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Sun Z, Liu J, Sun J, Xu Z, Liu W, Mao N, Chu T, Guo H, Che K, Xu X, Bai W, Liu X, Wang H, Lu X, Liu J, Shi Y, Sun C, Li W, Sui Y, Zhang Z, Lin S, Dong J, Xie H, Ma H, Qin W. Decreased Regional Spontaneous Brain Activity and Cognitive Dysfunction in Patients with Coronary Heart Disease: a Resting-state Functional MRI Study. Acad Radiol 2022; 30:1081-1091. [PMID: 36513572 DOI: 10.1016/j.acra.2022.11.022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2022] [Revised: 11/13/2022] [Accepted: 11/16/2022] [Indexed: 12/14/2022]
Abstract
OBJECTIVES Chronic coronary heart disease (CHD) is correlated with an increased risk of cognitive impairment (CI), but the mechanisms underlying these changes remain unclear. The aim of the present study was to explore the potential changes in regional spontaneous brain activities and their association with CI, to explore the pathophysiological mechanisms underlying CI in patients with CHD. MATERIALS AND METHODS A total of 71 CHD patients and 73 matched healthy controls (HCs) were included in this study. Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) were used to assess the participants' cognitive functions. Regional homogeneity (ReHo) and fractional amplitude of low-frequency fluctuation(fALFF) values were calculated to determine regional spontaneous brain activity. Coronary artery calcium (CAC) score provides a measure of the total coronary plaque burden. Mediation analyses were performed to test whether CHD's effects on cognitive decline are mediated by decreased regional spontaneous brain activity. RESULTS Patients with CHD had significantly lower MMSE and MoCA scores than the HCs. Compared with the HCs, the patients with CHD demonstrated significantly decreased ReHo and fALFF values in the bilateral medial superior frontal gyrus (SFGmed), left superior temporal gyrus (TPOsup) and left middle temporal gyrus (TPOmid). Impaired cognitive performance was positively correlated with decreased activities in the SFGmed. Mediation analyses revealed that the decreased regional spontaneous brain activity in the SFGmed played a critical role in the relationship between the increase in CAC score and the MoCA and MMSE scores. CONCLUSION The abnormalities of spontaneous brain activity in SFGmed may provide insights into the neurological pathophysiology underlying CHD associated with cognitive dysfunction.
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Affiliation(s)
- Zhaolei Sun
- Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University School of Medicine, No. 20, Yudong Road, Zhifu District, Yantai, Shandong, China
| | - Jing Liu
- Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University School of Medicine, No. 20, Yudong Road, Zhifu District, Yantai, Shandong, China
| | - Jian Sun
- Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University School of Medicine, No. 20, Yudong Road, Zhifu District, Yantai, Shandong, China
| | - Zixue Xu
- Qingdao University, 38 Dengzhou Road, Shibei District, Qingdao, Shandong, China
| | - Wanchen Liu
- Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University School of Medicine, No. 20, Yudong Road, Zhifu District, Yantai, Shandong, China; Qingdao University, 38 Dengzhou Road, Shibei District, Qingdao, Shandong, China
| | - Ning Mao
- Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University School of Medicine, No. 20, Yudong Road, Zhifu District, Yantai, Shandong, China
| | - Tongpeng Chu
- Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University School of Medicine, No. 20, Yudong Road, Zhifu District, Yantai, Shandong, China
| | - Hao Guo
- Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University School of Medicine, No. 20, Yudong Road, Zhifu District, Yantai, Shandong, China
| | - Kaili Che
- Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University School of Medicine, No. 20, Yudong Road, Zhifu District, Yantai, Shandong, China
| | - Xiao Xu
- Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University School of Medicine, No. 20, Yudong Road, Zhifu District, Yantai, Shandong, China
| | - Wei Bai
- Department of Radiology, State Key Laboratory of Biotherapy, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Xiaoliang Liu
- Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University School of Medicine, No. 20, Yudong Road, Zhifu District, Yantai, Shandong, China
| | - Haiyan Wang
- Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University School of Medicine, No. 20, Yudong Road, Zhifu District, Yantai, Shandong, China
| | - Xin Lu
- Navy 971 Hopspital of PLA, Qingdao, Shandong, China
| | - Jiandong Liu
- Department of Cardiology, Rocket army characteristic medical center, Xicheng District, Beijing, china
| | - Yinghong Shi
- Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University School of Medicine, No. 20, Yudong Road, Zhifu District, Yantai, Shandong, China
| | - Chunjuan Sun
- Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University School of Medicine, No. 20, Yudong Road, Zhifu District, Yantai, Shandong, China
| | - Wenjuan Li
- Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University School of Medicine, No. 20, Yudong Road, Zhifu District, Yantai, Shandong, China
| | - Yanbin Sui
- Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University School of Medicine, No. 20, Yudong Road, Zhifu District, Yantai, Shandong, China
| | - Zhongsheng Zhang
- Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University School of Medicine, No. 20, Yudong Road, Zhifu District, Yantai, Shandong, China
| | - Shujuan Lin
- Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University School of Medicine, No. 20, Yudong Road, Zhifu District, Yantai, Shandong, China
| | - Jianjun Dong
- Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University School of Medicine, No. 20, Yudong Road, Zhifu District, Yantai, Shandong, China
| | - Haizhu Xie
- Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University School of Medicine, No. 20, Yudong Road, Zhifu District, Yantai, Shandong, China
| | - Heng Ma
- Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University School of Medicine, No. 20, Yudong Road, Zhifu District, Yantai, Shandong, China; Qingdao University, 38 Dengzhou Road, Shibei District, Qingdao, Shandong, China.
| | - Wen Qin
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
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2
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Huang YT, Hong FF, Yang SL. Atherosclerosis: The Culprit and Co-victim of Vascular Dementia. Front Neurosci 2021; 15:673440. [PMID: 34421513 PMCID: PMC8377286 DOI: 10.3389/fnins.2021.673440] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2021] [Accepted: 06/11/2021] [Indexed: 11/24/2022] Open
Abstract
Vascular dementia (VD), a cerebrovascular disease which causes cognitive impairment, is one of the significant factors that affects the quality of senectitude. Atherosclerosis (AS) is a chronic inflammatory syndrome and closely associated with VD. Analyzing the role of AS in VD contribute greatly to its early detection and prevention, but their relationship has not been integrated into a complete network. This review summarizes AS biomarkers as VD predictors for the first time and describes the direct mechanisms of AS causing VD from five aspects: vascular morphogenesis, hemodynamic change, neurovascular unit damage (NVU), oxidative stress, and microRNA (miRNA). Finally, it discriminates the relationship between AS and VD in common risk factors which can be disease or some molecules. In particular, these data imply that the role of AS in VD is not only a pathogenic factor but also a comorbidity in VD. This review aims to bring new ideas for the prediction and treatment of VD.
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Affiliation(s)
- Ya-Ting Huang
- Department of Physiology, College of Medicine, Nanchang University, Nanchang, China.,Queen Marry College, School of Medicine, Nanchang University, Nanchang, China
| | - Fen-Fang Hong
- Experimental Center of Pathogen Biology, Nanchang University, Nanchang, China
| | - Shu-Long Yang
- Department of Physiology, College of Medicine, Nanchang University, Nanchang, China.,Department of Physiology, Fuzhou Medical College, Fuzhou, China
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3
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Park J, Kim TJ, Song JH, Jang H, Kim JS, Kang SH, Kim HR, Hwangbo S, Shin HY, Na DL, Seo SW, Kim HJ, Kim JJ. Helicobacter Pylori Infection Is Associated with Neurodegeneration in Cognitively Normal Men. J Alzheimers Dis 2021; 82:1591-1599. [PMID: 34180413 DOI: 10.3233/jad-210119] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
BACKGROUND An association between Helicobacter pylori (H. pylori) infection and dementia was reported in previous studies; however, the evidence is inconsistent. OBJECTIVE In the present study, the association between H. pylori infection and brain cortical thickness as a biomarker of neurodegeneration was investigated. METHODS A cross-sectional study of 822 men who underwent a medical health check-up, including an esophagogastroduodenoscopy and 3.0 T magnetic resonance imaging, was performed. H. pylori infection status was assessed based on histology. Multiple linear regression analyses were conducted to evaluate the relationship between H. pylori infection and brain cortical thickness. RESULTS Men with H. pylori infection exhibited overall brain cortical thinning (p = 0.022), especially in the parietal (p = 0.008) and occipital lobes (p = 0.050) compared with non-infected men after adjusting for age, educational level, alcohol intake, smoking status, and intracranial volume. 3-dimentional topographical analysis showed that H. pylori infected men had cortical thinning in the bilateral lateral temporal, lateral frontal, and right occipital areas compared with non-infected men with the same adjustments (false discovery rate corrected, Q < 0.050). The association remained significant after further adjusting for inflammatory marker (C-reactive protein) and metabolic factors (obesity, dyslipidemia, fasting glucose, and blood pressure). CONCLUSION Our results indicate H. pylori infection is associated with neurodegenerative changes in cognitive normal men. H. pylori infection may play a pathophysiologic role in the neurodegeneration and further studies are needed to validate this association.
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Affiliation(s)
- Jaehong Park
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.,Alzheimer's Disease Convergence Research Center, Samsung Medical Center, Seoul, Korea
| | - Tae Jun Kim
- Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Joo Hye Song
- Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Hyemin Jang
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.,Alzheimer's Disease Convergence Research Center, Samsung Medical Center, Seoul, Korea
| | - Ji Sun Kim
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.,Alzheimer's Disease Convergence Research Center, Samsung Medical Center, Seoul, Korea
| | - Sung Hoon Kang
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.,Alzheimer's Disease Convergence Research Center, Samsung Medical Center, Seoul, Korea.,Department of Neurology, Korea University Guro Hospital, Korea University College of Medicine, Seoul, Korea
| | - Hang-Rai Kim
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.,Alzheimer's Disease Convergence Research Center, Samsung Medical Center, Seoul, Korea.,Department of Neurology, Dongguk University Ilsan Hospital, Dongguk University College of Medicine, Goyang, Korea
| | - Song Hwangbo
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.,Alzheimer's Disease Convergence Research Center, Samsung Medical Center, Seoul, Korea
| | - Hee Young Shin
- Center for Health Promotion, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Duk L Na
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.,Alzheimer's Disease Convergence Research Center, Samsung Medical Center, Seoul, Korea.,Department of Health Science and Technology, SAIHST, Sungkyunkwan University, Seoul, Korea
| | - Sang Won Seo
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.,Alzheimer's Disease Convergence Research Center, Samsung Medical Center, Seoul, Korea.,Department of Health Science and Technology, SAIHST, Sungkyunkwan University, Seoul, Korea.,Department of Intelligent Precision Healthcare Convergence, Sungkyunkwan University, Suwon, Korea
| | - Hee Jin Kim
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.,Alzheimer's Disease Convergence Research Center, Samsung Medical Center, Seoul, Korea.,Department of Health Science and Technology, SAIHST, Sungkyunkwan University, Seoul, Korea.,Department of Digital Health, SAIHST, Sungkyunkwan University, Seoul, Korea
| | - Jae J Kim
- Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
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Seiler A, Schöngrundner S, Stock B, Nöth U, Hattingen E, Steinmetz H, Klein JC, Baudrexel S, Wagner M, Deichmann R, Gracien RM. Cortical aging - new insights with multiparametric quantitative MRI. Aging (Albany NY) 2020; 12:16195-16210. [PMID: 32852283 PMCID: PMC7485732 DOI: 10.18632/aging.103629] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2020] [Accepted: 06/22/2020] [Indexed: 02/07/2023]
Abstract
Understanding the microstructural changes related to physiological aging of the cerebral cortex is pivotal to differentiate healthy aging from neurodegenerative processes. The aim of this study was to investigate the age-related global changes of cortical microstructure and regional patterns using multiparametric quantitative MRI (qMRI) in healthy subjects with a wide age range. 40 healthy participants (age range: 2nd to 8th decade) underwent high-resolution qMRI including T1, PD as well as T2, T2* and T2′ mapping at 3 Tesla. Cortical reconstruction was performed with the FreeSurfer toolbox, followed by tests for correlations between qMRI parameters and age. Cortical T1 values were negatively correlated with age (p=0.007) and there was a widespread age-related decrease of cortical T1 involving the frontal and the parietotemporal cortex, while T2 was correlated positively with age, both in frontoparietal areas and globally (p=0.004). Cortical T2′ values showed the most widespread associations across the cortex and strongest correlation with age (r= -0.724, p=0.0001). PD and T2* did not correlate with age. Multiparametric qMRI allows to characterize cortical aging, unveiling parameter-specific patterns. Quantitative T2′ mapping seems to be a promising imaging biomarker of cortical age-related changes, suggesting that global cortical iron deposition is a prominent process in healthy aging.
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Affiliation(s)
- Alexander Seiler
- Department of Neurology, Goethe University, Frankfurt am Main, Germany.,Brain Imaging Center, Goethe University, Frankfurt am Main, Germany
| | - Sophie Schöngrundner
- Department of Neurology, Goethe University, Frankfurt am Main, Germany.,Department of Neuroradiology, Goethe University, Frankfurt am Main, Germany.,Brain Imaging Center, Goethe University, Frankfurt am Main, Germany
| | - Benjamin Stock
- Department of Neurology, Goethe University, Frankfurt am Main, Germany.,Department of Neuroradiology, Goethe University, Frankfurt am Main, Germany.,Brain Imaging Center, Goethe University, Frankfurt am Main, Germany
| | - Ulrike Nöth
- Brain Imaging Center, Goethe University, Frankfurt am Main, Germany
| | - Elke Hattingen
- Department of Neuroradiology, Goethe University, Frankfurt am Main, Germany
| | - Helmuth Steinmetz
- Department of Neurology, Goethe University, Frankfurt am Main, Germany
| | - Johannes C Klein
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Simon Baudrexel
- Department of Neurology, Goethe University, Frankfurt am Main, Germany.,Brain Imaging Center, Goethe University, Frankfurt am Main, Germany
| | - Marlies Wagner
- Department of Neuroradiology, Goethe University, Frankfurt am Main, Germany.,Brain Imaging Center, Goethe University, Frankfurt am Main, Germany
| | - Ralf Deichmann
- Brain Imaging Center, Goethe University, Frankfurt am Main, Germany
| | - René-Maxime Gracien
- Department of Neurology, Goethe University, Frankfurt am Main, Germany.,Brain Imaging Center, Goethe University, Frankfurt am Main, Germany
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5
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Seiler A, Brandhofe A, Gracien RM, Pfeilschifter W, Hattingen E, Deichmann R, Nöth U, Wagner M. Microstructural Alterations Analogous to Accelerated Aging of the Cerebral Cortex in Carotid Occlusive Disease. Clin Neuroradiol 2020; 31:709-720. [PMID: 32638029 PMCID: PMC8463359 DOI: 10.1007/s00062-020-00928-9] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2020] [Accepted: 06/10/2020] [Indexed: 11/28/2022]
Abstract
Purpose To investigate cortical thickness and cortical quantitative T2 values as imaging markers of microstructural tissue damage in patients with unilateral high-grade internal carotid artery occlusive disease (ICAOD). Methods A total of 22 patients with ≥70% stenosis (mean age 64.8 years) and 20 older healthy control subjects (mean age 70.8 years) underwent structural magnetic resonance imaging (MRI) and high-resolution quantitative (q)T2 mapping. Generalized linear mixed models (GLMM) controlling for age and white matter lesion volume were employed to investigate the effect of ICAOD on imaging parameters of cortical microstructural integrity in multivariate analyses. Results There was a significant main effect (p < 0.05) of the group (patients/controls) on both cortical thickness and cortical qT2 values with cortical thinning and increased cortical qT2 in patients compared to controls, irrespective of the hemisphere. The presence of upstream carotid stenosis had a significant main effect on cortical qT2 values (p = 0.01) leading to increased qT2 in the poststenotic hemisphere, which was not found for cortical thickness. The GLMM showed that in general cortical thickness was decreased and cortical qT2 values were increased with increasing age (p < 0.05). Conclusion Unilateral high-grade carotid occlusive disease is associated with widespread cortical thinning and prolongation of cortical qT2, presumably reflecting hypoperfusion-related microstructural cortical damage similar to accelerated aging of the cerebral cortex. Cortical thinning and increase of cortical qT2 seem to reflect different aspects and different pathophysiological states of cortical degeneration. Quantitative T2 mapping might be a sensitive imaging biomarker for early cortical microstructural damage.
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Affiliation(s)
- Alexander Seiler
- Department of Neurology, Goethe University Frankfurt, Schleusenweg 2-16, 60528, Frankfurt, Germany. .,Brain Imaging Center, Goethe University Frankfurt, Frankfurt, Germany.
| | - Annemarie Brandhofe
- Department of Neurology, Goethe University Frankfurt, Schleusenweg 2-16, 60528, Frankfurt, Germany.,Brain Imaging Center, Goethe University Frankfurt, Frankfurt, Germany
| | - René-Maxime Gracien
- Department of Neurology, Goethe University Frankfurt, Schleusenweg 2-16, 60528, Frankfurt, Germany.,Brain Imaging Center, Goethe University Frankfurt, Frankfurt, Germany
| | - Waltraud Pfeilschifter
- Department of Neurology, Goethe University Frankfurt, Schleusenweg 2-16, 60528, Frankfurt, Germany
| | - Elke Hattingen
- Institute of Neuroradiology, Goethe University Frankfurt, Frankfurt, Germany
| | - Ralf Deichmann
- Brain Imaging Center, Goethe University Frankfurt, Frankfurt, Germany
| | - Ulrike Nöth
- Brain Imaging Center, Goethe University Frankfurt, Frankfurt, Germany
| | - Marlies Wagner
- Institute of Neuroradiology, Goethe University Frankfurt, Frankfurt, Germany
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6
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Aycheh HM, Seong JK, Shin JH, Na DL, Kang B, Seo SW, Sohn KA. Biological Brain Age Prediction Using Cortical Thickness Data: A Large Scale Cohort Study. Front Aging Neurosci 2018; 10:252. [PMID: 30186151 PMCID: PMC6113379 DOI: 10.3389/fnagi.2018.00252] [Citation(s) in RCA: 57] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2017] [Accepted: 07/31/2018] [Indexed: 01/18/2023] Open
Abstract
Brain age estimation from anatomical features has been attracting more attention in recent years. This interest in brain age estimation is motivated by the importance of biological age prediction in health informatics, with an application to early prediction of neurocognitive disorders. It is well-known that normal brain aging follows a specific pattern, which enables researchers and practitioners to predict the age of a human's brain from its degeneration. In this paper, we model brain age predicted by cortical thickness data gathered from large cohort brain images. We collected 2,911 cognitively normal subjects (age 45-91 years) at a single medical center and acquired their brain magnetic resonance (MR) images. All images were acquired using the same scanner with the same protocol. We propose to first apply Sparse Group Lasso (SGL) for feature selection by utilizing the brain's anatomical grouping. Once the features are selected, a non-parametric non-linear regression using the Gaussian Process Regression (GPR) algorithm is applied to fit the final age prediction model. Experimental results demonstrate that the proposed method achieves the mean absolute error of 4.05 years, which is comparable with or superior to several recent methods. Our method can also be a critical tool for clinicians to differentiate patients with neurodegenerative brain disease by extracting a cortical thinning pattern associated with normal aging.
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Affiliation(s)
- Habtamu M. Aycheh
- Department of Software and Computer Engineering, Ajou University, Suwon, South Korea
| | - Joon-Kyung Seong
- School of Biomedical Engineering, Korea University, Seoul, South Korea
| | - Jeong-Hyeon Shin
- School of Biomedical Engineering, Korea University, Seoul, South Korea
| | - Duk L. Na
- Department of Neurology, Samsung Medical Center, School of Medicine, Sungkyunkwan University, Seoul, South Korea
- Neuroscience Center, Samsung Medical Center, Seoul, South Korea
- Department of Health Sciences and Technology, Clinical Research Design and Evaluation, SAIHST, Sungkyunkwan University, Seoul, South Korea
| | - Byungkon Kang
- Department of Software and Computer Engineering, Ajou University, Suwon, South Korea
| | - Sang W. Seo
- Department of Neurology, Samsung Medical Center, School of Medicine, Sungkyunkwan University, Seoul, South Korea
- Neuroscience Center, Samsung Medical Center, Seoul, South Korea
- Department of Health Sciences and Technology, Clinical Research Design and Evaluation, SAIHST, Sungkyunkwan University, Seoul, South Korea
| | - Kyung-Ah Sohn
- Department of Software and Computer Engineering, Ajou University, Suwon, South Korea
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