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Coskun A, Ertaylan G, Pusparum M, Van Hoof R, Kaya ZZ, Khosravi A, Zarrabi A. Advancing personalized medicine: Integrating statistical algorithms with omics and nano-omics for enhanced diagnostic accuracy and treatment efficacy. Biochim Biophys Acta Mol Basis Dis 2024; 1870:167339. [PMID: 38986819 DOI: 10.1016/j.bbadis.2024.167339] [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] [Received: 04/04/2024] [Revised: 06/25/2024] [Accepted: 07/03/2024] [Indexed: 07/12/2024]
Abstract
Medical laboratory services enable precise measurement of thousands of biomolecules and have become an inseparable part of high-quality healthcare services, exerting a profound influence on global health outcomes. The integration of omics technologies into laboratory medicine has transformed healthcare, enabling personalized treatments and interventions based on individuals' distinct genetic and metabolic profiles. Interpreting laboratory data relies on reliable reference values. Presently, population-derived references are used for individuals, risking misinterpretation due to population heterogeneity, and leading to medical errors. Thus, personalized references are crucial for precise interpretation of individual laboratory results, and the interpretation of omics data should be based on individualized reference values. We reviewed recent advancements in personalized laboratory medicine, focusing on personalized omics, and discussed strategies for implementing personalized statistical approaches in omics technologies to improve global health and concluded that personalized statistical algorithms for interpretation of omics data have great potential to enhance global health. Finally, we demonstrated that the convergence of nanotechnology and omics sciences is transforming personalized laboratory medicine by providing unparalleled diagnostic precision and innovative therapeutic strategies.
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Affiliation(s)
- Abdurrahman Coskun
- Acibadem University, School of Medicine, Department of Medical Biochemistry, Istanbul, Turkey.
| | - Gökhan Ertaylan
- Unit Health, Environmental Intelligence, Flemish Institute for Technological Research (VITO), Mol 2400, Belgium
| | - Murih Pusparum
- Unit Health, Environmental Intelligence, Flemish Institute for Technological Research (VITO), Mol 2400, Belgium; I-Biostat, Data Science Institute, Hasselt University, Hasselt 3500, Belgium
| | - Rebekka Van Hoof
- Unit Health, Environmental Intelligence, Flemish Institute for Technological Research (VITO), Mol 2400, Belgium
| | - Zelal Zuhal Kaya
- Nisantasi University, School of Medicine, Department of Medical Biochemistry, Istanbul, Turkey
| | - Arezoo Khosravi
- Department of Genetics and Bioengineering, Faculty of Engineering and Natural Sciences, Istanbul Okan University, Istanbul 34959, Turkey
| | - Ali Zarrabi
- Department of Biomedical Engineering, Faculty of Engineering and Natural Sciences, Istinye University, Istanbul 34396, Turkey; Graduate School of Biotehnology and Bioengeneering, Yuan Ze University, Taoyuan 320315, Taiwan; Department of Research Analytics, Saveetha Dental College and Hospitals, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai 600 077, India
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Peng J, Mai Y, Liu J. Guideline for the cognitive assessment and follow-up in the Guangdong-Hong Kong-Macao Greater Bay Area (2024 edition). Aging Med (Milton) 2024; 7:258-268. [PMID: 38975298 PMCID: PMC11222743 DOI: 10.1002/agm2.12325] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2024] [Revised: 04/10/2024] [Accepted: 05/29/2024] [Indexed: 07/09/2024] Open
Abstract
This practice guideline focuses on the cognitive assessment for mild cognitive impairment in the Guangdong-Hong Kong-Macao Greater Bay Area. To achieve the standardization and normalization of its clinical practice and generate individualized intervention, the National Core Cognitive Center of the Second Affiliated Hospital of Guangzhou Medical University, the Cognitive Disorders Branch of Chinese Geriatic Society, the Dementia Group of Neurology Branch of Guangdong Medical Association and specialists from Hong Kong and Macao developed guidelines based on China's actual conditions and efficiency, economic cost and accuracy. The article addresses the significance, background, and the process of the assessment and follow-up to realize the promotion and dissemination of cognitive assessment.
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Affiliation(s)
- Jialing Peng
- Department of Neurology, Institute of Neuroscience, Key Laboratory of Neurogenetics and Channelopathies of Guangdong Province and the Ministry of Education of China, The Second Affiliated HospitalGuangzhou Medical UniversityGuangzhouChina
| | - Yingreng Mai
- Department of Neurology, Institute of Neuroscience, Key Laboratory of Neurogenetics and Channelopathies of Guangdong Province and the Ministry of Education of China, The Second Affiliated HospitalGuangzhou Medical UniversityGuangzhouChina
| | - Jun Liu
- Department of Neurology, Institute of Neuroscience, Key Laboratory of Neurogenetics and Channelopathies of Guangdong Province and the Ministry of Education of China, The Second Affiliated HospitalGuangzhou Medical UniversityGuangzhouChina
- National Core Cognitive CenterThe Second Affiliated Hospital of Guangzhou Medical UniversityGuangzhouChina
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Chen Z, Bi S, Shan Y, Cui B, Yang H, Qi Z, Zhao Z, Han Y, Yan S, Lu J. Multiparametric hippocampal signatures for early diagnosis of Alzheimer's disease using 18F-FDG PET/MRI Radiomics. CNS Neurosci Ther 2024; 30:e14539. [PMID: 38031997 PMCID: PMC11017421 DOI: 10.1111/cns.14539] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2023] [Revised: 10/18/2023] [Accepted: 11/10/2023] [Indexed: 12/01/2023] Open
Abstract
PURPOSE This study aimed to explore the utility of hippocampal radiomics using multiparametric simultaneous positron emission tomography (PET)/magnetic resonance imaging (MRI) for early diagnosis of Alzheimer's disease (AD). METHODS A total of 53 healthy control (HC) participants, 55 patients with amnestic mild cognitive impairment (aMCI), and 51 patients with AD were included in this study. All participants accepted simultaneous PET/MRI scans, including 18F-fluorodeoxyglucose (18F-FDG) PET, 3D arterial spin labeling (ASL), and high-resolution T1-weighted imaging (3D T1WI). Radiomics features were extracted from the hippocampus region on those three modal images. Logistic regression models were trained to classify AD and HC, AD and aMCI, aMCI and HC respectively. The diagnostic performance and radiomics score (Rad-Score) of logistic regression models were evaluated from 5-fold cross-validation. RESULTS The hippocampal radiomics features demonstrated favorable diagnostic performance, with the multimodal classifier outperforming the single-modal classifier in the binary classification of HC, aMCI, and AD. Using the multimodal classifier, we achieved an area under the receiver operating characteristic curve (AUC) of 0.98 and accuracy of 96.7% for classifying AD from HC, and an AUC of 0.86 and accuracy of 80.6% for classifying aMCI from HC. The value of Rad-Score differed significantly between the AD and HC (p < 0.001), aMCI and HC (p < 0.001) groups. Decision curve analysis showed superior clinical benefits of multimodal classifiers compared to neuropsychological tests. CONCLUSION Multiparametric hippocampal radiomics using PET/MRI aids in the identification of early AD, and may provide a potential biomarker for clinical applications.
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Affiliation(s)
- Zhigeng Chen
- Department of Radiology and Nuclear Medicine, Xuanwu HospitalCapital Medical UniversityBeijingChina
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain InformaticsBeijingChina
- Key Laboratory of Neurodegenerative DiseasesMinistry of EducationBeijingChina
| | - Sheng Bi
- Department of Radiology and Nuclear Medicine, Xuanwu HospitalCapital Medical UniversityBeijingChina
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain InformaticsBeijingChina
- Key Laboratory of Neurodegenerative DiseasesMinistry of EducationBeijingChina
| | - Yi Shan
- Department of Radiology and Nuclear Medicine, Xuanwu HospitalCapital Medical UniversityBeijingChina
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain InformaticsBeijingChina
- Key Laboratory of Neurodegenerative DiseasesMinistry of EducationBeijingChina
| | - Bixiao Cui
- Department of Radiology and Nuclear Medicine, Xuanwu HospitalCapital Medical UniversityBeijingChina
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain InformaticsBeijingChina
- Key Laboratory of Neurodegenerative DiseasesMinistry of EducationBeijingChina
| | - Hongwei Yang
- Department of Radiology and Nuclear Medicine, Xuanwu HospitalCapital Medical UniversityBeijingChina
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain InformaticsBeijingChina
- Key Laboratory of Neurodegenerative DiseasesMinistry of EducationBeijingChina
| | - Zhigang Qi
- Department of Radiology and Nuclear Medicine, Xuanwu HospitalCapital Medical UniversityBeijingChina
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain InformaticsBeijingChina
- Key Laboratory of Neurodegenerative DiseasesMinistry of EducationBeijingChina
| | - Zhilian Zhao
- Department of Radiology and Nuclear Medicine, Xuanwu HospitalCapital Medical UniversityBeijingChina
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain InformaticsBeijingChina
- Key Laboratory of Neurodegenerative DiseasesMinistry of EducationBeijingChina
| | - Ying Han
- Department of Neurology, Xuanwu HospitalCapital Medical UniversityBeijingChina
| | - Shaozhen Yan
- Department of Radiology and Nuclear Medicine, Xuanwu HospitalCapital Medical UniversityBeijingChina
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain InformaticsBeijingChina
- Key Laboratory of Neurodegenerative DiseasesMinistry of EducationBeijingChina
| | - Jie Lu
- Department of Radiology and Nuclear Medicine, Xuanwu HospitalCapital Medical UniversityBeijingChina
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain InformaticsBeijingChina
- Key Laboratory of Neurodegenerative DiseasesMinistry of EducationBeijingChina
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Di Domenico F, Lanzillotta C, Perluigi M. Redox imbalance and metabolic defects in the context of Alzheimer disease. FEBS Lett 2024. [PMID: 38472147 DOI: 10.1002/1873-3468.14840] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2023] [Revised: 02/12/2024] [Accepted: 02/12/2024] [Indexed: 03/14/2024]
Abstract
Redox reactions play a critical role for intracellular processes, including pathways involved in metabolism and signaling. Reactive oxygen species (ROS) act either as second messengers or generators of protein modifications, fundamental mechanisms for signal transduction. Disturbance of redox homeostasis is associated with many disorders. Among these, Alzheimer's disease is a neurodegenerative pathology that presents hallmarks of oxidative damage such as increased ROS production, decreased activity of antioxidant enzymes, oxidative modifications of macromolecules, and changes in mitochondrial homeostasis. Interestingly, alteration of redox homeostasis is closely associated with defects of energy metabolism, involving both carbohydrates and lipids, the major energy fuels for the cell. As the brain relies exclusively on glucose metabolism, defects of glucose utilization represent a harmful event for the brain. During aging, a progressive perturbation of energy metabolism occurs resulting in brain hypometabolism. This condition contributes to increase neuronal cell vulnerability ultimately resulting in cognitive impairment. The current review discusses the crosstalk between alteration of redox homeostasis and brain energy defects that seems to act in concert in promoting Alzheimer's neurodegeneration.
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Affiliation(s)
- Fabio Di Domenico
- Department of Biochemical Sciences "A. Rossi Fanelli", Sapienza University of Rome, Italy
| | - Chiara Lanzillotta
- Department of Biochemical Sciences "A. Rossi Fanelli", Sapienza University of Rome, Italy
| | - Marzia Perluigi
- Department of Biochemical Sciences "A. Rossi Fanelli", Sapienza University of Rome, Italy
- Laboratory Affiliated to Istituto Pasteur Italia-Fondazione Cenci Bolognetti, Rome, Italy
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Du L, Roy S, Wang P, Li Z, Qiu X, Zhang Y, Yuan J, Guo B. Unveiling the future: Advancements in MRI imaging for neurodegenerative disorders. Ageing Res Rev 2024; 95:102230. [PMID: 38364912 DOI: 10.1016/j.arr.2024.102230] [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] [Received: 01/11/2024] [Revised: 02/11/2024] [Accepted: 02/11/2024] [Indexed: 02/18/2024]
Abstract
Neurodegenerative disorders represent a significant and growing global health challenge, necessitating continuous advancements in diagnostic tools for accurate and early detection. This work explores the recent progress in Magnetic Resonance Imaging (MRI) techniques and their application in the realm of neurodegenerative disorders. The introductory section provides a comprehensive overview of the study's background, significance, and objectives. Recognizing the current challenges associated with conventional MRI, the manuscript delves into advanced imaging techniques such as high-resolution structural imaging (HR-MRI), functional MRI (fMRI), diffusion tensor imaging (DTI), and positron emission tomography-MRI (PET-MRI) fusion. Each technique is critically examined regarding its potential to address theranostic limitations and contribute to a more nuanced understanding of the underlying pathology. A substantial portion of the work is dedicated to exploring the applications of advanced MRI in specific neurodegenerative disorders, including Parkinson's disease, Alzheimer's disease, Huntington's disease, and Amyotrophic Lateral Sclerosis (ALS). In addressing the future landscape, the manuscript examines technological advances, including the integration of machine learning and artificial intelligence in neuroimaging. The conclusion summarizes key findings, outlines implications for future research, and underscores the importance of these advancements in reshaping our understanding and approach to neurodegenerative disorders.
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Affiliation(s)
- Lixin Du
- Department of Medical Imaging, Shenzhen Longhua District Central Hospital, Shenzhen Longhua District Key Laboratory of Neuroimaging, Shenzhen 518110, China.
| | - Shubham Roy
- School of Science, Shenzhen Key Laboratory of Flexible Printed Electronics Technology, Shenzhen Key Laboratory of Advanced Functional Carbon Materials Research and Comprehensive Application, Harbin Institute of Technology, Shenzhen 518055, China
| | - Pan Wang
- Department of Medical Imaging, Shenzhen Longhua District Central Hospital, Shenzhen Longhua District Key Laboratory of Neuroimaging, Shenzhen 518110, China
| | - Zhigang Li
- Department of Medical Imaging, Shenzhen Longhua District Central Hospital, Shenzhen Longhua District Key Laboratory of Neuroimaging, Shenzhen 518110, China
| | - Xiaoting Qiu
- Department of Medical Imaging, Shenzhen Longhua District Central Hospital, Shenzhen Longhua District Key Laboratory of Neuroimaging, Shenzhen 518110, China
| | - Yinghe Zhang
- School of Science, Shenzhen Key Laboratory of Flexible Printed Electronics Technology, Shenzhen Key Laboratory of Advanced Functional Carbon Materials Research and Comprehensive Application, Harbin Institute of Technology, Shenzhen 518055, China
| | - Jianpeng Yuan
- Department of Radiology, The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen 518107, China.
| | - Bing Guo
- School of Science, Shenzhen Key Laboratory of Flexible Printed Electronics Technology, Shenzhen Key Laboratory of Advanced Functional Carbon Materials Research and Comprehensive Application, Harbin Institute of Technology, Shenzhen 518055, China.
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Vanderlinden G, Carron C, Vandenberghe R, Vandenbulcke M, Van Laere K. In vivo PET of synaptic density as potential diagnostic marker for cognitive disorders: prospective comparison with current imaging markers for neuronal dysfunction and relation to symptomatology - study protocol. BMC Med Imaging 2024; 24:41. [PMID: 38347458 PMCID: PMC10860316 DOI: 10.1186/s12880-024-01224-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2023] [Accepted: 02/05/2024] [Indexed: 02/15/2024] Open
Abstract
BACKGROUND 18F-FDG brain PET is clinically used for differential diagnosis in cognitive dysfunction of unclear etiology and for exclusion of a neurodegenerative cause in patients with cognitive impairment in late-life psychiatric disorders. 18F-FDG PET measures regional glucose metabolism, which represents a combination of neuronal/synaptic activity but also astrocytic activity and neuroinflammation. Recently, imaging of synaptic vesicle protein 2 A (SV2A) has become available and was shown to be a proxy of synaptic density. This prospective study will investigate the use of 18F-SynVesT-1 for imaging SV2A and its discriminative power for differential diagnosis in cognitive disorders in a head-to-head comparison to 18F-FDG PET. In addition, simultaneous PET/MR allows an evaluation of contributing factors and the additional value of advanced MRI imaging to FDG/SV2A PET imaging will be investigated. In this work, the study design and protocol are depicted. METHODS In this prospective, multimodal imaging study, 110 patients with uncertain diagnosis of cognitive impairment who are referred for 18F-FDG PET brain imaging in their diagnostic work-up in a tertiary memory clinic will be recruited. In addition, 40 healthy volunteers (HV) between 18 and 85 years (M/F) will be included. All study participants will undergo simultaneous 18F-SynVesT-1 PET/MR and an extensive neuropsychological evaluation. Amyloid status will be measured by PET using 18FNAV4694, in HV above 50 years of age. Structural T1-weighted and T2-weighted fluid-attenuated inversion recovery MR images, triple-tagging arterial spin labeling (ASL) and resting-state functional MRI (rs-fMRI) will be obtained. The study has been registered on ClinicalTrials.gov (NCT05384353) and is approved by the local Research Ethics Committee. DISCUSSION The main endpoint of the study will be the comparison of the diagnostic accuracy between 18F-SynVesT-1 and 18F-FDG PET in cognitive disorders with uncertain etiology and in exclusion of a neurodegenerative cause in patients with cognitive impairment in late-life psychiatric disorders. The strength of the relationship between cognition and imaging data will be assessed, as well as the potential incremental diagnostic value of including MR volumetry, ASL perfusion and rs-fMRI.
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Affiliation(s)
- Greet Vanderlinden
- Nuclear Medicine and Molecular Imaging, Imaging and Pathology, KU Leuven, Leuven, Belgium.
| | - Charles Carron
- Nuclear Medicine and Molecular Imaging, Imaging and Pathology, KU Leuven, Leuven, Belgium
- Division of Nuclear Medicine, University Hospitals UZ Leuven, Leuven, Belgium
| | - Rik Vandenberghe
- Department of Neurology, University Hospitals UZ Leuven, Leuven, Belgium
- Laboratory for Cognitive Neurology, Department of Neurosciences, KU Leuven, Leuven, Belgium
| | - Mathieu Vandenbulcke
- Research Group Psychiatry, KU Leuven, Leuven, Belgium
- Department of Old-Age Psychiatry, University Hospitals UZ Leuven, Leuven, Belgium
- Leuven Brain Institute, Leuven, Belgium
| | - Koen Van Laere
- Nuclear Medicine and Molecular Imaging, Imaging and Pathology, KU Leuven, Leuven, Belgium
- Division of Nuclear Medicine, University Hospitals UZ Leuven, Leuven, Belgium
- Leuven Brain Institute, Leuven, Belgium
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Huang L, Li Q, Lu Y, Pan F, Cui L, Wang Y, Miao Y, Chen T, Li Y, Wu J, Chen X, Jia J, Guo Q. Consensus on rapid screening for prodromal Alzheimer's disease in China. Gen Psychiatr 2024; 37:e101310. [PMID: 38313393 PMCID: PMC10836380 DOI: 10.1136/gpsych-2023-101310] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/31/2023] [Accepted: 12/19/2023] [Indexed: 02/06/2024] Open
Abstract
Alzheimer's disease (AD) is a common cause of dementia, characterised by cerebral amyloid-β deposition, pathological tau and neurodegeneration. The prodromal stage of AD (pAD) refers to patients with mild cognitive impairment (MCI) and evidence of AD's pathology. At this stage, disease-modifying interventions should be used to prevent the progression to dementia. Given the inherent heterogeneity of MCI, more specific biomarkers are needed to elucidate the underlying AD's pathology. Although the uses of cerebrospinal fluid and positron emission tomography are widely accepted methods for detecting AD's pathology, their clinical applications are limited by their high costs and invasiveness, particularly in low-income areas in China. Therefore, to improve the early detection of Alzheimer's disease (AD) pathology through cost-effective screening methods, a panel of 45 neurologists, psychiatrists and gerontologists was invited to establish a formal consensus on the screening of pAD in China. The supportive evidence and grades of recommendations are based on a systematic literature review and focus group discussion. National meetings were held to allow participants to review, vote and provide their expert opinions to reach a consensus. A majority (two-thirds) decision was used for questions for which consensus could not be reached. Recommended screening methods are presented in this publication, including neuropsychological assessment, peripheral biomarkers and brain imaging. In addition, a general workflow for screening pAD in China is established, which will help clinicians identify individuals at high risk and determine therapeutic targets.
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Affiliation(s)
- Lin Huang
- Department of Gerontology, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Qinjie Li
- Department of Gerontology, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yao Lu
- Department of Gerontology, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Fengfeng Pan
- Department of Gerontology, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Liang Cui
- Department of Gerontology, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Ying Wang
- Department of Gerontology, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Ya Miao
- Department of Gerontology, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Tianlu Chen
- Center for Translational Medicine and Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yatian Li
- Shanghai BestCovered, Shanghai, China
| | | | - Xiaochun Chen
- Department of Neurology, Fujian Medical University Union Hospital, Fuzhou, China
| | - Jianping Jia
- Department of Neurology, National Clinical Research Center for Geriatric Diseases, Beijing, China
| | - Qihao Guo
- Department of Gerontology, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
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Bi S, Yan S, Chen Z, Cui B, Shan Y, Yang H, Qi Z, Zhao Z, Han Y, Lu J. Comparison of 18F-FDG PET and arterial spin labeling MRI in evaluating Alzheimer's disease and amnestic mild cognitive impairment using integrated PET/MR. EJNMMI Res 2024; 14:9. [PMID: 38270821 PMCID: PMC10811308 DOI: 10.1186/s13550-024-01068-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2023] [Accepted: 01/14/2024] [Indexed: 01/26/2024] Open
Abstract
BACKGROUND Developing biomarkers for early stage AD patients is crucial. Glucose metabolism measured by 18F-FDG PET is the most common biomarker for evaluating cellular energy metabolism to diagnose AD. Arterial spin labeling (ASL) MRI can potentially provide comparable diagnostic information to 18F-FDG PET in patients with neurodegenerative disorders. However, the conclusions about the diagnostic performance of AD are still controversial between 18F-FDG PET and ASL. This study aims to compare quantitative cerebral blood flow (CBF) and glucose metabolism measured by 18F-FDG PET diagnostic values in patients with Alzheimer's disease (AD) and amnestic mild cognitive impairment (aMCI) using integrated PET/MR. RESULTS Analyses revealed overlapping between decreased regional rCBF and 18F-FDG PET SUVR in patients with AD compared with NC participants in the bilateral parietotemporal regions, frontal cortex, and cingulate cortex. Compared with NC participants, patients with aMCI exclusively demonstrated lower 18F-FDG PET SUVR in the bilateral temporal cortex, insula cortex, and inferior frontal cortex. Comparison of the rCBF in patients with aMCI and NC participants revealed no significant difference (P > 0.05). The ROC analysis of rCBF in the meta-ROI could diagnose patients with AD (AUC, 0.87) but not aMCI (AUC, 0.61). The specificity of diagnosing aMCI has been improved to 75.56% when combining rCBF and 18F-FDG PET SUVR. CONCLUSION ASL could detect similar aberrant patterns of abnormalities compared to 18F-FDG PET in patients with AD compared with NC participants but not in aMCI. The diagnostic efficiency of 18F-FDG-PET for AD and aMCI patients remained higher to ASL. Our findings support that applying 18F-FDG PET may be preferable for diagnosing AD and aMCI.
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Affiliation(s)
- Sheng Bi
- Department of Radiology & Nuclear Medicine, Xuanwu Hospital, Capital Medical University, 45 Changchun Street, Xicheng District, Beijing, 100053, China
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, China
- Key Laboratory of Neurodegenerative Diseases, Ministry of Education, Beijing, China
| | - Shaozhen Yan
- Department of Radiology & Nuclear Medicine, Xuanwu Hospital, Capital Medical University, 45 Changchun Street, Xicheng District, Beijing, 100053, China
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, China
- Key Laboratory of Neurodegenerative Diseases, Ministry of Education, Beijing, China
| | - Zhigeng Chen
- Department of Radiology & Nuclear Medicine, Xuanwu Hospital, Capital Medical University, 45 Changchun Street, Xicheng District, Beijing, 100053, China
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, China
- Key Laboratory of Neurodegenerative Diseases, Ministry of Education, Beijing, China
| | - Bixiao Cui
- Department of Radiology & Nuclear Medicine, Xuanwu Hospital, Capital Medical University, 45 Changchun Street, Xicheng District, Beijing, 100053, China
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, China
- Key Laboratory of Neurodegenerative Diseases, Ministry of Education, Beijing, China
| | - Yi Shan
- Department of Radiology & Nuclear Medicine, Xuanwu Hospital, Capital Medical University, 45 Changchun Street, Xicheng District, Beijing, 100053, China
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, China
- Key Laboratory of Neurodegenerative Diseases, Ministry of Education, Beijing, China
| | - Hongwei Yang
- Department of Radiology & Nuclear Medicine, Xuanwu Hospital, Capital Medical University, 45 Changchun Street, Xicheng District, Beijing, 100053, China
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, China
- Key Laboratory of Neurodegenerative Diseases, Ministry of Education, Beijing, China
| | - Zhigang Qi
- Department of Radiology & Nuclear Medicine, Xuanwu Hospital, Capital Medical University, 45 Changchun Street, Xicheng District, Beijing, 100053, China
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, China
- Key Laboratory of Neurodegenerative Diseases, Ministry of Education, Beijing, China
| | - Zhilian Zhao
- Department of Radiology & Nuclear Medicine, Xuanwu Hospital, Capital Medical University, 45 Changchun Street, Xicheng District, Beijing, 100053, China
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, China
- Key Laboratory of Neurodegenerative Diseases, Ministry of Education, Beijing, China
| | - Ying Han
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Jie Lu
- Department of Radiology & Nuclear Medicine, Xuanwu Hospital, Capital Medical University, 45 Changchun Street, Xicheng District, Beijing, 100053, China.
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, China.
- Key Laboratory of Neurodegenerative Diseases, Ministry of Education, Beijing, China.
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Shan Y, Yan SZ, Wang Z, Cui BX, Yang HW, Yuan JM, Yin YY, Shi F, Lu J. Impact of brain segmentation methods on regional metabolism quantification in 18F-FDG PET/MR analysis. EJNMMI Res 2023; 13:79. [PMID: 37668814 PMCID: PMC10480127 DOI: 10.1186/s13550-023-01028-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2023] [Accepted: 08/28/2023] [Indexed: 09/06/2023] Open
Abstract
BACKGROUND Accurate analysis of quantitative PET data plays a crucial role in studying small, specific brain structures. The integration of PET and MRI through an integrated PET/MR system presents an opportunity to leverage the benefits of precisely aligned structural MRI and molecular PET images in both spatial and temporal dimensions. However, in many clinical workflows, PET studies are often performed without the aid of individually matched structural MRI scans, primarily for the sake of convenience in the data collection and brain segmentation possesses. Currently, two commonly employed segmentation strategies for brain PET analysis are distinguished: methods with or without MRI registration and methods employing either atlas-based or individual-based algorithms. Moreover, the development of artificial intelligence (AI)-assisted methods for predicting brain segmentation holds promise but requires further validation of their efficiency and accuracy for clinical applications. This study aims to compare and evaluate the correlations, consistencies, and differences among the above-mentioned brain segmentation strategies in quantification of brain metabolism in 18F-FDG PET/MR analysis. RESULTS Strong correlations were observed among all methods (r = 0.932 to 0.999, P < 0.001). The variances attributable to subject and brain region were higher than those caused by segmentation methods (P < 0.001). However, intraclass correlation coefficient (ICC)s between methods with or without MRI registration ranged from 0.924 to 0.975, while ICCs between methods with atlas- or individual-based algorithms ranged from 0.741 to 0.879. Brain regions exhibiting significant standardized uptake values (SUV) differences due to segmentation methods were the basal ganglia nuclei (maximum to 11.50 ± 4.67%), and various cerebral cortexes in temporal and occipital regions (maximum to 18.03 ± 5.52%). The AI-based method demonstrated high correlation (r = 0.998 and 0.999, P < 0.001) and ICC (0.998 and 0.997) with FreeSurfer, substantially reducing the time from 8.13 h to 57 s on per subject. CONCLUSIONS Different segmentation methods may have impact on the calculation of brain metabolism in basal ganglia nuclei and specific cerebral cortexes. The AI-based approach offers improved efficiency and is recommended for its enhanced performance.
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Affiliation(s)
- Yi Shan
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, #45 Changchunjie, Xicheng District, Beijing, 100053, China
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, 100053, China
| | - Shao-Zhen Yan
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, #45 Changchunjie, Xicheng District, Beijing, 100053, China
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, 100053, China
| | - Zhe Wang
- Central Research Institute, United Imaging Healthcare Group, Shanghai, 201807, China
| | - Bi-Xiao Cui
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, #45 Changchunjie, Xicheng District, Beijing, 100053, China
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, 100053, China
| | - Hong-Wei Yang
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, #45 Changchunjie, Xicheng District, Beijing, 100053, China
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, 100053, China
| | - Jian-Min Yuan
- Central Research Institute, United Imaging Healthcare Group, Shanghai, 201807, China
| | - Ya-Yan Yin
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, #45 Changchunjie, Xicheng District, Beijing, 100053, China
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, 100053, China
| | - Feng Shi
- Shanghai United Imaging Intelligence Co., Ltd., Shanghai, 200030, China
| | - Jie Lu
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, #45 Changchunjie, Xicheng District, Beijing, 100053, China.
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, 100053, China.
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10
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Hari E, Kizilates-Evin G, Kurt E, Bayram A, Ulasoglu-Yildiz C, Gurvit H, Demiralp T. Functional and structural connectivity in the Papez circuit in different stages of Alzheimer's disease. Clin Neurophysiol 2023; 153:33-45. [PMID: 37451080 DOI: 10.1016/j.clinph.2023.06.008] [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] [Received: 02/23/2023] [Revised: 04/12/2023] [Accepted: 06/16/2023] [Indexed: 07/18/2023]
Abstract
OBJECTIVE Alzheimer's disease (AD) is a progressive neurodegenerative continuum with memory impairment. We aimed to examine the detailed functional (FC) and structural connectivity (SC) pattern of the Papez circuit, known as the memory circuit, along the AD. METHODS MRI data of 15 patients diagnosed with AD dementia (ADD), 15 patients with the amnestic mild cognitive impairment (MCI), and 15 patients with subjective cognitive impairment were analyzed. The FC analyses were performed between main nodes of the Papez circuit, and the SC was quantified as fractional anisotropy (FA) of the main white matter pathways of the Papez circuit. RESULTS The FC between the retrosplenial (RSC) and parahippocampal cortices (PHC) was the earliest affected FC, while a manifest SC change in the ventral cingulum and fornix was observed in the later ADD stage. The RSC-PHC FC and the ventral cingulum FA efficiently predicted the memory performance of the non-demented participants. CONCLUSIONS Our findings revealed the importance of the Papez circuit as target regions along the AD. SIGNIFICANCE The ventral cingulum connecting the RSC and PHC, a critical overlap area between the Papez circuit and the default mode network, seems to be a target region associated with the earliest objective memory findings in AD.
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Affiliation(s)
- Emre Hari
- Graduate School of Health Sciences, Istanbul University, 34216 Istanbul, Turkey; Department of Neuroscience, Aziz Sancar Institute of Experimental Medicine, Istanbul University, 34093 Istanbul, Turkey; Hulusi Behcet Life Sciences Research Laboratory, Neuroimaging Unit, Istanbul University, 34093 Istanbul, Turkey.
| | - Gozde Kizilates-Evin
- Department of Neuroscience, Aziz Sancar Institute of Experimental Medicine, Istanbul University, 34093 Istanbul, Turkey; Hulusi Behcet Life Sciences Research Laboratory, Neuroimaging Unit, Istanbul University, 34093 Istanbul, Turkey.
| | - Elif Kurt
- Department of Neuroscience, Aziz Sancar Institute of Experimental Medicine, Istanbul University, 34093 Istanbul, Turkey; Hulusi Behcet Life Sciences Research Laboratory, Neuroimaging Unit, Istanbul University, 34093 Istanbul, Turkey.
| | - Ali Bayram
- Department of Neuroscience, Aziz Sancar Institute of Experimental Medicine, Istanbul University, 34093 Istanbul, Turkey; Hulusi Behcet Life Sciences Research Laboratory, Neuroimaging Unit, Istanbul University, 34093 Istanbul, Turkey.
| | - Cigdem Ulasoglu-Yildiz
- Department of Neuroscience, Aziz Sancar Institute of Experimental Medicine, Istanbul University, 34093 Istanbul, Turkey; Hulusi Behcet Life Sciences Research Laboratory, Neuroimaging Unit, Istanbul University, 34093 Istanbul, Turkey.
| | - Hakan Gurvit
- Hulusi Behcet Life Sciences Research Laboratory, Neuroimaging Unit, Istanbul University, 34093 Istanbul, Turkey; Department of Neurology, Behavioral Neurology and Movement Disorders Unit, Istanbul Faculty of Medicine, Istanbul University, 34093 Istanbul, Turkey.
| | - Tamer Demiralp
- Hulusi Behcet Life Sciences Research Laboratory, Neuroimaging Unit, Istanbul University, 34093 Istanbul, Turkey; Department of Physiology, Istanbul Faculty of Medicine, Istanbul University, 34093 Istanbul, Turkey.
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11
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Satoh Y, Hanaoka K, Ikegawa C, Imai M, Watanabe S, Morimoto-Ishikawa D, Onishi H, Ito T, Komoike Y, Ishii K. Organ-Specific Positron Emission Tomography Scanners for Breast Imaging: Comparison between the Performances of Prior and Novel Models. Diagnostics (Basel) 2023; 13:diagnostics13061079. [PMID: 36980385 PMCID: PMC10047304 DOI: 10.3390/diagnostics13061079] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2023] [Revised: 03/02/2023] [Accepted: 03/11/2023] [Indexed: 03/14/2023] Open
Abstract
The performances of photomultiplier tube (PMT)-based dedicated breast positron emission tomography (PET) and silicon photomultiplier tube (SiPM)-based time-of-flight (TOF) PET, which is applicable not only to breast imaging but also to head imaging, were compared using a phantom study. A cylindrical phantom containing four spheres (3–10 mm in diameter) filled with 18F-FDG at two signal-to-background ratios (SBRs), 4:1 and 8:1, was scanned. The phantom images, which were reconstructed using three-dimensional list-mode dynamic row-action maximum likelihood algorithm with various β-values and post-smoothing filters, were visually and quantitatively compared. Visual evaluation showed that the 3 mm sphere was more clearly visualized with higher β and smaller post-filters, while the background was noisier; SiPM-based TOF-PET was superior to PMT-based dbPET in sharpness, smoothness, and detectability, although the background was noisier at the SBR of 8:1. Quantitative evaluation revealed that the detection index (DI) and recovery coefficient (CRC) of SiPM-based TOF-PET images were higher than those of PMT-based PET images, despite a higher background coefficient of variation (CVBG). The two organ-specific PET systems showed that a 3 mm lesion in the breast could be visualized at the center of the detector, and there was less noise in the SiPM-based TOF-PET image.
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Affiliation(s)
- Yoko Satoh
- Yamanashi PET Imaging Clinic, Chuo 409-3821, Japan
- Department of Radiology, University of Yamanashi, Chuo 409-3898, Japan
- Correspondence:
| | - Kohei Hanaoka
- Division of Positron Emission Tomography, Institute of Advanced Clinical Medicine, Kindai University, Osakasayama 589-8511, Japan
| | | | | | - Shota Watanabe
- Division of Positron Emission Tomography, Institute of Advanced Clinical Medicine, Kindai University, Osakasayama 589-8511, Japan
| | - Daisuke Morimoto-Ishikawa
- Division of Positron Emission Tomography, Institute of Advanced Clinical Medicine, Kindai University, Osakasayama 589-8511, Japan
| | - Hiroshi Onishi
- Department of Radiology, University of Yamanashi, Chuo 409-3898, Japan
| | - Toshikazu Ito
- Division of Breast and Endocrine Surgery, Department of Surgery, Kindai University Faculty of Medicine, Osakasayama 589-8511, Japan
| | - Yoshifumi Komoike
- Division of Breast and Endocrine Surgery, Department of Surgery, Kindai University Faculty of Medicine, Osakasayama 589-8511, Japan
| | - Kazunari Ishii
- Division of Positron Emission Tomography, Institute of Advanced Clinical Medicine, Kindai University, Osakasayama 589-8511, Japan
- Department of Radiology, Kindai University Faculty of Medicine, Osakasayama 577-8502, Japan
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12
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Yin Z, Wang Z, Li Y, Zhou J, Chen Z, Xia M, Zhang X, Wu J, Zhao L, Liang F. Neuroimaging studies of acupuncture on Alzheimer's disease: a systematic review. BMC Complement Med Ther 2023; 23:63. [PMID: 36823586 PMCID: PMC9948384 DOI: 10.1186/s12906-023-03888-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2022] [Accepted: 02/14/2023] [Indexed: 02/25/2023] Open
Abstract
BACKGROUND Acupuncture effectively improves cognitive function in Alzheimer's disease (AD). Many neuroimaging studies have found significant brain alterations after acupuncture treatment of AD, but the underlying central modulation mechanism is unclear. OBJECTIVE This review aims to provide neuroimaging evidence to understand the central mechanisms of acupuncture in patients with AD. METHODS Relevant neuroimaging studies about acupuncture for AD were retrieved from eight English and Chinese medicine databases (PubMed, Embase, Cochrane Library, Web of Science, SinoMed, CNKI, WF, VIP) and other resources from inception of databases until June 1, 2022, and their methodological quality was assessed using RoB 2.0 and ROBINS - I. Brain neuroimaging information was extracted to investigate the potential neural mechanism of acupuncture for AD. Descriptive statistics were used for data analysis. RESULTS Thirteen neuroimaging studies involving 275 participants were included in this review, and the overall methodological quality of included studies was moderate. The approaches applied included task-state functional magnetic resonance imaging (ts-fMRI; n = 9 studies) and rest-state functional magnetic resonance imaging (rs-fMRI; n = 4 studies). All studies focused on the instant effect of acupuncture on the brains of AD participants, including the cingulate gyrus, middle frontal gyrus, and cerebellum, indicating that acupuncture may regulate the default mode, central executive, and frontoparietal networks. CONCLUSION This study provides evidence of the neural mechanisms underlying the effect of acupuncture on AD involving cognitive- and motor-associated networks. However, this evidence is still in the preliminary investigation stage. Large-scale, well-designed, multimodal neuroimaging trials are still required to provide comprehensive insight into the central mechanism underlying the effect of acupuncture on AD. (Systematic review registration at PROSPERO, No. CRD42022331527).
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Affiliation(s)
- Zihan Yin
- grid.411304.30000 0001 0376 205XSchool of Acu-Mox and Tuina, Chengdu University of Traditional Chinese Medicine, Chengdu, China ,Acupuncture Clinical Research Center of Sichuan Province, Chengdu, China
| | - Ziqi Wang
- grid.517561.1the Fourth People’s Hospital of Chengdu, Chengdu, China
| | - Yaqin Li
- grid.411304.30000 0001 0376 205XSchool of Acu-Mox and Tuina, Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Jun Zhou
- grid.411304.30000 0001 0376 205XSchool of Acu-Mox and Tuina, Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Zhenghong Chen
- grid.411304.30000 0001 0376 205XSchool of Acu-Mox and Tuina, Chengdu University of Traditional Chinese Medicine, Chengdu, China ,Acupuncture Clinical Research Center of Sichuan Province, Chengdu, China
| | - Manze Xia
- grid.411304.30000 0001 0376 205XSchool of Acu-Mox and Tuina, Chengdu University of Traditional Chinese Medicine, Chengdu, China ,Acupuncture Clinical Research Center of Sichuan Province, Chengdu, China
| | - Xinyue Zhang
- grid.411304.30000 0001 0376 205XSchool of Acu-Mox and Tuina, Chengdu University of Traditional Chinese Medicine, Chengdu, China ,Acupuncture Clinical Research Center of Sichuan Province, Chengdu, China
| | - Jiajing Wu
- grid.417409.f0000 0001 0240 6969School of Nursing, Zunyi Medical University, Zunyi, China
| | - Ling Zhao
- School of Acu-Mox and Tuina, Chengdu University of Traditional Chinese Medicine, Chengdu, China. .,Acupuncture Clinical Research Center of Sichuan Province, Chengdu, China.
| | - Fanrong Liang
- School of Acu-Mox and Tuina, Chengdu University of Traditional Chinese Medicine, Chengdu, China. .,Acupuncture Clinical Research Center of Sichuan Province, Chengdu, China.
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13
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Atay LO, Saka E, Akdemir UO, Yetim E, Balcı E, Arsava EM, Topcuoglu MA. Hybrid PET/MRI with Flutemetamol and FDG in Alzheimer's Disease Clinical Continuum. Curr Alzheimer Res 2023; 20:481-495. [PMID: 38050727 DOI: 10.2174/0115672050243131230925034334] [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] [Received: 12/28/2022] [Revised: 07/26/2023] [Accepted: 08/17/2023] [Indexed: 12/06/2023]
Abstract
AIMS We aimed to investigate the interaction between β -amyloid (Aβ) accumulation and cerebral glucose metabolism, cerebral perfusion, and cerebral structural changes in the Alzheimer's disease (AD) clinical continuum. BACKGROUND Utility of positron emission tomography (PET) / magnetic resonance imaging (MRI) hybrid imaging for diagnostic categorization of the AD clinical continuum including subjective cognitive decline (SCD), amnestic mild cognitive impairment (aMCI) and Alzheimer's disease dementia (ADD) has not been fully crystallized. OBJECTIVE To evaluate the interaction between Aβ accumulation and cerebral glucose metabolism, cerebral perfusion, and cerebral structural changes such as cortex thickness or cerebral white matter disease burden and to detect the discriminative yields of these imaging modalities in the AD clinical continuum. METHODS Fifty patients (20 women and 30 men; median age: 64 years) with clinical SCD (n=11), aMCI (n=17) and ADD (n=22) underwent PET/MRI with [18F]-fluoro-D-glucose (FDG) and [18F]- Flutemetamol in addition to cerebral blood flow (CBF) and quantitative structural imaging along with detailed cognitive assessment. RESULTS High Aβ deposition (increased temporal [18F]-Flutemetamol standardized uptake value ratio (SUVr) and centiloid score), low glucose metabolism (decreased temporal lobe and posterior cingulate [18F]-FDG SUVr), low parietal CBF and right hemispheric cortical thickness were independent predictors of low cognitive test performance. CONCLUSION Integrated use of structural, metabolic, molecular (Aβ) and perfusion (CBF) parameters contribute to the discrimination of SCD, aMCI, and ADD.
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Affiliation(s)
- Lutfiye Ozlem Atay
- Department of Nuclear Medicine, Faculty of Medicine, Gazi University, Ankara, Turkey
| | - Esen Saka
- Department of Neurology, Faculty of Medicine, Hacettepe University, Ankara, Turkey
| | - Umit Ozgur Akdemir
- Department of Nuclear Medicine, Faculty of Medicine, Gazi University, Ankara, Turkey
| | - Ezgi Yetim
- Department of Neurology, Faculty of Medicine, Hacettepe University, Ankara, Turkey
| | - Erdem Balcı
- Department of Nuclear Medicine, Faculty of Medicine, Gazi University, Ankara, Turkey
| | - Ethem Murat Arsava
- Department of Neurology, Faculty of Medicine, Hacettepe University, Ankara, Turkey
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14
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Qiu T, Zeng Q, Zhang Y, Luo X, Xu X, Li X, Shen Z, Li K, Wang C, Huang P, Zhang M, Dai S, Xie F. Altered functional connectivity pattern of hippocampal subfields in individuals with objectively-defined subtle cognitive decline and its association with cognition and cerebrospinal fluid biomarkers. Eur J Neurosci 2022; 56:6227-6238. [PMID: 36342704 PMCID: PMC10100315 DOI: 10.1111/ejn.15860] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2022] [Revised: 10/17/2022] [Accepted: 10/31/2022] [Indexed: 11/09/2022]
Abstract
Recent studies have shown that in the preclinical phase of Alzheimer's disease (AD), subtle cognitive changes can be detected using sensitive neuropsychological measures, and have proposed the concept of objectively-defined subtle cognitive decline (Obj-SCD). We aimed to assess the functional alteration of hippocampal subfields in individuals with Obj-SCD and its association with cognition and pathological biomarkers. Forty-two participants with cognitively normal (CN), 29 with Obj-SCD, and 55 with mild cognitive impairment (MCI) were retrospectively collected from the ADNI database. Neuropsychological performance, functional MRI, and cerebrospinal fluid (CSF) data were obtained. We calculated the seed-based functional connectivity (FC) of hippocampal subfields (cornu ammonis1 [CA1], CA2/3/dentate gyrus [DG], and subiculum) with whole-brain voxels. Additionally, we analyzed the correlation between FC values of significantly altered regions and neuropsychological performance and CSF biomarkers. The Obj-SCD group showed lower FC between left CA1-CA2/3/DG and right thalamus and higher FC between right subiculum and right superior parietal gyrus (SPG) compared with the CN and MCI groups. In the Obj-SCD group, FC values between left CA2/3/DG and right thalamus were positively associated with Auditory Verbal Learning Test (AVLT) recognition (r = 0.395, p = 0.046) and CSF Aβ1-42 levels (r = 0.466, p = 0.019), and FC values between left CA1 and right thalamus were positively correlated with CSF Aβ1-42 levels (r = 0.530, p = 0.006). Taken together, dysfunction in CA1-CA2/3/DG subregions suggests subtle cognitive impairment and AD-specific pathological changes in individuals with Obj-SCD. Additionally, increased subiculum connectivity may indicate early functional compensation for subtle cognitive changes.
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Affiliation(s)
- Tiantian Qiu
- Department of RadiologyLinyi People's HospitalLinyiChina
| | - Qingze Zeng
- Department of RadiologyThe Second Affiliated Hospital of Zhejiang University School of MedicineHangzhouChina
| | - Yusong Zhang
- Department of RadiologyLinyi People's HospitalLinyiChina
| | - Xiao Luo
- Department of RadiologyThe Second Affiliated Hospital of Zhejiang University School of MedicineHangzhouChina
| | - Xiaopei Xu
- Department of RadiologyThe Second Affiliated Hospital of Zhejiang University School of MedicineHangzhouChina
| | - Xiaodong Li
- Department of RadiologyLinyi People's HospitalLinyiChina
| | - Zhujing Shen
- Department of RadiologyThe Second Affiliated Hospital of Zhejiang University School of MedicineHangzhouChina
| | - Kaicheng Li
- Department of RadiologyThe Second Affiliated Hospital of Zhejiang University School of MedicineHangzhouChina
| | - Chao Wang
- Department of RadiologyThe Second Affiliated Hospital of Zhejiang University School of MedicineHangzhouChina
| | - Peiyu Huang
- Department of RadiologyThe Second Affiliated Hospital of Zhejiang University School of MedicineHangzhouChina
| | - Minming Zhang
- Department of RadiologyThe Second Affiliated Hospital of Zhejiang University School of MedicineHangzhouChina
| | - Shouping Dai
- Department of RadiologyLinyi People's HospitalLinyiChina
| | - Fei Xie
- Department of Equipment and Medical EngineeringLinyi People's HospitalLinyiChina
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15
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Functional Connectivity Alterations Based on Hypometabolic Region May Predict Clinical Prognosis of Temporal Lobe Epilepsy: A Simultaneous 18F-FDG PET/fMRI Study. BIOLOGY 2022; 11:biology11081178. [PMID: 36009805 PMCID: PMC9404714 DOI: 10.3390/biology11081178] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/16/2022] [Revised: 07/28/2022] [Accepted: 08/03/2022] [Indexed: 11/16/2022]
Abstract
(1) Background: Accurate localization of the epileptogenic zone and understanding the related functional connectivity (FC) alterations are critical for the prediction of clinical prognosis in patients with temporal lobe epilepsy (TLE). We aim to localize the hypometabolic region in TLE patients, compare the differences in FC alterations based on hypometabolic region and structural lesion, respectively, and explore their relationships with clinical prognosis. (2) Methods: Thirty-two TLE patients and 26 controls were recruited. Patients underwent 18F-FDG PET/MR scan, surgical treatment, and a 2−3-year follow-up. Visual assessment and voxel-wise analyses were performed to identify hypometabolic regions. ROI-based FC analyses were performed. Relationships between clinical prognosis and FC values were performed by using Pearson correlation analyses and receiver operating characteristic (ROC) analysis. (3) Results: Hypometabolic regions in TLE patients were found in the ipsilateral hippocampus, parahippocampal gyrus, and temporal lobe (p < 0.001). Functional alterations based on hypometabolic regions showed a more extensive whole-brain FC reduction. FC values of these regions negatively correlated with epilepsy duration (p < 0.05), and the ROC curve of them showed significant accuracy in predicting postsurgical outcome. (4) Conclusions: In TLE patients, FC related with hypometabolic region obtained by PET/fMRI may provide value in the prediction of disease progression and seizure-free outcome.
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16
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Rummel NG, Butterfield DA. Altered Metabolism in Alzheimer Disease Brain: Role of Oxidative Stress. Antioxid Redox Signal 2022; 36:1289-1305. [PMID: 34416829 PMCID: PMC9229240 DOI: 10.1089/ars.2021.0177] [Citation(s) in RCA: 40] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
Significance: Alzheimer disease (AD) is an all-too-common condition in the aging population. However, aging does not automatically equal neurodegeneration and memory decline. Recent Advances: This review article involves metabolic changes in the AD brain that are related to oxidative stress. Selected pathways are identified as potential targets for intervention in AD. Critical Issues: One of the main factors of AD is the oxidative imbalance within the central nervous system, causing a disruption in metabolic processes. Reactive oxygen species (ROS) are a natural consequence of many cellular processes, especially those associated with mitochondria, such as the electron transport chain. Some ROS, when kept under control and maintained at reasonable levels, often play roles in cell signaling. The cellular damage of ROS arises when oxidative imbalance occurs, in which case ROS are not controlled, leading to a myriad of alterations in cellular metabolic processes. These altered pathways include, among others, dysfunctional glycolysis, calcium regulation, lipid metabolism, mitochondrial processes, and mammalian target of rapamycin pathway dysregulation. Future Directions: Understanding how ROS can lead to these alterations can, ideally, elucidate therapeutic options for retarding AD progression in the aging population. Antioxid. Redox Signal. 36, 1289-1305.
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Affiliation(s)
- Nicole G Rummel
- Department of Chemistry and University of Kentucky, Lexington, Kentucky, USA
| | - D Allan Butterfield
- Department of Chemistry and University of Kentucky, Lexington, Kentucky, USA.,Sanders-Brown Center on Aging, University of Kentucky, Lexington, Kentucky, USA
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17
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Wu Y, Zheng Y, Li J, Liu Y, Liang X, Chen Y, Zhang H, Wang N, Weng X, Qiu S, Wang J. Subregion-specific, modality-dependent and timescale-sensitive hippocampal connectivity alterations in patients with first-episode, drug-naïve major depression disorder. J Affect Disord 2022; 305:159-172. [PMID: 35218862 DOI: 10.1016/j.jad.2022.02.052] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/22/2021] [Revised: 01/11/2022] [Accepted: 02/18/2022] [Indexed: 12/25/2022]
Abstract
BACKGROUND Despite accumulating evidence for the hippocampus as a key dysfunctional node in major depressive disorder (MDD), previous findings are controversial possibly due to heterogeneous and small clinical samples, complicated hippocampal structure, and different imaging modalities and analytical methods. METHODS We collected structural and resting-state functional MRI data from 100 first-episode, drug-naïve MDD patients and 99 healthy controls. A subset of the participants (34 patients and 33 controls) also completed a battery of neuropsychological tests and childhood trauma questionnaires. Seed-based morphological and functional (static and dynamic) connectivity were calculated for ten hippocampal subregions, followed by analyses of dynamic functional connectivity states (k-means clustering), connectivity cross-modality relationships (cosine similarity), and connectivity associations with clinical and neuropsychological variables (Spearman correlation). RESULTS Between-group comparisons revealed abnormal hippocampal connectivity in the patients that depended on 1) hippocampal subdivisions: the cornu ammonis (CA) was the most seriously affected subregion, in particular the right CA1 for functional connectivity alterations; 2) imaging modality: morphological connectivity revealed seldom and sporadic alterations with different lobes, while functional connectivity identified numerous and convergent alterations with prefrontal regions; and 3) time scale: dynamic functional connectivity was more sensitive than static functional connectivity, in particular in revealing alterations between the right CA1 and contralateral prefrontal cortex. Among the 34 patients, functional connectivity alterations of the CA1 were related to the history of childhood trauma in the patients. LIMITATIONS Only a subset of the patients completed the neuropsychological tests, which may cause underestimation of cognitive relevance of hippocampal connectivity alterations. CONCLUSIONS Disrupted hippocampal CA1 functional connectivity plays key roles in the pathophysiology of MDD and may act as a potential diagnostic biomarker for the disease.
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Affiliation(s)
- Yujie Wu
- Institute for Brain Research and Rehabilitation, South China Normal University, 510631 Guangzhou, China; School of Psychology, South China Normal University, Guangzhou, China
| | - Yanting Zheng
- Department of Radiology, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangdong 510405, China; Department of Radiology, Guangzhou First People's Hospital, Guangdong 510180, China
| | - Junle Li
- Institute for Brain Research and Rehabilitation, South China Normal University, 510631 Guangzhou, China
| | - Yujie Liu
- Department of Radiology, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangdong 510405, China; Department of Radiology, Guangzhou First People's Hospital, Guangdong 510180, China
| | - Xinyu Liang
- The First School of Clinical Medicine, Guangzhou University of Chinese Medicine, Guangzhou, Guangdong 510006, China
| | - Yaoping Chen
- The Third Affliated Hospital of Sun Yat-Sen University, Guangzhou, Guangdong 510630, China
| | - Hanyue Zhang
- Department of Radiology, Guangzhou First People's Hospital, Guangdong 510180, China
| | - Ningkai Wang
- Institute for Brain Research and Rehabilitation, South China Normal University, 510631 Guangzhou, China
| | - Xuchu Weng
- Institute for Brain Research and Rehabilitation, South China Normal University, 510631 Guangzhou, China; Key Laboratory of Brain, Cognition and Education Sciences, Ministry of Education, China; Center for Studies of Psychological Application, South China Normal University, 510631 Guangzhou, China; Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, 510631 Guangzhou, China
| | - Shijun Qiu
- Department of Radiology, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangdong 510405, China.
| | - Jinhui Wang
- Institute for Brain Research and Rehabilitation, South China Normal University, 510631 Guangzhou, China; Key Laboratory of Brain, Cognition and Education Sciences, Ministry of Education, China; Center for Studies of Psychological Application, South China Normal University, 510631 Guangzhou, China; Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, 510631 Guangzhou, China.
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18
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Bi XA, Zhou W, Luo S, Mao Y, Hu X, Zeng B, Xu L. Feature aggregation graph convolutional network based on imaging genetic data for diagnosis and pathogeny identification of Alzheimer's disease. Brief Bioinform 2022; 23:6572662. [PMID: 35453149 DOI: 10.1093/bib/bbac137] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2022] [Revised: 03/15/2022] [Accepted: 03/23/2022] [Indexed: 12/30/2022] Open
Abstract
The roles of brain regions activities and gene expressions in the development of Alzheimer's disease (AD) remain unclear. Existing imaging genetic studies usually has the problem of inefficiency and inadequate fusion of data. This study proposes a novel deep learning method to efficiently capture the development pattern of AD. First, we model the interaction between brain regions and genes as node-to-node feature aggregation in a brain region-gene network. Second, we propose a feature aggregation graph convolutional network (FAGCN) to transmit and update the node feature. Compared with the trivial graph convolutional procedure, we replace the input from the adjacency matrix with a weight matrix based on correlation analysis and consider common neighbor similarity to discover broader associations of nodes. Finally, we use a full-gradient saliency graph mechanism to score and extract the pathogenetic brain regions and risk genes. According to the results, FAGCN achieved the best performance among both traditional and cutting-edge methods and extracted AD-related brain regions and genes, providing theoretical and methodological support for the research of related diseases.
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Affiliation(s)
- Xia-An Bi
- Hunan Provincial Key Laboratory of Intelligent Computing and Language Information Processing, and the College of Information Science and Engineering in Hunan Normal University, P.R. China
| | - Wenyan Zhou
- College of Information Science and Engineering, Hunan Normal University, Changsha, China
| | - Sheng Luo
- College of Information Science and Engineering, Hunan Normal University, Changsha, China
| | - Yuhua Mao
- College of Information Science and Engineering, Hunan Normal University, Changsha, China
| | - Xi Hu
- College of Information Science and Engineering, Hunan Normal University, Changsha, China
| | - Bin Zeng
- Hunan Youdao Information Technology Co., Ltd, P.R. China
| | - Luyun Xu
- College of Business in Hunan Normal University, P.R. China
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19
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Shan Y, Wang Z, Song S, Xue Q, Ge Q, Yang H, Cui B, Zhang M, Zhou Y, Lu J. Integrated Positron Emission Tomography/Magnetic Resonance Imaging for Resting-State Functional and Metabolic Imaging in Human Brain: What Is Correlated and What Is Impacted. Front Neurosci 2022; 16:824152. [PMID: 35310105 PMCID: PMC8926297 DOI: 10.3389/fnins.2022.824152] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2021] [Accepted: 01/24/2022] [Indexed: 12/04/2022] Open
Abstract
Integrated positron emission tomography (PET)/magnetic resonance imaging (MRI) could simultaneously obtain both functional MRI (fMRI) and 18F-fluorodeoxyglucose (FDG) PET and thus provide multiparametric information for the analysis of brain metabolism. In this study, we aimed to, for the first time, investigate the interplay of simultaneous fMRI and FDG PET scan using a randomized self-control protocol. In total, 24 healthy volunteers underwent PET/MRI scan for 30–40 min after the injection of FDG. A 22-min brain scan was separated into MRI-off mode (without fMRI pulsing) and MRI-on mode (with fMRI pulsing), with each one lasting for 11 min. We calculated the voxel-wise fMRI metrics (regional homogeneity, amplitude of low-frequency fluctuations, fractional amplitude of low-frequency fluctuations, and degree centrality), resting networks, relative standardized uptake value ratios (SUVr), SUVr slope, and regional cerebral metabolic rate of glucose (rCMRGlu) maps. Paired two-sample t-tests were applied to assess the statistical differences between SUVr, SUVr slope, correlation coefficients of fMRI metrics, and rCMRGlu between MRI-off and MRI-on modes, respectively. The voxel-wise whole-brain SUVr revealed no statistical difference (P > 0.05), while the SUVr slope was significantly elevated in sensorimotor, dorsal attention, ventral attention, control, default, and auditory networks (P < 0.05) during fMRI scan. The task-based group independent-component analysis revealed that the most active network components derived from the combined MRI-off and MRI-on static PET images were frontal pole, superior frontal gyrus, middle temporal gyrus, and occipital pole. High correlation coefficients were found among fMRI metrics with rCMRGlu in both MRI-off and MRI-on mode (P < 0.05). Our results systematically evaluated the impact of simultaneous fMRI scan on the quantification of human brain metabolism from an integrated PET/MRI system.
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Affiliation(s)
- Yi Shan
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, Beijing, China
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, China
| | - Zhe Wang
- Central Research Institute, United Imaging Healthcare Group, Shanghai, China
| | - Shuangshuang Song
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, Beijing, China
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, China
| | - Qiaoyi Xue
- Central Research Institute, United Imaging Healthcare Group, Shanghai, China
| | - Qi Ge
- Central Research Institute, United Imaging Healthcare Group, Shanghai, China
| | - Hongwei Yang
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, Beijing, China
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, China
| | - Bixiao Cui
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, Beijing, China
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, China
| | - Miao Zhang
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, Beijing, China
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, China
| | - Yun Zhou
- Central Research Institute, United Imaging Healthcare Group, Shanghai, China
| | - Jie Lu
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, Beijing, China
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, China
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20
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Yang J, Sui H, Jiao R, Zhang M, Zhao X, Wang L, Deng W, Liu X. Random-Forest-Algorithm-Based Applications of the Basic Characteristics and Serum and Imaging Biomarkers to Diagnose Mild Cognitive Impairment. Curr Alzheimer Res 2022; 19:76-83. [PMID: 35088670 PMCID: PMC9189735 DOI: 10.2174/1567205019666220128120927] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2021] [Revised: 12/04/2021] [Accepted: 01/13/2022] [Indexed: 11/24/2022]
Abstract
Background
Mild cognitive impairment (MCI) is considered the early stage of Alzheimer's Disease (AD). The purpose of our study was to analyze the basic characteristics and serum and imaging biomarkers for the diagnosis of MCI patients as a more objective and accurate approach. Methods
The Montreal Cognitive Test was used to test 119 patients aged ≥65. Such serum biomarkers were detected as preprandial blood glucose, triglyceride, total cholesterol, Aβ1-40, Aβ1-42, and P-tau. All the subjects were scanned with 1.5T MRI (GE Healthcare, WI, USA) to obtain DWI, DTI, and ASL images. DTI was used to calculate the anisotropy fraction (FA), DWI was used to calculate the apparent diffusion coefficient (ADC), and ASL was used to calculate the cerebral blood flow (CBF). All the images were then registered to the SPACE of the Montreal Neurological Institute (MNI). In 116 brain regions, the medians of FA, ADC, and CBF were extracted by automatic anatomical labeling. The basic characteristics included gender, education level, and previous disease history of hypertension, diabetes, and coronary heart disease. The data were randomly divided into training sets and test ones. The recursive random forest algorithm was applied to the diagnosis of MCI patients, and the recursive feature elimination (RFE) method was used to screen the significant basic features and serum and imaging biomarkers. The overall accuracy, sensitivity, and specificity were calculated, respectively, and so were the ROC curve and the area under the curve (AUC) of the test set. Results
When the variable of the MCI diagnostic model was an imaging biomarker, the training accuracy of the random forest was 100%, the correct rate of the test was 86.23%, the sensitivity was 78.26%, and the specificity was 100%. When combining the basic characteristics, the serum and imaging biomarkers as variables of the MCI diagnostic model, the training accuracy of the random forest was found to be 100%; the test accuracy was 97.23%, the sensitivity was 94.44%, and the specificity was 100%. RFE analysis showed that age, Aβ1-40, and cerebellum_4_6 were the most important basic feature, serum biomarker, imaging biomarker, respectively. Conclusion
Imaging biomarkers can effectively diagnose MCI. The diagnostic capacity of the basic trait biomarkers or serum biomarkers for MCI is limited, but their combination with imaging biomarkers can improve the diagnostic capacity, as indicated by the sensitivity of 94.44% and the specificity of 100% in our model. As a machine learning method, a random forest can help diagnose MCI effectively while screening important influencing factors.
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Affiliation(s)
- Juan Yang
- Department of Neurology, Shanghai Tenth People's Hospital, School of Medicine, Tongji University, Shanghai, 200092, China
- Department of Neurology, Shanghai Pudong New Area People's Hospital,Shanghai, 201299, China
| | - Haijing Sui
- Department of Radiology, Shanghai Pudong New Area People's Hospital, Shanghai, People's Republic of China
| | - Ronghong Jiao
- Department of Clinical Laboratory, Shanghai Pudong New Area People's Hospital, Shanghai, People's Republic of China
| | - Min Zhang
- hcit.ai Co., Shanghai, People's Republic of China
| | - Xiaohui Zhao
- Department of Neurology, Shanghai Pudong New Area People's Hospital, Shanghai, People's Republic of China
| | - Lingling Wang
- Department of Neurology, Shanghai Pudong New Area People's Hospital, Shanghai, People's Republic of China
| | - Wenping Deng
- Huawei Technology Co., Ltd Co, Shanghai, People's Republic of China
| | - Xueyuan Liu
- Department of Neurology, Shanghai Tenth People's Hospital, School of Medicine, Tongji University, Shanghai, 200092, China
- Department of Neurology, Shanghai Pudong New Area People's Hospital,Shanghai, 201299, China
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21
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Wang W, Kong W, Wang S, Wei K. Detecting Biomarkers of Alzheimer's Disease Based on Multi-constrained Uncertainty-Aware Adaptive Sparse Multi-view Canonical Correlation Analysis. J Mol Neurosci 2022; 72:841-865. [PMID: 35080765 DOI: 10.1007/s12031-021-01963-y] [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: 08/31/2021] [Accepted: 12/29/2021] [Indexed: 12/01/2022]
Abstract
Image genetics mainly explores the pathogenesis of Alzheimer's disease (AD) by studying the relationship between genetic data (such as SNP, gene expression data, and DNA methylation) and imaging data (such as structural MRI (sMRI), fMRI, and PET). Most of the existing research on brain imaging genomics uses two-way or three-way bi-multivariate methods to explore the correlation analysis between genes and brain imaging. However, many of these methods are still affected by the gradient domination or cannot take into account the effect of feature redundancy on the results, so that the typical correlation coefficient and program running speed are not significantly improved. In order to solve the above problems, this paper proposes a multi-constrained uncertainty-aware adaptive sparse multi-view canonical correlation analysis method (MC-unAdaSMCCA) to explore associations among SNPs, gene expression data, and sMRI; that is, based on traditional unAdaSMCCA, orthogonal constraints are imposed on the weights of the three data features through linear programming, which can reduce the redundancy of feature weights to improve the correlation between the data and reduce the complexity of the algorithm to significantly speed up the running speed of the program. Three adaptive sparse multi-view canonical correlation analysis methods are used as benchmarks to evaluate the difference between real neuroimaging data and synthetic data. Compared with the other three methods, our proposed method has obtained better or comparable typical correlation coefficients and typical weights. Moreover, the following experimental results show that the MC-unAdaSMCCA method cannot only identify biomarkers related to AD and mild cognitive impairment (MCI), but also has a strong ability to resist noise and process high-dimensional data. Therefore, our proposed method provides a reliable approach to multi-modal imaging genetic researches.
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Affiliation(s)
- Wenbo Wang
- College of Information Engineering, Shanghai Maritime University, 1550 Haigang Ave., Shanghai, 201306, People's Republic of China
| | - Wei Kong
- College of Information Engineering, Shanghai Maritime University, 1550 Haigang Ave., Shanghai, 201306, People's Republic of China.
| | - Shuaiqun Wang
- College of Information Engineering, Shanghai Maritime University, 1550 Haigang Ave., Shanghai, 201306, People's Republic of China
| | - Kai Wei
- College of Information Engineering, Shanghai Maritime University, 1550 Haigang Ave., Shanghai, 201306, People's Republic of China
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22
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Um YH, Wang SM, Kang DW, Kim NY, Lim HK. Subcortical and Cerebellar Neural Correlates of Prodromal Alzheimer’s Disease with Prolonged Sleep Latency. J Alzheimers Dis 2022; 86:565-578. [PMID: 35068468 PMCID: PMC9028620 DOI: 10.3233/jad-215460] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
Background: Despite the important associations among sleep, Alzheimer’s disease (AD), subcortical structures, and the cerebellum, structural and functional magnetic resonance imaging (MRI) with regard to these regions and sleep on patients in AD trajectory are scarce. Objective: This study aimed to evaluate the influence of prolonged sleep latency on the structural and functional alterations in the subcortical and cerebellar neural correlates in amyloid-β positive amnestic mild cognitive impairment patients (Aβ+aMCI). Methods: A total of 60 patients with aMCI who were identified as amyloid positive ([18F] flutemetamol+) were recruited in the study, 24 patients with normal sleep latency (aMCI-n) and 36 patients prolonged sleep latency (aMCI-p). Cortical thickness and volumes between the two groups were compared. Volumetric analyses were implemented on the brainstem, thalamus, and hippocampus. Subcortical and cerebellar resting state functional connectivity (FC) differences were measured between the both groups through seed-to-voxel analysis. Additionally, group x Aβ interactive effects on FC values were tested with a general linear model. Result: There was a significantly decreased brainstem volume in aMCI-p subjects. We observed a significant reduction of the locus coeruleus (LC) FC with frontal, temporal, insular cortices, hippocampus, and left thalamic FC with occipital cortex. Moreover, the LC FC with occipital cortex and left hippocampal FC with frontal cortex were increased in aMCI-p subjects. In addition, there was a statistically significant group by regional standardized uptake value ratio interactions discovered in cerebro-cerebellar networks. Conclusion: The aforementioned findings suggest that prolonged sleep latency may be a detrimental factor in compromising structural and functional correlates of subcortical structures and the cerebellum, which may accelerate AD pathophysiology.
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Affiliation(s)
- Yoo Hyun Um
- Department of Psychiatry, St. Vincent’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Sheng-Min Wang
- Department of Psychiatry, Yeouido St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea
| | - Dong Woo Kang
- Department of Psychiatry, Seoul St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea
| | - Nak-Young Kim
- Department of Psychiatry, Keyo Hospital, Keyo Medical Foundation, Uiwang, Republic of Korea
| | - Hyun Kook Lim
- Department of Psychiatry, Yeouido St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea
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23
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Liu H, Zhang D, Lin H, Zhang Q, Zheng L, Zheng Y, Yin X, Li Z, Liang S, Huang S. Meta-Analysis of Neurochemical Changes Estimated via Magnetic Resonance Spectroscopy in Mild Cognitive Impairment and Alzheimer's Disease. Front Aging Neurosci 2021; 13:738971. [PMID: 34744689 PMCID: PMC8569809 DOI: 10.3389/fnagi.2021.738971] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2021] [Accepted: 08/26/2021] [Indexed: 11/18/2022] Open
Abstract
The changes of neurochemicals in mild cognitive impairment (MCI) and Alzheimer's disease (AD) patients has been observed via magnetic resonance spectroscopy in several studies. However, whether it exists the consistent pattern of changes of neurochemicals in the encephalic region during the progression of MCI to AD were still not clear. The study performed meta-analysis to investigate the patterns of neurochemical changes in the encephalic region in the progress of AD. We searched the PubMed, Embase, Cochrane Library, and Web of Science databases, and finally included 63 studies comprising 1,086 MCI patients, 1,256 AD patients, and 1,907 healthy controls. It showed that during the progression from MCI to AD, N-acetyl aspartate (NAA) decreased continuously in the posterior cingulate (PC) (SMD: −0.42 [95% CI: −0.62 to −0.21], z = −3.89, P < 0.05), NAA/Cr (creatine) was consistently reduced in PC (SMD: −0.58 [95% CI: −0.86 to −0.30], z = −4.06, P < 0.05) and hippocampus (SMD: −0.65 [95% CI: −1.11 to −0.12], z = −2.44, P < 0.05), while myo-inositol (mI) (SMD: 0.44 [95% CI: 0.26–0.61], z = 4.97, P < 0.05) and mI/Cr (SMD: 0.43 [95% CI: 0.17–0.68], z = 3.30, P < 0.05) were raised in PC. Furthermore, these results were further verified by a sustained decrease in the NAA/mI of PC (SMD: −0.94 [95% CI: −1.24 to −0.65], z = −6.26, P < 0.05). Therefore, the levels of NAA and mI were associated with the cognitive decline and might be used as potentially biomarkers to predict the possible progression from MCI to AD. Systematic Review Registration:https://www.crd.york.ac.uk/PROSPERO/, identifier: CRD42020200308.
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Affiliation(s)
- Huanhuan Liu
- National-Local Joint Engineering Research Center of Rehabilitation Medicine Technology, Fujian University of Traditional Chinese Medicine, Fuzhou, China.,Rehabilitation Industry Institute, Fujian University of Traditional Chinese Medicine, Fuzhou, China.,College of Rehabilitation Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou, China
| | - Dandan Zhang
- College of Traditional Chinese Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou, China
| | - Huawei Lin
- National-Local Joint Engineering Research Center of Rehabilitation Medicine Technology, Fujian University of Traditional Chinese Medicine, Fuzhou, China.,Rehabilitation Industry Institute, Fujian University of Traditional Chinese Medicine, Fuzhou, China.,College of Rehabilitation Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou, China
| | - Qi Zhang
- College of Rehabilitation Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou, China
| | - Ling Zheng
- College of Rehabilitation Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou, China
| | - Yuxin Zheng
- College of Rehabilitation Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou, China
| | - Xiaolong Yin
- National-Local Joint Engineering Research Center of Rehabilitation Medicine Technology, Fujian University of Traditional Chinese Medicine, Fuzhou, China.,Rehabilitation Industry Institute, Fujian University of Traditional Chinese Medicine, Fuzhou, China
| | - Zuanfang Li
- Academy of Integrative Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou, China.,Fujian Key Laboratory of Integrative Medicine on Geriatrics, Fuzhou, China
| | - Shengxiang Liang
- National-Local Joint Engineering Research Center of Rehabilitation Medicine Technology, Fujian University of Traditional Chinese Medicine, Fuzhou, China.,Rehabilitation Industry Institute, Fujian University of Traditional Chinese Medicine, Fuzhou, China.,Traditional Chinese Medicine Rehabilitation Research Center of State Administration of Traditional Chinese Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou, China
| | - Saie Huang
- Department of Neurological Rehabilitation, Fujian University of Traditional Chinese Medicine Subsidiary Rehabilitation Hospital, Fuzhou, China
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24
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Ding C, Du W, Zhang Q, Wang L, Han Y, Jiang J. Coupling relationship between glucose and oxygen metabolisms to differentiate preclinical Alzheimer's disease and normal individuals. Hum Brain Mapp 2021; 42:5051-5062. [PMID: 34291850 PMCID: PMC8449101 DOI: 10.1002/hbm.25599] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2021] [Revised: 06/10/2021] [Accepted: 07/12/2021] [Indexed: 11/11/2022] Open
Abstract
The discovery of preclinical Alzheimer's disease (preAD) provides a wide time window for the early intervention of AD. The coupling relationships between glucose and oxygen metabolisms from hybrid PET/MRI can provide complementary information on the brain's physiological state for preAD. In this study, we purpose to explore the change of coupling relationship among 27 normal controls (NCs), 20 preADs, and 15 cognitive impairments (CIs). For each subject, we calculated the Spearman partial correlation between the fractional amplitude of low-frequency fluctuations (fALFF) and the regional homogeneity (ReHo) from functional image (fMRI), and the standard uptake value ratio (SUVR) from [18F] fluorodeoxyglucose positron emission tomography (18 F-FDG PET), in the whole-brain and default mode network (DMN) as a novel potential biomarker. The diagnostic performance of this biomarker was evaluated by the receiver operating characteristic analysis. Significant Spearman correlations between the FDG SUVR and the fALFF/ReHo were found in 98% of subjects. For the DMN-based biomarker, there was a significant decreasing trend for the preAD and CI groups compared to the NC group, whereas no significant difference in preAD based on whole-brain. The correlation ρ value for the FDG SUVR/ReHo showed the highest area under curve of the preAD classification (0.787). The results imply the coupling relationship changed during the preAD stage in the DMN area.
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Affiliation(s)
- Changchang Ding
- Key Laboratory of Specialty Fiber Optics and Optical Access Networks, Joint International Research Laboratory of Specialty Fiber Optics and Advanced Communication, School of Communication and Information EngineeringShanghai UniversityShanghaiChina
| | - Wenying Du
- Department of NeurologyXuanwu Hospital of Capital Medical UniversityBeijingChina
| | - Qi Zhang
- Key Laboratory of Specialty Fiber Optics and Optical Access Networks, Joint International Research Laboratory of Specialty Fiber Optics and Advanced Communication, School of Communication and Information EngineeringShanghai UniversityShanghaiChina
| | - Luyao Wang
- School of Mechatronical EngineeringBeijing Institute of TechnologyBeijingChina
| | - Ying Han
- Department of NeurologyXuanwu Hospital of Capital Medical UniversityBeijingChina
- Center of Alzheimer's DiseaseBeijing Institute for Brain DisordersBeijingChina
- National Clinical Research Center for Geriatric DisordersBeijingChina
- Biomedical Engineering InstituteHainan UniversityHaikouChina
| | - Jiehui Jiang
- Key Laboratory of Specialty Fiber Optics and Optical Access Networks, Joint International Research Laboratory of Specialty Fiber Optics and Advanced Communication, School of Communication and Information EngineeringShanghai UniversityShanghaiChina
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25
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Lorking N, Murray AD, O'Brien JT. The use of positron emission tomography/magnetic resonance imaging in dementia: A literature review. Int J Geriatr Psychiatry 2021; 36:1501-1513. [PMID: 34490651 DOI: 10.1002/gps.5586] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/15/2021] [Revised: 04/22/2021] [Accepted: 05/17/2021] [Indexed: 11/08/2022]
Abstract
OBJECTIVES Positron emission tomography-magnetic resonance imaging (PET/MRI) is an emerging hybrid imaging system in clinical nuclear medicine. Research demonstrates a comparative utility to current unimodal and hybrid methods, including PET-computed tomography (PET/CT), in several medical subspecialities such as neuroimaging. The aim of this review is to critically evaluate the literature from 2016 to 2021 using PET/MRI for the investigation of patients with mild cognitive impairment or dementia, and discuss the evidence base for widening its application into clinical practice. METHODS A comprehensive literature search using the PubMed database was conducted to retrieve studies using PET/MRI in relation to the topics of mild cognitive impairment, dementia, or Alzheimer's disease between January 2016 and January 2021. This search strategy enabled studies on all dementia types to be included in the analysis. Studies were required to have a minimum of 10 human subjects and incorporate simultaneous PET/MRI. RESULTS A total of 116 papers were retrieved, with 39 papers included in the final selection. These were broadly categorised into reviews (12), technical/methodological papers (11) and new data studies (16). For the current review, discussion focused on findings from the new data studies. CONCLUSIONS PET/MRI offers additional insight into the underlying anatomical, metabolic and functional changes associated with dementia when compared with unimodal methods and PET/CT, particularly relating to brain regions including the hippocampus and default mode network. Furthermore, the improved diagnostic utility of PET/MRI, as reported by radiologists, offers improved classification of dementia patients, with important implications for clinical management.
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Affiliation(s)
- Nicole Lorking
- School of Medicine, University of Aberdeen, Scotland, UK
| | | | - John T O'Brien
- Department of Psychiatry, University of Cambridge, Cambridge, UK
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26
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Kure AJ, Savas H, Hijaz TA, Hussaini SF, Korutz AW. Advancements in Positron Emission Tomography/Magnetic Resonance Imaging and Applications to Diagnostic Challenges in Neuroradiology. Semin Ultrasound CT MR 2021; 42:434-451. [PMID: 34537113 DOI: 10.1053/j.sult.2021.07.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
Since the clinical adoption of magnetic resonance (MR) in medical imaging, MR has proven to be a workhorse in diagnostic neuroradiology, with the ability to provide superb anatomic detail as well as additional functional and physiologic data, depending on the techniques utilized. Positron emission tomography/computed tomography has also shown irreplaceable diagnostic value in certain disease processes of the central nervous system by providing molecular and metabolic information through the development of numerous disease-specific PET tracers, many of which can be utilized as a diagnostic technique in and of themselves or can provide a valuable adjunct to information derived from MR. Despite these advances, many challenges still remain in neuroradiology, particularly in malignancy, neurodegenerative disease, epilepsy, and cerebrovascular disease. Through improvements in attenuation correction, motion correction, and PET detectors, combining the 2 modalities of PET and MR through simultaneous imaging has proven feasible and allows for improved spatial and temporal resolution without compromising either of the 2 individual modalities. The complementary information offered by both technologies has provided increased diagnostic accuracy in both research and many clinical applications in neuroradiology.
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Affiliation(s)
- Andrew J Kure
- Department of Radiology, Northwestern University, Feinberg School of Medicine, Chicago, IL.
| | - Hatice Savas
- Department of Radiology, Northwestern University, Feinberg School of Medicine, Chicago, IL.
| | - Tarek A Hijaz
- Department of Radiology, Northwestern University, Feinberg School of Medicine, Chicago, IL.
| | - Syed F Hussaini
- Department of Radiology, Northwestern University, Feinberg School of Medicine, Chicago, IL.
| | - Alexander W Korutz
- Department of Radiology, Northwestern University, Feinberg School of Medicine, Chicago, IL.
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27
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Abstract
A decade of PET/MRI clinical imaging has passed and many of the pitfalls are similar to those on earlier studies. However, techniques to overcome them have emerged and continue to develop. Although clinically significant lung nodules are demonstrable, smaller nodules may be detected using ultrashort/zero echo-time (TE) lung MRI. Fast reconstruction ultrashort TE sequences have also been used to achieve high-resolution lung MRI even with free-breathing. The introduction and improvement of time-of-flight scanners and increasing the axial length of the PET detector arrays have more than doubled the sensitivity of the PET part of the system. MRI for attenuation correction has provided many potential pitfalls, including misclassification of tissue classes based on MRI information for attenuation correction. Although the use of short echo times have helped to address these pitfalls, one of the most exciting developments has been the use of deep learning algorithms and computational neural networks to rapidly provide soft tissue, fat, bone and air information for the attenuation correction as a supplement to the attenuation correction information from fat-water imaging. Challenges with motion correction, particularly respiratory and cardiac remain but are being addressed with respiratory monitors and using PET data. In order to address truncation artefacts, the system manufacturers have developed methods to extend the MR field-of-view for the purpose of the attenuation and scatter corrections. General pitfalls like stitching of body sections for individual studies, optimum delivery of images for viewing and reporting, and resource implications for the sheer volume of data generated remain Methods to overcome these pitfalls serve as a strong foundation for the future of PET/MRI. Advances in the underlying technology with significant evolution in hard-ware and software and the exiting developments in use of deep learning algorithms and computational neural networks will drive the next decade of PET/MRI imaging.
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Affiliation(s)
- Asim Afaq
- University of Iowa Carver College of Medicine, Iowa City; Institute of Nuclear Medicine, UCL/ UCLH London, UK
| | | | | | - Simon Wan
- Institute of Nuclear Medicine, UCL/ UCLH London, UK
| | - Thomas A Hope
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA
| | - Patrick Veit Haibach
- Toronto Joint Dept. Medical Imaging, University Health Network, Sinai Health System, Women's College University of Toronto, Canada
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28
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Salman MM, Al-Obaidi Z, Kitchen P, Loreto A, Bill RM, Wade-Martins R. Advances in Applying Computer-Aided Drug Design for Neurodegenerative Diseases. Int J Mol Sci 2021; 22:4688. [PMID: 33925236 PMCID: PMC8124449 DOI: 10.3390/ijms22094688] [Citation(s) in RCA: 58] [Impact Index Per Article: 19.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2021] [Revised: 04/26/2021] [Accepted: 04/26/2021] [Indexed: 12/11/2022] Open
Abstract
Neurodegenerative diseases (NDs) including Alzheimer's disease, Parkinson's disease, amyotrophic lateral sclerosis, and Huntington's disease are incurable and affect millions of people worldwide. The development of treatments for this unmet clinical need is a major global research challenge. Computer-aided drug design (CADD) methods minimize the huge number of ligands that could be screened in biological assays, reducing the cost, time, and effort required to develop new drugs. In this review, we provide an introduction to CADD and examine the progress in applying CADD and other molecular docking studies to NDs. We provide an updated overview of potential therapeutic targets for various NDs and discuss some of the advantages and disadvantages of these tools.
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Affiliation(s)
- Mootaz M. Salman
- Department of Physiology, Anatomy and Genetics, University of Oxford, Parks Road, Oxford OX1 3QX, UK;
- Oxford Parkinson’s Disease Centre, University of Oxford, South Parks Road, Oxford OX1 3QX, UK
| | - Zaid Al-Obaidi
- Department of Pharmaceutical Chemistry, College of Pharmacy, University of Alkafeel, Najaf 54001, Iraq;
- Department of Chemistry and Biochemistry, College of Medicine, University of Kerbala, Karbala 56001, Iraq
| | - Philip Kitchen
- School of Biosciences, College of Health and Life Sciences, Aston University, Aston Triangle, Birmingham B4 7ET, UK; (P.K.); (R.M.B.)
| | - Andrea Loreto
- Department of Physiology, Anatomy and Genetics, University of Oxford, Parks Road, Oxford OX1 3QX, UK;
- John Van Geest Centre for Brain Repair, University of Cambridge, Cambridge CB2 0PY, UK
| | - Roslyn M. Bill
- School of Biosciences, College of Health and Life Sciences, Aston University, Aston Triangle, Birmingham B4 7ET, UK; (P.K.); (R.M.B.)
| | - Richard Wade-Martins
- Department of Physiology, Anatomy and Genetics, University of Oxford, Parks Road, Oxford OX1 3QX, UK;
- Oxford Parkinson’s Disease Centre, University of Oxford, South Parks Road, Oxford OX1 3QX, UK
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29
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Yan S, Zheng C, Paranjpe MD, Li Y, Li W, Wang X, Benzinger TLS, Lu J, Zhou Y. Sex modifies APOE ε4 dose effect on brain tau deposition in cognitively impaired individuals. Brain 2021; 144:3201-3211. [PMID: 33876815 PMCID: PMC8634082 DOI: 10.1093/brain/awab160] [Citation(s) in RCA: 31] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2020] [Revised: 03/16/2021] [Accepted: 04/08/2021] [Indexed: 11/23/2022] Open
Abstract
Recent studies in cognitively unimpaired elderly individuals suggest that the APOE ε4 allele exerts a dosage-dependent effect on brain tau deposition. The aim of this study was to investigate sex differences in APOE ε4 gene dosage effects on brain tau deposition in cognitively impaired individuals using quantitative 18F-flortaucipir PET. Preprocessed 18F-flortaucipir tau PET images, T1-weighted structural MRI, demographic information, global cortical amyloid-β burden measured by 18F-florbetapir PET, CSF total tau and phosphorylated tau measurements were obtained from the Alzheimer’s Disease Neuroimaging Initiative database. Two hundred and sixty-eight cognitively impaired individuals with 146 APOE ε4 non-carriers and 122 carriers (85 heterozygotes and 37 homozygotes) were included in the study. An iterative reblurred Van Cittert iteration partial volume correction method was applied to all downloaded PET images. Magnetic resonance images were used for PET spatial normalization. Twelve regional standardized uptake value ratios relative to the cerebellum were computed in standard space. APOE ε4 dosage × sex interaction effect on 18F-flortaucipir standardized uptake value ratios was assessed using generalized linear models and sex-stratified analysis. We observed a significant APOE ε4 dosage × sex interaction effect on tau deposition in the lateral temporal, posterior cingulate, medial temporal, inferior temporal, entorhinal cortex, amygdala, parahippocampal gyrus regions after adjusting for age and education level (P < 0.05). The medial temporal, entorhinal cortex, amygdala and parahippocampal gyrus regions retained a significant APOE ε4 dosage × sex interaction effect on tau deposition after adjusting for global cortical amyloid-β (P < 0.05). In sex-stratified analysis, there was no significant difference in tau deposition between female homozygotes and heterozygotes (P > 0.05). In contrast, male homozygotes standardized uptake value ratios were significantly greater than heterozygotes or non-carriers throughout all 12 regions of interest (P < 0.05). Female heterozygotes exhibited significantly increased tau deposition compared to male heterozygotes in the orbitofrontal, posterior cingulate, lateral temporal, inferior temporal, entorhinal cortex, amygdala and parahippocampal gyrus (P < 0.05). Results from voxel-wise analysis were similar to the ones obtained from regions of interest analysis. Our findings indicate that an APOE ε4 dosage effect on brain region-specific tau deposition exists in males, but not females. These results have important clinical implications towards developing sex and genotype-guided therapeutics in Alzheimer’s disease and uncovers a potential explanation underlying differential APOE ε4-associated Alzheimer’s risk in males and females.
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Affiliation(s)
- Shaozhen Yan
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, Beijing, China.,Mallinckrodt Institute of Radiology, Washington University in St. Louis School of Medicine, St. Louis, MO, USA
| | - Chaojie Zheng
- Mallinckrodt Institute of Radiology, Washington University in St. Louis School of Medicine, St. Louis, MO, USA.,Central Research Institute, United Imaging Healthcare Group Co., Ltd, Shanghai, China
| | - Manish D Paranjpe
- Harvard-MIT Program in Health Sciences and Technology, Harvard Medical School, Boston, MA, USA
| | - Yanxiao Li
- Central Research Institute, United Imaging Healthcare Group Co., Ltd, Shanghai, China.,School of Computer Science, the University of Sydney, NSW 2006, Australia
| | - Weihua Li
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Xiuying Wang
- School of Computer Science, the University of Sydney, NSW 2006, Australia
| | - Tammie L S Benzinger
- Mallinckrodt Institute of Radiology, Washington University in St. Louis School of Medicine, St. Louis, MO, USA.,Department of Neurology, Washington University in St. Louis School of Medicine, Saint Louis, MO, USA
| | - Jie Lu
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Yun Zhou
- Mallinckrodt Institute of Radiology, Washington University in St. Louis School of Medicine, St. Louis, MO, USA.,Central Research Institute, United Imaging Healthcare Group Co., Ltd, Shanghai, China
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30
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Chen Y, Wang J, Cui C, Su Y, Jing D, Wu L, Liang P, Liang Z. Evaluating the association between brain atrophy, hypometabolism, and cognitive decline in Alzheimer's disease: a PET/MRI study. Aging (Albany NY) 2021; 13:7228-7246. [PMID: 33640881 PMCID: PMC7993730 DOI: 10.18632/aging.202580] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2020] [Accepted: 01/14/2021] [Indexed: 11/25/2022]
Abstract
Glucose metabolism reduction and brain volume losses are widely reported in Alzheimer’s disease (AD). Considering that neuroimaging changes in the hippocampus and default mode network (DMN) are promising important candidate biomarkers and have been included in the research criteria for the diagnosis of AD, it is hypothesized that atrophy and metabolic changes of the abovementioned regions could be evaluated concurrently to fully explore the neural mechanisms underlying cognitive impairment in AD. Twenty-three AD patients and Twenty-four age-, sex- and education level-matched normal controls underwent a clinical interview, a detailed neuropsychological assessment and a simultaneous 18F-fluoro-2-deoxy-D-glucose positron emission tomography (18F-FDG PET)/high-resolution T1-weighted magnetic resonance imaging (MRI) scan on a hybrid GE SIGNA PET/MR scanner. Brain volume and glucose metabolism were examined in patients and controls to reveal group differences. Multiple linear regression models were employed to explore the relationship between multiple imaging features and cognitive performance in AD. The AD group had significantly reduced volume in the hippocampus and DMN regions (P < 0.001) relative to that of normal controls determined by using ROI analysis. Compared to normal controls, significantly decreased metabolism in the DMN (P < 0.001) was also found in AD patients, which still survived after controlling for gray matter atrophy (P < 0.001). These findings from ROI analysis were further confirmed by whole-brain confirmatory analysis (P < 0.001, FWE-corrected). Finally, multiple linear regression results showed that impairment of multiple cognitive tasks was significantly correlated with the combination of DMN hypometabolism and atrophy in the hippocampus and DMN regions. This study demonstrated that combining functional and structural features can better explain the cognitive decline of AD patients than unimodal FDG or brain volume changes alone. These findings may have important implications for understanding the neural mechanisms of cognitive decline in AD.
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Affiliation(s)
- Yifan Chen
- Department of Nuclear Medicine, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Junkai Wang
- Department of Psychology, Tsinghua University, Beijing, China.,School of Psychology, Capital Normal University, Beijing, China.,Beijing Key Laboratory of Learning and Cognition, Beijing, China
| | - Chunlei Cui
- Department of Nuclear Medicine, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Yusheng Su
- Department of Nuclear Medicine, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Donglai Jing
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - LiYong Wu
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Peipeng Liang
- School of Psychology, Capital Normal University, Beijing, China.,Beijing Key Laboratory of Learning and Cognition, Beijing, China
| | - Zhigang Liang
- Department of Nuclear Medicine, Xuanwu Hospital, Capital Medical University, Beijing, China
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31
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Ando T, Kemp B, Warnock G, Sekine T, Kaushik S, Wiesinger F, Delso G. Zero Echo Time MRAC on FDG-PET/MR Maintains Diagnostic Accuracy for Alzheimer's Disease; A Simulation Study Combining ADNI-Data. Front Neurosci 2020; 14:569706. [PMID: 33324141 PMCID: PMC7725704 DOI: 10.3389/fnins.2020.569706] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2020] [Accepted: 11/03/2020] [Indexed: 11/13/2022] Open
Abstract
Aim Attenuation correction using zero-echo time (ZTE) - magnetic resonance imaging (MRI) (ZTE-MRAC) has become one of the standard methods for brain-positron emission tomography (PET) on commercial PET/MR scanners. Although the accuracy of the net tracer-uptake quantification based on ZTE-MRAC has been validated, that of the diagnosis for dementia has not yet been clarified, especially in terms of automated statistical analysis. The aim of this study was to clarify the impact of ZTE-MRAC on the diagnosis of Alzheimer's disease (AD) by performing simulation study. Methods We recruited 27 subjects, who underwent both PET/computed tomography (CT) and PET/MR (GE SIGNA) examinations. Additionally, we extracted 107 subjects from the Alzheimer Disease Neuroimaging Initiative (ADNI) dataset. From the PET raw data acquired on PET/MR, three FDG-PET series were generated, using two vendor-provided MRAC methods (ZTE and Atlas) and CT-based AC. Following spatial normalization to Montreal Neurological Institute (MNI) space, we calculated each patient's specific error maps, which correspond to the difference between the PET image corrected using the CTAC method and the PET images corrected using the MRAC methods. To simulate PET maps as if ADNI data had been corrected using MRAC methods, we multiplied each of these 27 error maps with each of the 107 ADNI cases in MNI space. To evaluate the probability of AD in each resulting image, we calculated a cumulative t-value using a fully automated method which had been validated not only in the original ADNI dataset but several multi-center studies. In the method, PET score = 1 is the 95% prediction limit of AD. PET score and diagnostic accuracy for the discrimination of AD were evaluated in simulated images using the original ADNI dataset as reference. Results Positron emission tomography score was slightly underestimated both in ZTE and Atlas group compared with reference CTAC (-0.0796 ± 0.0938 vs. -0.0784 ± 0.1724). The absolute error of PET score was lower in ZTE than Atlas group (0.098 ± 0.075 vs. 0.145 ± 0.122, p < 0.001). A higher correlation to the original PET score was observed in ZTE vs. Atlas group (R 2: 0.982 vs. 0.961). The accuracy for the discrimination of AD patients from normal control was maintained in ZTE and Atlas compared to CTAC (ZTE vs. Atlas. vs. original; 82.5% vs. 82.1% vs. 83.2% (CI 81.8-84.5%), respectively). Conclusion For FDG-PET images on PET/MR, attenuation correction using ZTE-MRI had superior accuracy to an atlas-based method in classification for dementia. ZTE maintains the diagnostic accuracy for AD.
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Affiliation(s)
- Takahiro Ando
- Department of Radiology, Nippon Medical School, Tokyo, Japan
| | - Bradley Kemp
- Department of Radiology, Mayo Clinic, Rochester, MN, United States
| | - Geoffrey Warnock
- Institute of Pharmacology and Toxicology, University of Zurich, Zurich, Switzerland.,PMOD Technologies Ltd., Zurich, Switzerland
| | - Tetsuro Sekine
- Department of Radiology, Nippon Medical School, Tokyo, Japan.,Department of Radiology, Nippon Medical School Musashi-Kosugi Hospital, Kawasaki, Japan.,Department of Nuclear Medicine, University Hospital Zurich, Zurich, Switzerland
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32
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Honda G, Nagamachi S, Nonokuma M, Takano K, Kuwabara Y, Yoshimitsu K, Iida H, Ogomori K, Kawasaki H, Tsuboi Y. The development of new method to differentiate between Dementia with Lewy bodies and Alzheimer's disease by cerebral perfusion SPECT-comparison to CIScore. Jpn J Radiol 2020; 39:198-205. [PMID: 32939741 DOI: 10.1007/s11604-020-01041-0] [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: 07/18/2020] [Accepted: 09/03/2020] [Indexed: 11/28/2022]
Abstract
PURPOSE The Cingulate Island Sign score (CIScore) by rCBF SPECT is used in the differentiation between Dementia with Lewy bodies (DLB) and Alzheimer's disease (AD) but has some false-positive AD cases. To resolve the problem, we developed new differential diagnosing method incorporating occipital lobe and para-hippocampal rCBF. MATERIALS AND METHODS In 27 DLB and 31 AD cases undertaken Tc-99 m-ECD SPECT, we evaluated the mean Z score in the bilateral superior, middle, inferior occipital gyri, cuneus, amygdala, hippocampus, and para-hippocampus. One criterion of DLB was defined as the case with CIScore lower than 0.27. The other criteria were the cases of following either or both two conditions were satisfied. (1) The number of occipital gyri with mean Z score higher than 1 is three or more. (2) The number of hippocampal regions with mean Z score higher than 1 is one or less. We compared the differential diagnostic ability among these four criterions. RESULTS The diagnostic accuracy by CIscore was 69% and that of the occipital gyri analysis 84%, para-hippocampal regions analysis 76% and combined occipital gyri and para-hippocampal regions analysis 93%. CONCLUSION The new method by combined rCBF analysis of occipital gyri and para-hippocampal regions showed best diagnostic ability in differentiating DLB from AD.
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Affiliation(s)
- Gaku Honda
- Department of Radiology, Faculty of Medicine, Fukuoka University, 7-45-1 Nanakuma, Jonan-ku, Fukuoka, 814-0180, Japan
| | - Shigeki Nagamachi
- Department of Radiology, Faculty of Medicine, Fukuoka University, 7-45-1 Nanakuma, Jonan-ku, Fukuoka, 814-0180, Japan.
| | - Masanari Nonokuma
- Department of Radiology, Faculty of Medicine, Fukuoka University, 7-45-1 Nanakuma, Jonan-ku, Fukuoka, 814-0180, Japan
| | - Koichi Takano
- Department of Radiology, Faculty of Medicine, Fukuoka University, 7-45-1 Nanakuma, Jonan-ku, Fukuoka, 814-0180, Japan
| | - Yasuo Kuwabara
- Department of Radiology, Faculty of Medicine, Fukuoka University, 7-45-1 Nanakuma, Jonan-ku, Fukuoka, 814-0180, Japan
| | - Kengo Yoshimitsu
- Department of Radiology, Faculty of Medicine, Fukuoka University, 7-45-1 Nanakuma, Jonan-ku, Fukuoka, 814-0180, Japan
| | - Hitoshi Iida
- Department of Psychiatry, Faculty of Medicine, Fukuoka University, 7-45-1 Nanakuma, Jonan-ku, Fukuoka, 814-0180, Japan
| | - Koji Ogomori
- Department of Psychiatry, Faculty of Medicine, Fukuoka University, 7-45-1 Nanakuma, Jonan-ku, Fukuoka, 814-0180, Japan
| | - Hiroaki Kawasaki
- Department of Psychiatry, Faculty of Medicine, Fukuoka University, 7-45-1 Nanakuma, Jonan-ku, Fukuoka, 814-0180, Japan
| | - Yoshio Tsuboi
- Department of Neurology, Faculty of Medicine, Fukuoka University, 7-45-1 Nanakuma, Jonan-ku, Fukuoka, 814-0180, Japan
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