":3.3000,"publicationDate":"2024-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Estimated Brain Age in Healthy Aging and Across Multiple Neurological Disorders.\",\"authors\":\"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\",\"doi\":\"10.1002/jmri.29667\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>The brain aging in the general population and patients with neurological disorders is not well understood.</p><p><strong>Purpose: </strong>To characterize brain aging in the above conditions and its clinical relevance.</p><p><strong>Study type: </strong>Retrospective.</p><p><strong>Population: </strong>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).</p><p><strong>Field strength/sequence: </strong>3.0 T/Three-dimensional (3D) T1-weighted images.</p><p><strong>Assessment: </strong>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.</p><p><strong>Statistical tests: </strong>Student's t test, Wilcoxon test, chi-square test or Fisher's exact test, and correlation analysis. P < 0.05 was considered statistically significant.</p><p><strong>Results: </strong>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).</p><p><strong>Data conclusion: </strong>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.</p><p><strong>Level of evidence: </strong>4 TECHNICAL EFFICACY: Stage 2.</p>\",\"PeriodicalId\":16140,\"journal\":{\"name\":\"Journal of Magnetic Resonance Imaging\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":3.3000,\"publicationDate\":\"2024-11-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Magnetic Resonance Imaging\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1002/jmri.29667\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Magnetic Resonance Imaging","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1002/jmri.29667","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING","Score":null,"Total":0}
Estimated Brain Age in Healthy Aging and Across Multiple Neurological Disorders.
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.
期刊介绍：
The Journal of Magnetic Resonance Imaging (JMRI) is an international journal devoted to the timely publication of basic and clinical research, educational and review articles, and other information related to the diagnostic applications of magnetic resonance.
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