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Ross FC, Mayer DE, Horn J, Cryan JF, Del Rio D, Randolph E, Gill CIR, Gupta A, Ross RP, Stanton C, Mayer EA. Potential of dietary polyphenols for protection from age-related decline and neurodegeneration: a role for gut microbiota? Nutr Neurosci 2024; 27:1058-1076. [PMID: 38287652 DOI: 10.1080/1028415x.2023.2298098] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/31/2024]
Abstract
Many epidemiological studies have shown the beneficial effects of a largely plant-based diet, and the strong association between the consumption of a Mediterranean-type diet with healthy aging including a lower risk of cognitive decline. The Mediterranean diet is characterized by a high intake of olive oil, fruits and vegetables and is rich in dietary fiber and polyphenols - both of which have been postulated to act as important mediators of these benefits. Polyphenols are large molecules produced by plants to protect them from environmental threats and injury. When ingested by humans, as little as 5% of these molecules are absorbed in the small intestine with the majority metabolized by the gut microbiota into absorbable simple phenolic compounds. Flavan-3-ols, a type of flavonoid, contained in grapes, berries, pome fruits, tea, and cocoa have been associated with many beneficial effects on several risk factors for cardiovascular disease, cognitive function and brain regions involved in memory formation. Both preclinical and clinical studies suggest that these brain and heart benefits can be attributed to endothelial vascular effects and anti-inflammatory properties among others. More recently the gut microbiota has emerged as a potential modulator of the aging brain and intriguingly polyphenols have been shown to alter microbiota composition and be metabolized by different microbial species. However, there is a need for well controlled studies in large populations to identify predictors of response, particularly given the vast inter-individual variation of human gut microbiota.
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Affiliation(s)
- F C Ross
- APC Microbiome Ireland, University College Cork, Co. Cork, Ireland
| | - D E Mayer
- Institute of Human Nutrition, Columbia University, New York, USA
| | - J Horn
- Oppenheimer Centre for Neurobiology of Stress and Resilience, Vatche and Tamar Manoukian Division of Digestive Diseases, David Geffen School of Medicine, UCLA, Los Angeles, USA
| | - J F Cryan
- APC Microbiome Ireland, University College Cork, Co. Cork, Ireland
- Department Anatomy & Neuroscience, University College Cork, Co. Cork, Ireland
| | - D Del Rio
- Department of Food and Drugs, University of Parma, Parma, Italy
| | - E Randolph
- Oppenheimer Centre for Neurobiology of Stress and Resilience, Vatche and Tamar Manoukian Division of Digestive Diseases, David Geffen School of Medicine, UCLA, Los Angeles, USA
| | - C I R Gill
- Nutrition Innovation Centre for Food and Health, Northern Ireland, UK
| | - A Gupta
- Division of Digestive Diseases, UCLA, Los Angeles, USA
- Goodman Luskin Microbiome Center at UCLA, Los Angeles, CA, USA
| | - R P Ross
- APC Microbiome Ireland, University College Cork, Co. Cork, Ireland
| | - C Stanton
- Teagasc Food Research Centre, Moorepark, Fermoy, Co. Cork, Ireland
| | - E A Mayer
- Oppenheimer Centre for Neurobiology of Stress and Resilience, Vatche and Tamar Manoukian Division of Digestive Diseases, David Geffen School of Medicine, UCLA, Los Angeles, USA
- Goodman Luskin Microbiome Center at UCLA, Los Angeles, CA, USA
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Flaherty R, Sui YV, Masurkar AV, Betensky RA, Rusinek H, Lazar M. Diffusion imaging markers of accelerated aging of the lower cingulum in subjective cognitive decline. Front Neurol 2024; 15:1360273. [PMID: 38784911 PMCID: PMC11111894 DOI: 10.3389/fneur.2024.1360273] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2023] [Accepted: 04/29/2024] [Indexed: 05/25/2024] Open
Abstract
Introduction Alzheimer's Disease (AD) typically starts in the medial temporal lobe, then develops into a neurodegenerative cascade which spreads to other brain regions. People with subjective cognitive decline (SCD) are more likely to develop dementia, especially in the presence of amyloid pathology. Thus, we were interested in the white matter microstructure of the medial temporal lobe in SCD, specifically the lower cingulum bundle that leads into the hippocampus. Diffusion tensor imaging (DTI) has been shown to differentiate SCD participants who will progress to mild cognitive impairment from those who will not. However, the biology underlying these DTI metrics is unclear, and results in the medial temporal lobe have been inconsistent. Methods To better characterize the microstructure of this region, we applied DTI to cognitively normal participants in the Cam-CAN database over the age of 55 with cognitive testing and diffusion MRI available (N = 325, 127 SCD). Diffusion MRI was processed to generate regional and voxel-wise diffusion tensor values in bilateral lower cingulum white matter, while T1-weighted MRI was processed to generate regional volume and cortical thickness in the medial temporal lobe white matter, entorhinal cortex, temporal pole, and hippocampus. Results SCD participants had thinner cortex in bilateral entorhinal cortex and right temporal pole. No between-group differences were noted for any of the microstructural metrics of the lower cingulum. However, correlations with delayed story recall were significant for all diffusion microstructure metrics in the right lower cingulum in SCD, but not in controls, with a significant interaction effect. Additionally, the SCD group showed an accelerated aging effect in bilateral lower cingulum with MD, AxD, and RD. Discussion The diffusion profiles observed in both interaction effects are suggestive of a mixed neuroinflammatory and neurodegenerative pathology. Left entorhinal cortical thinning correlated with decreased FA and increased RD, suggestive of demyelination. However, right entorhinal cortical thinning also correlated with increased AxD, suggestive of a mixed pathology. This may reflect combined pathologies implicated in early AD. DTI was more sensitive than cortical thickness to the associations between SCD, memory, and age. The combined effects of mixed pathology may increase the sensitivity of DTI metrics to variations with age and cognition.
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Affiliation(s)
- Ryn Flaherty
- Center for Advanced Imaging Innovation and Research, Department of Radiology, New York University Grossman School of Medicine, New York, NY, United States
- Vilcek Institute of Graduate Biomedical Sciences, New York University Grossman School of Medicine, New York, NY, United States
| | - Yu Veronica Sui
- Center for Advanced Imaging Innovation and Research, Department of Radiology, New York University Grossman School of Medicine, New York, NY, United States
| | - Arjun V. Masurkar
- Department of Neurology, New York University Grossman School of Medicine, New York, NY, United States
- Neuroscience Institute, New York University Grossman School of Medicine, New York, NY, United States
| | - Rebecca A. Betensky
- Department of Biostatistics, New York University School of Global Public Health, New York, NY, United States
| | - Henry Rusinek
- Center for Advanced Imaging Innovation and Research, Department of Radiology, New York University Grossman School of Medicine, New York, NY, United States
- Department of Psychiatry, New York University Grossman School of Medicine, New York, NY, United States
| | - Mariana Lazar
- Center for Advanced Imaging Innovation and Research, Department of Radiology, New York University Grossman School of Medicine, New York, NY, United States
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Subramanyam Rallabandi V, Seetharaman K. Deep learning-based classification of healthy aging controls, mild cognitive impairment and Alzheimer’s disease using fusion of MRI-PET imaging. Biomed Signal Process Control 2023. [DOI: 10.1016/j.bspc.2022.104312] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
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Liu S, Ni J, Yan F, Yin N, Li X, Ma R, Wu J, Zhou G, Feng J. Functional changes of the prefrontal cortex, insula, caudate and associated cognitive impairment (chemobrain) in NSCLC patients receiving different chemotherapy regimen. Front Oncol 2022; 12:1027515. [PMID: 36408140 PMCID: PMC9667024 DOI: 10.3389/fonc.2022.1027515] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2022] [Accepted: 10/21/2022] [Indexed: 01/24/2023] Open
Abstract
INTRODUCTION Chemotherapy-induced cognitive impairment (CICI), termed "chemobrain", is highly prevalent in cancer patients following the administration of chemotherapeutic agents. However, the potential pathophysiological mechanisms underlying CICI remain unknown. This study aimed to explore the functional changes of the brain and associated cognitive impairment in non-small cell lung cancer (NSCLC) patients receiving different chemotherapy regimen. METHODS A total of 49 NSCLC patients (25 patients receiving pemetrexed plus carboplatin chemotherapy (PeCC) and 24 patients receiving paclitaxel plus carboplatin chemotherapy (PaCC)) and 61 healthy controls (HCs) were recruited and underwent resting-state functional magnetic resonance imaging (rs-fMRI) scanning, as well as cognitive function tests including Mini Mental State Exam (MMSE), Montreal Cognitive Assessment (MoCA), Functional Assessment of Cancer Therapy-Cognitive Function (FACT-Cog). Brain functional activities were measured by regional homogeneity (ReHo) values, which were calculated and compared between groups. In addition, the associations between ReHo values of changed brain regions and scores of cognitive scales were evaluated. RESULTS NSCLC patients showed decreased scores of MMSE, MoCA and FACT-Cog and decreased ReHo values in the bilateral superior frontal gyrus (medial), middle frontal gyrus, left inferior frontal gyrus (orbital part) and increased ReHo values in the bilateral insula and caudate. Compared with HCs, patients receiving PeCC demonstrated decreased ReHo values in the right superior frontal gyrus (dorsolateral), left superior frontal gyrus (medial orbital), middle frontal gyrus, insula and rectus gyrus while patients receiving PaCC presented increased ReHo values in the right rolandic operculum, left insula and right caudate. Compared with patients receiving PaCC, patients receiving PeCC had decreased ReHo values in the left superior frontal gyrus (orbital part), middle frontal gyrus and increased ReHo values in the left inferior temporal gyrus, lingual gyrus. Moreover, positive relationships were found between ReHo values of the left and right superior frontal gyrus (medial) and the total scores of FACT-Cog in the patient group. CONCLUSION The findings provided evidences that carboplatin-based chemotherapy could cause CICI accompanied by functional changes in the prefrontal cortex, insula, caudate. These might be the pathophysiological basis for CICI of NSCLC patients and were affected by the differences of chemotherapeutic agent administration through different biological mechanisms.
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Affiliation(s)
- Siwen Liu
- Research Center for Clinical Oncology, Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research & The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, China
| | - Jie Ni
- Department of Oncology, Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research & The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, China
| | - Fei Yan
- Department of Oncology, Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research & The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, China
| | - Na Yin
- Department of Radiology, Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research & The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, China
| | - Xiaoyou Li
- Department of Oncology, Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research & The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, China
| | - Rong Ma
- Research Center for Clinical Oncology, Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research & The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, China
| | - Jianzhong Wu
- Research Center for Clinical Oncology, Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research & The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, China
| | - Guoren Zhou
- Department of Oncology, Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research & The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, China,*Correspondence: Jifeng Feng, ; Guoren Zhou,
| | - Jifeng Feng
- Research Center for Clinical Oncology, Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research & The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, China,Department of Oncology, Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research & The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, China,*Correspondence: Jifeng Feng, ; Guoren Zhou,
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Rizzi L, Aventurato ÍK, Balthazar MLF. Neuroimaging Research on Dementia in Brazil in the Last Decade: Scientometric Analysis, Challenges, and Peculiarities. Front Neurol 2021; 12:640525. [PMID: 33790850 PMCID: PMC8005640 DOI: 10.3389/fneur.2021.640525] [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: 12/11/2020] [Accepted: 02/18/2021] [Indexed: 12/12/2022] Open
Abstract
The last years have evinced a remarkable growth in neuroimaging studies around the world. All these studies have contributed to a better understanding of the cerebral outcomes of dementia, even in the earliest phases. In low- and middle-income countries, studies involving structural and functional neuroimaging are challenging due to low investments and heterogeneous populations. Outstanding the importance of diagnosing mild cognitive impairment and dementia, the purpose of this paper is to offer an overview of neuroimaging dementia research in Brazil. The review includes a brief scientometric analysis of quantitative information about the development of this field over the past 10 years. Besides, discusses some peculiarities and challenges that have limited neuroimaging dementia research in this big and heterogeneous country of Latin America. We systematically reviewed existing neuroimaging literature with Brazilian authors that presented outcomes related to a dementia syndrome, published from 2010 to 2020. Briefly, the main neuroimaging methods used were morphometrics, followed by fMRI, and DTI. The major diseases analyzed were Alzheimer's disease, mild cognitive impairment, and vascular dementia, respectively. Moreover, research activity in Brazil has been restricted almost entirely to a few centers in the Southeast region, and funding could be the main driver for publications. There was relative stability concerning the number of publications per year, the citation impact has historically been below the world average, and the author's gender inequalities are not relevant in this specific field. Neuroimaging research in Brazil is far from being developed and widespread across the country. Fortunately, increasingly collaborations with foreign partnerships contribute to the impact of Brazil's domestic research. Although the challenges, neuroimaging researches performed in the native population regarding regional peculiarities and adversities are of pivotal importance.
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Affiliation(s)
- Liara Rizzi
- Department of Neurology, University of Campinas (UNICAMP), Campinas, Brazil
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Li TR, Wu Y, Jiang JJ, Lin H, Han CL, Jiang JH, Han Y. Radiomics Analysis of Magnetic Resonance Imaging Facilitates the Identification of Preclinical Alzheimer's Disease: An Exploratory Study. Front Cell Dev Biol 2020; 8:605734. [PMID: 33344457 PMCID: PMC7744815 DOI: 10.3389/fcell.2020.605734] [Citation(s) in RCA: 31] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2020] [Accepted: 11/09/2020] [Indexed: 12/12/2022] Open
Abstract
Diagnosing Alzheimer's disease (AD) in the preclinical stage offers opportunities for early intervention; however, there is currently a lack of convenient biomarkers to facilitate the diagnosis. Using radiomics analysis, we aimed to determine whether the features extracted from multiparametric magnetic resonance imaging (MRI) can be used as potential biomarkers. This study was part of the Sino Longitudinal Study on Cognitive Decline project (NCT03370744), a prospective cohort study. All participants were cognitively healthy at baseline. Cohort 1 (n = 183) was divided into individuals with preclinical AD (n = 78) and controls (n = 105) using amyloid-positron emission tomography, and this cohort was used as the training dataset (80%) and validation dataset (the remaining 20%); cohort 2 (n = 51) was selected retrospectively and divided into "converters" and "nonconverters" according to individuals' future cognitive status, and this cohort was used as a separate test dataset; cohort three included 37 converters (13 from the Alzheimer's Disease Neuroimaging Initiative) and was used as another test set for independent longitudinal research. We extracted radiomics features from multiparametric MRI scans from each participant, using t-tests, autocorrelation tests, and three independent selection algorithms. We then established two classification models (support vector machine [SVM] and random forest [RF]) to verify the efficiency of the retained features. Five-fold cross-validation and 100 repetitions were carried out for the above process. Furthermore, the acquired stable high-frequency features were tested in cohort three by paired two-sample t-tests and survival analyses to identify whether their levels changed with cognitive decline and impact conversion time. The SVM and RF models both showed excellent classification efficiency, with an average accuracy of 89.7-95.9% and 87.1-90.8% in the validation set and 81.9-89.1% and 83.2-83.7% in the test set, respectively. Three stable high-frequency features were identified, all based on the structural MRI modality: the large zone high-gray-level emphasis feature of the right posterior cingulate gyrus, the variance feature of the left superior parietal gyrus, and the coarseness feature of the left posterior cingulate gyrus; their levels were correlated with amyloid-β deposition and predicted future cognitive decline (areas under the curve 0.649-0.761). In addition, levels of the variance feature at baseline decreased with cognitive decline and could affect the conversion time (p < 0.05). In conclusion, this exploratory study shows that the radiomics features of multiparametric MRI scans could represent potential biomarkers of preclinical AD.
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Affiliation(s)
- Tao-Ran Li
- Department of Neurology, Xuanwu Hospital of Capital Medical University, Beijing, China
| | - Yue Wu
- Key Laboratory of Specialty Fiber Optics and Optical Access Networks, Joint International Research Laboratory of Specialty Fiber Optics and Advanced Communication, School of Information and Communication Engineering, Shanghai University, Shanghai, China
| | - Juan-Juan Jiang
- Key Laboratory of Specialty Fiber Optics and Optical Access Networks, Joint International Research Laboratory of Specialty Fiber Optics and Advanced Communication, School of Information and Communication Engineering, Shanghai University, Shanghai, China
| | - Hua Lin
- Department of Neurology, Xuanwu Hospital of Capital Medical University, Beijing, China
| | - Chun-Lei Han
- Turku PET Centre and Turku University Hospital, Turku, Finland
| | - Jie-Hui Jiang
- Key Laboratory of Specialty Fiber Optics and Optical Access Networks, Joint International Research Laboratory of Specialty Fiber Optics and Advanced Communication, School of Information and Communication Engineering, Shanghai University, Shanghai, China
| | - Ying Han
- Department of Neurology, Xuanwu Hospital of Capital Medical University, Beijing, China
- Center of Alzheimer’s Disease, Beijing Institute for Brain Disorders, Beijing, China
- National Clinical Research Center for Geriatric Disorders, Beijing, China
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Zhang YD, Dong Z, Wang SH, Yu X, Yao X, Zhou Q, Hu H, Li M, Jiménez-Mesa C, Ramirez J, Martinez FJ, Gorriz JM. Advances in multimodal data fusion in neuroimaging: Overview, challenges, and novel orientation. AN INTERNATIONAL JOURNAL ON INFORMATION FUSION 2020; 64:149-187. [PMID: 32834795 PMCID: PMC7366126 DOI: 10.1016/j.inffus.2020.07.006] [Citation(s) in RCA: 132] [Impact Index Per Article: 26.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/30/2020] [Revised: 07/06/2020] [Accepted: 07/14/2020] [Indexed: 05/13/2023]
Abstract
Multimodal fusion in neuroimaging combines data from multiple imaging modalities to overcome the fundamental limitations of individual modalities. Neuroimaging fusion can achieve higher temporal and spatial resolution, enhance contrast, correct imaging distortions, and bridge physiological and cognitive information. In this study, we analyzed over 450 references from PubMed, Google Scholar, IEEE, ScienceDirect, Web of Science, and various sources published from 1978 to 2020. We provide a review that encompasses (1) an overview of current challenges in multimodal fusion (2) the current medical applications of fusion for specific neurological diseases, (3) strengths and limitations of available imaging modalities, (4) fundamental fusion rules, (5) fusion quality assessment methods, and (6) the applications of fusion for atlas-based segmentation and quantification. Overall, multimodal fusion shows significant benefits in clinical diagnosis and neuroscience research. Widespread education and further research amongst engineers, researchers and clinicians will benefit the field of multimodal neuroimaging.
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Affiliation(s)
- Yu-Dong Zhang
- School of Informatics, University of Leicester, Leicester, LE1 7RH, Leicestershire, UK
- Department of Information Systems, Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah 21589, Saudi Arabia
| | - Zhengchao Dong
- Department of Psychiatry, Columbia University, USA
- New York State Psychiatric Institute, New York, NY 10032, USA
| | - Shui-Hua Wang
- Department of Information Systems, Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah 21589, Saudi Arabia
- School of Architecture Building and Civil engineering, Loughborough University, Loughborough, LE11 3TU, UK
- School of Mathematics and Actuarial Science, University of Leicester, LE1 7RH, UK
| | - Xiang Yu
- School of Informatics, University of Leicester, Leicester, LE1 7RH, Leicestershire, UK
| | - Xujing Yao
- School of Informatics, University of Leicester, Leicester, LE1 7RH, Leicestershire, UK
| | - Qinghua Zhou
- School of Informatics, University of Leicester, Leicester, LE1 7RH, Leicestershire, UK
| | - Hua Hu
- Department of Psychiatry, Columbia University, USA
- Department of Neurology, The Second Affiliated Hospital of Soochow University, China
| | - Min Li
- Department of Psychiatry, Columbia University, USA
- School of Internet of Things, Hohai University, Changzhou, China
| | - Carmen Jiménez-Mesa
- Department of Signal Theory, Networking and Communications, University of Granada, Granada, Spain
| | - Javier Ramirez
- Department of Signal Theory, Networking and Communications, University of Granada, Granada, Spain
| | - Francisco J Martinez
- Department of Signal Theory, Networking and Communications, University of Granada, Granada, Spain
| | - Juan Manuel Gorriz
- Department of Signal Theory, Networking and Communications, University of Granada, Granada, Spain
- Department of Psychiatry, University of Cambridge, Cambridge CB21TN, UK
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Wang R, Wang C, Dai Z, Chen Y, Shen Z, Xiao G, Chen Y, Zhou JN, Zhuang Z, Wu R. An Amyloid-β Targeting Chemical Exchange Saturation Transfer Probe for In Vivo Detection of Alzheimer's Disease. ACS Chem Neurosci 2019; 10:3859-3867. [PMID: 31343167 DOI: 10.1021/acschemneuro.9b00334] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023] Open
Abstract
A reliable and reproducible detection of Aβ deposits would be beneficial for the early diagnosis of Alzheimer's disease (AD). In the present study, the feasibility of applying chemical exchange saturation transfer (CEST) for Aβ deposit detection using angiopep-2 as a probe was evaluated, and it was demonstrated that CEST could detect angiopep-2 and Aβ-angiopep-2 aggregates in vitro. Furthermore, APP/PS1 mice injected with angiopep-2 exhibited a significantly higher in vivo CEST effect when compared with controls. The distribution of Aβ deposits detected by CEST imaging was consistent with the histological staining results. The present study is the first to report a reliable exogenous CEST probe to noninvasively evaluate Aβ deposits in APP/PS1 mice. Furthermore, these results demonstrate the potential for clinical AD diagnosis and Aβ-targeted drug therapy assessment using CEST imaging with the angiopep-2 probe.
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Affiliation(s)
- Runrun Wang
- Department of Medical Imaging, Second Affiliated Hospital , Shantou University Medical College , Shantou , Guangdong 515000 , P. R. China
| | - Chenwei Wang
- CAS Key Laboratory of Brain Function and Disease, School of Life Sciences , University of Science and Technology of China , Hefei , Anhui 230000 , P. R. China
| | - Zhuozhi Dai
- Department of Medical Imaging, Second Affiliated Hospital , Shantou University Medical College , Shantou , Guangdong 515000 , P. R. China
| | - Yanzi Chen
- Department of Medical Imaging, Second Affiliated Hospital , Shantou University Medical College , Shantou , Guangdong 515000 , P. R. China
| | - Zhiwei Shen
- Department of Medical Imaging, Second Affiliated Hospital , Shantou University Medical College , Shantou , Guangdong 515000 , P. R. China
| | - Gang Xiao
- Department of Mathematics and Statistics , Hanshan Normal University , Chaozhou 515000 , P. R. China
| | - Yuanfeng Chen
- Department of Medical Imaging, Second Affiliated Hospital , Shantou University Medical College , Shantou , Guangdong 515000 , P. R. China
| | - Jiang-Ning Zhou
- CAS Key Laboratory of Brain Function and Disease, School of Life Sciences , University of Science and Technology of China , Hefei , Anhui 230000 , P. R. China
- Center for Excellence in Brain Science and Intelligence Technology , Chinese Academy of Sciences , Shanghai 200031 , China
| | - Zerui Zhuang
- Department of Medical Imaging, Second Affiliated Hospital , Shantou University Medical College , Shantou , Guangdong 515000 , P. R. China
| | - Renhua Wu
- Department of Medical Imaging, Second Affiliated Hospital , Shantou University Medical College , Shantou , Guangdong 515000 , P. R. China
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Wang R, Chen P, Shen Z, Lin G, Xiao G, Dai Z, Zhang B, Chen Y, Lai L, Zong X, Li Y, Tang Y, Wu R. Brain Amide Proton Transfer Imaging of Rat With Alzheimer's Disease Using Saturation With Frequency Alternating RF Irradiation Method. Front Aging Neurosci 2019; 11:217. [PMID: 31507405 PMCID: PMC6713910 DOI: 10.3389/fnagi.2019.00217] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2019] [Accepted: 08/02/2019] [Indexed: 02/05/2023] Open
Abstract
Amyloid-β (Aβ) deposits and some proteins play essential roles in the pathogenesis of Alzheimer's disease (AD). Amide proton transfer (APT) imaging, as an imaging modality to detect tissue protein, has shown promising features for the diagnosis of AD disease. In this study, we chose 10 AD model rats as the experimental group and 10 sham-operated rats as the control group. All the rats underwent a Y-maze test before APT image acquisition, using saturation with frequency alternating RF irradiation (APTSAFARI) method on a 7.0 T animal MRI scanner. Compared with the control group, APT (3.5 ppm) values of brain were significantly reduced in AD models (p < 0.002). The APTSAFARI imaging is more significant than APT imaging (p < 0.0001). AD model mice showed spatial learning and memory loss in the Y-maze experiment. In addition, there was significant neuronal loss in the hippocampal CA1 region and cortex compared with sham-operated rats. In conclusion, we demonstrated that APT imaging could potentially provide molecular biomarkers for the non-invasive diagnosis of AD. APTSAFARI MRI could be used as an effective tool to improve the accuracy of diagnosis of AD compared with conventional APT imaging.
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Affiliation(s)
- Runrun Wang
- Department of Medical Imaging, The Second Affiliated Hospital, Shantou University Medical College, Shantou, China
| | - Peidong Chen
- Department of Medical Imaging, The Second Affiliated Hospital, Shantou University Medical College, Shantou, China
| | - Zhiwei Shen
- Department of Medical Imaging, The Second Affiliated Hospital, Shantou University Medical College, Shantou, China
- Philips Healthcare, Shantou, China
| | - Guisen Lin
- Department of Medical Imaging, The Second Affiliated Hospital, Shantou University Medical College, Shantou, China
| | - Gang Xiao
- Department of Mathematics and Statistics, Hanshan Normal University, Chaozhou, China
| | - Zhuozhi Dai
- Department of Medical Imaging, The Second Affiliated Hospital, Shantou University Medical College, Shantou, China
| | - Bingna Zhang
- Translational Medicine, The Second Affiliated Hospital, Shantou University Medical College, Shantou, China
| | - Yuanfeng Chen
- Department of Medical Imaging, The Second Affiliated Hospital, Shantou University Medical College, Shantou, China
| | - Lihua Lai
- Department of Medical Imaging, The Second Affiliated Hospital, Shantou University Medical College, Shantou, China
| | - Xiaodan Zong
- Department of Medical Imaging, The Second Affiliated Hospital, Shantou University Medical College, Shantou, China
| | - Yan Li
- Department of Medical Imaging, The Second Affiliated Hospital, Shantou University Medical College, Shantou, China
| | - Yanyan Tang
- Department of Medical Imaging, The Second Affiliated Hospital, Shantou University Medical College, Shantou, China
| | - Renhua Wu
- Department of Medical Imaging, The Second Affiliated Hospital, Shantou University Medical College, Shantou, China
- *Correspondence: Renhua Wu,
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Pool size ratio of the substantia nigra in Parkinson's disease derived from two different quantitative magnetization transfer approaches. Neuroradiology 2017; 59:1251-1263. [PMID: 28986653 DOI: 10.1007/s00234-017-1911-2] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2017] [Accepted: 08/22/2017] [Indexed: 12/27/2022]
Abstract
PURPOSE We sought to measure quantitative magnetization transfer (qMT) properties of the substantia nigra pars compacta (SNc) in patients with Parkinson's disease (PD) and healthy controls (HCs) using a full qMT analysis and determine whether a rapid single-point measurement yields equivalent results for pool size ratio (PSR). METHODS Sixteen different MT-prepared MRI scans were obtained at 3 T from 16 PD patients and eight HCs, along with B1, B0, and relaxation time maps. Maps of PSR, free and macromolecular pool transverse relaxation times ([Formula: see text], [Formula: see text]) and rate of MT exchange between pools (k mf ) were generated using a full qMT model. PSR maps were also generated using a single-point qMT model requiring just two MT-prepared images. qMT parameter values of the SNc, red nucleus, cerebral crus, and gray matter were compared between groups and methods. RESULTS PSR of the SNc was the only qMT parameter to differ significantly between groups (p < 0.05). PSR measured via single-point analysis was less variable than with the full MT model, provided slightly better differentiation of PD patients from HCs (area under curve 0.77 vs. 0.75) with sensitivity of 0.75 and specificity of 0.87, and was better than transverse relaxation time in distinguishing PD patients from HCs (area under curve 0.71, sensitivity 0.87, and specificity 0.50). CONCLUSION The increased PSR observed in the SNc of PD patients may provide a novel biomarker of PD, possibly associated with an increased macromolecular content. Single-point PSR mapping with reduced variability and shorter scan times relative to the full qMT model appears clinically feasible.
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