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Seitz-Holland J, Alemán-Gómez Y, Cho KIK, Pasternak O, Cleusix M, Jenni R, Baumann PS, Klauser P, Conus P, Hagmann P, Do KQ, Kubicki M, Dwir D. Matrix metalloproteinase 9 (MMP-9) activity, hippocampal extracellular free water, and cognitive deficits are associated with each other in early phase psychosis. Neuropsychopharmacology 2024; 49:1140-1150. [PMID: 38431757 PMCID: PMC11109110 DOI: 10.1038/s41386-024-01814-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/13/2023] [Revised: 12/18/2023] [Accepted: 01/29/2024] [Indexed: 03/05/2024]
Abstract
Increasing evidence points toward the role of the extracellular matrix, specifically matrix metalloproteinase 9 (MMP-9), in the pathophysiology of psychosis. MMP-9 is a critical regulator of the crosstalk between peripheral and central inflammation, extracellular matrix remodeling, hippocampal development, synaptic pruning, and neuroplasticity. Here, we aim to characterize the relationship between plasma MMP-9 activity, hippocampal microstructure, and cognition in healthy individuals and individuals with early phase psychosis. We collected clinical, blood, and structural and diffusion-weighted magnetic resonance imaging data from 39 individuals with early phase psychosis and 44 age and sex-matched healthy individuals. We measured MMP-9 plasma activity, hippocampal extracellular free water (FW) levels, and hippocampal volumes. We used regression analyses to compare MMP-9 activity, hippocampal FW, and volumes between groups. We then examined associations between MMP-9 activity, FW levels, hippocampal volumes, and cognitive performance assessed with the MATRICS battery. All analyses were controlled for age, sex, body mass index, cigarette smoking, and years of education. Individuals with early phase psychosis demonstrated higher MMP-9 activity (p < 0.0002), higher left (p < 0.05) and right (p < 0.05) hippocampal FW levels, and lower left (p < 0.05) and right (p < 0.05) hippocampal volume than healthy individuals. MMP-9 activity correlated positively with hippocampal FW levels (all participants and individuals with early phase psychosis) and negatively with hippocampal volumes (all participants and healthy individuals). Higher MMP-9 activity and higher hippocampal FW levels were associated with slower processing speed and worse working memory performance in all participants. Our findings show an association between MMP-9 activity and hippocampal microstructural alterations in psychosis and an association between MMP-9 activity and cognitive performance. Further, more extensive longitudinal studies should examine the therapeutic potential of MMP-9 modulators in psychosis.
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Affiliation(s)
- Johanna Seitz-Holland
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
| | - Yasser Alemán-Gómez
- Connectomics Lab, Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- Center for Psychiatric Neuroscience, Department of Psychiatry, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- Medical Image Analysis Laboratory, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Kang Ik K Cho
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Ofer Pasternak
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Martine Cleusix
- Center for Psychiatric Neuroscience, Department of Psychiatry, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- Service of General Psychiatry, Department of Psychiatry, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Raoul Jenni
- Center for Psychiatric Neuroscience, Department of Psychiatry, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- Service of General Psychiatry, Department of Psychiatry, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Philipp S Baumann
- Service of General Psychiatry, Department of Psychiatry, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Paul Klauser
- Center for Psychiatric Neuroscience, Department of Psychiatry, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- Service of Child and Adolescent Psychiatry, Department of Psychiatry, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Philippe Conus
- Center for Psychiatric Neuroscience, Department of Psychiatry, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- Service of General Psychiatry, Department of Psychiatry, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Patric Hagmann
- Connectomics Lab, Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Kim Q Do
- Center for Psychiatric Neuroscience, Department of Psychiatry, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Marek Kubicki
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Daniella Dwir
- Center for Psychiatric Neuroscience, Department of Psychiatry, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.
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Zhang P, Feng Y, Xu T, Li Y, Xia J, Zhang H, Sun Z, Tian W, Zhang J. Brain white matter microstructural alterations in patients with systemic lupus erythematosus: an automated fiber quantification study. Brain Imaging Behav 2024; 18:622-629. [PMID: 38332385 DOI: 10.1007/s11682-024-00861-2] [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] [Accepted: 01/30/2024] [Indexed: 02/10/2024]
Abstract
This study aimed to identify damaged segments of brain white matter fiber tracts in patients with systemic lupus erythematosus (SLE) using diffusion tensor imaging (DTI)-based automated fiber quantification (AFQ), and analyze their relationship with cognitive impairment. Clinical and imaging data for 39 female patients with SLE and for 44 female healthy controls (HCs) were collected. AFQ was used to track whole-brain white matter tracts in each participant, and each tract was segmented into 100 equally spaced nodes. DTI metrics including fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) were calculated at each node. Correlations were also explored between DTI metrics in the damaged segments of white matter fiber tracts and neuropsychological test scores of patients with SLE. Compared with HCs, SLE patients exhibited significantly lower FA values, and significantly higher MD, AD, RD values in many white matter tracts (all P < 0.05, false discovery rate-corrected). FA values in nodes 97-100 of the left inferior fronto-occipital fasciculus (IFOF) positively correlated with the mini-mental state examination score. AFQ enables precise and accurate identification of damage to white matter fiber tracts in brains of patients with SLE. FA values in the left IFOF correlate with cognitive impairment in SLE.
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Affiliation(s)
- Peng Zhang
- Graduate School of Dalian Medical University, Liaoning, 116044, China
- The First Affiliated Hospital of Baotou Medical College, Baotou, 014010, China
| | - Yanhong Feng
- Graduate School of Dalian Medical University, Liaoning, 116044, China
| | - Tianye Xu
- Graduate School of Dalian Medical University, Liaoning, 116044, China
| | - Yifan Li
- School of Medicine, Nantong University, Jiangsu, 226019, China
| | - Jianguo Xia
- Department of Imaging, The Affiliated Taizhou People's Hospital of Nanjing Medical University, Jiangsu, 225300, China.
| | - Hongxia Zhang
- Department of Imaging, The Affiliated Taizhou People's Hospital of Nanjing Medical University, Jiangsu, 225300, China.
| | - Zhongru Sun
- Department of Imaging, The Affiliated Taizhou People's Hospital of Nanjing Medical University, Jiangsu, 225300, China
| | - Weizhong Tian
- Department of Imaging, The Affiliated Taizhou People's Hospital of Nanjing Medical University, Jiangsu, 225300, China
| | - Ji Zhang
- Department of Imaging, The Affiliated Taizhou People's Hospital of Nanjing Medical University, Jiangsu, 225300, China
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Yamashiro K, Takabayashi K, Kamagata K, Nishimoto Y, Togashi Y, Yamauchi Y, Ogaki K, Li Y, Hatano T, Motoi Y, Suzuki M, Miyakawa K, Ishikawa D, Aoki S, Urabe T, Hattori N. Free water in gray matter linked to gut microbiota changes with decreased butyrate producers in Alzheimer's disease and mild cognitive impairment. Neurobiol Dis 2024; 193:106464. [PMID: 38452948 DOI: 10.1016/j.nbd.2024.106464] [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: 01/05/2024] [Revised: 02/28/2024] [Accepted: 03/04/2024] [Indexed: 03/09/2024] Open
Abstract
Neuroinflammation contributes to the pathology and progression of Alzheimer's disease (AD), and it can be observed even with mild cognitive impairment (MCI), a prodromal phase of AD. Free water (FW) imaging estimates the extracellular water content and has been used to study neuroinflammation across several neurological diseases including AD. Recently, the role of gut microbiota has been implicated in the pathogenesis of AD. The relationship between FW imaging and gut microbiota was examined in patients with AD and MCI. Fifty-six participants underwent neuropsychological assessments, FW imaging, and gut microbiota analysis targeting the bacterial 16S rRNA gene. They were categorized into the cognitively normal control (NC) (n = 19), MCI (n = 19), and AD (n = 18) groups according to the neuropsychological assessments. The correlations of FW values, neuropsychological assessment scores, and the relative abundance of gut microbiota were analyzed. FW was higher in several white matter tracts and in gray matter regions, predominantly the frontal, temporal, limbic and paralimbic regions in the AD/MCI group than in the NC group. In the AD/MCI group, higher FW values in the temporal (superior temporal and temporal pole), limbic and paralimbic (insula, hippocampus and amygdala) regions were the most associated with worse neuropsychological assessment scores. In the AD/MCI group, FW values in these regions were negatively correlated with the relative abundances of butyrate-producing genera Anaerostipes, Lachnospiraceae UCG-004, and [Ruminococcus] gnavus group, which showed a significant decreasing trend in the order of the NC, MCI, and AD groups. The present study showed that increased FW in the gray matter regions related to cognitive impairment was associated with low abundances of butyrate producers in the AD/MCI group. These findings suggest an association between neuroinflammation and decreased levels of the short-chain fatty acid butyrate that is one of the major gut microbial metabolites having a potentially beneficial role in brain homeostasis.
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Affiliation(s)
- Kazuo Yamashiro
- Department of Neurology, Juntendo University School of Medicine, 2-1-1 Hongo, Bunkyo-ku, Tokyo 113-8421, Japan; Department of Neurology, Juntendo University Urayasu Hospital, 2-1-1 Tomioka, Urayasu, Chiba 279-0021, Japan.
| | - Kaito Takabayashi
- Department of Radiology, Juntendo University School of Medicine, 2-1-1 Hongo, Bunkyo-ku, Tokyo 113-8421, Japan
| | - Koji Kamagata
- Department of Radiology, Juntendo University School of Medicine, 2-1-1 Hongo, Bunkyo-ku, Tokyo 113-8421, Japan
| | - Yuichiro Nishimoto
- Metagen Inc., 246-2 Mizukami, Kakuganji, Tsuruoka, Yamagata 997-0052, Japan
| | - Yuka Togashi
- Metagen Inc., 246-2 Mizukami, Kakuganji, Tsuruoka, Yamagata 997-0052, Japan
| | - Yohsuke Yamauchi
- Metagen Inc., 246-2 Mizukami, Kakuganji, Tsuruoka, Yamagata 997-0052, Japan
| | - Kotaro Ogaki
- Department of Neurology, Juntendo University Urayasu Hospital, 2-1-1 Tomioka, Urayasu, Chiba 279-0021, Japan
| | - Yuanzhe Li
- Department of Neurology, Juntendo University School of Medicine, 2-1-1 Hongo, Bunkyo-ku, Tokyo 113-8421, Japan
| | - Taku Hatano
- Department of Neurology, Juntendo University School of Medicine, 2-1-1 Hongo, Bunkyo-ku, Tokyo 113-8421, Japan
| | - Yumiko Motoi
- Department of Neurology, Juntendo University School of Medicine, 2-1-1 Hongo, Bunkyo-ku, Tokyo 113-8421, Japan
| | - Michimasa Suzuki
- Department of Radiology, Juntendo University Urayasu Hospital, 2-1-1 Tomioka, Urayasu, Chiba 279-0021, Japan
| | - Koichi Miyakawa
- Department of Psychiatry, Juntendo University Urayasu Hospital, 2-1-1 Tomioka, Urayasu, Chiba 279-0021, Japan
| | - Dai Ishikawa
- Metagen Inc., 246-2 Mizukami, Kakuganji, Tsuruoka, Yamagata 997-0052, Japan; Department of Gastroenterology, Juntendo University School of Medicine, 2-1-1 Hongo, Bunkyo-ku, Tokyo 113-8421, Japan
| | - Shigeki Aoki
- Department of Radiology, Juntendo University School of Medicine, 2-1-1 Hongo, Bunkyo-ku, Tokyo 113-8421, Japan
| | - Takao Urabe
- Department of Neurology, Juntendo University Urayasu Hospital, 2-1-1 Tomioka, Urayasu, Chiba 279-0021, Japan
| | - Nobutaka Hattori
- Department of Neurology, Juntendo University School of Medicine, 2-1-1 Hongo, Bunkyo-ku, Tokyo 113-8421, Japan; Neurodegenerative Disorders Collaborative Laboratory, RIKEN Center for Brain Science, 2-1 Hirosawa Wako, Saitama 351-0198, Japan
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Parsaei M, Hasehmi SM, Seyedmirzaei H, Cattarinussi G, Sambataro F, Brambilla P, Delvecchio G. Microstructural white matter alterations associated with social anxiety disorders: A systematic review. J Affect Disord 2024; 350:78-88. [PMID: 38220105 DOI: 10.1016/j.jad.2024.01.118] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/21/2023] [Revised: 12/04/2023] [Accepted: 01/09/2024] [Indexed: 01/16/2024]
Abstract
BACKGROUND Social anxiety disorder (SAD) is a psychiatric condition characterized by impaired social functioning that negatively impacts individuals' quality of life. Previous neuroimaging studies have revealed morphological and functional changes in various brain regions associated with SAD. Recent advances in diffusion tensor imaging (DTI) and diffusion-weighted imaging (DWI) have enabled the investigation of microstructural white matter (WM) alterations in SAD. This study aims to provide an overview of DTI/DWI studies exploring WM microstructure changes in SAD. METHODS A systematic search on PubMed, Scopus, Web of Science, and PsycINFO was conducted for relevant records on July 8, 2023. An exploratory meta-analysis was also performed. RESULTS Eight studies were reviewed. Consistent findings indicated reduced fractional anisotropy and increased diffusivity measures in different WM tracts in SAD patients compared to healthy controls. These alterations were mostly observed within regions of the fronto-limbic network, like uncinate fasciculus (UF) and superior and inferior longitudinal fasciculi (SLF and ILF). Finally, our exploratory meta-analysis on four studies utilizing a voxel-wise analytic approach yielded no significant differences between SAD patients and controls. LIMITATIONS Limited number of studies, small sample sizes, and heterogeneity in analysis methods. CONCLUSIONS Patients with SAD exhibited altered WM integrity, particularly in the UF, SLF, and ILF, compared to healthy controls. However, due to the limited number of included studies, our meta-analysis yielded no significant differences between SAD patients and controls. Therefore, future research is crucial to unravel the link between altered WM structure and the involvement of other limbic and cortical structures in SAD pathogenesis.
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Affiliation(s)
- Mohammadamin Parsaei
- Maternal, Fetal & Neonatal Research Center, Family Health Research Institute, Tehran University of Medical Sciences, Tehran, Iran
| | | | - Homa Seyedmirzaei
- School of Medicine, Tehran University of Medical Sciences, Tehran, Iran; Interdisciplinary Neuroscience Research Program Tehran University of Medical Sciences, Tehran, Iran
| | - Giulia Cattarinussi
- Department of Neuroscience (DNS), Padua Neuroscience Center, University of Padova, Padua, Italy; Padua Neuroscience Center, University of Padova, Padua, Italy
| | - Fabio Sambataro
- Department of Neuroscience (DNS), Padua Neuroscience Center, University of Padova, Padua, Italy; Padua Neuroscience Center, University of Padova, Padua, Italy
| | - Paolo Brambilla
- Department of Pathophysiology and Transplantation, University of Milan, Milan, Italy; Department of Neurosciences and Mental Health, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Giuseppe Delvecchio
- Department of Neurosciences and Mental Health, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, 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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Singh SP, Gupta S, Rajapakse JC. Sparse Deep Neural Network for Encoding and Decoding the Structural Connectome. IEEE JOURNAL OF TRANSLATIONAL ENGINEERING IN HEALTH AND MEDICINE 2024; 12:371-381. [PMID: 38633564 PMCID: PMC11023626 DOI: 10.1109/jtehm.2024.3366504] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/19/2022] [Revised: 11/17/2023] [Accepted: 02/12/2024] [Indexed: 04/19/2024]
Abstract
Brain state classification by applying deep learning techniques on neuroimaging data has become a recent topic of research. However, unlike domains where the data is low dimensional or there are large number of available training samples, neuroimaging data is high dimensional and has few training samples. To tackle these issues, we present a sparse feedforward deep neural architecture for encoding and decoding the structural connectome of the human brain. We use a sparsely connected element-wise multiplication as the first hidden layer and a fixed transform layer as the output layer. The number of trainable parameters and the training time is significantly reduced compared to feedforward networks. We demonstrate superior performance of this architecture in encoding the structural connectome implicated in Alzheimer's disease (AD) and Parkinson's disease (PD) from DTI brain scans. For decoding, we propose recursive feature elimination (RFE) algorithm based on DeepLIFT, layer-wise relevance propagation (LRP), and Integrated Gradients (IG) algorithms to remove irrelevant features and thereby identify key biomarkers associated with AD and PD. We show that the proposed architecture reduces 45.1% and 47.1% of the trainable parameters compared to a feedforward DNN with an increase in accuracy by 2.6 % and 3.1% for cognitively normal (CN) vs AD and CN vs PD classification, respectively. We also show that the proposed RFE method leads to a further increase in accuracy by 2.1% and 4% for CN vs AD and CN vs PD classification, while removing approximately 90% to 95% irrelevant features. Furthermore, we argue that the biomarkers (i.e., key brain regions and connections) identified are consistent with previous literature. We show that relevancy score-based methods can yield high discriminative power and are suitable for brain decoding. We also show that the proposed approach led to a reduction in the number of trainable network parameters, an increase in classification accuracy, and a detection of brain connections and regions that were consistent with earlier studies.
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Affiliation(s)
- Satya P. Singh
- Division of Electronics and Communication EngineeringNetaji Subhas University of TechnologyDwarkaNew Delhi110078India
| | - Sukrit Gupta
- Department of Computer Science and EngineeringIndian Institute of Technology RoparRupnagarPunjab140001India
| | - Jagath C. Rajapakse
- School of Computer Science and EngineeringNanyang Technological UniversityNanyangSingapore639798
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Voorter PHM, van Dinther M, Jansen WJ, Postma AA, Staals J, Jansen JFA, van Oostenbrugge RJ, van der Thiel MM, Backes WH. Blood-Brain Barrier Disruption and Perivascular Spaces in Small Vessel Disease and Neurodegenerative Diseases: A Review on MRI Methods and Insights. J Magn Reson Imaging 2024; 59:397-411. [PMID: 37658640 DOI: 10.1002/jmri.28989] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2023] [Revised: 08/17/2023] [Accepted: 08/17/2023] [Indexed: 09/03/2023] Open
Abstract
Perivascular spaces (PVS) and blood-brain barrier (BBB) disruption are two key features of cerebral small vessel disease (cSVD) and neurodegenerative diseases that have been linked to cognitive impairment and are involved in the cerebral waste clearance system. Magnetic resonance imaging (MRI) offers the possibility to study these pathophysiological processes noninvasively in vivo. This educational review provides an overview of the MRI techniques used to assess PVS functionality and BBB disruption. MRI-visible PVS can be scored on structural images by either (subjectively) counting or (automatically) delineating the PVS. We highlight emerging (diffusion) techniques to measure proxies of perivascular fluid and its movement, which may provide a more comprehensive understanding of the role of PVS in diseases. For the measurement of BBB disruption, we explain the most commonly used MRI technique, dynamic contrast-enhanced (DCE) MRI, as well as a more recently developed technique based on arterial spin labeling (ASL). DCE MRI and ASL are thought to measure complementary characteristics of the BBB. Furthermore, we describe clinical studies that have utilized these MRI techniques in cSVD and neurodegenerative diseases, particularly Alzheimer's disease (AD). These studies demonstrate the role of PVS and BBB dysfunction in these diseases and provide insight into the large overlap, but also into the differences between cSVD and AD. Overall, MRI techniques may provide valuable insights into the pathophysiological mechanisms underlying these diseases and have the potential to be used as markers for disease progression and treatment response. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY: Stage 2.
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Affiliation(s)
- Paulien H M Voorter
- Department of Radiology and Nuclear Medicine, Maastricht University Medical Center, Maastricht, the Netherlands
- School for Mental Health and Neuroscience, Maastricht University, Maastricht, the Netherlands
| | - Maud van Dinther
- School for Cardiovascular Disease, Maastricht University, Maastricht, the Netherlands
- Department of Neurology, Maastricht University Medical Center, Maastricht, the Netherlands
| | - Willemijn J Jansen
- School for Mental Health and Neuroscience, Maastricht University, Maastricht, the Netherlands
- Department of Psychiatry and Neuropsychology, Alzheimer Center Limburg, Maastricht University, Maastricht, the Netherlands
| | - Alida A Postma
- Department of Radiology and Nuclear Medicine, Maastricht University Medical Center, Maastricht, the Netherlands
| | - Julie Staals
- School for Cardiovascular Disease, Maastricht University, Maastricht, the Netherlands
- Department of Neurology, Maastricht University Medical Center, Maastricht, the Netherlands
| | - Jacobus F A Jansen
- Department of Radiology and Nuclear Medicine, Maastricht University Medical Center, Maastricht, the Netherlands
- School for Mental Health and Neuroscience, Maastricht University, Maastricht, the Netherlands
- Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, the Netherlands
| | - Robert J van Oostenbrugge
- School for Mental Health and Neuroscience, Maastricht University, Maastricht, the Netherlands
- School for Cardiovascular Disease, Maastricht University, Maastricht, the Netherlands
- Department of Neurology, Maastricht University Medical Center, Maastricht, the Netherlands
| | - Merel M van der Thiel
- Department of Radiology and Nuclear Medicine, Maastricht University Medical Center, Maastricht, the Netherlands
- School for Mental Health and Neuroscience, Maastricht University, Maastricht, the Netherlands
- Department of Psychiatry and Neuropsychology, Alzheimer Center Limburg, Maastricht University, Maastricht, the Netherlands
| | - Walter H Backes
- Department of Radiology and Nuclear Medicine, Maastricht University Medical Center, Maastricht, the Netherlands
- School for Mental Health and Neuroscience, Maastricht University, Maastricht, the Netherlands
- School for Cardiovascular Disease, Maastricht University, Maastricht, the Netherlands
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Kent SA, Miron VE. Microglia regulation of central nervous system myelin health and regeneration. Nat Rev Immunol 2024; 24:49-63. [PMID: 37452201 DOI: 10.1038/s41577-023-00907-4] [Citation(s) in RCA: 14] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/13/2023] [Indexed: 07/18/2023]
Abstract
Microglia are resident macrophages of the central nervous system that have key functions in its development, homeostasis and response to damage and infection. Although microglia have been increasingly implicated in contributing to the pathology that underpins neurological dysfunction and disease, they also have crucial roles in neurological homeostasis and regeneration. This includes regulation of the maintenance and regeneration of myelin, the membrane that surrounds neuronal axons, which is required for axonal health and function. Myelin is damaged with normal ageing and in several neurodegenerative diseases, such as multiple sclerosis and Alzheimer disease. Given the lack of approved therapies targeting myelin maintenance or regeneration, it is imperative to understand the mechanisms by which microglia support and restore myelin health to identify potential therapeutic approaches. However, the mechanisms by which microglia regulate myelin loss or integrity are still being uncovered. In this Review, we discuss recent work that reveals the changes in white matter with ageing and neurodegenerative disease, how this relates to microglia dynamics during myelin damage and regeneration, and factors that influence the regenerative functions of microglia.
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Affiliation(s)
- Sarah A Kent
- UK Dementia Research Institute at The University of Edinburgh, Edinburgh, UK
- Centre for Discovery Brain Sciences, Chancellor's Building, The University of Edinburgh, Edinburgh, UK
| | - Veronique E Miron
- UK Dementia Research Institute at The University of Edinburgh, Edinburgh, UK.
- Centre for Discovery Brain Sciences, Chancellor's Building, The University of Edinburgh, Edinburgh, UK.
- Barlo Multiple Sclerosis Centre, St Michael's Hospital, Toronto, Ontario, Canada.
- Keenan Research Centre for Biomedical Science, St Michael's Hospital, Toronto, Ontario, Canada.
- Department of Immunology, The University of Toronto, Toronto, Ontario, Canada.
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Cho CH, Deyneko IV, Cordova-Martinez D, Vazquez J, Maguire AS, Diaz JR, Carbonell AU, Tindi JO, Cui MH, Fleysher R, Molholm S, Lipton ML, Branch CA, Hodgson L, Jordan BA. ANKS1B encoded AIDA-1 regulates social behaviors by controlling oligodendrocyte function. Nat Commun 2023; 14:8499. [PMID: 38129387 PMCID: PMC10739966 DOI: 10.1038/s41467-023-43438-1] [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: 04/08/2022] [Accepted: 11/09/2023] [Indexed: 12/23/2023] Open
Abstract
Heterozygous deletions in the ANKS1B gene cause ANKS1B neurodevelopmental syndrome (ANDS), a rare genetic disease characterized by autism spectrum disorder (ASD), attention deficit/hyperactivity disorder, and speech and motor deficits. The ANKS1B gene encodes for AIDA-1, a protein that is enriched at neuronal synapses and regulates synaptic plasticity. Here we report an unexpected role for oligodendroglial deficits in ANDS pathophysiology. We show that Anks1b-deficient mouse models display deficits in oligodendrocyte maturation, myelination, and Rac1 function, and recapitulate white matter abnormalities observed in ANDS patients. Selective loss of Anks1b from the oligodendrocyte lineage, but not from neuronal populations, leads to deficits in social preference and sensory reactivity previously observed in a brain-wide Anks1b haploinsufficiency model. Furthermore, we find that clemastine, an antihistamine shown to increase oligodendrocyte precursor cell maturation and central nervous system myelination, rescues deficits in social preference in 7-month-old Anks1b-deficient mice. Our work shows that deficits in social behaviors present in ANDS may originate from abnormal Rac1 activity within oligodendrocytes.
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Affiliation(s)
- Chang Hoon Cho
- Dominick P. Purpura Department of Neuroscience, Albert Einstein College of Medicine, Bronx, NY, USA
- Human Pathobiology and OMNI Reverse Translation, Genentech, Inc., San Francisco, CA, USA
| | - Ilana Vasilisa Deyneko
- Dominick P. Purpura Department of Neuroscience, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Dylann Cordova-Martinez
- Dominick P. Purpura Department of Neuroscience, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Juan Vazquez
- Dominick P. Purpura Department of Neuroscience, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Anne S Maguire
- Dominick P. Purpura Department of Neuroscience, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Jenny R Diaz
- Dominick P. Purpura Department of Neuroscience, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Abigail U Carbonell
- Dominick P. Purpura Department of Neuroscience, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Jaafar O Tindi
- Dominick P. Purpura Department of Neuroscience, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Min-Hui Cui
- Department of Radiology, Albert Einstein College of Medicine, Bronx, NY, USA
- Gruss Magnetic Resonance Research Center, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Roman Fleysher
- Department of Radiology, Albert Einstein College of Medicine, Bronx, NY, USA
- Gruss Magnetic Resonance Research Center, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Sophie Molholm
- Dominick P. Purpura Department of Neuroscience, Albert Einstein College of Medicine, Bronx, NY, USA
- Department of Pediatrics, Albert Einstein College of Medicine, Bronx, NY, USA
- Department of Psychiatry and Behavioral Sciences, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Michael L Lipton
- Dominick P. Purpura Department of Neuroscience, Albert Einstein College of Medicine, Bronx, NY, USA
- Department of Radiology, Albert Einstein College of Medicine, Bronx, NY, USA
- Gruss Magnetic Resonance Research Center, Albert Einstein College of Medicine, Bronx, NY, USA
- Department of Psychiatry and Behavioral Sciences, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Craig A Branch
- Department of Radiology, Albert Einstein College of Medicine, Bronx, NY, USA
- Gruss Magnetic Resonance Research Center, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Louis Hodgson
- Department of Molecular Pharmacology, Albert Einstein College of Medicine, Bronx, NY, USA
- Gruss-Lipper Biophotonics Center, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Bryen A Jordan
- Dominick P. Purpura Department of Neuroscience, Albert Einstein College of Medicine, Bronx, NY, USA.
- Department of Psychiatry and Behavioral Sciences, Albert Einstein College of Medicine, Bronx, NY, USA.
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Sun X, Zhao C, Chen SY, Chang Y, Han YL, Li K, Sun HM, Wang ZF, Liang Y, Jia JJ. Free Water MR Imaging of White Matter Microstructural Changes is a Sensitive Marker of Amyloid Positivity in Alzheimer's Disease. J Magn Reson Imaging 2023. [PMID: 38100518 DOI: 10.1002/jmri.29189] [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: 04/13/2023] [Revised: 12/01/2023] [Accepted: 12/02/2023] [Indexed: 12/17/2023] Open
Abstract
BACKGROUND Extracellular free water (FW) resulting from white matter degeneration limits the sensitivity of diffusion tensor imaging (DTI) in predicting Alzheimer's disease (AD). PURPOSE To evaluate the sensitivity of FW-DTI in detecting white matter microstructural changes in AD. To validate the effectiveness of FW-DTI indices to predict amyloid-beta (Aβ) positivity in mild cognitive impairment (MCI) subtypes. STUDY TYPE Retrospective. POPULATION Thirty-eight Aβ-negative cognitively healthy (CH) controls (68.74 ± 8.28 years old, 55% female), 15 Aβ-negative MCI patients (MCI-n) (68.87 ± 8.83 years old, 60% female), 29 Aβ-positive MCI patients (MCI-p) (73.03 ± 7.05 years old, 52% female), and 29 Aβ-positive AD patients (72.93 ± 9.11 years old, 55% female). FIELD STRENGTH/SEQUENCE 3.0T; DTI, T1 -weighted, T2 -weighted, T2 star-weighted angiography, and Aβ PET (18 F-florbetaben or 11 C-PIB). ASSESSMENT FW-corrected and standard diffusion indices were analyzed using trace-based spatial statistics. Area under the curve (AUC) in distinguishing MCI subtypes were compared using support vector machine (SVM). STATISTICAL TESTS Chi-squared test, one-way analysis of covariance, general linear regression analyses, nonparametric permutation tests, partial Pearson's correlation, receiver operating characteristic curve analysis, and linear SVM. A P value <0.05 was considered statistically significant. RESULTS Compared with CH/MCI-n/MCI-p, AD showed significant change in tissue compartment indices of FW-DTI. No difference was found in the FW index among pair-wise group comparisons (the minimum FWE-corrected P = 0.114). There was a significant association between FW-DTI indices and memory and visuospatial function. The SVM classifier with tissue radial diffusivity as an input feature had the best classification performance of MCI subtypes (AUC = 0.91), and the classifying accuracy of FW-DTI was all over 89.89%. DATA CONCLUSION FW-DTI indices prove to be potential biomarkers of AD. The classification of MCI subtypes based on SVM and FW-DTI indices has good accuracy and could help early diagnosis. EVIDENCE LEVEL 4 TECHNICAL EFFICACY: Stage 2.
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Affiliation(s)
- Xuan Sun
- Medical School of Chinese PLA, Beijing, China
- Department of Geriatric Neurology, The Second Medical Centre, Chinese PLA General Hospital, Beijing, China
- National Clinical Research Center of Geriatric Diseases, Chinese PLA General Hospital, Beijing, China
| | - Cui Zhao
- School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China
| | - Si-Yu Chen
- Medical School of Chinese PLA, Beijing, China
- Department of Geriatric Neurology, The Second Medical Centre, Chinese PLA General Hospital, Beijing, China
- National Clinical Research Center of Geriatric Diseases, Chinese PLA General Hospital, Beijing, China
| | - Yan Chang
- Department of Nuclear Medicine, The First Medical Centre, Chinese PLA General Hospital, Beijing, China
| | - Yu-Liang Han
- Department of Neurology, The 305 Hospital of PLA, Beijing, China
| | - Ke Li
- Department of Geriatric Neurology, The Second Medical Centre, Chinese PLA General Hospital, Beijing, China
- National Clinical Research Center of Geriatric Diseases, Chinese PLA General Hospital, Beijing, China
| | - Hong-Mei Sun
- Medical School of Chinese PLA, Beijing, China
- Institute of Geriatrics, Chinese PLA General Hospital, Beijing, China
| | - Zhen-Fu Wang
- Department of Geriatric Neurology, The Second Medical Centre, Chinese PLA General Hospital, Beijing, China
- National Clinical Research Center of Geriatric Diseases, Chinese PLA General Hospital, Beijing, China
| | - Ying Liang
- School of Biomedical Engineering, Capital Medical University, Beijing, China
| | - Jian-Jun Jia
- National Clinical Research Center of Geriatric Diseases, Chinese PLA General Hospital, Beijing, China
- Institute of Geriatrics, Chinese PLA General Hospital, Beijing, China
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11
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Obis E, Sol J, Andres-Benito P, Martín-Gari M, Mota-Martorell N, Galo-Licona JD, Piñol-Ripoll G, Portero-Otin M, Ferrer I, Jové M, Pamplona R. Lipidomic Alterations in the Cerebral Cortex and White Matter in Sporadic Alzheimer's Disease. Aging Dis 2023; 14:1887-1916. [PMID: 37196109 PMCID: PMC10529741 DOI: 10.14336/ad.2023.0217] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2022] [Accepted: 02/17/2023] [Indexed: 05/19/2023] Open
Abstract
Non-targeted LC-MS/MS-based lipidomic analysis was conducted in post-mortem human grey matter frontal cortex area 8 (GM) and white matter of the frontal lobe centrum semi-ovale (WM) to identify lipidome fingerprints in middle-aged individuals with no neurofibrillary tangles and senile plaques, and cases at progressive stages of sporadic Alzheimer's disease (sAD). Complementary data were obtained using RT-qPCR and immunohistochemistry. The results showed that WM presents an adaptive lipid phenotype resistant to lipid peroxidation, characterized by a lower fatty acid unsaturation, peroxidizability index, and higher ether lipid content than the GM. Changes in the lipidomic profile are more marked in the WM than in GM in AD with disease progression. Four functional categories are associated with the different lipid classes affected in sAD: membrane structural composition, bioenergetics, antioxidant protection, and bioactive lipids, with deleterious consequences affecting both neurons and glial cells favoring disease progression.
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Affiliation(s)
- Elia Obis
- Department of Experimental Medicine, Lleida University (UdL), Lleida Biomedical Research Institute (IRBLleida), Lleida, Spain.
| | - Joaquim Sol
- Department of Experimental Medicine, Lleida University (UdL), Lleida Biomedical Research Institute (IRBLleida), Lleida, Spain.
- Catalan Institute of Health (ICS), Lleida, Spain, Research Support Unit (USR), Fundació Institut Universitari per a la Recerca en Atenció Primària de Salut Jordi Gol i Gurina (IDIAP JGol), Lleida, Spain.
| | - Pol Andres-Benito
- CIBERNED (Network Centre of Biomedical Research of Neurodegenerative Diseases), Institute of Health Carlos III, Ministry of Economy and Competitiveness, Madrid, Spain.
- Bellvitge University Hospital-Bellvitge Biomedical Research Institute (IDIBELL), E-08907 Hospitalet de Llobregat, Barcelona, Spain.
| | - Meritxell Martín-Gari
- Department of Experimental Medicine, Lleida University (UdL), Lleida Biomedical Research Institute (IRBLleida), Lleida, Spain.
| | - Natàlia Mota-Martorell
- Department of Experimental Medicine, Lleida University (UdL), Lleida Biomedical Research Institute (IRBLleida), Lleida, Spain.
| | - José Daniel Galo-Licona
- Department of Experimental Medicine, Lleida University (UdL), Lleida Biomedical Research Institute (IRBLleida), Lleida, Spain.
| | - Gerard Piñol-Ripoll
- Unitat Trastorns Cognitius, Clinical Neuroscience Research, Santa Maria University Hospital, IRBLleida, Lleida, Spain.
| | - Manuel Portero-Otin
- Department of Experimental Medicine, Lleida University (UdL), Lleida Biomedical Research Institute (IRBLleida), Lleida, Spain.
| | - Isidro Ferrer
- CIBERNED (Network Centre of Biomedical Research of Neurodegenerative Diseases), Institute of Health Carlos III, Ministry of Economy and Competitiveness, Madrid, Spain.
- Bellvitge University Hospital-Bellvitge Biomedical Research Institute (IDIBELL), E-08907 Hospitalet de Llobregat, Barcelona, Spain.
- Department of Pathology and Experimental Therapeutics, University of Barcelona, L’Hospitalet de Llobregat, Barcelona, Spain.
| | - Mariona Jové
- Department of Experimental Medicine, Lleida University (UdL), Lleida Biomedical Research Institute (IRBLleida), Lleida, Spain.
| | - Reinald Pamplona
- Department of Experimental Medicine, Lleida University (UdL), Lleida Biomedical Research Institute (IRBLleida), Lleida, Spain.
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12
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Agnollitto MISS, Leoni RF, Foss MP, Palaretti J, Cayres M, Pansarim V, Nather JC, Zotin MCZ, Ferrioli E, Lima NK, dos Santos AC, Moriguti JC. Influence of cerebral blood flow on volumetric loss related to Alzheimer's disease. Dement Neuropsychol 2023; 17:e20230004. [PMID: 37810430 PMCID: PMC10552620 DOI: 10.1590/1980-5764-dn-2023-0004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2023] [Revised: 04/04/2023] [Accepted: 05/24/2023] [Indexed: 10/10/2023] Open
Abstract
CBF measured with Arterial Spin Labeling (ASL) obtained by Magnetic Resonance Imaging (MRI) may become an important biomarker by showing changes in early stages of AD, such as in the prodromal stage of Mild Cognitive Impairment (MCI). Objective Verify the correlation between atrophy and CBF in patients with MCI and mild phase ADD, to demonstrate whether changes in CBF can be considered as vascular biomarkers in the diagnosis of the DA continuum. Methods 11 healthy volunteers, 16 MCI and 15 mild ADD were evaluated. Images of the brain were acquired, including CBF measured with Arterial Spin Labeling (ASL). Results When comparing MCI with control, a reduction in normalized CBF was observed in left posterior cingulate (estimated difference -0.38; p=0.02), right posterior cingulate (estimated difference -0.45; p=0.02) and right precuneus (estimated difference -0.28; p <0.01); also increase in normalized CBF in right upper temporal pole (estimated difference 0.22; p=0.03). It was also observed that in MCI, the smaller the gray matter volume, the smaller the CBF in the left posterior cingulate; as well as the greater the cerebrospinal fluid volume, consequent to the encephalic volumetric reduction associated with atrophy, the greater the CBF in the right superior temporal pole. When comparing controls, MCI and mild AD, in relation to the other variables, no other correlations were observed between CBF and atrophy. Conclusion In patients with MCI, the reduction of CBF in the left posterior cingulate correlated with gray matter atrophy, as well as the increase of CBF in the right upper temporal pole correlated with an increase in cerebrospinal fluid consequent to the encephalic volumetric reduction associated with atrophy, demonstrating the influence of CBF in AD related brain atrophy. These findings position CBF as a possible vascular biomarker for early-stage AD diagnoses.
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Affiliation(s)
| | - Renata Ferranti Leoni
- Universidade de São Paulo, Faculdade de Filosofia Ciências e Letras de Ribeirão Preto, Ribeirão Preto SP, Brazil
| | - Maria Paula Foss
- Universidade de São Paulo, Faculdade de Filosofia Ciências e Letras de Ribeirão Preto, Ribeirão Preto SP, Brazil
| | - Julia Palaretti
- Universidade de São Paulo, Faculdade de Filosofia Ciências e Letras de Ribeirão Preto, Ribeirão Preto SP, Brazil
| | - Marcela Cayres
- Universidade de São Paulo, Faculdade de Filosofia Ciências e Letras de Ribeirão Preto, Ribeirão Preto SP, Brazil
| | - Vitor Pansarim
- Universidade de São Paulo, Faculdade de Filosofia Ciências e Letras de Ribeirão Preto, Ribeirão Preto SP, Brazil
| | - Julio Cesar Nather
- Universidade de São Paulo, Faculdade de Medicina de Ribeirão Preto, Ribeirão Preto SP, Brazil
| | - Maria Clara Zanon Zotin
- Universidade de São Paulo, Faculdade de Medicina de Ribeirão Preto, Ribeirão Preto SP, Brazil
| | - Eduardo Ferrioli
- Universidade de São Paulo, Faculdade de Medicina de Ribeirão Preto, Ribeirão Preto SP, Brazil
| | - Nereida Kilza Lima
- Universidade de São Paulo, Faculdade de Medicina de Ribeirão Preto, Ribeirão Preto SP, Brazil
| | | | - Julio Cesar Moriguti
- Universidade de São Paulo, Faculdade de Medicina de Ribeirão Preto, Ribeirão Preto SP, Brazil
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Seitz-Holland J, Nägele FL, Kubicki M, Pasternak O, Cho KIK, Hough M, Mulert C, Shenton ME, Crow TJ, James ACD, Lyall AE. Shared and distinct white matter abnormalities in adolescent-onset schizophrenia and adolescent-onset psychotic bipolar disorder. Psychol Med 2023; 53:4707-4719. [PMID: 35796024 PMCID: PMC11119277 DOI: 10.1017/s003329172200160x] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
BACKGROUND While adolescent-onset schizophrenia (ADO-SCZ) and adolescent-onset bipolar disorder with psychosis (psychotic ADO-BPD) present a more severe clinical course than their adult forms, their pathophysiology is poorly understood. Here, we study potentially state- and trait-related white matter diffusion-weighted magnetic resonance imaging (dMRI) abnormalities along the adolescent-onset psychosis continuum to address this need. METHODS Forty-eight individuals with ADO-SCZ (20 female/28 male), 15 individuals with psychotic ADO-BPD (7 female/8 male), and 35 healthy controls (HCs, 18 female/17 male) underwent dMRI and clinical assessments. Maps of extracellular free-water (FW) and fractional anisotropy of cellular tissue (FAT) were compared between individuals with psychosis and HCs using tract-based spatial statistics and FSL's Randomise. FAT and FW values were extracted, averaged across all voxels that demonstrated group differences, and then utilized to test for the influence of age, medication, age of onset, duration of illness, symptom severity, and intelligence. RESULTS Individuals with adolescent-onset psychosis exhibited pronounced FW and FAT abnormalities compared to HCs. FAT reductions were spatially more widespread in ADO-SCZ. FW increases, however, were only present in psychotic ADO-BPD. In HCs, but not in individuals with adolescent-onset psychosis, FAT was positively related to age. CONCLUSIONS We observe evidence for cellular (FAT) and extracellular (FW) white matter abnormalities in adolescent-onset psychosis. Although cellular white matter abnormalities were more prominent in ADO-SCZ, such alterations may reflect a shared trait, i.e. neurodevelopmental pathology, present across the psychosis spectrum. Extracellular abnormalities were evident in psychotic ADO-BPD, potentially indicating a more dynamic, state-dependent brain reaction to psychosis.
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Affiliation(s)
- Johanna Seitz-Holland
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Felix L. Nägele
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
- Psychiatry Neuroimaging Branch, Department of Psychiatry and Psychotherapy, University Medical Center Hamburg-Eppendorf, University of Hamburg, Hamburg, Germany
| | - Marek Kubicki
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
| | - Ofer Pasternak
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
- Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
| | - Kang Ik K. Cho
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
| | - Morgan Hough
- SANE POWIC, University Department of Psychiatry, Warneford Hospital, Oxford, UK
- Highfield Unit, University Department of Psychiatry, Warneford Hospital, Oxford, UK
| | - Christoph Mulert
- Psychiatry Neuroimaging Branch, Department of Psychiatry and Psychotherapy, University Medical Center Hamburg-Eppendorf, University of Hamburg, Hamburg, Germany
- Centre for Psychiatry and Psychotherapy, Justus-Liebig-University, Giessen, Germany
| | - Martha E. Shenton
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
| | - Timothy J. Crow
- SANE POWIC, University Department of Psychiatry, Warneford Hospital, Oxford, UK
| | - Anthony C. D. James
- SANE POWIC, University Department of Psychiatry, Warneford Hospital, Oxford, UK
- Highfield Unit, University Department of Psychiatry, Warneford Hospital, Oxford, UK
| | - Amanda E. Lyall
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
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14
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Yang Y, Schilling K, Shashikumar N, Jasodanand V, Moore EE, Pechman KR, Bilgel M, Beason‐Held LL, An Y, Shafer A, Risacher SL, Landman BA, Jefferson AL, Saykin AJ, Resnick SM, Hohman TJ, Archer DB. White matter microstructural metrics are sensitively associated with clinical staging in Alzheimer's disease. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2023; 15:e12425. [PMID: 37213219 PMCID: PMC10192723 DOI: 10.1002/dad2.12425] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/18/2022] [Revised: 03/06/2023] [Accepted: 03/12/2023] [Indexed: 05/23/2023]
Abstract
Introduction White matter microstructure may be abnormal along the Alzheimer's disease (AD) continuum. Methods Diffusion magnetic resonance imaging (dMRI) data from the Alzheimer's Disease Neuroimaging Initiative (ADNI, n = 627), Baltimore Longitudinal Study of Aging (BLSA, n = 684), and Vanderbilt Memory & Aging Project (VMAP, n = 296) cohorts were free-water (FW) corrected and conventional, and FW-corrected microstructural metrics were quantified within 48 white matter tracts. Microstructural values were subsequently harmonized using the Longitudinal ComBat technique and inputted as independent variables to predict diagnosis (cognitively unimpaired [CU], mild cognitive impairment [MCI], AD). Models were adjusted for age, sex, race/ethnicity, education, apolipoprotein E (APOE) ε4 carrier status, and APOE ε2 carrier status. Results Conventional dMRI metrics were associated globally with diagnostic status; following FW correction, the FW metric itself exhibited global associations with diagnostic status, but intracellular metric associations were diminished. Discussion White matter microstructure is altered along the AD continuum. FW correction may provide further understanding of the white matter neurodegenerative process in AD. Highlights Longitudinal ComBat successfully harmonized large-scale diffusion magnetic resonance imaging (dMRI) metrics.Conventional dMRI metrics were globally sensitive to diagnostic status.Free-water (FW) correction mitigated intracellular associations with diagnostic status.The FW metric itself was globally sensitive to diagnostic status. Multivariate conventional and FW-corrected models may provide complementary information.
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Affiliation(s)
- Yisu Yang
- Vanderbilt Memory and Alzheimer's CenterVanderbilt University School of MedicineNashvilleTennesseeUSA
| | - Kurt Schilling
- Vanderbilt University Institute of Imaging ScienceVanderbilt University Medical CenterNashvilleTennesseeUSA
- Department of Radiology & Radiological SciencesVanderbilt University Medical CenterNashvilleTennesseeUSA
| | - Niranjana Shashikumar
- Vanderbilt Memory and Alzheimer's CenterVanderbilt University School of MedicineNashvilleTennesseeUSA
| | - Varuna Jasodanand
- Vanderbilt Memory and Alzheimer's CenterVanderbilt University School of MedicineNashvilleTennesseeUSA
| | - Elizabeth E. Moore
- Vanderbilt Memory and Alzheimer's CenterVanderbilt University School of MedicineNashvilleTennesseeUSA
| | - Kimberly R. Pechman
- Vanderbilt Memory and Alzheimer's CenterVanderbilt University School of MedicineNashvilleTennesseeUSA
| | - Murat Bilgel
- Laboratory of Behavioral NeuroscienceNational Institute on AgingNational Institutes of HealthBaltimoreMarylandUSA
| | - Lori L. Beason‐Held
- Laboratory of Behavioral NeuroscienceNational Institute on AgingNational Institutes of HealthBaltimoreMarylandUSA
| | - Yang An
- Laboratory of Behavioral NeuroscienceNational Institute on AgingNational Institutes of HealthBaltimoreMarylandUSA
| | - Andrea Shafer
- Laboratory of Behavioral NeuroscienceNational Institute on AgingNational Institutes of HealthBaltimoreMarylandUSA
| | - Shannon L. Risacher
- Indiana University School of MedicineIndianapolisIndianaUSA
- Indiana Alzheimer's Disease Research CenterIndianapolisIndianaUSA
| | - Bennett A. Landman
- Vanderbilt Memory and Alzheimer's CenterVanderbilt University School of MedicineNashvilleTennesseeUSA
- Vanderbilt University Institute of Imaging ScienceVanderbilt University Medical CenterNashvilleTennesseeUSA
- Department of Radiology & Radiological SciencesVanderbilt University Medical CenterNashvilleTennesseeUSA
- Department of Biomedical EngineeringVanderbilt UniversityNashvilleTennesseeUSA
- Department of Electrical and Computer EngineeringVanderbilt UniversityNashvilleTennesseeUSA
| | - Angela L. Jefferson
- Vanderbilt Memory and Alzheimer's CenterVanderbilt University School of MedicineNashvilleTennesseeUSA
- Vanderbilt Genetics InstituteVanderbilt University Medical CenterNashvilleTennesseeUSA
- Department of MedicineVanderbilt University Medical CenterNashvilleTennesseeUSA
| | - Andrew J. Saykin
- Indiana University School of MedicineIndianapolisIndianaUSA
- Indiana Alzheimer's Disease Research CenterIndianapolisIndianaUSA
| | - Susan M. Resnick
- Laboratory of Behavioral NeuroscienceNational Institute on AgingNational Institutes of HealthBaltimoreMarylandUSA
| | - Timothy J. Hohman
- Vanderbilt Memory and Alzheimer's CenterVanderbilt University School of MedicineNashvilleTennesseeUSA
- Vanderbilt Genetics InstituteVanderbilt University Medical CenterNashvilleTennesseeUSA
| | - Derek B. Archer
- Vanderbilt Memory and Alzheimer's CenterVanderbilt University School of MedicineNashvilleTennesseeUSA
- Vanderbilt Genetics InstituteVanderbilt University Medical CenterNashvilleTennesseeUSA
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15
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Chen Y, Wang Y, Song Z, Fan Y, Gao T, Tang X. Abnormal white matter changes in Alzheimer's disease based on diffusion tensor imaging: A systematic review. Ageing Res Rev 2023; 87:101911. [PMID: 36931328 DOI: 10.1016/j.arr.2023.101911] [Citation(s) in RCA: 15] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2022] [Revised: 03/01/2023] [Accepted: 03/13/2023] [Indexed: 03/17/2023]
Abstract
Alzheimer's disease (AD) is a degenerative neurological disease in elderly individuals. Subjective cognitive decline (SCD), mild cognitive impairment (MCI) and further development to dementia (d-AD) are considered to be major stages of the progressive pathological development of AD. Diffusion tensor imaging (DTI), one of the most important modalities of MRI, can describe the microstructure of white matter through its tensor model. It is widely used in understanding the central nervous system mechanism and finding appropriate potential biomarkers for the early stages of AD. Based on the multilevel analysis methods of DTI (voxelwise, fiberwise and networkwise), we summarized that AD patients mainly showed extensive microstructural damage, structural disconnection and topological abnormalities in the corpus callosum, fornix, and medial temporal lobe, including the hippocampus and cingulum. The diffusion features and structural connectomics of specific regions can provide information for the early assisted recognition of AD. The classification accuracy of SCD and normal controls can reach 92.68% at present. And due to the further changes of brain structure and function, the classification accuracy of MCI, d-AD and normal controls can reach more than 97%. Finally, we summarized the limitations of current DTI-based AD research and propose possible future research directions.
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Affiliation(s)
- Yu Chen
- School of Medical Technology, Beijing Institute of Technology, Beijing 100081, China
| | - Yifei Wang
- School of Life Science, Beijing Institute of Technology, Beijing 100081, China
| | - Zeyu Song
- School of Medical Technology, Beijing Institute of Technology, Beijing 100081, China
| | - Yingwei Fan
- School of Medical Technology, Beijing Institute of Technology, Beijing 100081, China
| | - Tianxin Gao
- School of Life Science, Beijing Institute of Technology, Beijing 100081, China.
| | - Xiaoying Tang
- School of Medical Technology, Beijing Institute of Technology, Beijing 100081, China; School of Life Science, Beijing Institute of Technology, Beijing 100081, China.
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Sharp FR, DeCarli CS, Jin LW, Zhan X. White matter injury, cholesterol dysmetabolism, and APP/Abeta dysmetabolism interact to produce Alzheimer's disease (AD) neuropathology: A hypothesis and review. Front Aging Neurosci 2023; 15:1096206. [PMID: 36845656 PMCID: PMC9950279 DOI: 10.3389/fnagi.2023.1096206] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2022] [Accepted: 01/30/2023] [Indexed: 02/12/2023] Open
Abstract
We postulate that myelin injury contributes to cholesterol release from myelin and cholesterol dysmetabolism which contributes to Abeta dysmetabolism, and combined with genetic and AD risk factors, leads to increased Abeta and amyloid plaques. Increased Abeta damages myelin to form a vicious injury cycle. Thus, white matter injury, cholesterol dysmetabolism and Abeta dysmetabolism interact to produce or worsen AD neuropathology. The amyloid cascade is the leading hypothesis for the cause of Alzheimer's disease (AD). The failure of clinical trials based on this hypothesis has raised other possibilities. Even with a possible new success (Lecanemab), it is not clear whether this is a cause or a result of the disease. With the discovery in 1993 that the apolipoprotein E type 4 allele (APOE4) was the major risk factor for sporadic, late-onset AD (LOAD), there has been increasing interest in cholesterol in AD since APOE is a major cholesterol transporter. Recent studies show that cholesterol metabolism is intricately involved with Abeta (Aβ)/amyloid transport and metabolism, with cholesterol down-regulating the Aβ LRP1 transporter and upregulating the Aβ RAGE receptor, both of which would increase brain Aβ. Moreover, manipulating cholesterol transport and metabolism in rodent AD models can ameliorate pathology and cognitive deficits, or worsen them depending upon the manipulation. Though white matter (WM) injury has been noted in AD brain since Alzheimer's initial observations, recent studies have shown abnormal white matter in every AD brain. Moreover, there is age-related WM injury in normal individuals that occurs earlier and is worse with the APOE4 genotype. Moreover, WM injury precedes formation of plaques and tangles in human Familial Alzheimer's disease (FAD) and precedes plaque formation in rodent AD models. Restoring WM in rodent AD models improves cognition without affecting AD pathology. Thus, we postulate that the amyloid cascade, cholesterol dysmetabolism and white matter injury interact to produce and/or worsen AD pathology. We further postulate that the primary initiating event could be related to any of the three, with age a major factor for WM injury, diet and APOE4 and other genes a factor for cholesterol dysmetabolism, and FAD and other genes for Abeta dysmetabolism.
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Affiliation(s)
| | - Charles S. DeCarli
- Department of Neurology, The MIND Institute, University of California at Davis Medical Center, Sacramento, CA, United States
| | - Lee-Way Jin
- Department of Neurology, The MIND Institute, University of California at Davis Medical Center, Sacramento, CA, United States
| | - Xinhua Zhan
- Department of Neurology, The MIND Institute, University of California at Davis Medical Center, Sacramento, CA, United States
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17
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Rogojin A, Gorbet DJ, Hawkins KM, Sergio LE. Differences in structural MRI and diffusion tensor imaging underlie visuomotor performance declines in older adults with an increased risk for Alzheimer's disease. Front Aging Neurosci 2023; 14:1054516. [PMID: 36711200 PMCID: PMC9877535 DOI: 10.3389/fnagi.2022.1054516] [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: 09/26/2022] [Accepted: 12/26/2022] [Indexed: 01/13/2023] Open
Abstract
Introduction Visuomotor impairments have been demonstrated in preclinical AD in individuals with a positive family history of dementia and APOE e4 carriers. Previous behavioral findings have also reported sex-differences in performance of visuomotor tasks involving a visual feedback reversal. The current study investigated the relationship between grey and white matter changes and non-standard visuomotor performance, as well as the effects of APOE status, family history of dementia, and sex on these brain-behavior relationships. Methods Older adults (n = 49) with no cognitive impairments completed non-standard visuomotor tasks involving a visual feedback reversal, plane-change, or combination of the two. Participants with a family history of dementia or who were APOE e4 carriers were considered at an increased risk for AD. T1-weighted anatomical scans were used to quantify grey matter volume and thickness, and diffusion tensor imaging measures were used to quantify white matter integrity. Results In APOE e4 carriers, grey and white matter structural measures were associated with visuomotor performance. Regression analyses showed that visuomotor deficits were predicted by lower grey matter thickness and volume in areas of the medial temporal lobe previously implicated in visuomotor control (entorhinal and parahippocampal cortices). This finding was replicated in the diffusion data, where regression analyses revealed that lower white matter integrity (lower FA, higher MD, higher RD, higher AxD) was a significant predictor of worse visuomotor performance in the forceps minor, forceps major, cingulum, inferior fronto-occipital fasciculus (IFOF), inferior longitudinal fasciculus (ILF), superior longitudinal fasciculus (SLF), and uncinate fasciculus (UF). Some of these tracts overlap with those important for visuomotor integration, namely the forceps minor, forceps major, SLF, IFOF, and ILF. Conclusion These findings suggest that measuring the dysfunction of brain networks underlying visuomotor control in early-stage AD may provide a novel behavioral target for dementia risk detection that is easily accessible, non-invasive, and cost-effective. The results also provide insight into the structural differences in inferior parietal lobule that may underlie previously reported sex-differences in performance of the visual feedback reversal task.
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Affiliation(s)
- Alica Rogojin
- School of Kinesiology and Health Science, York University, Toronto, ON, Canada,Centre for Vision Research, York University, Toronto, ON, Canada,Vision: Science to Applications (VISTA) Program, York University, Toronto, ON, Canada
| | - Diana J. Gorbet
- School of Kinesiology and Health Science, York University, Toronto, ON, Canada,Centre for Vision Research, York University, Toronto, ON, Canada
| | - Kara M. Hawkins
- School of Kinesiology and Health Science, York University, Toronto, ON, Canada
| | - Lauren E. Sergio
- School of Kinesiology and Health Science, York University, Toronto, ON, Canada,Centre for Vision Research, York University, Toronto, ON, Canada,*Correspondence: Lauren E. Sergio, ✉
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18
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Arezza NJJ, Santini T, Omer M, Baron CA. Estimation of free water-corrected microscopic fractional anisotropy. Front Neurosci 2023; 17:1074730. [PMID: 36960165 PMCID: PMC10027922 DOI: 10.3389/fnins.2023.1074730] [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: 10/19/2022] [Accepted: 02/16/2023] [Indexed: 03/09/2023] Open
Abstract
Water diffusion anisotropy MRI is sensitive to microstructural changes in the brain that are hallmarks of various neurological conditions. However, conventional metrics like fractional anisotropy are confounded by neuron fiber orientation dispersion, and the relatively low resolution of diffusion-weighted MRI gives rise to significant free water partial volume effects in many brain regions that are adjacent to cerebrospinal fluid. Microscopic fractional anisotropy is a recent metric that can report water diffusion anisotropy independent of neuron fiber orientation dispersion but is still susceptible to free water contamination. In this paper, we present a free water elimination (FWE) technique to estimate microscopic fractional anisotropy and other related diffusion indices by implementing a signal representation in which the MRI signal within a voxel is assumed to come from two distinct sources: a tissue compartment and a free water compartment. A two-part algorithm is proposed to rapidly fit a set of diffusion-weighted MRI volumes containing both linear- and spherical-tensor encoding acquisitions to the representation. Simulations and in vivo acquisitions with four healthy volunteers indicated that the FWE method may be a feasible technique for measuring microscopic fractional anisotropy and other indices with greater specificity to neural tissue characteristics than conventional methods.
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Affiliation(s)
- Nico J. J. Arezza
- Department of Medical Biophysics, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada
- Centre for Functional and Metabolic Mapping (CFMM), Robarts Research Institute, Western University, London, ON, Canada
- *Correspondence: Nico J. J. Arezza,
| | - Tales Santini
- Department of Medical Biophysics, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada
- Centre for Functional and Metabolic Mapping (CFMM), Robarts Research Institute, Western University, London, ON, Canada
| | - Mohammad Omer
- Department of Medical Biophysics, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada
| | - Corey A. Baron
- Department of Medical Biophysics, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada
- Centre for Functional and Metabolic Mapping (CFMM), Robarts Research Institute, Western University, London, ON, Canada
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19
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Maillard P, Hillmer LJ, Lu H, Arfanakis K, Gold BT, Bauer CE, Kramer JH, Staffaroni AM, Stables L, Wang DJ, Seshadri S, Satizabal CL, Beiser A, Habes M, Fornage M, Mosley TH, Rosenberg GA, Singh B, Singh H, Schwab K, Helmer KG, Greenberg SM, DeCarli C, Caprihan A. MRI free water as a biomarker for cognitive performance: Validation in the MarkVCID consortium. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2022; 14:e12362. [PMID: 36523847 PMCID: PMC9745638 DOI: 10.1002/dad2.12362] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/22/2022] [Revised: 08/11/2022] [Accepted: 08/29/2022] [Indexed: 12/15/2022]
Abstract
Introduction To evaluate the clinical validity of free water (FW), a diffusion tensor imaging-based biomarker kit proposed by the MarkVCID consortium, by investigating the association between mean FW (mFW) and executive function. Methods Baseline mFW was related to a baseline composite measure of executive function (EFC), adjusting for relevant covariates, in three MarkVCID sub-cohorts, and replicated in five, large, independent legacy cohorts. In addition, we tested whether baseline mFW predicted accelerated EFC score decline (mean follow-up time: 1.29 years). Results Higher mFW was found to be associated with lower EFC scores in MarkVCID legacy and sub-cohorts (p-values < 0.05). In addition, higher baseline mFW was associated significantly with accelerated decline in EFC scores (p = 0.0026). Discussion mFW is a sensitive biomarker of cognitive decline, providing a strong clinical rational for its use as a marker of white matter (WM) injury in multi-site observational studies and clinical trials of vascular cognitive impairment and dementia (VCID).
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Affiliation(s)
- Pauline Maillard
- Department of NeurologyUniversity of CaliforniaDavisCaliforniaUSA
| | - Laura J. Hillmer
- Department of NeurologyUniversity of New MexicoAlbuquerqueNew MexicoUSA
| | - Hanzhang Lu
- Department of RadiologyJohns Hopkins University School of MedicineBaltimoreMarylandUSA
| | - Konstantinos Arfanakis
- Department of Biomedical EngineeringIllinois Institute of TechnologyChicagoIllinoisUSA
- Rush Alzheimer's Disease CenterDepartment of Diagnostic Radiology and Nuclear MedicineRush University Medical CenterChicagoIllinoisUSA
| | - Brian T. Gold
- Department of NeuroscienceUniversity of KentuckyLexingtonKentuckyUSA
| | | | - Joel H. Kramer
- Department of NeurologyMemory and Aging CenterWeill Institute for NeurosciencesUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - Adam M. Staffaroni
- Department of NeurologyMemory and Aging CenterWeill Institute for NeurosciencesUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - Lara Stables
- Department of NeurologyMemory and Aging CenterWeill Institute for NeurosciencesUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - Danny J.J. Wang
- Laboratory of FMRI Technology (LOFT)Stevens Neuroimaging and Informatics InstituteKeck School of MedicineUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
| | - Sudha Seshadri
- Department of NeurologyBoston University School of MedicineBostonMassachusettsUSA
- Glenn Biggs Institute for Alzheimer's & Neurodegenerative DiseasesUniversity of Texas Health San AntonioSan AntonioTexasUSA
| | - Claudia L. Satizabal
- Department of NeurologyBoston University School of MedicineBostonMassachusettsUSA
- Glenn Biggs Institute for Alzheimer's & Neurodegenerative DiseasesUniversity of Texas Health San AntonioSan AntonioTexasUSA
- Department of Population Health SciencesUniversity of Texas Health San AntonioSan AntonioTexasUSA
| | - Alexa Beiser
- Department of NeurologyBoston University School of MedicineBostonMassachusettsUSA
- Department of BiostatisticsBoston University School of Public HealthBostonMassachusettsUSA
| | - Mohamad Habes
- Glenn Biggs Institute for Alzheimer's & Neurodegenerative DiseasesUniversity of Texas Health San AntonioSan AntonioTexasUSA
| | - Myriam Fornage
- Brown Foundation Institute of Molecular MedicineMcGovern Medical SchoolSchool of Public HealthThe University of Texas Health Science Center at HoustonHoustonTexasUSA
- Human Genetics CenterSchool of Public HealthThe University of Texas Health Science Center at HoustonHoustonTexasUSA
| | - Thomas H. Mosley
- MIND CenterUniversity of Mississippi Medical CenterJacksonMississippiUSA
| | - Gary A. Rosenberg
- Department of NeurologyUniversity of New MexicoAlbuquerqueNew MexicoUSA
| | - Baljeet Singh
- Department of NeurologyUniversity of CaliforniaDavisCaliforniaUSA
| | - Herpreet Singh
- Department of NeurologyMassachusetts General HospitalBostonMassachusettsUSA
| | - Kristin Schwab
- Department of NeurologyMassachusetts General HospitalBostonMassachusettsUSA
| | - Karl G. Helmer
- Department of RadiologyHarvard Medical SchoolBostonMassachusettsUSA
- Department of RadiologyMassachusetts General HospitalBostonMassachusettsUSA
| | | | - Charles DeCarli
- Department of NeurologyUniversity of CaliforniaDavisCaliforniaUSA
| | - Arvind Caprihan
- The Mind Research NetworkAlbuquerqueNew MexicoAlbuquerqueNew MexicoUSA
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20
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Giraldo DL, Smith RE, Struyfs H, Niemantsverdriet E, De Roeck E, Bjerke M, Engelborghs S, Romero E, Sijbers J, Jeurissen B. Investigating Tissue-Specific Abnormalities in Alzheimer's Disease with Multi-Shell Diffusion MRI. J Alzheimers Dis 2022; 90:1771-1791. [PMID: 36336929 PMCID: PMC9789487 DOI: 10.3233/jad-220551] [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] [Indexed: 12/12/2022]
Abstract
BACKGROUND Most studies using diffusion-weighted MRI (DW-MRI) in Alzheimer's disease (AD) have focused their analyses on white matter (WM) microstructural changes using the diffusion (kurtosis) tensor model. Although recent works have addressed some limitations of the tensor model, such as the representation of crossing fibers and partial volume effects with cerebrospinal fluid (CSF), the focus remains in modeling and analyzing the WM. OBJECTIVE In this work, we present a brain analysis approach for DW-MRI that disentangles multiple tissue compartments as well as micro- and macroscopic effects to investigate differences between groups of subjects in the AD continuum and controls. METHODS By means of the multi-tissue constrained spherical deconvolution of multi-shell DW-MRI, underlying brain tissue is modeled with a WM fiber orientation distribution function along with the contributions of gray matter (GM) and CSF to the diffusion signal. From this multi-tissue model, a set of measures capturing tissue diffusivity properties and morphology are extracted. Group differences were interrogated following fixel-, voxel-, and tensor-based morphometry approaches while including strong FWE control across multiple comparisons. RESULTS Abnormalities related to AD stages were detected in WM tracts including the splenium, cingulum, longitudinal fasciculi, and corticospinal tract. Changes in tissue composition were identified, particularly in the medial temporal lobe and superior longitudinal fasciculus. CONCLUSION This analysis framework constitutes a comprehensive approach allowing simultaneous macro and microscopic assessment of WM, GM, and CSF, from a single DW-MRI dataset.
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Affiliation(s)
- Diana L. Giraldo
- Computer Imaging and Medical Applications Laboratory - Cim@Lab, Universidad Nacional de Colombia, Bogotá, Colombia,imec-Vision Lab, Department of Physics, University of Antwerp, Antwerp, Belgium,μNEURO Research Center of Excellence, University of Antwerp, Antwerp, Belgium
| | - Robert E. Smith
- The Florey Institute of Neuroscience and Mental Health, Heidelberg, VIC, Australia,The Florey Department of Neuroscience and Mental Health, The University of Melbourne, Parkville, VIC, Australia
| | - Hanne Struyfs
- Reference Center for Biological Markers of Dementia (BIODEM), Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
| | - Ellis Niemantsverdriet
- Reference Center for Biological Markers of Dementia (BIODEM), Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
| | - Ellen De Roeck
- Reference Center for Biological Markers of Dementia (BIODEM), Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium,Department of Neurology and Memory Clinic, Hospital Network Antwerp (ZNA) Middelheim and Hoge Beuken, Antwerp, Belgium
| | - Maria Bjerke
- Reference Center for Biological Markers of Dementia (BIODEM), Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium,Laboratory of Neurochemistry, Department of Clinical Chemistry, and Center for Neurosciences (C4N), Universitair Ziekenhuis Brussel, Vrije Universiteit Brussel (VUB), Brussels, Belgium
| | - Sebastiaan Engelborghs
- Reference Center for Biological Markers of Dementia (BIODEM), Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium,Department of Neurology, and Center for Neurosciences (C4N), Universitair Ziekenhuis Brussel, Vrije Universiteit Brussel (VUB), Brussels, Belgium
| | - Eduardo Romero
- Computer Imaging and Medical Applications Laboratory - Cim@Lab, Universidad Nacional de Colombia, Bogotá, Colombia
| | - Jan Sijbers
- imec-Vision Lab, Department of Physics, University of Antwerp, Antwerp, Belgium,μNEURO Research Center of Excellence, University of Antwerp, Antwerp, Belgium
| | - Ben Jeurissen
- imec-Vision Lab, Department of Physics, University of Antwerp, Antwerp, Belgium,μNEURO Research Center of Excellence, University of Antwerp, Antwerp, Belgium,Lab for Equilibrium Investigations and Aerospace, Department of Physics, University of Antwerp, Antwerp, Belgium,Correspondence to: Ben Jeurissen, PhD, imec - Vision Lab, Department of Physics, University of Antwerp (CDE), Universiteitsplein 1, Building N, 2610 Antwerp, Belgium. Tel.: +32 3 265 24 77; E-mail:
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21
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Nakaya M, Sato N, Matsuda H, Maikusa N, Shigemoto Y, Sone D, Yamao T, Ogawa M, Kimura Y, Chiba E, Ohnishi M, Kato K, Okita K, Tsukamoto T, Yokoi Y, Sakata M, Abe O. Free water derived by multi-shell diffusion MRI reflects tau/neuroinflammatory pathology in Alzheimer's disease. ALZHEIMER'S & DEMENTIA (NEW YORK, N. Y.) 2022; 8:e12356. [PMID: 36304723 PMCID: PMC9594557 DOI: 10.1002/trc2.12356] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/18/2022] [Revised: 08/03/2022] [Accepted: 08/20/2022] [Indexed: 11/23/2022]
Abstract
INTRODUCTION Free-water (FW) imaging, a new analysis method for diffusion magnetic resonance imaging (MRI), can indicate neuroinflammation and degeneration. We evaluated FW in Alzheimer's disease (AD) using tau/inflammatory and amyloid positron emission tomography (PET). METHODS Seventy-one participants underwent multi-shell diffusion MRI, 18F-THK5351 PET, 11C-Pittsburgh compound B PET, and neuropsychological assessments. They were categorized into two groups: healthy controls (HCs) (n = 40) and AD-spectrum group (AD-S) (n = 31) using the Centiloid scale with amyloid PET and cognitive function. We analyzed group comparisons in FW and PET, correlations between FW and PET, and correlation analysis with neuropsychological scores. RESULTS In AD-S group, there was a significant positive correlation between FW and 18F-THK5351 in the temporal lobes. In addition, there were negative correlations between FW and cognitive function in the temporal lobe and cingulate gyrus, and negative correlations between 18F-THK5351 and cognitive function in the same regions. DISCUSSION FW imaging could be a biomarker for tau in AD alongside clinical correlations.
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Affiliation(s)
- Moto Nakaya
- Departmentof RadiologyNational Center Hospital of Neurology and PsychiatryOgawa‐HigashiKodairaTokyoJapan,Department of RadiologyGraduate School of MedicineUniversity of TokyoHongoBunkyo‐kuTokyoJapan
| | - Noriko Sato
- Departmentof RadiologyNational Center Hospital of Neurology and PsychiatryOgawa‐HigashiKodairaTokyoJapan
| | - Hiroshi Matsuda
- Departmentof RadiologyNational Center Hospital of Neurology and PsychiatryOgawa‐HigashiKodairaTokyoJapan,Drug Discovery and Cyclotron Research CenterSouthern TOHOKU Research Institute for NeuroscienceKoriyamaJapan
| | - Norihide Maikusa
- Departmentof RadiologyNational Center Hospital of Neurology and PsychiatryOgawa‐HigashiKodairaTokyoJapan
| | - Yoko Shigemoto
- Departmentof RadiologyNational Center Hospital of Neurology and PsychiatryOgawa‐HigashiKodairaTokyoJapan
| | - Daichi Sone
- Department of PsychiatryThe Jikei University School of MedicineTokyoJapan,Integrative Brain Imaging CenterNational Center of Neurology and PsychiatryTokyoJapan
| | - Tensho Yamao
- Department of Radiological SciencesSchool of Health SciencesFukushima Medical UniversityFukushimaJapan
| | - Masayo Ogawa
- Integrative Brain Imaging CenterNational Center of Neurology and PsychiatryTokyoJapan
| | - Yukio Kimura
- Departmentof RadiologyNational Center Hospital of Neurology and PsychiatryOgawa‐HigashiKodairaTokyoJapan
| | - Emiko Chiba
- Departmentof RadiologyNational Center Hospital of Neurology and PsychiatryOgawa‐HigashiKodairaTokyoJapan
| | - Masahiro Ohnishi
- Departmentof RadiologyNational Center Hospital of Neurology and PsychiatryOgawa‐HigashiKodairaTokyoJapan
| | - Koichi Kato
- Integrative Brain Imaging CenterNational Center of Neurology and PsychiatryTokyoJapan
| | - Kyoji Okita
- Integrative Brain Imaging CenterNational Center of Neurology and PsychiatryTokyoJapan
| | - Tadashi Tsukamoto
- Department of NeurologyNational Center of Neurology and PsychiatryKodairaTokyoJapan
| | - Yuma Yokoi
- Department of PsychiatryNational Center of Neurology and PsychiatryKodairaTokyoJapan
| | - Masuhiro Sakata
- Department of PsychiatryNational Center of Neurology and PsychiatryKodairaTokyoJapan
| | - Osamu Abe
- Department of RadiologyGraduate School of MedicineUniversity of TokyoHongoBunkyo‐kuTokyoJapan
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22
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Zhou J, Zhang P, Zhang B, Kong Y. White Matter Damage in Alzheimer's Disease: Contribution of Oligodendrocytes. Curr Alzheimer Res 2022; 19:CAR-EPUB-127137. [PMID: 36281858 PMCID: PMC9982194 DOI: 10.2174/1567205020666221021115321] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2022] [Revised: 09/15/2022] [Accepted: 09/23/2022] [Indexed: 11/22/2022]
Abstract
Alzheimer's disease (AD) is an age-related neurodegenerative disease, seriously influencing the quality of life and is a global health problem. Many factors affect the onset and development of AD, but specific mechanisms underlying the disease are unclear. Most studies investigating AD have focused on neurons and the gray matter in the central nervous system (CNS) but have not led to effective treatments. Recently, an increasing number of studies have focused on the white matter (WM). Magnetic resonance imaging and pathology studies have shown different degrees of WM abnormality during the progression of AD. Myelin sheaths, the main component of WM in the CNS, wrap and insulate axons to ensure conduction of the rapid action potential and axonal integrity. WM damage is characterized by progressive degeneration of axons, oligodendrocytes (OLs), and myelin in one or more areas of the CNS. The contributions of OLs to AD progression have, until recently, been largely overlooked. OLs are integral to myelin production, and the proliferation and differentiation of OLs, an early characteristic of AD, provide a promising target for preclinical diagnosis and treatment. However, despite some progress, the key mechanisms underlying the contributions of OLs to AD remain unclear. Given the heavy burden of medical treatment, a better understanding of the pathophysiological mechanisms underlying AD is vital. This review comprehensively summarize the results on WM abnormalities in AD and explores the relationship between OL progenitor cells and the pathogenesis of AD. Finally, the underlying molecular mechanisms and potential future research directions are discussed.
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Affiliation(s)
- Jinyu Zhou
- Department of Rehabilitation Medicine, The First Affiliated Hospital of Chongqing Medical University, Chongqing-400042, China
| | - Peng Zhang
- Department of Neurology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing-400010, China
| | - Bo Zhang
- Department of Basic Medicine, Chongqing Medical and Pharmaceutical College, Chongqing-401331, China
| | - Yuhan Kong
- Department of Rehabilitation Medicine, The First Affiliated Hospital of Chongqing Medical University, Chongqing-400042, China
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23
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Xiao D, Wang K, Theriault L, Charbel E. White matter integrity and key structures affected in Alzheimer's disease characterized by diffusion tensor imaging. Eur J Neurosci 2022; 56:5319-5331. [PMID: 36048971 DOI: 10.1111/ejn.15815] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2021] [Revised: 08/13/2022] [Accepted: 08/22/2022] [Indexed: 12/14/2022]
Abstract
White matter (WM) degeneration is suggested to predict the early signs of Alzheimer's disease (AD). The exact structural regions of brain circuitry involved are not known. This study aims to examine the associations between WM tract integrity, represented by the diffusion tensor imaging (DTI) measures, and AD diagnosis and to denote the key substrates in predicting AD. It included DTI measures of mean diffusivity (MD), fractional anisotropy, radial diffusivity and axial diffusivity of 18 main WM tracts in 84 non-Hispanic white participants from the Alzheimer's Disease Neuroimaging Initiative dataset. The multivariable general linear model was used to examine the association of AD diagnosis with each DTI measure adjusting for age, gender and education. The corpus callosum, fornix, cingulum hippocampus, uncinate fasciculus, sagittal striatum, left posterior thalamic radiation and fornix-stria terminalis showed significant increases in MD, radial and axial diffusivity, whereas the splenium of corpus callosum and the fornix showed significant decreases in fractional anisotropy among AD patients. Variable cluster analysis identified that hippocampus volume, mini-mental state examination (MMSE), cingulate gyrus/hippocampus, inferior fronto-occipital fasciculus and uncinate fasciculus are highly correlated in one cluster with MD measures. In conclusion, there were significant differences in DTI measures between the brain WM of AD patients and controls. Age is the risk factor associated with AD, not gender or education. Right cingulum gyrus and right uncinate fasciculus are particularly affected, correlating well with a cognitive test MMSE and MD measures for dementia in AD patients and could be a region of focus for AD staging.
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Affiliation(s)
- Danqing Xiao
- Department of STEM, School of Arts and Sciences, Regis College, Weston, Massachusetts, USA.,Neuroimaging Center, McLean Hospital, Belmont, Massachusetts, USA
| | - Kesheng Wang
- Department of Family and Community Health, School of Nursing, Health Sciences Center, West Virginia University, Morgantown, West Virginia, USA
| | - Luke Theriault
- Department of STEM, School of Arts and Sciences, Regis College, Weston, Massachusetts, USA.,School of Medicine, St. George's University, Saint George's, Grenada
| | - Elhelou Charbel
- Department of STEM, School of Arts and Sciences, Regis College, Weston, Massachusetts, USA
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24
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Kern KC, Wright CB, Leigh R. Global changes in diffusion tensor imaging during acute ischemic stroke and post-stroke cognitive performance. J Cereb Blood Flow Metab 2022; 42:1854-1866. [PMID: 35579236 PMCID: PMC9536124 DOI: 10.1177/0271678x221101644] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Post-stroke cognitive impairment is related to the effects of the acute stroke and pre-stroke brain health. We tested whether diffusion tensor imaging (DTI) can detect acute, global effects of stroke and predict post-stroke cognitive performance. Patients with stroke or TIA enrolled in a prospective cohort study were included if they had 1) at least one DTI acquisition at acute presentation, 24 hours, 5 days, or 30 days, and 2) follow-up testing with the telephone Montreal Cognitive Assessment (T-MoCA) at 30 and/or 90 days. A whole brain, white-matter skeleton excluding the infarct was used to derive mean global DTI measures for mean diffusivity (MD), fractional anisotropy (FA), free water (FW), FW-corrected MD (MDtissue), and FW-corrected FA (FAtissue). In 74 patients with ischemic stroke or TIA, there was a transient 4.2% increase in mean global FW between acute presentation and 24 hours (p = 0.024) that returned to initial values by 30 days (p = 0.03). Each acute global DTI measure was associated with 30-day T-MoCA score (n = 61, p = 0.0011-0.0076). Acute global FW, MD, FA and FAtissue were also associated with 90-day T-MoCA (n = 56, p = 0.0034-0.049). Transient global FW elevation likely reflects stroke-related interstitial edema, whereas other global DTI measures are more representative of pre-stroke brain health.
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Affiliation(s)
- Kyle C Kern
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Clinton B Wright
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Richard Leigh
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA.,Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
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Oestreich LKL, O'Sullivan MJ. Transdiagnostic In Vivo Magnetic Resonance Imaging Markers of Neuroinflammation. BIOLOGICAL PSYCHIATRY. COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2022; 7:638-658. [PMID: 35051668 DOI: 10.1016/j.bpsc.2022.01.003] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/07/2021] [Revised: 01/03/2022] [Accepted: 01/04/2022] [Indexed: 05/13/2023]
Abstract
Accumulating evidence suggests that inflammation is not limited to archetypal inflammatory diseases such as multiple sclerosis, but instead represents an intrinsic feature of many psychiatric and neurological disorders not typically classified as neuroinflammatory. A growing body of research suggests that neuroinflammation can be observed in early and prodromal stages of these disorders and, under certain circumstances, may lead to tissue damage. Traditional methods to assess neuroinflammation include serum or cerebrospinal fluid markers and positron emission tomography. These methods require invasive procedures or radiation exposure and lack the exquisite spatial resolution of magnetic resonance imaging (MRI). There is, therefore, an increasing interest in noninvasive neuroimaging tools to evaluate neuroinflammation reliably and with high specificity. While MRI does not provide information at a cellular level, it facilitates the characterization of several biophysical tissue properties that are closely linked to neuroinflammatory processes. The purpose of this review is to evaluate the potential of MRI as a noninvasive, accessible, and cost-effective technology to image neuroinflammation across neurological and psychiatric disorders. We provide an overview of current and developing MRI methods used to study different aspects of neuroinflammation and weigh their strengths and shortcomings. Novel MRI contrast agents are increasingly able to target inflammatory processes directly, therefore offering a high degree of specificity, particularly if used in conjunction with multitissue, biophysical diffusion MRI compartment models. The capability of these methods to characterize several aspects of the neuroinflammatory milieu will likely push MRI to the forefront of neuroimaging modalities used to characterize neuroinflammation transdiagnostically.
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Affiliation(s)
- Lena K L Oestreich
- Centre for Clinical Research, The University of Queensland, Brisbane, Queensland, Australia; Centre for Advanced Imaging, The University of Queensland, Brisbane, Queensland, Australia.
| | - Michael J O'Sullivan
- Centre for Clinical Research, The University of Queensland, Brisbane, Queensland, Australia; Institute of Molecular Bioscience, The University of Queensland, Brisbane, Queensland, Australia; Department of Neurology, Royal Brisbane and Women's Hospital, Brisbane, Queensland, Australia
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Improved diffusion parameter estimation by incorporating T 2 relaxation properties into the DKI-FWE model. Neuroimage 2022; 256:119219. [PMID: 35447354 DOI: 10.1016/j.neuroimage.2022.119219] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2021] [Revised: 04/08/2022] [Accepted: 04/14/2022] [Indexed: 11/23/2022] Open
Abstract
The free water elimination (FWE) model and its kurtosis variant (DKI-FWE) can separate tissue and free water signal contributions, thus providing tissue-specific diffusional information. However, a downside of these models is that the associated parameter estimation problem is ill-conditioned, necessitating the use of advanced estimation techniques that can potentially bias the parameter estimates. In this work, we propose the T2-DKI-FWE model that exploits the T2 relaxation properties of both compartments, thereby better conditioning the parameter estimation problem and providing, at the same time, an additional potential biomarker (the T2 of tissue). In our approach, the T2 of tissue is estimated as an unknown parameter, whereas the T2 of free water is assumed known a priori and fixed to a literature value (1573 ms). First, the error propagation of an erroneous assumption on the T2 of free water is studied. Next, the improved conditioning of T2-DKI-FWE compared to DKI-FWE is illustrated using the Cramér-Rao lower bound matrix. Finally, the performance of the T2-DKI-FWE model is compared to that of the DKI-FWE and T2-DKI models on both simulated and real datasets. The error due to a biased approximation of the T2 of free water was found to be relatively small in various diffusion metrics and for a broad range of erroneous assumptions on its underlying ground truth value. Compared to DKI-FWE, using the T2-DKI-FWE model is beneficial for the identifiability of the model parameters. Our results suggest that the T2-DKI-FWE model can achieve precise and accurate diffusion parameter estimates, through effective reduction of free water partial volume effects and by using a standard nonlinear least squares approach. In conclusion, incorporating T2 relaxation properties into the DKI-FWE model improves the conditioning of the model fitting, while only requiring an acquisition scheme with at least two different echo times.
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Ettehadi N, Kashyap P, Zhang X, Wang Y, Semanek D, Desai K, Guo J, Posner J, Laine AF. Automated Multiclass Artifact Detection in Diffusion MRI Volumes via 3D Residual Squeeze-and-Excitation Convolutional Neural Networks. Front Hum Neurosci 2022; 16:877326. [PMID: 35431841 PMCID: PMC9005752 DOI: 10.3389/fnhum.2022.877326] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2022] [Accepted: 03/07/2022] [Indexed: 12/14/2022] Open
Abstract
Diffusion MRI (dMRI) is widely used to investigate neuronal and structural development of brain. dMRI data is often contaminated with various types of artifacts. Hence, artifact type identification in dMRI volumes is an essential pre-processing step prior to carrying out any further analysis. Manual artifact identification amongst a large pool of dMRI data is a highly labor-intensive task. Previous attempts at automating this process are often limited to a binary classification ("poor" vs. "good" quality) of the dMRI volumes or focus on detecting a single type of artifact (e.g., motion, Eddy currents, etc.). In this work, we propose a deep learning-based automated multiclass artifact classifier for dMRI volumes. Our proposed framework operates in 2 steps. In the first step, the model predicts labels associated with 3D mutually exclusive collectively exhaustive (MECE) sub-volumes or "slabs" extracted from whole dMRI volumes. In the second step, through a voting process, the model outputs the artifact class present in the whole volume under investigation. We used two different datasets for training and evaluating our model. Specifically, we utilized 2,494 poor-quality dMRI volumes from the Adolescent Brain Cognitive Development (ABCD) and 4,226 from the Healthy Brain Network (HBN) dataset. Our results demonstrate accurate multiclass volume-level main artifact type prediction with 96.61 and 97.52% average accuracies on the ABCD and HBN test sets, respectively. Finally, in order to demonstrate the effectiveness of the proposed framework in dMRI pre-processing pipelines, we conducted a proof-of-concept dMRI analysis exploring the relationship between whole-brain fractional anisotropy (FA) and participant age, to test whether the use of our model improves the brain-age association.
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Affiliation(s)
- Nabil Ettehadi
- Heffner Biomedical Imaging Laboratory, Department of Biomedical Engineering, Columbia University, New York, NY, United States
| | - Pratik Kashyap
- Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC, United States
| | - Xuzhe Zhang
- Heffner Biomedical Imaging Laboratory, Department of Biomedical Engineering, Columbia University, New York, NY, United States
| | - Yun Wang
- Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC, United States
| | - David Semanek
- Department of Psychiatry, Columbia University Medical Center, New York, NY, United States
| | - Karan Desai
- Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC, United States
| | - Jia Guo
- Department of Psychiatry, Columbia University Medical Center, New York, NY, United States
- Zuckerman Institute, Columbia University, New York, NY, United States
| | - Jonathan Posner
- Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC, United States
| | - Andrew F. Laine
- Heffner Biomedical Imaging Laboratory, Department of Biomedical Engineering, Columbia University, New York, NY, United States
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Zhu Z, Zeng Q, Zhang R, Luo X, Li K, Xu X, Zhang M, Yang Y, Huang P. White Matter Free Water Outperforms Cerebral Small Vessel Disease Total Score in Predicting Cognitive Decline in Persons with Mild Cognitive Impairment. J Alzheimers Dis 2022; 86:741-751. [PMID: 35124653 DOI: 10.3233/jad-215541] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND Vascular pathology is an important partner of Alzheimer's disease (AD). Both total cerebral small vessel disease (CSVD) score and white matter free water (FW) are useful markers that could reflect cerebral vascular injury. OBJECTIVE We aim to investigate the efficacy of these two metrics in predicting cognitive declines in patients with mild cognitive impairment (MCI). METHODS We enrolled 126 MCI subjects with 3D T1-weighted images, fluid-attenuated inversion recovery images, T2 * images, diffusion tensor imaging images, cerebrospinal fluid biomarkers and neuropsychological tests from the Alzheimer's Disease Neuroimaging Initiative database. The total CSVD score and FW values were calculated. Simple and multiple linear regression analyses were applied to explore the association between vascular and cognitive impairments. Linear mixed effect models were constructed to investigate the efficacy of total CSVD score and FW on predicting cognitive decline. RESULTS FW was associated with baseline cognition and could predict the decline of executive and language functions in MCI subjects, while no association was found between total CSVD score and cognitive declines. CONCLUSION FW is a promising imaging marker for investigating the effect of CSVD on AD progression.
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Affiliation(s)
- Zili Zhu
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Shangcheng District, Hangzhou, China.,Department of Radiology, The First Affiliated Hospital of Wenzhou Medical University, Ouhai District, Wenzhou, China
| | - Qingze Zeng
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Shangcheng District, Hangzhou, China
| | - Ruiting Zhang
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Shangcheng District, Hangzhou, China
| | - Xiao Luo
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Shangcheng District, Hangzhou, China
| | - Kaicheng Li
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Shangcheng District, Hangzhou, China
| | - Xiaopei Xu
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Shangcheng District, Hangzhou, China
| | - Minming Zhang
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Shangcheng District, Hangzhou, China
| | - Yunjun Yang
- Department of Radiology, The First Affiliated Hospital of Wenzhou Medical University, Ouhai District, Wenzhou, China
| | - Peiyu Huang
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Shangcheng District, Hangzhou, China.,Department of Radiology, The First Affiliated Hospital of Wenzhou Medical University, Ouhai District, Wenzhou, China
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Chen JF, Wang F, Huang NX, Xiao L, Mei F. Oligodendrocytes and Myelin: Active players in Neurodegenerative brains? Dev Neurobiol 2022; 82:160-174. [PMID: 35081276 DOI: 10.1002/dneu.22867] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2021] [Revised: 01/18/2022] [Accepted: 01/19/2022] [Indexed: 11/10/2022]
Abstract
Oligodendrocytes (OLs) are a major type of glial cells in the central nervous system that generate multiple myelin sheaths to wrap axons. Myelin ensures fast and efficient propagation of action potentials along axons and supports neurons with nourishment. The decay of OLs and myelin has been implicated in age-related neurodegenerative diseases and these changes are generally considered as an inevitable result of neuron loss and axon degeneration. Noticeably, OLs and myelin undergo dynamic changes in healthy adult brains, that is, newly formed OLs are continuously added throughout life from the differentiation of oligodendrocyte precursor cells (OPCs) and the pre-existing myelin sheaths may undergo degeneration or remodeling. Increasing evidence has shown that changes in OLs and myelin are present in the early stages of neurodegenerative diseases, and even prior to significant neuronal loss and functional deficits. More importantly, oligodendroglia-specific manipulation, by either deletion of the disease gene or enhancement of myelin renewal, can alleviate functional impairments in neurodegenerative animal models. These findings underscore the possibility that OLs and myelin are not passively but actively involved in neurodegenerative diseases and may play an important role in modulating neuronal function and survival. In this review, we summarize recent work characterizing OL and myelin changes in both healthy and neurodegenerative brains and discuss the potential of targeting oligodendroglial cells in treating neurodegenerative diseases. This article is protected by copyright. All rights reserved.
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Affiliation(s)
- Jing-Fei Chen
- Brain and Intelligence Research Key Laboratory of Chongqing Education Commission, Department of Histology and Embryology, Third Military Medical University, Chongqing, 400038, China
| | - Fei Wang
- Brain and Intelligence Research Key Laboratory of Chongqing Education Commission, Department of Histology and Embryology, Third Military Medical University, Chongqing, 400038, China
| | - Nan-Xing Huang
- Brain and Intelligence Research Key Laboratory of Chongqing Education Commission, Department of Histology and Embryology, Third Military Medical University, Chongqing, 400038, China
| | - Lan Xiao
- Brain and Intelligence Research Key Laboratory of Chongqing Education Commission, Department of Histology and Embryology, Third Military Medical University, Chongqing, 400038, China
| | - Feng Mei
- Brain and Intelligence Research Key Laboratory of Chongqing Education Commission, Department of Histology and Embryology, Third Military Medical University, Chongqing, 400038, China
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30
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Bergamino M, Keeling EG, Baxter LC, Sisco NJ, Walsh RR, Stokes AM. Sex Differences in Alzheimer's Disease Revealed by Free-Water Diffusion Tensor Imaging and Voxel-Based Morphometry. J Alzheimers Dis 2022; 85:395-414. [PMID: 34842185 PMCID: PMC9015709 DOI: 10.3233/jad-210406] [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] [Indexed: 02/06/2023]
Abstract
BACKGROUND Imaging biomarkers are increasingly used in Alzheimer's disease (AD), and the identification of sex differences using neuroimaging may provide insight into disease heterogeneity, progression, and therapeutic targets. OBJECTIVE The purpose of this study was to investigate differences in grey matter (GM) volume and white matter (WM) microstructural disorganization between males and females with AD using voxel-based morphometry (VBM) and free-water-corrected diffusion tensor imaging (FW-DTI). METHODS Data were downloaded from the OASIS-3 database, including 158 healthy control (HC; 86 females) and 46 mild AD subjects (24 females). VBM and FW-DTI metrics (fractional anisotropy (FA), axial and radial diffusivities (AxD and RD, respectively), and FW index) were compared using effect size for the main effects of group, sex, and their interaction. RESULTS Significant group and sex differences were observed, with no significant interaction. Post-hoc comparisons showed that AD is associated with reduced GM volume, reduced FW-FA, and higher FW-RD/FW-index, consistent with neurodegeneration. Females in both groups exhibited higher GM volume than males, while FW-DTI metrics showed sex differences only in the AD group. Lower FW, lower FW-FA and higher FW-RD were observed in females relative to males in the AD group. CONCLUSION The combination of VBM and DTI may reveal complementary sex-specific changes in GM and WM associated with AD and aging. Sex differences in GM volume were observed for both groups, while FW-DTI metrics only showed significant sex differences in the AD group, suggesting that WM tract disorganization may play a differential role in AD pathophysiology between females and males.
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Affiliation(s)
| | - Elizabeth G. Keeling
- Neuroimaging Research, Barrow Neurological Institute,School of Life Sciences, Arizona State University
| | | | | | - Ryan R. Walsh
- Muhammad Ali Parkinson Center at Barrow Neurological
Institute
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31
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Lee KH, Kang KM. Association between Cerebral Small Vessel and Alzheimer’s Disease. JOURNAL OF THE KOREAN SOCIETY OF RADIOLOGY 2022; 83:486-507. [PMID: 36238505 PMCID: PMC9514514 DOI: 10.3348/jksr.2022.0041] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/05/2022] [Revised: 05/15/2022] [Accepted: 05/16/2022] [Indexed: 11/15/2022]
Abstract
뇌소혈관질환은 뇌 자기공명영상에서 흔히 관찰되는 혈관성 변화로 뇌백질 고신호강도, 뇌미세출혈, 열공성 경색, 혈관주위공간 등을 포함한다. 이러한 혈관성 변화가 알츠하이머병(Alzheimer’s disease; 이하 AD)의 발병 및 진행과 관련되어 있고, 대표 병리인 베타 아밀로이드 및 타우 단백의 침착과도 연관되어 있다는 증거들이 축적되고 있다. 혈관성 변화는 생활 습관 개선이나 약물 치료를 통해 예방과 개선이 가능하기 때문에 뇌소혈관질환과 AD 및 AD 생체지표의 관련성을 연구하는 것이 중요하다. 본 종설에서는 AD와 AD 생체지표에 대해 간략히 소개하고, AD와 혈관성 변화의 관련성에 대해 축적된 증거들을 제시한 다음, 뇌소혈관질환의 병태 생리와 MR 영상 소견을 설명하고자 한다. 또 뇌소혈관질환과 AD 진단의 위험도 및 AD 생체지표와의 관련성에 대한 기존 연구 결과들을 정리하고자 한다.
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Affiliation(s)
- Kyung Hoon Lee
- Department of Radiology, Seoul National University Hospital, Seoul, Korea
| | - Koung Mi Kang
- Department of Radiology, Seoul National University Hospital, Seoul, Korea
- Department of Radiology, Seoul National University College of Medicine, Seoul, Korea
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Chen H, Zhang Z, Jin M, Wang F. Prediction of dMRI signals with neural architecture search. J Neurosci Methods 2022; 365:109389. [PMID: 34687797 DOI: 10.1016/j.jneumeth.2021.109389] [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: 02/07/2021] [Revised: 10/11/2021] [Accepted: 10/17/2021] [Indexed: 11/27/2022]
Abstract
BACKGROUND There is growing interest in the neuroscience community in estimating and mapping microscopic properties of brain tissue non-invasively using magnetic resonance measurements. Machine learning methods are actively investigated to predict the signals measured in diffusion magnetic resonance imaging (dMRI). NEW METHOD We applied the neural architecture search (NAS) to train a recurrent neural network to generate a multilayer perceptron to predict the dMRI data of unknown signals based on the different acquisition parameters and training data. The search space of NAS is the number of neurons in each layer of the multilayer perceptron network. To our best knowledge, this is the first time to apply NAS to solve the dMRI signal prediction problem. RESULTS The experimental results demonstrate that the proposed NAS method can achieve fast training and predict dMRI signals accurately. For dMRI signals with four acquisition strategies of double diffusion encoding (DDE), double oscillating diffusion encoding (DODE), multi-shell and DSI-like pulsed gradient spin-echo (PGSE), the mean squared errors of the multilayer perceptron network designed by NAS are 0.0043, 0.0034, 0.0147 and 0.0199, respectively. COMPARISON WITH EXISTING METHOD(S) We also compared NAS with other machine learning prediction methods, such as support vector regression (SVR), decision tree (DT) and random forest (RF), k-nearest neighbors (KNN), adaboost regressor (AR), gradient boosting regressor (GBR) and extra-trees regressor (ET). NAS achieved the better prediction performance in most cases. CONCLUSION In this study, NAS was developed for the prediction of dMRI signals and could become an effective prediction tool.
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Affiliation(s)
- Haoze Chen
- School of Instrument and Electronics, North University of China, Taiyuan 030051, China; School of Instrument and Electronics, North University of China, Key Laboratory of Instrumentation Science & Dynamic Measurement (North University of China), Ministry of Education, Taiyuan 030051 China.
| | - Zhijie Zhang
- School of Instrument and Electronics, North University of China, Taiyuan 030051, China; School of Instrument and Electronics, North University of China, Key Laboratory of Instrumentation Science & Dynamic Measurement (North University of China), Ministry of Education, Taiyuan 030051 China.
| | - Mingwu Jin
- Department of Physics, University of Texas at Arlington, 502 Yates Street, Box 19059, Arlington, TX 76019, United States.
| | - Fengxiang Wang
- School of Instrument and Electronics, North University of China, Taiyuan 030051, China; School of Instrument and Electronics, North University of China, Key Laboratory of Instrumentation Science & Dynamic Measurement (North University of China), Ministry of Education, Taiyuan 030051 China
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Duan W, Sehrawat P, Zhou TD, Becker JT, Lopez OL, Gach HM, Dai W. Pattern of Altered Magnetization Transfer Rate in Alzheimer's Disease. J Alzheimers Dis 2022; 88:693-705. [PMID: 35694929 PMCID: PMC9382719 DOI: 10.3233/jad-220335] [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] [Indexed: 11/15/2022]
Abstract
BACKGROUND Biomarkers for Alzheimer's disease (AD) are crucial for early diagnosis and treatment monitoring once disease modifying therapies become available. OBJECTIVE This study aims to quantify the forward magnetization transfer rate (kfor) map from brain tissue water to macromolecular protons and use it to identify the brain regions with abnormal kfor in AD and AD progression. METHODS From the Cardiovascular Health Study (CHS) cognition study, magnetization transfer imaging (MTI) was acquired at baseline from 63 participants, including 20 normal controls (NC), 18 with mild cognitive impairment (MCI), and 25 AD subjects. Of those, 53 participants completed a follow-up MRI scan and were divided into four groups: 15 stable NC, 12 NC-to-MCI, 12 stable MCI, and 14 MCI/AD-to-AD subjects. kfor maps were compared across NC, MCI, and AD groups at baseline for the cross-sectional study and across four longitudinal groups for the longitudinal study. RESULTS We found a lower kfor in the frontal gray matter (GM), parietal GM, frontal corona radiata (CR) white matter (WM) tracts, frontal and parietal superior longitudinal fasciculus (SLF) WM tracts in AD relative to both NC and MCI. Further, we observed progressive decreases of kfor in the frontal GM, parietal GM, frontal and parietal CR WM tracts, and parietal SLF WM tracts in stable MCI. In the parietal GM, parietal CR WM tracts, and parietal SLF WM tracts, we found trend differences between MCI/AD-to-AD and stable NC. CONCLUSION Forward magnetization transfer rate is a promising biomarker for AD diagnosis and progression.
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Affiliation(s)
- Wenna Duan
- Department of Computer Science, State University of New York at Binghamton, Binghamton, NY
| | - Parshant Sehrawat
- Department of Computer Science, State University of New York at Binghamton, Binghamton, NY
| | - Tony D. Zhou
- Departments of Radiation Oncology, Radiology, and Biomedical Engineering, Washington University in St. Louis, Saint Louis, MO
| | - James T. Becker
- Department of Psychology, University of Pittsburgh, Pittsburgh, PA
- Department of Psychiatry and Neurology, University of Pittsburgh, Pittsburgh, PA
| | - Oscar L. Lopez
- Department of Psychiatry and Neurology, University of Pittsburgh, Pittsburgh, PA
| | - H. Michael Gach
- Departments of Radiation Oncology, Radiology, and Biomedical Engineering, Washington University in St. Louis, Saint Louis, MO
| | - Weiying Dai
- Department of Computer Science, State University of New York at Binghamton, Binghamton, NY
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Giannakopoulos P, Rodriguez C, Montandon ML, Garibotto V, Haller S, Herrmann FR. Personality Impact on Alzheimer's Disease-Signature and Vascular Imaging Markers: A PET-MRI Study. J Alzheimers Dis 2021; 85:1807-1817. [PMID: 34958019 DOI: 10.3233/jad-215062] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND Several studies postulated that personality is an independent determinant of cognitive trajectories in old age. OBJECTIVE This study explores the impact of personality on widely used Alzheimer's disease (AD) and vascular imaging markers. METHODS We examined the association between personality and three classical AD imaging markers (centiloid-based-amyloid load, MRI volumetry in hippocampus, and media temporal lobe atrophy), and two vascular MRI parameters (Fazekas score and number of cortical microbleeds) assessed at baseline and upon a 54-month-follow-up. Personality was assessed with the Neuroticism Extraversion Openness Personality Inventory-Revised. Regression models were used to identify predictors of imaging markers including sex, personality factors, presence of APOE ɛ4 allele and cognitive evolution over time. RESULTS Cortical GM volumes were negatively associated with higher levels of Conscientiousness both at baseline and follow-up. In contrast, higher scores of Openness were related to better preservation of left hippocampal volumes in these two time points and negatively associated with medial temporal atrophy at baseline. Amyloid load was not affected by personality factors. Cases with higher Extraversion scores displayed higher numbers of cortical microbleeds at baseline. CONCLUSION Personality impact on brain morphometry is detected only in some among the routinely used imaging markers. The most robust associations concern the positive role of high levels of Conscientiousness and Openness on AD-signature MRI markers. Higher extraversion levels are associated with increased vulnerability to cortical microbleeds pointing to the fact that the socially favorable traits may have a detrimental effect on brain integrity in old age.
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Affiliation(s)
- Panteleimon Giannakopoulos
- Department of Psychiatry, University of Geneva, Geneva, Switzerland.,Medical Direction, Geneva University Hospitals, Geneva, Switzerland
| | - Cristelle Rodriguez
- Department of Psychiatry, University of Geneva, Geneva, Switzerland.,Medical Direction, Geneva University Hospitals, Geneva, Switzerland
| | - Marie-Louise Montandon
- Department of Psychiatry, University of Geneva, Geneva, Switzerland.,Department of Rehabilitation and Geriatrics, Geneva University Hospitals and University of Geneva, Geneva, Switzerland
| | - Valentina Garibotto
- Department of Nuclear Medicine and Molecular Imaging, Diagnostic Department, Geneva University Hospitals and University of Geneva, Geneva, Switzerland
| | - Sven Haller
- CIMC - Centre d'Imagerie Médicale de Cornavin, Geneva, Switzerland.,Department of Surgical Sciences, Radiology, Uppsala University, Uppsala, Sweden.,Faculty of Medicine of the University of Geneva, Geneva, Switzerland.,Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - François R Herrmann
- Department of Rehabilitation and Geriatrics, Geneva University Hospitals and University of Geneva, Geneva, Switzerland
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Ettehadi N, Zhang X, Wang Y, Semanek D, Guo J, Posner J, Laine AF. Automatic Volumetric Quality Assessment of Diffusion MR Images via Convolutional Neural Network Classifiers. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2021; 2021:2756-2760. [PMID: 34891820 DOI: 10.1109/embc46164.2021.9630834] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Diffusion Tensor Imaging (DTI) is widely used to find brain biomarkers for various stages of brain structural and neuronal development. Processing DTI data requires a detailed Quality Assessment (QA) to detect artifactual volumes amongst a large pool of data. Since large cohorts of brain DTI data are often used in different studies, manual QA of such images is very labor-intensive. In this paper, a deep learning-based tool is developed for quick automatic QA of 3D raw diffusion MR images. We propose a 2-step framework to automate the process of binary (i.e., 'good' vs 'poor') quality classification of diffusion MR images. In the first step, using two separately trained 3D convolutional neural networks with different input sizes, quality labels for individual Regions of Interest (ROIs) sampled from whole DTI volumes are predicted. In the second step, two distinct novel voting systems are designed and fine-tuned to predict the quality label of whole brain DTI volumes using the individual ROI labels predicted in the previous step. Our results demonstrate the validity and practicality of our tool. Specifically, using a balanced dataset of 6,940 manually-labeled 3D DTI volumes from 85 unique subjects for training, validation, and testing, our model achieves 100% accuracy via one voting system, and 98% accuracy via another voting system on the same test set.
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Farrher E, Chiang CW, Cho KH, Grinberg F, Buschbeck RP, Chen MJ, Wu KJ, Wang Y, Huang SM, Abbas Z, Choi CH, Shah NJ, Kuo LW. Spatiotemporal characterisation of ischaemic lesions in transient stroke animal models using diffusion free water elimination and mapping MRI with echo time dependence. Neuroimage 2021; 244:118605. [PMID: 34592438 DOI: 10.1016/j.neuroimage.2021.118605] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2020] [Revised: 09/14/2021] [Accepted: 09/19/2021] [Indexed: 11/16/2022] Open
Abstract
BACKGROUND AND PURPOSE The excess fluid as a result of vasogenic oedema and the subsequent tissue cavitation obscure the microstructural characterisation of ischaemic tissue by conventional diffusion and relaxometry MRI. They lead to a pseudo-normalisation of the water diffusivity and transverse relaxation time maps in the subacute and chronic phases of stroke. Within the context of diffusion MRI, the free water elimination and mapping method (FWE) with echo time dependence has been proposed as a promising approach to measure the amount of free fluid in brain tissue robustly and to eliminate its biasing effect on other biomarkers. In this longitudinal study of transient middle cerebral artery occlusion (MCAo) in the rat brain, we investigated the use of FWE MRI with echo time dependence for the characterisation of the tissue microstructure and explored the potential of the free water fraction as a novel biomarker of ischaemic tissue condition. METHODS Adult rats received a transient MCAo. Diffusion- and transverse relaxation-weighted MRI experiments were performed longitudinally, pre-occlusion and on days 1, 3, 4, 5, 6, 7 and 10 after MCAo on four rats. Histology was performed for non-stroke and 1, 3 and 10 days after MCAo on three different rats at each time point. RESULTS The free water fraction was homogeneously increased in the ischaemic cortex one day after stroke. Between three and ten days after stroke, the core of the ischaemic tissue showed a progressive normalisation in the amount of free water, whereas the inner and outer border zones of the ischaemic cortex depicted a large, monotonous increase with time. The specific lesions in brain sections were verified by H&E and immunostaining. The tissue-specific diffusion and relaxometry MRI metrics in the ischaemic cortex were significantly different compared to their conventional counterpart. CONCLUSIONS Our results demonstrate that the free water fraction in FWE MRI with echo time dependence is a valuable biomarker, sensitive to the progressive degeneration in ischaemic tissue. We showed that part of the heterogeneity previously observed in conventional parameter maps can be accounted for by a heterogeneous distribution of free water in the tissue. Our results suggest that the temporal evolution of the free fluid fraction map at the core and inner border zone can be associated with the pathological changes linked to the evolution of vasogenic oedema. Namely, the homogeneous increase in free water one day after stroke and its tendency to normalise in the core of the ischaemic cortex starting three days after stroke, followed by a progressive increase in free water at the inner border zone from three to ten days after stroke. Finally, the monotonous increase in free fluid in the outer border zone of the cortex reflects the formation of fluid-filled cysts.
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Affiliation(s)
- Ezequiel Farrher
- Institute of Neuroscience and Medicine 4, INM-4, Forschungszentrum Jülich, Germany.
| | - Chia-Wen Chiang
- Institute of Biomedical Engineering and Nanomedicine, National Health Research Institutes, Miaoli, Taiwan
| | - Kuan-Hung Cho
- Institute of Biomedical Engineering and Nanomedicine, National Health Research Institutes, Miaoli, Taiwan
| | - Farida Grinberg
- Institute of Neuroscience and Medicine 4, INM-4, Forschungszentrum Jülich, Germany
| | - Richard P Buschbeck
- Institute of Neuroscience and Medicine 4, INM-4, Forschungszentrum Jülich, Germany
| | - Ming-Jye Chen
- Institute of Biomedical Engineering and Nanomedicine, National Health Research Institutes, Miaoli, Taiwan
| | - Kuo-Jen Wu
- Center for Neuropsychiatric Research, National Health Research Institutes, Miaoli, Taiwan
| | - Yun Wang
- Center for Neuropsychiatric Research, National Health Research Institutes, Miaoli, Taiwan
| | - Sheng-Min Huang
- Institute of Biomedical Engineering and Nanomedicine, National Health Research Institutes, Miaoli, Taiwan
| | - Zaheer Abbas
- Institute of Neuroscience and Medicine 4, INM-4, Forschungszentrum Jülich, Germany
| | - Chang-Hoon Choi
- Institute of Neuroscience and Medicine 4, INM-4, Forschungszentrum Jülich, Germany
| | - N Jon Shah
- Institute of Neuroscience and Medicine 4, INM-4, Forschungszentrum Jülich, Germany; Department of Neurology, RWTH Aachen University, Aachen, Germany; JARA - BRAIN - Translational Medicine, Aachen, Germany; Institute of Neuroscience and Medicine 11, INM-11, JARA, Forschungszentrum Jülich, Germany
| | - Li-Wei Kuo
- Institute of Biomedical Engineering and Nanomedicine, National Health Research Institutes, Miaoli, Taiwan; Institute of Medical Device and Imaging, National Taiwan University College of Medicine, Taipei, Taiwan.
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Seitz-Holland J, Lyons M, Kushan L, Lin A, Villalon-Reina JE, Cho KIK, Zhang F, Billah T, Bouix S, Kubicki M, Bearden CE, Pasternak O. Opposing white matter microstructure abnormalities in 22q11.2 deletion and duplication carriers. Transl Psychiatry 2021; 11:580. [PMID: 34759270 PMCID: PMC8581007 DOI: 10.1038/s41398-021-01703-1] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/01/2020] [Revised: 09/30/2021] [Accepted: 10/15/2021] [Indexed: 12/20/2022] Open
Abstract
Deletions and duplications at the 22q11.2 locus are associated with significant neurodevelopmental and psychiatric morbidity. Previous diffusion-weighted magnetic resonance imaging (MRI) studies in 22q11.2 deletion carriers (22q-del) found nonspecific white matter (WM) abnormalities, characterized by higher fractional anisotropy. Here, utilizing novel imaging and processing methods that allow separation of signal contribution from different tissue properties, we investigate whether higher anisotropy is driven by (1) extracellular changes, (2) selective degeneration of secondary fibers, or (3) volumetric differences. We further, for the first time, investigate WM microstructure in 22q11.2 duplication carriers (22q-dup). Multi-shell diffusion-weighted images were acquired from 26 22q-del, 19 22q-dup, and 18 healthy individuals (HC). Images were fitted with the free-water model to estimate anisotropy following extracellular free-water elimination and with the novel BedpostX model to estimate fractional volumes of primary and secondary fiber populations. Outcome measures were compared between groups, with and without correction for WM and cerebrospinal fluid (CSF) volumes. In 22q-del, anisotropy following free-water elimination remained significantly higher compared with controls. BedpostX did not identify selective secondary fiber degeneration. Higher anisotropy diminished when correcting for the higher CSF and lower WM volumes. In contrast, 22q-dup had lower anisotropy and greater extracellular space than HC, not influenced by macrostructural volumes. Our findings demonstrate opposing effects of reciprocal 22q11.2 copy-number variation on WM, which may arise from distinct pathologies. In 22q-del, microstructural abnormalities may be secondary to enlarged CSF space and more densely packed WM. In 22q-dup, we see evidence for demyelination similar to what is commonly observed in neuropsychiatric disorders.
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Affiliation(s)
- Johanna Seitz-Holland
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, 02115, MA, USA.
| | - Monica Lyons
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, 02115, MA, USA
| | - Leila Kushan
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California at Los Angeles, Los Angeles, 90095, CA, USA
| | - Amy Lin
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California at Los Angeles, Los Angeles, 90095, CA, USA
| | - Julio E Villalon-Reina
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California at Los Angeles, Los Angeles, 90095, CA, USA
| | - Kang Ik Kevin Cho
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, 02115, MA, USA
| | - Fan Zhang
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, 02115, MA, USA
| | - Tashrif Billah
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, 02115, MA, USA
| | - Sylvain Bouix
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, 02115, MA, USA
| | - Marek Kubicki
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, 02115, MA, USA
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, 02114, MA, USA
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, 02115, MA, USA
| | - Carrie E Bearden
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California at Los Angeles, Los Angeles, 90095, CA, USA
- Department of Psychology, University of California at Los Angeles, Los Angeles, 90095, CA, USA
| | - Ofer Pasternak
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, 02115, MA, USA
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, 02115, MA, USA
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Zheng M, Liu Z, Mana L, Qin G, Huang S, Gong Z, Tian M, He Y, Wang P. Shenzhiling oral liquid protects the myelin sheath against Alzheimer's disease through the PI3K/Akt-mTOR pathway. JOURNAL OF ETHNOPHARMACOLOGY 2021; 278:114264. [PMID: 34082015 DOI: 10.1016/j.jep.2021.114264] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/20/2020] [Revised: 05/22/2021] [Accepted: 05/27/2021] [Indexed: 06/12/2023]
Abstract
ETHNOPHARMACOLOGICAL RELEVANCE Shenzhiling oral liquid (SZL), a traditional Chinese medicine (TCM) compound, is firstly approved by the Chinese Food and Drug Administration (CFDA) for the treatment of mild to moderate Alzheimer's disease (AD). SZL is composed of ten Chinese herbs, and the precise therapy mechanism of its action to AD is far from fully understood. AIM OF THE STUDY The purpose of this study was to observe whether SZL is an effective therapy for amyloid-beta (Aβ)-induced myelin sheath and oligodendrocytes impairments. Notably, the primary aim was to elucidate whether and through what underlying mechanism SZL protects the myelin sheath through the PI3K/Akt-mTOR signaling pathway in Aβ42-induced OLN-93 oligodendrocytes in vitro. MATERIALS AND METHODS APP/PS1 mice were treated with SZL or donepezil continuously for three months, and Aβ42-induced oligodendrocyte OLN-93 cells mimicking AD pathogenesis of myelin sheath impairments were incubated with SZL-containing serum or with donepezil. LC-MS/MS was used to analysis the active components of SZL and SZL-containing serum. The Y maze test was administered after 3 months of treatment, and the hippocampal tissues of the APP/PS1 mice were then harvested for observation of myelin sheath and oligodendrocyte morphology. Cell viability and toxicity were assessed using CCK-8 and lactate dehydrogenase (LDH) release assays, and flow cytometry was used to measure cell apoptosis. The expression of the myelin proteins MBP, PLP, and MAG and that of Aβ42 and Aβ40 in the hippocampi of APP/PS1 mice were examined after SZL treatment. Simultaneously, the expression of p-PI3K, PI3K, p-Akt, Akt, p-mTOR, and mTOR were also examined. The expression of proteins, including CNPase, Olig2, NKX2.2, MBP, PLP, MAG, MOG, p-PI3K, PI3K, p-Akt, Akt, p-mTOR, and mTOR, was determined by immunofluorescence and Western blot, and the corresponding gene expression was evaluated by qPCR in Aβ42-induced OLN-93 oligodendrocytes. RESULTS LC-MS/MS detected a total of 126 active compounds in SZL-containing serum, including terpenoids, flavones, phenols, phenylpropanoids and phenolic acids. SZL treatment significantly improved memory and cognition in APP/PS1 mice and decreased the G-ratio of myelin sheath, alleviated myelin sheath and oligodendrocyte impairments by decreasing Aβ42 and Aβ40 accumulation and increasing the expression of myelin proteins MBP, PLP, MAG, and PI3K/Akt-mTOR signaling pathway associated protein in the hippocampi of APP/PS1 mice. SZL-containing serum also significantly reversed the OLN-93 cell injury induced by Aβ42 by increasing cell viability and enhanced the expression of MBP, PLP, MAG, and MOG. Meanwhile, SZL-containing serum facilitated the maturation and differentiation of oligodendrocytes in Aβ42-induced OLN-93 cells by heightening the expression of CNPase, Olig2 and NKX2.2. SZL-containing serum treatment also fostered the expression of p-PI3K, PI3K, p-Akt, Akt, p-mTOR, and mTOR, indicating an activating PI3K/Akt-mTOR signaling pathway in OLN-93 cells. Furthermore, the effects of SZL on myelin proteins, p-Akt, and p-mTOR were clearly inhibited by LY294002 and/or rapamycin, antagonists of PI3K and m-TOR, respectively. CONCLUSIONS Our findings indicate that SZL exhibits a neuroprotective effect on the myelin sheath by promoting the expression of myelin proteins during AD, and its mechanism of action is closely related to the activation of the PI3K/Akt-mTOR signaling pathway.
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Affiliation(s)
- Mingcui Zheng
- Key Laboratory of Chinese Internal Medicine of Ministry of Education and Beijing, Dongzhimen Hospital, Beijing University of Chinese Medicine (BUCM), Beijing, 100700, China; Key Laboratory of Pharmacology Dongzhimen Hospital (BUCM), State Administration of Traditional Chinese Medicine, Beijing, 100700, China.
| | - Zhenhong Liu
- Key Laboratory of Chinese Internal Medicine of Ministry of Education and Beijing, Dongzhimen Hospital, Beijing University of Chinese Medicine (BUCM), Beijing, 100700, China; Key Laboratory of Pharmacology Dongzhimen Hospital (BUCM), State Administration of Traditional Chinese Medicine, Beijing, 100700, China; Institute for Brain Disorders, Beijing University of Chinese Medicine (BUCM), Beijing, 100029, China.
| | - Lulu Mana
- Key Laboratory of Chinese Internal Medicine of Ministry of Education and Beijing, Dongzhimen Hospital, Beijing University of Chinese Medicine (BUCM), Beijing, 100700, China; Key Laboratory of Pharmacology Dongzhimen Hospital (BUCM), State Administration of Traditional Chinese Medicine, Beijing, 100700, China; Xinjiang Medical University, Urumqi, 830011, China.
| | - Gaofeng Qin
- Key Laboratory of Chinese Internal Medicine of Ministry of Education and Beijing, Dongzhimen Hospital, Beijing University of Chinese Medicine (BUCM), Beijing, 100700, China; Key Laboratory of Pharmacology Dongzhimen Hospital (BUCM), State Administration of Traditional Chinese Medicine, Beijing, 100700, China.
| | - Shuaiyang Huang
- Key Laboratory of Chinese Internal Medicine of Ministry of Education and Beijing, Dongzhimen Hospital, Beijing University of Chinese Medicine (BUCM), Beijing, 100700, China; Key Laboratory of Pharmacology Dongzhimen Hospital (BUCM), State Administration of Traditional Chinese Medicine, Beijing, 100700, China.
| | - Zhuoyan Gong
- Key Laboratory of Chinese Internal Medicine of Ministry of Education and Beijing, Dongzhimen Hospital, Beijing University of Chinese Medicine (BUCM), Beijing, 100700, China; Key Laboratory of Pharmacology Dongzhimen Hospital (BUCM), State Administration of Traditional Chinese Medicine, Beijing, 100700, China.
| | - Meijing Tian
- Key Laboratory of Chinese Internal Medicine of Ministry of Education and Beijing, Dongzhimen Hospital, Beijing University of Chinese Medicine (BUCM), Beijing, 100700, China; Key Laboratory of Pharmacology Dongzhimen Hospital (BUCM), State Administration of Traditional Chinese Medicine, Beijing, 100700, China.
| | - Yannan He
- Key Laboratory of Chinese Internal Medicine of Ministry of Education and Beijing, Dongzhimen Hospital, Beijing University of Chinese Medicine (BUCM), Beijing, 100700, China; Key Laboratory of Pharmacology Dongzhimen Hospital (BUCM), State Administration of Traditional Chinese Medicine, Beijing, 100700, China.
| | - Pengwen Wang
- Key Laboratory of Chinese Internal Medicine of Ministry of Education and Beijing, Dongzhimen Hospital, Beijing University of Chinese Medicine (BUCM), Beijing, 100700, China; Key Laboratory of Pharmacology Dongzhimen Hospital (BUCM), State Administration of Traditional Chinese Medicine, Beijing, 100700, China.
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The relationship between white matter microstructure and self-perceived cognitive decline. Neuroimage Clin 2021; 32:102794. [PMID: 34479171 PMCID: PMC8414539 DOI: 10.1016/j.nicl.2021.102794] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2021] [Revised: 08/12/2021] [Accepted: 08/13/2021] [Indexed: 11/20/2022]
Abstract
Subjective cognitive decline (SCD) is a perceived cognitive change prior to objective cognitive deficits, and although it is associated with Alzheimer's disease (AD) pathology, it likely results from multiple underlying pathologies. We investigated the association of white matter microstructure to SCD as a sensitive and early marker of cognitive decline and quantified the contribution of white matter microstructure separate from amyloidosis. Vanderbilt Memory & Aging Project participants with diffusion MRI data and a 45-item measure of SCD were included [n = 236, 137 cognitively unimpaired (CU), 99 with mild cognitive impairment (MCI), 73 ± 7 years, 37% female]. A subset of participants (64 CU, 40 MCI) underwent a fasting lumbar puncture for quantification of cerebrospinal fluid (CSF) amyloid-β(CSF Aβ42), total tau (CSF t-tau), and phosphorylated tau (CSF p-tau). Diffusion MRI data was post-processed using the free-water (FW) elimination technique, which allowed quantification of extracellular (FW) and intracellular compartment (fractional anisotropy, mean diffusivity, axial diffusivity, and radial diffusivity) microstructure. Microstructural values were quantified within 11 cognitive-related white matter tracts, including medial temporal lobe, frontal transcallosal, and fronto-parietal tracts using a region of interest approach. General linear modeling related each tract to SCD scores adjusting for age, sex, race/ethnicity, education, Framingham Stroke Risk Profile scores, APOE ε4 carrier status, diagnosis, Geriatric Depression Scale scores, hippocampal volume, and total white matter volume. Competitive models were analyzed to determine if white matter microstructural values have a unique role in SCD scores separate from CSF Aβ42. FW-corrected radial diffusivity (RDT) was related to SCD scores in 8 tracts: cingulum bundle, inferior longitudinal fasciculus, as well as inferior frontal gyrus (IFG) pars opercularis, IFG orbitalis, IFG pars triangularis, tapetum, medial frontal gyrus, and middle frontal gyrus transcallosal tracts. While CSF Aβ42 was related to SCD scores in our cohort (Radj2 = 39.03%; β = -0.231; p = 0.020), competitive models revealed that fornix and IFG pars triangularis transcallosal tract RDT contributed unique variance to SCD scores beyond CSF Aβ42 (Radj2 = 44.35% and Radj2 = 43.09%, respectively), with several other tract measures demonstrating nominal significance. All tracts which demonstrated nominal significance (in addition to covariates) were input into a backwards stepwise regression analysis. ILF RDT, fornix RDT, and UF FW were best associated with SCD scores (Radj2 = 46.69%; p = 6.37 × 10-12). Ultimately, we found that medial temporal lobe and frontal transcallosal tract microstructure is an important driver of SCD scores independent of early amyloid deposition. Our results highlight the potential importance of abnormal white matter diffusivity as an early contributor to cognitive decline. These results also highlight the value of incorporating multiple biomarkers to help disentangle the mechanistic heterogeneity of SCD as an early stage of cognitive decline.
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Cantero JL, Atienza M, Lage C, Zaborszky L, Vilaplana E, Lopez-Garcia S, Pozueta A, Rodriguez-Rodriguez E, Blesa R, Alcolea D, Lleo A, Sanchez-Juan P, Fortea J. Atrophy of Basal Forebrain Initiates with Tau Pathology in Individuals at Risk for Alzheimer's Disease. Cereb Cortex 2021; 30:2083-2098. [PMID: 31799623 DOI: 10.1093/cercor/bhz224] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2019] [Revised: 07/30/2019] [Accepted: 08/28/2019] [Indexed: 12/12/2022] Open
Abstract
Evidence suggests that the basal forebrain (BF) cholinergic system degenerates early in the course of Alzheimer's disease (AD), likely due to the vulnerability of BF cholinergic neurons to tau pathology. However, it remains unclear whether the presence of tauopathy is the only requirement for initiating the BF degeneration in asymptomatic subjects at risk for AD (AR-AD), and how BF structural deficits evolve from normal aging to preclinical and prodromal AD. Here, we provide human in vivo magnetic resonance imaging evidence supporting that abnormal cerebrospinal fluid levels of phosphorylated tau (T+) are selectively associated with bilateral volume loss of the nucleus basalis of Meynert (nbM, Ch4) in AR-AD individuals. Spreading of atrophy to medial septum and vertical limb of diagonal band Broca (Ch1-Ch2) occurred in both preclinical and prodromal AD. With the exception of A+, all groups revealed significant correlations between volume reduction of BF cholinergic compartments and atrophy of their innervated regions. Overall, these results support the central role played by tauopathy in instigating the nbM degeneration in AR-AD individuals and the necessary coexistence of both AD proteinopathies for spreading damage to larger BF territories, thus affecting the core of the BF cholinergic projection system.
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Affiliation(s)
- Jose L Cantero
- Laboratory of Functional Neuroscience, Pablo de Olavide University, 41013 Seville, Spain
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, 28031 Madrid, Spain
| | - Mercedes Atienza
- Laboratory of Functional Neuroscience, Pablo de Olavide University, 41013 Seville, Spain
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, 28031 Madrid, Spain
| | - Carmen Lage
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, 28031 Madrid, Spain
- Service of Neurology, IDIVAL, University Hospital Marques de Valdecilla, University of Cantabria, 39008 Santander, Spain
| | - Laszlo Zaborszky
- Center for Molecular and Behavioral Neuroscience, Rutgers, The State University of New Jersey, Newark, 07102 NJ, USA
| | - Eduard Vilaplana
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, 28031 Madrid, Spain
- Department of Neurology, Institut d'Investigacions Biomediques Sant Pau-Hospital Santa Creu i Sant Pau, Universitat Autonoma de Barcelona, 08025 Barcelona, Spain
| | - Sara Lopez-Garcia
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, 28031 Madrid, Spain
- Service of Neurology, IDIVAL, University Hospital Marques de Valdecilla, University of Cantabria, 39008 Santander, Spain
| | - Ana Pozueta
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, 28031 Madrid, Spain
- Service of Neurology, IDIVAL, University Hospital Marques de Valdecilla, University of Cantabria, 39008 Santander, Spain
| | - Eloy Rodriguez-Rodriguez
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, 28031 Madrid, Spain
- Service of Neurology, IDIVAL, University Hospital Marques de Valdecilla, University of Cantabria, 39008 Santander, Spain
| | - Rafael Blesa
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, 28031 Madrid, Spain
- Department of Neurology, Institut d'Investigacions Biomediques Sant Pau-Hospital Santa Creu i Sant Pau, Universitat Autonoma de Barcelona, 08025 Barcelona, Spain
| | - Daniel Alcolea
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, 28031 Madrid, Spain
- Department of Neurology, Institut d'Investigacions Biomediques Sant Pau-Hospital Santa Creu i Sant Pau, Universitat Autonoma de Barcelona, 08025 Barcelona, Spain
| | - Alberto Lleo
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, 28031 Madrid, Spain
- Department of Neurology, Institut d'Investigacions Biomediques Sant Pau-Hospital Santa Creu i Sant Pau, Universitat Autonoma de Barcelona, 08025 Barcelona, Spain
| | - Pascual Sanchez-Juan
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, 28031 Madrid, Spain
- Service of Neurology, IDIVAL, University Hospital Marques de Valdecilla, University of Cantabria, 39008 Santander, Spain
| | - Juan Fortea
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, 28031 Madrid, Spain
- Department of Neurology, Institut d'Investigacions Biomediques Sant Pau-Hospital Santa Creu i Sant Pau, Universitat Autonoma de Barcelona, 08025 Barcelona, Spain
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Baek MS, Lee MJ, Kim HK, Lyoo CH. Temporal trajectory of biofluid markers in Parkinson's disease. Sci Rep 2021; 11:14820. [PMID: 34285331 PMCID: PMC8292456 DOI: 10.1038/s41598-021-94345-8] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2021] [Accepted: 07/09/2021] [Indexed: 11/18/2022] Open
Abstract
Full dynamics of biofluid biomarkers have been unknown in patients with Parkinson’s disease (PD). Using data from 396 PD patients and 182 controls in the Parkinson's Progression Markers Initiative (PPMI) database, we estimated long-term temporal trajectories of CSF α-synuclein (α-syn), amyloid-β (Aβ), total tau (t-tau), phosphorylated tau (p-tau) and serum neurofilament light chain (NfL) by integrating function between the baseline levels and annual changes. At baseline, PD patients showed lower CSF α-syn, Aβ, t-tau and p-tau levels than those of the controls. In all PD patients, CSF α-syn and Aβ decreased in a negative exponential pattern before the onset of motor symptoms, whereas CSF t-tau and p-tau, and serum NfL increased. Patients with cognitive impairment exhibited faster decline of Aβ and α-syn and faster rise of t-tau, p-tau and NfL, when compared to those without. Similarly, low Aβ group showed earlier decline of α-syn, faster rise of t-tau, p-tau and NfL, and faster decline of cognitive performances, when compared to high Aβ group. Our results suggest that longitudinal changes in biomarkers can be influenced by cognitive impairment and Aβ burden at baseline. PD patients with Aβ pathology may be associated with early appearance of α-synuclein pathology, rapid progression of axonal degeneration and neurodegeneration, and consequently greater cognitive decline.
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Affiliation(s)
- Min Seok Baek
- Department of Neurology, Wonju Severance Christian Hospital, Yonsei University Wonju College of Medicine, Wonju, Gangwon do, Republic of Korea.,Department of Neurology, Gangnam Severance Hospital, Yonsei University College of Medicine, 20 Eonjuro 63-gil, Gangnam-gu, Seoul, Republic of Korea
| | - Myung Jun Lee
- Department of Neurology, Pusan National University Hospital, Pusan National University School of Medicine and Biomedical Research Institute, Gudeok-ro 179, Seo-gu, Busan, 49241, Republic of Korea.
| | - Han-Kyeol Kim
- Department of Neurology, Gangnam Severance Hospital, Yonsei University College of Medicine, 20 Eonjuro 63-gil, Gangnam-gu, Seoul, Republic of Korea
| | - Chul Hyoung Lyoo
- Department of Neurology, Gangnam Severance Hospital, Yonsei University College of Medicine, 20 Eonjuro 63-gil, Gangnam-gu, Seoul, Republic of Korea
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Oligodendrocyte progenitor cell fate and function in development and disease. Curr Opin Cell Biol 2021; 73:35-40. [PMID: 34153742 DOI: 10.1016/j.ceb.2021.05.003] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2021] [Accepted: 05/11/2021] [Indexed: 01/03/2023]
Abstract
Differentiation of oligodendrocyte progenitor cells (OPCs) into myelination-capable mature oligodendrocytes is essential for proper function of the central nervous system. OPCs are tissue-resident stem cells that populate all regions of the central nervous system and exist beyond development into adulthood. Disorders that lead to disruption of this critical cell state change cause devastating myelin diseases that are often associated with shortened life span. Recent findings have also provided support for a newly appreciated contribution of perturbed OPC differentiation to neurodegenerative and psychiatric diseases. These findings emphasize the need for a more complete understanding of OPC differentiation in health and disease. Here, we review recent molecular and functional findings revealing new roles of OPCs. It is our hope that this review provides readers with an enticing snapshot of current OPC research and highlights the potential of controlling OPC fate and function to treat diseases of the brain.
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Kamagata K, Andica C, Kato A, Saito Y, Uchida W, Hatano T, Lukies M, Ogawa T, Takeshige-Amano H, Akashi T, Hagiwara A, Fujita S, Aoki S. Diffusion Magnetic Resonance Imaging-Based Biomarkers for Neurodegenerative Diseases. Int J Mol Sci 2021; 22:ijms22105216. [PMID: 34069159 PMCID: PMC8155849 DOI: 10.3390/ijms22105216] [Citation(s) in RCA: 29] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2021] [Revised: 05/10/2021] [Accepted: 05/10/2021] [Indexed: 12/27/2022] Open
Abstract
There has been an increasing prevalence of neurodegenerative diseases with the rapid increase in aging societies worldwide. Biomarkers that can be used to detect pathological changes before the development of severe neuronal loss and consequently facilitate early intervention with disease-modifying therapeutic modalities are therefore urgently needed. Diffusion magnetic resonance imaging (MRI) is a promising tool that can be used to infer microstructural characteristics of the brain, such as microstructural integrity and complexity, as well as axonal density, order, and myelination, through the utilization of water molecules that are diffused within the tissue, with displacement at the micron scale. Diffusion tensor imaging is the most commonly used diffusion MRI technique to assess the pathophysiology of neurodegenerative diseases. However, diffusion tensor imaging has several limitations, and new technologies, including neurite orientation dispersion and density imaging, diffusion kurtosis imaging, and free-water imaging, have been recently developed as approaches to overcome these constraints. This review provides an overview of these technologies and their potential as biomarkers for the early diagnosis and disease progression of major neurodegenerative diseases.
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Affiliation(s)
- Koji Kamagata
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo 113-8421, Japan; (C.A.); (Y.S.); (W.U.); (T.A.); (A.H.); (S.F.); (S.A.)
- Correspondence:
| | - Christina Andica
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo 113-8421, Japan; (C.A.); (Y.S.); (W.U.); (T.A.); (A.H.); (S.F.); (S.A.)
| | - Ayumi Kato
- Department of Multidisciplinary Internal Medicine, Faculty of Medicine, Tottori University, Yonago 683-8504, Japan;
| | - Yuya Saito
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo 113-8421, Japan; (C.A.); (Y.S.); (W.U.); (T.A.); (A.H.); (S.F.); (S.A.)
| | - Wataru Uchida
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo 113-8421, Japan; (C.A.); (Y.S.); (W.U.); (T.A.); (A.H.); (S.F.); (S.A.)
| | - Taku Hatano
- Department of Neurology, Juntendo University School of Medicine, Tokyo 113-8421, Japan; (T.H.); (T.O.); (H.T.-A.)
| | - Matthew Lukies
- Department of Diagnostic and Interventional Radiology, Alfred Health, Melbourne, VIC 3004, Australia;
| | - Takashi Ogawa
- Department of Neurology, Juntendo University School of Medicine, Tokyo 113-8421, Japan; (T.H.); (T.O.); (H.T.-A.)
| | - Haruka Takeshige-Amano
- Department of Neurology, Juntendo University School of Medicine, Tokyo 113-8421, Japan; (T.H.); (T.O.); (H.T.-A.)
| | - Toshiaki Akashi
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo 113-8421, Japan; (C.A.); (Y.S.); (W.U.); (T.A.); (A.H.); (S.F.); (S.A.)
| | - Akifumi Hagiwara
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo 113-8421, Japan; (C.A.); (Y.S.); (W.U.); (T.A.); (A.H.); (S.F.); (S.A.)
| | - Shohei Fujita
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo 113-8421, Japan; (C.A.); (Y.S.); (W.U.); (T.A.); (A.H.); (S.F.); (S.A.)
| | - Shigeki Aoki
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo 113-8421, Japan; (C.A.); (Y.S.); (W.U.); (T.A.); (A.H.); (S.F.); (S.A.)
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44
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A longitudinal analysis of brain extracellular free water in HIV infected individuals. Sci Rep 2021; 11:8273. [PMID: 33859326 PMCID: PMC8050285 DOI: 10.1038/s41598-021-87801-y] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2020] [Accepted: 04/05/2021] [Indexed: 11/13/2022] Open
Abstract
Initiation of combination antiretroviral therapy (cART) reduces inflammation in HIV-infected (HIV+) individuals. Recent studies demonstrated that diffusion MRI based extracellular free water (FW) modeling can be sensitive to neuroinflammation. Here, we investigate the FW in HIV-infection, its temporal evolution, and its association with blood markers, and cognitive scores. Using 96 age-matched participants, we found that FW was significantly elevated in grey and white matter in cART-naïve HIV+ compared to HIV-uninfected (HIV−) individuals at baseline. These increased FW values positively correlated with neurofilament light chain (NfL) and negatively correlated with CD4 counts. FW in grey and white matter, as well as NfL decreased in the HIV+ after 12 weeks of cART treatment. No significant FW differences were noted between the HIV+ and HIV− cohorts at 1 and 2-year follow-up. Results suggest that FW elevation in cART-naïve HIV+ participants is likely due to neuroinflammation. The correlation between FW and NfL, and the improvement in both FW and NfL after 12 weeks of cART treatment further reinforces this conclusion. The longer follow-up at 1 and 2 years suggests that cART helped control neuroinflammation as inferred by FW. Therefore, FW could be used as a biomarker to monitor HIV-associated neuroinflammation.
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Bergamino M, Walsh RR, Stokes AM. Free-water diffusion tensor imaging improves the accuracy and sensitivity of white matter analysis in Alzheimer's disease. Sci Rep 2021; 11:6990. [PMID: 33772083 PMCID: PMC7998032 DOI: 10.1038/s41598-021-86505-7] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2020] [Accepted: 03/09/2021] [Indexed: 12/11/2022] Open
Abstract
Magnetic resonance imaging (MRI) based diffusion tensor imaging (DTI) can assess white matter (WM) integrity through several metrics, such as fractional anisotropy (FA), axial/radial diffusivities (AxD/RD), and mode of anisotropy (MA). Standard DTI is susceptible to the effects of extracellular free water (FW), which can be removed using an advanced free-water DTI (FW-DTI) model. The purpose of this study was to compare standard and FW-DTI metrics in the context of Alzheimer’s disease (AD). Data were obtained from the Open Access Series of Imaging Studies (OASIS-3) database and included both healthy controls (HC) and mild-to-moderate AD. With both standard and FW-DTI, decreased FA was found in AD, mainly in the corpus callosum and fornix, consistent with neurodegenerative mechanisms. Widespread higher AxD and RD were observed with standard DTI; however, the FW index, indicative of AD-associated neurodegeneration, was significantly elevated in these regions in AD, highlighting the potential impact of free water contributions on standard DTI in neurodegenerative pathologies. Using FW-DTI, improved consistency was observed in FA, AxD, and RD, and the complementary FW index was higher in the AD group as expected. With both standard and FW-DTI, higher values of MA coupled with higher values of FA in AD were found in the anterior thalamic radiation and cortico-spinal tract, most likely arising from a loss of crossing fibers. In conclusion, FW-DTI better reflects the underlying pathology of AD and improves the accuracy of DTI metrics related to WM integrity in Alzheimer’s disease.
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Affiliation(s)
- Maurizio Bergamino
- Division of Neuroimaging Research, Barrow Neurological Institute, Phoenix, AZ, 85013, USA
| | - Ryan R Walsh
- Muhammad Ali Parkinson Center, Barrow Neurological Institute, Phoenix, AZ, 85013, USA
| | - Ashley M Stokes
- Division of Neuroimaging Research, Barrow Neurological Institute, Phoenix, AZ, 85013, USA.
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46
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Kim GW, Park SE, Park K, Jeong GW. White Matter Connectivity and Gray Matter Volume Changes Following Donepezil Treatment in Patients With Mild Cognitive Impairment: A Preliminary Study Using Probabilistic Tractography. Front Aging Neurosci 2021; 12:604940. [PMID: 33796017 PMCID: PMC8007874 DOI: 10.3389/fnagi.2020.604940] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2020] [Accepted: 12/21/2020] [Indexed: 11/13/2022] Open
Abstract
The donepezil treatment is associated with improved cognitive performance in patients with mild cognitive impairment (MCI), and its clinical effectiveness is well-known. However, the impact of the donepezil treatment on the enhanced white matter connectivity in MCI is still unclear. The purpose of this study was to evaluate the thalamo-cortical white matter (WM) connectivity and cortical thickness and gray matter (GM) volume changes in the cortical regions following donepezil treatment in patients with MCI using probabilistic tractography and voxel-based morphometry. Patients with MCI underwent magnetic resonance examinations before and after 6-month donepezil treatment. Compared with healthy controls, patients with MCI showed decreased WM connectivity of the thalamo-lateral prefrontal cortex, as well as reduced thickness in the medial/lateral orbitofrontal cortices (p < 0.05). The thalamo-lateral temporal cortex connectivity in patients with MCI was negatively correlated with Alzheimer's disease assessment scale-cognitive subscale (ADAS-cog) (r = −0.76, p = 0.01). The average score of the Korean version of the mini-mental state examination (K-MMSE) in patients with MCI was improved by 7.9% after 6-months of donepezil treatment. However, the patterns of WM connectivity and brain volume change in untreated and treated patients were not significantly different from each other, resulting from multiple comparison corrections. These findings will be valuable in understanding the neurophysiopathological mechanism on MCI as a prodromal phase of Alzheimer's disease in connection with brain functional connectivity and morphometric change.
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Affiliation(s)
- Gwang-Won Kim
- Advanced Institute of Aging Science, Chonnam National University, Gwangju, South Korea.,Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
| | - Shin-Eui Park
- Advanced Institute of Aging Science, Chonnam National University, Gwangju, South Korea
| | - Kwangsung Park
- Advanced Institute of Aging Science, Chonnam National University, Gwangju, South Korea.,Department of Urology, Chonnam National University Hospital, Chonnam National University Medical School, Gwangju, South Korea
| | - Gwang-Woo Jeong
- Department of Radiology, Chonnam National University Hospital, Chonnam National University Medical School, Gwangju, South Korea
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47
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Duncan GJ, Simkins TJ, Emery B. Neuron-Oligodendrocyte Interactions in the Structure and Integrity of Axons. Front Cell Dev Biol 2021; 9:653101. [PMID: 33763430 PMCID: PMC7982542 DOI: 10.3389/fcell.2021.653101] [Citation(s) in RCA: 46] [Impact Index Per Article: 15.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2021] [Accepted: 02/15/2021] [Indexed: 12/12/2022] Open
Abstract
The myelination of axons by oligodendrocytes is a highly complex cell-to-cell interaction. Oligodendrocytes and axons have a reciprocal signaling relationship in which oligodendrocytes receive cues from axons that direct their myelination, and oligodendrocytes subsequently shape axonal structure and conduction. Oligodendrocytes are necessary for the maturation of excitatory domains on the axon including nodes of Ranvier, help buffer potassium, and support neuronal energy metabolism. Disruption of the oligodendrocyte-axon unit in traumatic injuries, Alzheimer's disease and demyelinating diseases such as multiple sclerosis results in axonal dysfunction and can culminate in neurodegeneration. In this review, we discuss the mechanisms by which demyelination and loss of oligodendrocytes compromise axons. We highlight the intra-axonal cascades initiated by demyelination that can result in irreversible axonal damage. Both the restoration of oligodendrocyte myelination or neuroprotective therapies targeting these intra-axonal cascades are likely to have therapeutic potential in disorders in which oligodendrocyte support of axons is disrupted.
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Affiliation(s)
- Greg J Duncan
- Jungers Center for Neurosciences Research, Department of Neurology, Oregon Health & Science University, Portland, OR, United States
| | - Tyrell J Simkins
- Jungers Center for Neurosciences Research, Department of Neurology, Oregon Health & Science University, Portland, OR, United States.,Vollum Institute, Oregon Health & Science University, Portland, OR, United States.,Department of Neurology, VA Portland Health Care System, Portland, OR, United States
| | - Ben Emery
- Jungers Center for Neurosciences Research, Department of Neurology, Oregon Health & Science University, Portland, OR, United States
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48
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Huang P, Zhang R, Jiaerken Y, Wang S, Hong H, Yu W, Lian C, Li K, Zeng Q, Luo X, Yu X, Wu X, Xu X, Zhang M. White Matter Free Water is a Composite Marker of Cerebral Small Vessel Degeneration. Transl Stroke Res 2021; 13:56-64. [PMID: 33634379 DOI: 10.1007/s12975-021-00899-0] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2020] [Revised: 02/13/2021] [Accepted: 02/16/2021] [Indexed: 11/28/2022]
Abstract
To investigate the association between white matter free water (FW) and common imaging markers of cerebral small vessel diseases (CSVD) in two groups of subjects with different clinical status. One hundred and forty-four community subjects (mean age 60.5) and 84 CSVD subjects (mean age 61.2) were retrospectively included in the present study. All subjects received multi-modal magnetic resonance imaging and clinical assessments. The association between white matter FW and common CSVD imaging markers, including white matter hyperintensities (WMH), dilated perivascular space (PVS), lacunes, and microbleeds, were assessed using simple and multiple regression analysis. The association between FW and cognitive scores were also investigated. White matter FW was positively associated with WMH volume (β = 0.270, p = 0.001), PVS volume (β = 0.290, p < 0.001), number of microbleeds (β = 0.148, p = 0.043), and age (β = 0.170, p = 0.036) in the community cohort. In the CSVD cohort, FW was positively associated with WMH volume (β = 0.648, p < 0.001), PVS score (β = 0.224, p < 0.001), number of lacunes (β = 0.140, p = 0.046), and sex (β = 0.125, p = 0.036). The associations between FW and cognitive scores were stronger than conventional CSVD markers in both datasets. White matter FW is a potential composite marker that can sensitively detect cerebral small vessel degeneration and also reflect cognitive impairments.
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Affiliation(s)
- Peiyu Huang
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310000, China.
| | - Ruiting Zhang
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310000, China
| | - Yeerfan Jiaerken
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310000, China
| | - Shuyue Wang
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310000, China
| | - Hui Hong
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310000, China
| | - Wenke Yu
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310000, China
| | - Chunfeng Lian
- Department of Radiology and BRIC, University of North Carolina, Chapel Hill, NC, 27599, USA
| | - Kaicheng Li
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310000, China
| | - Qingze Zeng
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310000, China
| | - Xiao Luo
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310000, China
| | - Xinfeng Yu
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310000, China
| | - Xiao Wu
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310000, China
| | - Xiaopei Xu
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310000, China
| | - Minming Zhang
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310000, China.
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van Oostveen WM, de Lange ECM. Imaging Techniques in Alzheimer's Disease: A Review of Applications in Early Diagnosis and Longitudinal Monitoring. Int J Mol Sci 2021; 22:ijms22042110. [PMID: 33672696 PMCID: PMC7924338 DOI: 10.3390/ijms22042110] [Citation(s) in RCA: 59] [Impact Index Per Article: 19.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2020] [Revised: 02/15/2021] [Accepted: 02/16/2021] [Indexed: 12/20/2022] Open
Abstract
BACKGROUND Alzheimer's disease (AD) is a progressive neurodegenerative disorder affecting many individuals worldwide with no effective treatment to date. AD is characterized by the formation of senile plaques and neurofibrillary tangles, followed by neurodegeneration, which leads to cognitive decline and eventually death. INTRODUCTION In AD, pathological changes occur many years before disease onset. Since disease-modifying therapies may be the most beneficial in the early stages of AD, biomarkers for the early diagnosis and longitudinal monitoring of disease progression are essential. Multiple imaging techniques with associated biomarkers are used to identify and monitor AD. AIM In this review, we discuss the contemporary early diagnosis and longitudinal monitoring of AD with imaging techniques regarding their diagnostic utility, benefits and limitations. Additionally, novel techniques, applications and biomarkers for AD research are assessed. FINDINGS Reduced hippocampal volume is a biomarker for neurodegeneration, but atrophy is not an AD-specific measure. Hypometabolism in temporoparietal regions is seen as a biomarker for AD. However, glucose uptake reflects astrocyte function rather than neuronal function. Amyloid-β (Aβ) is the earliest hallmark of AD and can be measured with positron emission tomography (PET), but Aβ accumulation stagnates as disease progresses. Therefore, Aβ may not be a suitable biomarker for monitoring disease progression. The measurement of tau accumulation with PET radiotracers exhibited promising results in both early diagnosis and longitudinal monitoring, but large-scale validation of these radiotracers is required. The implementation of new processing techniques, applications of other imaging techniques and novel biomarkers can contribute to understanding AD and finding a cure. CONCLUSIONS Several biomarkers are proposed for the early diagnosis and longitudinal monitoring of AD with imaging techniques, but all these biomarkers have their limitations regarding specificity, reliability and sensitivity. Future perspectives. Future research should focus on expanding the employment of imaging techniques and identifying novel biomarkers that reflect AD pathology in the earliest stages.
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Affiliation(s)
- Wieke M. van Oostveen
- Faculty of Science, Leiden University, Einsteinweg 55, 2333 CC Leiden, The Netherlands;
| | - Elizabeth C. M. de Lange
- Division of Systems Biomedicine and Pharmacology, Leiden Academic Centre of Drug Research, Leiden University, Einsteinweg 55, 2333 CC Leiden, The Netherlands
- Correspondence: ; Tel.: +31-71-527-6330
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50
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Golub M, Neto Henriques R, Gouveia Nunes R. Free-water DTI estimates from single b-value data might seem plausible but must be interpreted with care. Magn Reson Med 2020; 85:2537-2551. [PMID: 33270935 DOI: 10.1002/mrm.28599] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2020] [Revised: 10/19/2020] [Accepted: 10/23/2020] [Indexed: 01/18/2023]
Abstract
PURPOSE Free-water elimination DTI (FWE-DTI) has been used widely to distinguish increases of free-water partial-volume effects from tissue's diffusion in healthy aging and degenerative diseases. Because the FWE-DTI fitting is only well-posed for multishell acquisitions, a regularized gradient descent (RGD) method was proposed to enable application to single-shell data, more common in the clinic. However, the validity of the RGD method has been poorly assessed. This study aims to quantify the specificity of FWE-DTI procedures on single-shell and multishell data. METHODS Different FWE-DTI fitting procedures were tested on an open-source in vivo diffusion data set and single-shell and multishell synthetic signals, including the RGD and standard nonlinear least-squares methods. Single-voxel simulations were carried out to compare initialization approaches. A multivoxel phantom simulation was performed to evaluate the effect of spatial regularization when comparing between methods. To test the algorithms' specificity, phantoms with two different types of lesions were simulated: with altered mean diffusivity or with modified free water. RESULTS Plausible parameter maps were obtained with RGD from single-shell in vivo data. The plausibility of these maps was shown to be determined by the initialization. Tests with simulated lesions inserted into the in vivo data revealed that the RGD approach cannot distinguish free water from tissue mean-diffusivity alterations, contrarily to the nonlinear least-squares algorithm. CONCLUSION The RGD FWE-DTI method has limited specificity; thus, its results from single-shell data should be carefully interpreted. When possible, multishell acquisitions and the nonlinear least-squares approach should be preferred instead.
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Affiliation(s)
- Marc Golub
- ISR-Lisboa/LARSyS and Department of Bioengineering, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal
| | | | - Rita Gouveia Nunes
- ISR-Lisboa/LARSyS and Department of Bioengineering, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal
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