1
|
Lin Y, Gao B, Du Y, Li M, Liu Y, Zhao X. Cortical thickness and structural covariance network alterations in cerebral amyloid angiopathy: A graph theoretical analysis. Neurobiol Dis 2025; 210:106911. [PMID: 40239845 DOI: 10.1016/j.nbd.2025.106911] [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: 03/29/2025] [Revised: 04/13/2025] [Accepted: 04/13/2025] [Indexed: 04/18/2025] Open
Abstract
AIMS This study investigates large-scale brain network alterations in cerebral amyloid angiopathy (CAA) using structural covariance network (SCN) analysis and graph theory based on 7 T MRI. METHODS We employed structural covariance network (SCN) analysis based on cortical thickness data from ultra-high field 7 T MRI to investigate network alterations in CAA patients. Graph theoretical analysis was applied to quantify topological properties, including small-worldness, nodal centrality, and network efficiency. Between-group differences were assessed using permutation tests and false discovery rate (FDR) correction. RESULTS CAA patients exhibited significant alterations in small-world properties, with decreased Gamma (p = 0.002) and Sigma (p < 0.001), suggesting a shift toward a less optimal network configuration. Local efficiency was significantly different between groups (p = 0.045), while global efficiency remained unchanged (p = 0.127), indicating regionally disrupted rather than globally impaired network efficiency. At the nodal level, the right superior frontal gyrus exhibited increased betweenness centrality (p = 0.013), whereas the right banks of the superior temporal sulcus, left postcentral gyrus, and left superior temporal gyrus showed significantly reduced centrality (all p < 0.05). Additionally, nodal degree and efficiency were altered in key memory-related and association regions, including the entorhinal cortex, fusiform gyrus, and temporal pole. CONCLUSION SCN analysis combined with graph theory offers a valuable approach for understanding disease-related connectivity disruptions and may contribute to the development of network-based biomarkers for CAA.
Collapse
Affiliation(s)
- Yijun Lin
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Bin Gao
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Yang Du
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Mengyao Li
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Yanfang Liu
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
| | - Xingquan Zhao
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China; China National Clinical Research Center for Neurological Diseases, Beijing, China.
| |
Collapse
|
2
|
Hu HY, Li HQ, Gong WK, Huang SY, Fu Y, Hu H, Dong Q, Cheng W, Tan L, Cui M, Yu JT. Microstructural white matter injury contributes to cognitive decline: Besides amyloid and tau. J Prev Alzheimers Dis 2025; 12:100037. [PMID: 39863331 DOI: 10.1016/j.tjpad.2024.100037] [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: 10/28/2024] [Revised: 12/09/2024] [Accepted: 12/10/2024] [Indexed: 01/27/2025]
Abstract
BACKGROUND Cognitive decline and the progression to Alzheimer's disease (AD) are traditionally associated with amyloid-beta (Aβ) and tau pathologies. This study aims to evaluate the relationships between microstructural white matter injury, cognitive decline and AD core biomarkers. METHODS We conducted a longitudinal study of 566 participants using peak width of skeletonized mean diffusivity (PSMD) to quantify microstructural white matter injury. The associations of PSMD with changes in cognitive functions, AD pathologies (Aβ, tau, and neurodegeneration), and volumes of AD-signature regions of interest (ROI) or hippocampus were estimated. The associations between PSMD and the incidences of clinical progression were also tested. Covariates included age, sex, education, apolipoprotein E4 status, smoking, and hypertension. RESULTS Higher PSMD was associated with greater cognitive decline (β=-0.012, P < 0.001 for Mini-Mental State Examination score; β<0, P < 0.05 for four cognitive domains) and a higher risk of clinical progression from normal cognition to mild cognitive impairment (MCI) or AD (Hazard ratio=2.11 [1.38-3.23], P < 0.001). These associations persisted independently of amyloid status. PSMD did not predict changes in Aβ or tau levels, but predicted changes in volumes of AD-signature ROI (β=-0.003, P < 0.001) or hippocampus (β=-0.002, P = 0.010). Besides, the whole-brain PSMD could predict cognitive decline better than regional PSMDs. CONCLUSIONS PSMD may be a valuable biomarker for predicting cognitive decline and clinical progression to MCI and AD, providing insights besides traditional Aβ and tau pathways. Further research could elucidate its role in clinical assessments and therapeutic strategies.
Collapse
Affiliation(s)
- He-Ying Hu
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, PR China.
| | - Hong-Qi Li
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, PR China.
| | - Wei-Kang Gong
- Institute of Science and Technology for Brain-inspired Intelligence, Fudan University, Shanghai, PR China.
| | - Shu-Yi Huang
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, PR China.
| | - Yan Fu
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, PR China.
| | - Hao Hu
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, PR China.
| | - Qiang Dong
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, PR China.
| | - Wei Cheng
- Institute of Science and Technology for Brain-inspired Intelligence, Fudan University, Shanghai, PR China.
| | - Lan Tan
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, PR China.
| | - Mei Cui
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, PR China.
| | - Jin-Tai Yu
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, PR China.
| |
Collapse
|
3
|
Tendler BC. Investigating time-independent and time-dependent diffusion phenomena using steady-state diffusion MRI. Sci Rep 2025; 15:3580. [PMID: 39875547 PMCID: PMC11775203 DOI: 10.1038/s41598-025-87377-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2024] [Accepted: 01/20/2025] [Indexed: 01/30/2025] Open
Abstract
Diffusion MRI is a leading method to non-invasively characterise brain tissue microstructure across multiple domains and scales. Diffusion-weighted steady-state free precession (DW-SSFP) is an established imaging sequence for post-mortem MRI, addressing the challenging imaging environment of fixed tissue with short T2 and low diffusivities. However, a current limitation of DW-SSFP is signal interpretation: it is not clear what diffusion 'regime' the sequence probes and therefore its potential to characterise tissue microstructure. Building on Extended Phase Graphs (EPG), I establish two alternative representations of the DW-SSFP signal in terms of (1) conventional b-values (time-independent diffusion) and (2) encoding power-spectra (time-dependent diffusion). The proposed representations provide insights into how different parameter regimes and gradient waveforms impact the diffusion sensitivity of DW-SSFP. I subsequently introduce an approach to incorporate existing biophysical models into DW-SSFP without the requirement of extensive derivations, with time dependence estimated via a Gaussian phase approximation representation of the DW-SSFP signal. Investigations incorporating free-diffusion and tissue-relevant microscopic restrictions (cylinder of varying radius) give excellent agreement to complementary analytical models and Monte Carlo simulations. Experimentally, the time-independent representation is used to derive Tensor and proof-of-principle NODDI estimates in a whole human post-mortem brain. A final SNR-efficiency investigation demonstrates the theoretical potential of DW-SSFP for ultra-high field microstructural imaging.
Collapse
Affiliation(s)
- Benjamin C Tendler
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.
| |
Collapse
|
4
|
You T, Wang Y, Chen S, Dong Q, Yu J, Cui M. Vascular cognitive impairment: Advances in clinical research and management. Chin Med J (Engl) 2024; 137:2793-2807. [PMID: 39048312 PMCID: PMC11649275 DOI: 10.1097/cm9.0000000000003220] [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: 01/07/2024] [Indexed: 07/27/2024] Open
Abstract
ABSTRACT Vascular cognitive impairment (VCI) encompasses a wide spectrum of cognitive disorders, ranging from mild cognitive impairment to vascular dementia. Its diagnosis relies on thorough clinical evaluations and neuroimaging. VCI predominately arises from vascular risk factors (VRFs) and cerebrovascular disease, either independently or in conjunction with neurodegeneration. Growing evidence underscores the prevalence of VRFs, highlighting their potential for early prediction of cognitive impairment and dementia in later life. The precise mechanisms linking vascular pathologies to cognitive deficits remain elusive. Chronic cerebrovascular pathology is the most common neuropathological feature of VCI, often interacting synergistically with neurodegenerative processes. Current research efforts are focused on developing and validating reliable biomarkers to unravel the etiology of vascular brain changes in VCI. The collaborative integration of these biomarkers into clinical practice, alongside routine incorporation into neuropathological assessments, presents a promising strategy for predicting and stratifying VCI. The cornerstone of VCI prevention remains the control of VRFs, which includes multi-domain lifestyle modifications. Identifying appropriate pharmacological approaches is also of paramount importance. In this review, we synthesize recent advancements in the field of VCI, including its definition, determinants of vascular risk, pathophysiology, neuroimaging and fluid-correlated biomarkers, predictive methodologies, and current intervention strategies. Increasingly evident is the notion that more rigorous research for VCI, which arises from a complex interplay of physiological events, is still needed to pave the way for better clinical outcomes and enhanced quality of life for affected individuals.
Collapse
Affiliation(s)
- Tongyao You
- Department of Neurology, Huashan Hospital, Fudan University, Shanghai 200040, China
| | - Yingzhe Wang
- Department of Neurology, Huashan Hospital, Fudan University, Shanghai 200040, China
| | - Shufen Chen
- Department of Neurology, Huashan Hospital, Fudan University, Shanghai 200040, China
| | - Qiang Dong
- Department of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Fudan University, Shanghai 200040, China
- National Center for Neurological Disorders, Huashan Hospital, Fudan University, Shanghai 200040, China
| | - Jintai Yu
- Department of Neurology, Huashan Hospital, Fudan University, Shanghai 200040, China
| | - Mei Cui
- Department of Neurology, Huashan Hospital, Fudan University, Shanghai 200040, China
- Department of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Fudan University, Shanghai 200040, China
| |
Collapse
|
5
|
Xu M, Xue K, Song X, Zhang Y, Cheng J, Cheng J. Peak width of skeletonized mean diffusivity as a neuroimaging biomarker in first-episode schizophrenia. Front Neurosci 2024; 18:1427947. [PMID: 39376541 PMCID: PMC11456572 DOI: 10.3389/fnins.2024.1427947] [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: 05/05/2024] [Accepted: 09/09/2024] [Indexed: 10/09/2024] Open
Abstract
Background and objective Peak width of skeletonized mean diffusivity (PSMD), a fully automated diffusion tensor imaging (DTI) biomarker of white matter (WM) microstructure damage, has been shown to be associated with cognition in various WM pathologies. However, its application in schizophrenic disease remains unexplored. This study aims to investigate PSMD along with other DTI markers in first-episode schizophrenia patients compared to healthy controls (HCs), and explore the correlations between these metrics and clinical characteristics. Methods A total of 56 first-episode drug-naive schizophrenia patients and 64 HCs were recruited for this study. Participants underwent structural imaging and DTI, followed by comprehensive clinical assessments, including the Positive and Negative Syndrome Scale (PANSS) for patients and cognitive function tests for all participants. We calculated PSMD, peak width of skeletonized fractional anisotropy (PSFA), axial diffusivity (PSAD), radial diffusivity (PSRD) values, skeletonized average mean diffusivity (MD), average fractional anisotropy (FA), average axial diffusivity (AD), and average radial diffusivity (RD) values as well as structural network global topological parameters, and examined between-group differences in these WM metrics. Furthermore, we investigated associations between abnormal metrics and clinical characteristics. Results Compared to HCs, patients exhibited significantly increased PSMD values (t = 2.467, p = 0.015), decreased global efficiency (Z = -2.188, p = 0.029), and increased normalized characteristic path length (lambda) (t = 2.270, p = 0.025). No significant differences were observed between the groups in the remaining metrics, including PSFA, PSAD, PSRD, average MD, FA, AD, RD, local efficiency, normalized cluster coefficient, small-worldness, assortativity, modularity, or hierarchy (p > 0.05). After adjusting for relevant variables, both PSMD and lambda values exhibited a significant negative correlation with reasoning and problem-solving scores (PSMD: r = -0.409, p = 0.038; lambda: r = -0.520, p = 0.006). No statistically significant correlations were observed between each PANSS score and the aforementioned metrics in the patient group (p > 0.05). Multivariate linear regression analysis revealed that increased PSMD (β = -0.426, t = -2.260, p = 0.034) and increased lambda (β = -0.490, t = -2.994, p = 0.007) were independently associated with decreased reasoning and problem-solving scores respectively (R a d j 2 = 0.295, F = 2.951, p = 0.029). But these significant correlations did not withstand FDR correction (p_FDR > 0.05). Conclusion PSMD can be considered as a valuable neuroimaging biomarker that complements conventional diffusion measurements for investigating abnormalities in WM microstructural integrity and cognitive functions in schizophrenia.
Collapse
Affiliation(s)
- Man Xu
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Engineering Research Center of Brain Function Development and Application of Henan Province, Zhengzhou, China
| | - Kangkang Xue
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Engineering Research Center of Brain Function Development and Application of Henan Province, Zhengzhou, China
| | - Xueqin Song
- Department of Psychiatry, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Yong Zhang
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Engineering Research Center of Brain Function Development and Application of Henan Province, Zhengzhou, China
| | - Jingliang Cheng
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Engineering Research Center of Brain Function Development and Application of Henan Province, Zhengzhou, China
| | - Junying Cheng
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Engineering Research Center of Brain Function Development and Application of Henan Province, Zhengzhou, China
| |
Collapse
|
6
|
Tazwar M, Evia AM, Ridwan AR, Leurgans SE, Bennett DA, Schneider JA, Arfanakis K. Limbic-predominant age-related TDP-43 encephalopathy neuropathological change (LATE-NC) is associated with abnormalities in white matter structural integrity and connectivity: An ex-vivo diffusion MRI and pathology investigation. Neurobiol Aging 2024; 140:81-92. [PMID: 38744041 PMCID: PMC11182335 DOI: 10.1016/j.neurobiolaging.2024.04.002] [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: 10/04/2023] [Revised: 04/04/2024] [Accepted: 04/04/2024] [Indexed: 05/16/2024]
Abstract
Limbic predominant age-related TDP-43 encephalopathy neuropathological change (LATE-NC) is common in older adults and is associated with neurodegeneration, cognitive decline and dementia. In this MRI and pathology investigation we tested the hypothesis that LATE-NC is associated with abnormalities in white matter structural integrity and connectivity of a network of brain regions typically harboring TDP-43 inclusions in LATE, referred to here as the "LATE-NC network". Ex-vivo diffusion MRI and detailed neuropathological data were collected on 184 community-based older adults. Linear regression revealed an independent association of higher LATE-NC stage with lower diffusion anisotropy in a set of white matter connections forming a pattern of connectivity that is consistent with the stereotypical spread of this pathology in the brain. Graph theory analysis revealed an association of higher LATE-NC stage with weaker integration and segregation in the LATE-NC network. Abnormalities were significant in stage 3, suggesting that they are detectable in later stages of the disease. Finally, LATE-NC network abnormalities were associated with faster cognitive decline, specifically in episodic and semantic memory.
Collapse
Affiliation(s)
- Mahir Tazwar
- Department of Biomedical Engineering, Illinois Institute of Technology, Chicago, IL, USA
| | - Arnold M Evia
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, USA
| | - Abdur Raquib Ridwan
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, USA
| | - Sue E Leurgans
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, USA; Department of Neurological Sciences, Rush University Medical Center, Chicago, IL, USA
| | - David A Bennett
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, USA; Department of Neurological Sciences, Rush University Medical Center, Chicago, IL, USA
| | - Julie A Schneider
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, USA; Department of Neurological Sciences, Rush University Medical Center, Chicago, IL, USA; Department of Pathology, Rush University Medical Center, Chicago, IL, USA
| | - Konstantinos Arfanakis
- Department of Biomedical Engineering, Illinois Institute of Technology, Chicago, IL, USA; Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, USA; Department of Diagnostic Radiology, Rush University Medical Center, Chicago, IL, USA.
| |
Collapse
|
7
|
Su H, Yan S, Zhu H, Liu Y, Zhang G, Peng X, Zhang S, Li Y, Zhu W. A normative modeling approach to quantify white matter changes and predict functional outcomes in stroke patients. Front Neurosci 2024; 18:1334508. [PMID: 38379757 PMCID: PMC10877717 DOI: 10.3389/fnins.2024.1334508] [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: 11/07/2023] [Accepted: 01/12/2024] [Indexed: 02/22/2024] Open
Abstract
Objectives The diverse nature of stroke necessitates individualized assessment, presenting challenges to case-control neuroimaging studies. The normative model, measuring deviations from a normal distribution, provides a solution. We aim to evaluate stroke-induced white matter microstructural abnormalities at group and individual levels and identify potential prognostic biomarkers. Methods Forty-six basal ganglia stroke patients and 46 healthy controls were recruited. Diffusion-weighted imaging and clinical assessment were performed within 7 days after stroke. We used automated fiber quantification to characterize intergroup alterations of segmental diffusion properties along 20 fiber tracts. Then each patient was compared to normative reference (46 healthy participants) by Mahalanobis distance tractometry for 7 significant fiber tracts. Mahalanobis distance-based deviation loads (MaDDLs) and fused MaDDLmulti were extracted to quantify individual deviations. We also conducted correlation and logistic regression analyses to explore relationships between MaDDL metrics and functional outcomes. Results Disrupted microstructural integrity was observed across the left corticospinal tract, bilateral inferior fronto-occipital fasciculus, left inferior longitudinal fasciculus, bilateral thalamic radiation, and right uncinate fasciculus. The correlation coefficients between MaDDL metrics and initial functional impairment ranged from 0.364 to 0.618 (p < 0.05), with the highest being MaDDLmulti. Furthermore, MaDDLmulti demonstrated a significant enhancement in predictive efficacy compared to MaDDL (integrated discrimination improvement [IDI] = 9.62%, p = 0.005) and FA (IDI = 34.04%, p < 0.001) of the left corticospinal tract. Conclusion MaDDLmulti allows for assessing behavioral disorders and predicting prognosis, offering significant implications for personalized clinical decision-making and stroke recovery. Importantly, our method demonstrates prospects for widespread application in heterogeneous neurological diseases.
Collapse
Affiliation(s)
| | | | | | | | | | | | | | - Yuanhao Li
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Wenzhen Zhu
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| |
Collapse
|
8
|
Wheeler KV, Irimia A, Braskie MN. Using Neuroimaging to Study Cerebral Amyloid Angiopathy and Its Relationship to Alzheimer's Disease. J Alzheimers Dis 2024; 97:1479-1502. [PMID: 38306032 DOI: 10.3233/jad-230553] [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: 02/03/2024]
Abstract
Cerebral amyloid angiopathy (CAA) is characterized by amyloid-β aggregation in the media and adventitia of the leptomeningeal and cortical blood vessels. CAA is one of the strongest vascular contributors to Alzheimer's disease (AD). It frequently co-occurs in AD patients, but the relationship between CAA and AD is incompletely understood. CAA may drive AD risk through damage to the neurovascular unit and accelerate parenchymal amyloid and tau deposition. Conversely, early AD may also drive CAA through cerebrovascular remodeling that impairs blood vessels from clearing amyloid-β. Sole reliance on autopsy examination to study CAA limits researchers' ability to investigate CAA's natural disease course and the effect of CAA on cognitive decline. Neuroimaging allows for in vivo assessment of brain function and structure and can be leveraged to investigate CAA staging and explore its associations with AD. In this review, we will discuss neuroimaging modalities that can be used to investigate markers associated with CAA that may impact AD vulnerability including hemorrhages and microbleeds, blood-brain barrier permeability disruption, reduced cerebral blood flow, amyloid and tau accumulation, white matter tract disruption, reduced cerebrovascular reactivity, and lowered brain glucose metabolism. We present possible areas for research inquiry to advance biomarker discovery and improve diagnostics.
Collapse
Affiliation(s)
- Koral V Wheeler
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina Del Rey, CA, USA
| | - Andrei Irimia
- Ethel Percy Andrus Gerontology Center, USC Leonard Davis School of Gerontology, University of Southern California, Los Angeles, CA, USA
- Department of Biomedical Engineering, Corwin D. Denney Research Center, Viterbi School of Engineering, University of Southern California, Los Angeles, CA, USA
| | - Meredith N Braskie
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina Del Rey, CA, USA
| |
Collapse
|
9
|
Huang J, Biessels GJ, de Leeuw FE, Ii Y, Skoog I, Mok V, Chen C, Hilal S. Cerebral microinfarcts revisited: Detection, causes, and clinical relevance. Int J Stroke 2024; 19:7-15. [PMID: 37470314 DOI: 10.1177/17474930231187979] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/21/2023]
Abstract
Cerebral microinfarcts (CMIs) are small ischemic lesions invisible to the naked eye at brain autopsy, while the larger ones (0.5-4 mm in diameter) have been visualized in-vivo on magnetic resonance imaging (MRI). CMIs can be detected on diffusion-weighted imaging (DWI) as incidental small DWI-positive lesions (ISDPLs) and on structural MRI for those confined to the cortex and in the chronic phase. ISDPLs may evolve into old cortical-CMIs, white matter hyperintensities or disappear depending on their location and size. Novel techniques in neuropathology and neuroimaging facilitate the detection of CMIs, which promotes understanding of these lesions. CMIs have heterogeneous causes, involving both cerebral small- and large-vessel disease as well as heart diseases such as atrial fibrillation and congestive heart failure. The underlying mechanisms incorporate vascular remodeling, inflammation, blood-brain barrier leakage, penetrating venule congestion, cerebral hypoperfusion, and microembolism. CMIs lead to clinical outcomes, including cognitive decline, a higher risk of stroke and mortality, and accelerated neurobehavioral disturbances. It has been suggested that CMIs can impair brain function and connectivity beyond the microinfarct core and are also associated with perilesional and global cortical atrophy. This review aims to summarize recent progress in studies involving both cortical-CMIs and ISDPLs since 2017, including their detection, etiology, risk factors, MRI correlates, and clinical consequences.
Collapse
Affiliation(s)
- Jiannan Huang
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore
| | - Geert Jan Biessels
- Department of Neurology, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Frank-Erik de Leeuw
- Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Yuichiro Ii
- Department of Neurology, Mie University Graduate School of Medicine, Tsu, Japan
- Department of Neuroimaging and Pathophysiology, Mie University School of Medicine, Tsu, Japan
| | - Ingmar Skoog
- Institute of Neuroscience and Physiology and Centre for Ageing and Health, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Department of Psychiatry Cognition and Old Age Psychiatry, Sahlgrenska University Hospital, Region Västra Götaland, Mölndal, Sweden
| | - Vincent Mok
- Division of Neurology, Department of Medicine and Therapeutics, Faculty of Medicine, The Chinese University of Hong Kong, Shatin, Hong Kong
- Lau Tat-chuen Research Centre of Brain Degenerative Diseases in Chinese and Li Ka Shing Institute of Health Sciences, Faculty of Medicine, The Chinese University of Hong Kong, Shatin, Hong Kong
| | - Christopher Chen
- Memory Aging and Cognition Centre, National University Health System, Singapore
- Department of Pharmacology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Saima Hilal
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore
- Department of Pharmacology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| |
Collapse
|
10
|
Schipper MR, Vlegels N, van Harten TW, Rasing I, Koemans EA, Voigt S, de Luca A, Kaushik K, van Etten ES, van Zwet EW, Terwindt GM, Biessels GJ, van Osch MJP, van Walderveen MAA, Wermer MJH. Microstructural white matter integrity in relation to vascular reactivity in Dutch-type hereditary cerebral amyloid angiopathy. J Cereb Blood Flow Metab 2023; 43:2144-2155. [PMID: 37708241 PMCID: PMC10925868 DOI: 10.1177/0271678x231200425] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/04/2023] [Revised: 08/04/2023] [Accepted: 08/07/2023] [Indexed: 09/16/2023]
Abstract
Cerebral Amyloid Angiopathy (CAA) is characterized by cerebrovascular amyloid-β accumulation leading to hallmark cortical MRI markers, such as vascular reactivity, but white matter is also affected. By studying the relationship in different disease stages of Dutch-type CAA (D-CAA), we tested the relation between vascular reactivity and microstructural white matter integrity loss. In a cross-sectional study in D-CAA, 3 T MRI was performed with Blood-Oxygen-Level-Dependent (BOLD) fMRI upon visual activation to assess vascular reactivity and diffusion tensor imaging to assess microstructural white matter integrity through Peak Width of Skeletonized Mean Diffusivity (PSMD). We assessed the relationship between BOLD parameters - amplitude, time-to-peak (TTP), and time-to-baseline (TTB) - and PSMD, with linear and quadratic regression modeling. In total, 25 participants were included (15/10 pre-symptomatic/symptomatic; mean age 36/59 y). A lowered BOLD amplitude (unstandardized β = 0.64, 95%CI [0.10, 1.18], p = 0.02, Adjusted R2 = 0.48), was quadratically associated with increased PSMD levels. A delayed BOLD response, with prolonged TTP (β = 8.34 × 10-6, 95%CI [1.84 × 10-6, 1.48 × 10-5], p = 0.02, Adj. R2 = 0.25) and TTB (β = 6.57 × 10-6, 95%CI [1.92 × 10-6, 1.12 × 10-5], p = 0.008, Adj. R2 = 0.29), was linearly associated with increased PSMD. In D-CAA subjects, predominantly in the symptomatic stage, impaired cerebrovascular reactivity is related to microstructural white matter integrity loss. Future longitudinal studies are needed to investigate whether this relation is causal.
Collapse
Affiliation(s)
- Manon R Schipper
- Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Naomi Vlegels
- Department of Neurology and Neurosurgery, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht, The Netherlands
- Institute for Stroke and Dementia Research, University Hospital, LMU Munich, Munich, Germany
| | - Thijs W van Harten
- Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Ingeborg Rasing
- Department of Neurology, Leiden University Medical Center, Leiden, The Netherlands
| | - Emma A Koemans
- Department of Neurology, Leiden University Medical Center, Leiden, The Netherlands
| | - Sabine Voigt
- Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
- Department of Neurology, Leiden University Medical Center, Leiden, The Netherlands
| | - Alberto de Luca
- Department of Neurology and Neurosurgery, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht, The Netherlands
- Image Sciences Institute, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Kanishk Kaushik
- Department of Neurology, Leiden University Medical Center, Leiden, The Netherlands
| | - Ellis S van Etten
- Department of Neurology, Leiden University Medical Center, Leiden, The Netherlands
| | - Erik W van Zwet
- Department of Biostatistics, Leiden University Medical Center, Leiden, The Netherlands
| | - Gisela M Terwindt
- Department of Neurology, Leiden University Medical Center, Leiden, The Netherlands
| | - Geert Jan Biessels
- Department of Neurology and Neurosurgery, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Matthias JP van Osch
- Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
| | | | - Marieke JH Wermer
- Department of Neurology, Leiden University Medical Center, Leiden, The Netherlands
- Department of Neurology, University Medical Center Groningen, Groningen, The Netherlands
| |
Collapse
|
11
|
Perosa V, Auger CA, Zanon Zotin MC, Oltmer J, Frosch MP, Viswanathan A, Greenberg SM, van Veluw SJ. Histopathological Correlates of Lobar Microbleeds in False-Positive Cerebral Amyloid Angiopathy Cases. Ann Neurol 2023; 94:856-870. [PMID: 37548609 PMCID: PMC11573502 DOI: 10.1002/ana.26761] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2023] [Revised: 07/05/2023] [Accepted: 07/31/2023] [Indexed: 08/08/2023]
Abstract
OBJECTIVE A definite diagnosis of cerebral amyloid angiopathy (CAA), characterized by the accumulation of amyloid β in walls of cerebral small vessels, can only be obtained through pathological examination. A diagnosis of probable CAA during life relies on the presence of hemorrhagic markers, including lobar cerebral microbleeds (CMBs). The aim of this project was to study the histopathological correlates of lobar CMBs in false-positive CAA cases. METHODS In 3 patients who met criteria for probable CAA during life, but showed no CAA upon neuropathological examination, lobar CMBs were counted on ex vivo 3T magnetic resonance imaging (MRI) and on ex vivo 7T MRI. Areas with lobar CMBs were next sampled and cut into serial sections, on which the CMBs were then identified. RESULTS Collectively, there were 25 lobar CMBs on in vivo MRI and 22 on ex vivo 3T MRI of the analyzed hemispheres. On ex vivo MRI, we targeted 12 CMBs for sampling, and definite histopathological correlates were retrieved for 9 of them, of which 7 were true CMBs. No CAA was found on any of the serial sections. The "culprit vessels" associated with the true CMBs instead showed moderate to severe arteriolosclerosis. Furthermore, CMBs in false-positive CAA cases tended to be located more often in the juxtacortical or subcortical white matter than in the cortical ribbon. INTERPRETATION These findings suggest that arteriolosclerosis can generate lobar CMBs and that more detailed investigations into the exact localization of CMBs with respect to the cortical ribbon could potentially aid the diagnosis of CAA during life. ANN NEUROL 2023;94:856-870.
Collapse
Affiliation(s)
- Valentina Perosa
- J. Philip Kistler Stroke Research Center, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Corinne A Auger
- MassGeneral Institute for Neurodegenerative Disease, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA
| | - Maria Clara Zanon Zotin
- J. Philip Kistler Stroke Research Center, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Center for Imaging Sciences and Medical Physics, Department of Medical Imaging, Hematology, and Clinical Oncology, Ribeirão Preto Medical School, University of São Paulo, São Paulo, Brazil
| | - Jan Oltmer
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA
| | - Matthew P Frosch
- Department of Neuropathology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Anand Viswanathan
- J. Philip Kistler Stroke Research Center, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Steven M Greenberg
- J. Philip Kistler Stroke Research Center, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Susanne J van Veluw
- J. Philip Kistler Stroke Research Center, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- MassGeneral Institute for Neurodegenerative Disease, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA
| |
Collapse
|
12
|
Jia Y, Sun H, Sun L, Wang Y, Xu Q, Liu Y, Chang X, He Y, Guo D, Shi M, Chen GC, Zheng J, Zhang Y, Zhu Z. Mendelian randomization analysis implicates bidirectional associations between brain imaging-derived phenotypes and ischemic stroke. Cereb Cortex 2023; 33:10848-10857. [PMID: 37697910 DOI: 10.1093/cercor/bhad329] [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: 07/24/2023] [Revised: 08/21/2023] [Accepted: 08/22/2023] [Indexed: 09/13/2023] Open
Abstract
Brian imaging-derived phenotypes (IDPs) have been suggested to be associated with ischemic stroke, but the causality between them remains unclear. In this bidirectional two-sample Mendelian randomization (MR) study, we explored the potential causal relationship between 461 imaging-derived phenotypes (n = 33,224, UK Biobank) and ischemic stroke (n = 34,217 cases/406,111 controls, Multiancestry Genome-Wide Association Study of Stroke). Forward MR analyses identified five IDPs associated with ischemic stroke, including mean diffusivity (MD) in the right superior fronto-occipital fasciculus (1.22 [95% CI, 1.11-1.34]), MD in the left superior fronto-occipital fasciculus (1.30 [1.17-1.44]), MD in the anterior limb of the right internal capsule (1.36 [1.22-1.51]), MD in the right anterior thalamic radiation (1.17 [1.09-1.26]), and MD in the right superior thalamic radiation (1.23 [1.11-1.35]). In the reverse MR analyses, ischemic stroke was identified to be associated with three IDPs, including high isotropic or free water volume fraction in the body of corpus callosum (beta, 0.189 [95% confidence interval, 0.107-0.271]), orientation dispersion index in the pontine crossing tract (0.175 [0.093-0.257]), and volume of the third ventricle (0.219 [0.138-0.301]). This bidirectional two-sample MR study suggested five predictors and three diagnostic markers for ischemic stroke at the brain-imaging level. Further studies are warranted to replicate our findings and clarify underlying mechanisms.
Collapse
Affiliation(s)
- Yiming Jia
- Department of Epidemiology, School of Public Health, Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Ministry of Education (MOE) Key Laboratory of Geriatric Diseases and Immunology, Suzhou Medical College of Soochow University, Suzhou 215123, China
| | - Hongyan Sun
- Department of Medical Imaging, The Affiliated Guangji Hospital of Soochow University, Suzhou 215137, China
| | - Lulu Sun
- Department of Epidemiology, School of Public Health, Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Ministry of Education (MOE) Key Laboratory of Geriatric Diseases and Immunology, Suzhou Medical College of Soochow University, Suzhou 215123, China
| | - Yinan Wang
- Department of Epidemiology, School of Public Health, Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Ministry of Education (MOE) Key Laboratory of Geriatric Diseases and Immunology, Suzhou Medical College of Soochow University, Suzhou 215123, China
| | - Qingyun Xu
- Department of Epidemiology, School of Public Health, Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Ministry of Education (MOE) Key Laboratory of Geriatric Diseases and Immunology, Suzhou Medical College of Soochow University, Suzhou 215123, China
| | - Yi Liu
- Department of Epidemiology, School of Public Health, Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Ministry of Education (MOE) Key Laboratory of Geriatric Diseases and Immunology, Suzhou Medical College of Soochow University, Suzhou 215123, China
| | - Xinyue Chang
- Department of Epidemiology, School of Public Health, Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Ministry of Education (MOE) Key Laboratory of Geriatric Diseases and Immunology, Suzhou Medical College of Soochow University, Suzhou 215123, China
| | - Yu He
- Department of Epidemiology, School of Public Health, Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Ministry of Education (MOE) Key Laboratory of Geriatric Diseases and Immunology, Suzhou Medical College of Soochow University, Suzhou 215123, China
| | - Daoxia Guo
- School of Nursing, Suzhou Medical College of Soochow University, Suzhou 215123, China
| | - Mengyao Shi
- Department of Epidemiology, School of Public Health, Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Ministry of Education (MOE) Key Laboratory of Geriatric Diseases and Immunology, Suzhou Medical College of Soochow University, Suzhou 215123, China
| | - Guo-Chong Chen
- Department of Nutrition and Food Hygiene, School of Public Health, Suzhou Medical College of Soochow University, Suzhou 215123, China
| | - Jin Zheng
- Department of Neurology, Minhang Hospital, Fudan University, Shanghai 200433, China
| | - Yonghong Zhang
- Department of Epidemiology, School of Public Health, Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Ministry of Education (MOE) Key Laboratory of Geriatric Diseases and Immunology, Suzhou Medical College of Soochow University, Suzhou 215123, China
| | - Zhengbao Zhu
- Department of Epidemiology, School of Public Health, Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Ministry of Education (MOE) Key Laboratory of Geriatric Diseases and Immunology, Suzhou Medical College of Soochow University, Suzhou 215123, China
| |
Collapse
|
13
|
Koemans EA, Chhatwal JP, van Veluw SJ, van Etten ES, van Osch MJP, van Walderveen MAA, Sohrabi HR, Kozberg MG, Shirzadi Z, Terwindt GM, van Buchem MA, Smith EE, Werring DJ, Martins RN, Wermer MJH, Greenberg SM. Progression of cerebral amyloid angiopathy: a pathophysiological framework. Lancet Neurol 2023; 22:632-642. [PMID: 37236210 DOI: 10.1016/s1474-4422(23)00114-x] [Citation(s) in RCA: 74] [Impact Index Per Article: 37.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2022] [Revised: 02/21/2023] [Accepted: 03/14/2023] [Indexed: 05/28/2023]
Abstract
Cerebral amyloid angiopathy, which is defined by cerebrovascular deposition of amyloid β, is a common age-related small vessel pathology associated with intracerebral haemorrhage and cognitive impairment. Based on complementary lines of evidence from in vivo studies of individuals with hereditary, sporadic, and iatrogenic forms of cerebral amyloid angiopathy, histopathological analyses of affected brains, and experimental studies in transgenic mouse models, we present a framework and timeline for the progression of cerebral amyloid angiopathy from subclinical pathology to the clinical manifestation of the disease. Key stages that appear to evolve sequentially over two to three decades are (stage one) initial vascular amyloid deposition, (stage two) alteration of cerebrovascular physiology, (stage three) non-haemorrhagic brain injury, and (stage four) appearance of haemorrhagic brain lesions. This timeline of stages and the mechanistic processes that link them have substantial implications for identifying disease-modifying interventions for cerebral amyloid angiopathy and potentially for other cerebral small vessel diseases.
Collapse
Affiliation(s)
- Emma A Koemans
- Department of Neurology and Department of Radiology, Leiden University Medical Center, Leiden, Netherlands
| | - Jasmeer P Chhatwal
- Department of Neurology and Department of Radiology, Massachusetts General Hospital, Boston, MA, USA
| | - Susanne J van Veluw
- Department of Neurology and Department of Radiology, Massachusetts General Hospital, Boston, MA, USA
| | - Ellis S van Etten
- Department of Neurology and Department of Radiology, Leiden University Medical Center, Leiden, Netherlands
| | - Matthias J P van Osch
- Department of Neurology and Department of Radiology, Leiden University Medical Center, Leiden, Netherlands
| | | | - Hamid R Sohrabi
- Centre for Healthy Ageing, Health Future Institute, Murdoch University, Perth, WA, Australia; Department of Biomedical Sciences, Macquarie University, North Ryde, NSW, Australia
| | - Mariel G Kozberg
- Department of Neurology and Department of Radiology, Massachusetts General Hospital, Boston, MA, USA
| | - Zahra Shirzadi
- Department of Neurology and Department of Radiology, Massachusetts General Hospital, Boston, MA, USA
| | - Gisela M Terwindt
- Department of Neurology and Department of Radiology, Leiden University Medical Center, Leiden, Netherlands
| | - Mark A van Buchem
- Department of Neurology and Department of Radiology, Leiden University Medical Center, Leiden, Netherlands
| | - Eric E Smith
- Department of Clinical Neurosciences and Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
| | - David J Werring
- Stroke Research Centre, Department of Brain Repair and Rehabilitation, University College London Queen Square Institute of Neurology, London, UK; National Hospital for Neurology and Neurosurgery, London, UK
| | - Ralph N Martins
- Centre for Healthy Ageing, Health Future Institute, Murdoch University, Perth, WA, Australia; Department of Biomedical Sciences, Macquarie University, North Ryde, NSW, Australia; School of Medical and Health Sciences, Edith Cowan University, Joondalup, WA, Australia
| | - Marieke J H Wermer
- Department of Neurology and Department of Radiology, Leiden University Medical Center, Leiden, Netherlands
| | - Steven M Greenberg
- Department of Neurology and Department of Radiology, Massachusetts General Hospital, Boston, MA, USA.
| |
Collapse
|
14
|
Piredda GF, Caneschi S, Hilbert T, Bonanno G, Joseph A, Egger K, Peter J, Klöppel S, Jehli E, Grieder M, Slotboom J, Seiffge D, Goeldlin M, Hoepner R, Willems T, Vulliemoz S, Seeck M, Venkategowda PB, Corredor Jerez RA, Maréchal B, Thiran JP, Wiest R, Kober T, Radojewski P. Submillimeter T 1 atlas for subject-specific abnormality detection at 7T. Magn Reson Med 2023; 89:1601-1616. [PMID: 36478417 DOI: 10.1002/mrm.29540] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2022] [Revised: 10/14/2022] [Accepted: 11/07/2022] [Indexed: 12/12/2022]
Abstract
PURPOSE Studies at 3T have shown that T1 relaxometry enables characterization of brain tissues at the single-subject level by comparing individual physical properties to a normative atlas. In this work, an atlas of normative T1 values at 7T is introduced with 0.6 mm isotropic resolution and its clinical potential is explored in comparison to 3T. METHODS T1 maps were acquired in two separate healthy cohorts scanned at 3T and 7T. Using transfer learning, a template-based brain segmentation algorithm was adapted to ultra-high field imaging data. After segmenting brain tissues, volumes were normalized into a common space, and an atlas of normative T1 values was established by modeling the T1 inter-subject variability. A method for single-subject comparisons restricted to white matter and subcortical structures was developed by computing Z-scores. The comparison was applied to eight patients scanned at both field strengths for proof of concept. RESULTS The proposed method for morphometry delivered segmentation masks without statistically significant differences from those derived with the original pipeline at 3T and achieved accurate segmentation at 7T. The established normative atlas allowed characterizing tissue alterations in single-subject comparisons at 7T, and showed greater anatomical details compared with 3T results. CONCLUSION A high-resolution quantitative atlas with an adapted pipeline was introduced and validated. Several case studies on different clinical conditions showed the feasibility, potential and limitations of high-resolution single-subject comparisons based on quantitative MRI atlases. This method in conjunction with 7T higher resolution broadens the range of potential applications of quantitative MRI in clinical practice.
Collapse
Affiliation(s)
- Gian Franco Piredda
- Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Lausanne, Switzerland.,Human Neuroscience Platform, Fondation Campus Biotech Geneva, Geneva, Switzerland.,CIBM-AIT, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Samuele Caneschi
- Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Lausanne, Switzerland.,Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.,LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Tom Hilbert
- Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Lausanne, Switzerland.,Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.,LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Gabriele Bonanno
- Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Bern, Switzerland.,Translational Imaging Center (TIC), Swiss Institute for Translational and Entrepreneurial Medicine, Bern, Switzerland.,Magnetic Resonance Methodology, Institute of Diagnostic and Interventional Neuroradiology, University of Bern, Bern, Switzerland
| | - Arun Joseph
- Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Bern, Switzerland.,Translational Imaging Center (TIC), Swiss Institute for Translational and Entrepreneurial Medicine, Bern, Switzerland.,Magnetic Resonance Methodology, Institute of Diagnostic and Interventional Neuroradiology, University of Bern, Bern, Switzerland
| | - Karl Egger
- Department of Neuroradiology, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Jessica Peter
- University Hospital of Old Age Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland
| | - Stefan Klöppel
- University Hospital of Old Age Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland
| | - Elisabeth Jehli
- Translational Research Center, University Hospital of Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland.,Department of Neurosurgery, University Hospital of Zurich, Zurich, Switzerland
| | - Matthias Grieder
- Translational Research Center, University Hospital of Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland
| | - Johannes Slotboom
- Support Center for Advanced Neuroimaging, Institute for Diagnostic and Interventional Neuroradiology, Inselspital, University of Bern, Bern, Switzerland
| | - David Seiffge
- Department of Neurology, University Hospital Bern, Inselspital, University of Bern, Bern, Switzerland
| | - Martina Goeldlin
- Department of Neurology, University Hospital Bern, Inselspital, University of Bern, Bern, Switzerland
| | - Robert Hoepner
- Department of Neurology, University Hospital Bern, Inselspital, University of Bern, Bern, Switzerland
| | - Tom Willems
- Institute of Psychology, University of Bern, Bern, Switzerland
| | - Serge Vulliemoz
- EEG and Epilepsy Unit, Department of Clinical Neurosciences, Geneva University Hospitals and Faculty of Medicine, Geneva, Switzerland
| | - Margitta Seeck
- EEG and Epilepsy Unit, Department of Clinical Neurosciences, Geneva University Hospitals and Faculty of Medicine, Geneva, Switzerland
| | | | - Ricardo A Corredor Jerez
- Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Lausanne, Switzerland.,Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.,LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Bénédicte Maréchal
- Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Lausanne, Switzerland.,Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.,LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Jean-Philippe Thiran
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.,LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Roland Wiest
- Translational Imaging Center (TIC), Swiss Institute for Translational and Entrepreneurial Medicine, Bern, Switzerland.,Support Center for Advanced Neuroimaging, Institute for Diagnostic and Interventional Neuroradiology, Inselspital, University of Bern, Bern, Switzerland
| | - Tobias Kober
- Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Lausanne, Switzerland.,Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.,LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Piotr Radojewski
- Translational Imaging Center (TIC), Swiss Institute for Translational and Entrepreneurial Medicine, Bern, Switzerland.,Support Center for Advanced Neuroimaging, Institute for Diagnostic and Interventional Neuroradiology, Inselspital, University of Bern, Bern, Switzerland
| |
Collapse
|
15
|
Zanon Zotin MC, Yilmaz P, Sveikata L, Schoemaker D, van Veluw SJ, Etherton MR, Charidimou A, Greenberg SM, Duering M, Viswanathan A. Peak Width of Skeletonized Mean Diffusivity: A Neuroimaging Marker for White Matter Injury. Radiology 2023; 306:e212780. [PMID: 36692402 PMCID: PMC9968775 DOI: 10.1148/radiol.212780] [Citation(s) in RCA: 25] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2021] [Revised: 10/01/2022] [Accepted: 10/14/2022] [Indexed: 01/25/2023]
Abstract
A leading cause of white matter (WM) injury in older individuals is cerebral small vessel disease (SVD). Cerebral SVD is the most prevalent vascular contributor to cognitive impairment and dementia. Therapeutic progress for cerebral SVD and other WM disorders depends on the development and validation of neuroimaging markers suitable as outcome measures in future interventional trials. Diffusion-tensor imaging (DTI) is one of the best-suited MRI techniques for assessing the extent of WM damage in the brain. But the optimal method to analyze individual DTI data remains hindered by labor-intensive and time-consuming processes. Peak width of skeletonized mean diffusivity (PSMD), a recently developed fast, fully automated DTI marker, was designed to quantify the WM damage secondary to cerebral SVD and reflect related cognitive impairment. Despite its promising results, knowledge about PSMD is still limited in the radiologic community. This focused review provides an overview of the technical details of PSMD while synthesizing the available data on its clinical and neuroimaging associations. From a critical expert viewpoint, the authors discuss the limitations of PSMD and its current validation status as a neuroimaging marker for vascular cognitive impairment. Finally, they point out the gaps to be addressed to further advance the field.
Collapse
Affiliation(s)
| | | | - Lukas Sveikata
- From the J. Philip Kistler Stroke Research Center, Department of
Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass
(M.C.Z.Z., P.Y., L.S., D.S., S.J.v.V., M.R.E., A.C., S.M.G., A.V.); Center for
Imaging Sciences and Medical Physics, Department of Medical Imaging, Hematology
and Clinical Oncology, Ribeirão Preto Medical School, University of
São Paulo, 3900 Ten. Catão Roxo Street, Monte Alegre, Campus
Universitário, Ribeirão Preto, SP 14015-010, Brazil (M.C.Z.Z.);
Departments of Epidemiology and Radiology and Nuclear Medicine, Erasmus Medical
Center, Rotterdam, the Netherlands (P.Y.); Division of Neurology, Department of
Clinical Neurosciences, Geneva University Hospital, Faculty of Medicine,
University of Geneva, Geneva, Switzerland (L.S.); Institute of Cardiology,
Medical Academy, Lithuanian University of Health Sciences, Kaunas, Lithuania
(L.S.); and Medical Image Analysis Center (MIAC AG) and Quantitative Biomedical
Imaging Group (qbig), Department of Biomedical Engineering, University of Basel,
Basel, Switzerland (M.D.)
| | - Dorothee Schoemaker
- From the J. Philip Kistler Stroke Research Center, Department of
Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass
(M.C.Z.Z., P.Y., L.S., D.S., S.J.v.V., M.R.E., A.C., S.M.G., A.V.); Center for
Imaging Sciences and Medical Physics, Department of Medical Imaging, Hematology
and Clinical Oncology, Ribeirão Preto Medical School, University of
São Paulo, 3900 Ten. Catão Roxo Street, Monte Alegre, Campus
Universitário, Ribeirão Preto, SP 14015-010, Brazil (M.C.Z.Z.);
Departments of Epidemiology and Radiology and Nuclear Medicine, Erasmus Medical
Center, Rotterdam, the Netherlands (P.Y.); Division of Neurology, Department of
Clinical Neurosciences, Geneva University Hospital, Faculty of Medicine,
University of Geneva, Geneva, Switzerland (L.S.); Institute of Cardiology,
Medical Academy, Lithuanian University of Health Sciences, Kaunas, Lithuania
(L.S.); and Medical Image Analysis Center (MIAC AG) and Quantitative Biomedical
Imaging Group (qbig), Department of Biomedical Engineering, University of Basel,
Basel, Switzerland (M.D.)
| | - Susanne J. van Veluw
- From the J. Philip Kistler Stroke Research Center, Department of
Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass
(M.C.Z.Z., P.Y., L.S., D.S., S.J.v.V., M.R.E., A.C., S.M.G., A.V.); Center for
Imaging Sciences and Medical Physics, Department of Medical Imaging, Hematology
and Clinical Oncology, Ribeirão Preto Medical School, University of
São Paulo, 3900 Ten. Catão Roxo Street, Monte Alegre, Campus
Universitário, Ribeirão Preto, SP 14015-010, Brazil (M.C.Z.Z.);
Departments of Epidemiology and Radiology and Nuclear Medicine, Erasmus Medical
Center, Rotterdam, the Netherlands (P.Y.); Division of Neurology, Department of
Clinical Neurosciences, Geneva University Hospital, Faculty of Medicine,
University of Geneva, Geneva, Switzerland (L.S.); Institute of Cardiology,
Medical Academy, Lithuanian University of Health Sciences, Kaunas, Lithuania
(L.S.); and Medical Image Analysis Center (MIAC AG) and Quantitative Biomedical
Imaging Group (qbig), Department of Biomedical Engineering, University of Basel,
Basel, Switzerland (M.D.)
| | - Mark R. Etherton
- From the J. Philip Kistler Stroke Research Center, Department of
Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass
(M.C.Z.Z., P.Y., L.S., D.S., S.J.v.V., M.R.E., A.C., S.M.G., A.V.); Center for
Imaging Sciences and Medical Physics, Department of Medical Imaging, Hematology
and Clinical Oncology, Ribeirão Preto Medical School, University of
São Paulo, 3900 Ten. Catão Roxo Street, Monte Alegre, Campus
Universitário, Ribeirão Preto, SP 14015-010, Brazil (M.C.Z.Z.);
Departments of Epidemiology and Radiology and Nuclear Medicine, Erasmus Medical
Center, Rotterdam, the Netherlands (P.Y.); Division of Neurology, Department of
Clinical Neurosciences, Geneva University Hospital, Faculty of Medicine,
University of Geneva, Geneva, Switzerland (L.S.); Institute of Cardiology,
Medical Academy, Lithuanian University of Health Sciences, Kaunas, Lithuania
(L.S.); and Medical Image Analysis Center (MIAC AG) and Quantitative Biomedical
Imaging Group (qbig), Department of Biomedical Engineering, University of Basel,
Basel, Switzerland (M.D.)
| | - Andreas Charidimou
- From the J. Philip Kistler Stroke Research Center, Department of
Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass
(M.C.Z.Z., P.Y., L.S., D.S., S.J.v.V., M.R.E., A.C., S.M.G., A.V.); Center for
Imaging Sciences and Medical Physics, Department of Medical Imaging, Hematology
and Clinical Oncology, Ribeirão Preto Medical School, University of
São Paulo, 3900 Ten. Catão Roxo Street, Monte Alegre, Campus
Universitário, Ribeirão Preto, SP 14015-010, Brazil (M.C.Z.Z.);
Departments of Epidemiology and Radiology and Nuclear Medicine, Erasmus Medical
Center, Rotterdam, the Netherlands (P.Y.); Division of Neurology, Department of
Clinical Neurosciences, Geneva University Hospital, Faculty of Medicine,
University of Geneva, Geneva, Switzerland (L.S.); Institute of Cardiology,
Medical Academy, Lithuanian University of Health Sciences, Kaunas, Lithuania
(L.S.); and Medical Image Analysis Center (MIAC AG) and Quantitative Biomedical
Imaging Group (qbig), Department of Biomedical Engineering, University of Basel,
Basel, Switzerland (M.D.)
| | - Steven M. Greenberg
- From the J. Philip Kistler Stroke Research Center, Department of
Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass
(M.C.Z.Z., P.Y., L.S., D.S., S.J.v.V., M.R.E., A.C., S.M.G., A.V.); Center for
Imaging Sciences and Medical Physics, Department of Medical Imaging, Hematology
and Clinical Oncology, Ribeirão Preto Medical School, University of
São Paulo, 3900 Ten. Catão Roxo Street, Monte Alegre, Campus
Universitário, Ribeirão Preto, SP 14015-010, Brazil (M.C.Z.Z.);
Departments of Epidemiology and Radiology and Nuclear Medicine, Erasmus Medical
Center, Rotterdam, the Netherlands (P.Y.); Division of Neurology, Department of
Clinical Neurosciences, Geneva University Hospital, Faculty of Medicine,
University of Geneva, Geneva, Switzerland (L.S.); Institute of Cardiology,
Medical Academy, Lithuanian University of Health Sciences, Kaunas, Lithuania
(L.S.); and Medical Image Analysis Center (MIAC AG) and Quantitative Biomedical
Imaging Group (qbig), Department of Biomedical Engineering, University of Basel,
Basel, Switzerland (M.D.)
| | - Marco Duering
- From the J. Philip Kistler Stroke Research Center, Department of
Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass
(M.C.Z.Z., P.Y., L.S., D.S., S.J.v.V., M.R.E., A.C., S.M.G., A.V.); Center for
Imaging Sciences and Medical Physics, Department of Medical Imaging, Hematology
and Clinical Oncology, Ribeirão Preto Medical School, University of
São Paulo, 3900 Ten. Catão Roxo Street, Monte Alegre, Campus
Universitário, Ribeirão Preto, SP 14015-010, Brazil (M.C.Z.Z.);
Departments of Epidemiology and Radiology and Nuclear Medicine, Erasmus Medical
Center, Rotterdam, the Netherlands (P.Y.); Division of Neurology, Department of
Clinical Neurosciences, Geneva University Hospital, Faculty of Medicine,
University of Geneva, Geneva, Switzerland (L.S.); Institute of Cardiology,
Medical Academy, Lithuanian University of Health Sciences, Kaunas, Lithuania
(L.S.); and Medical Image Analysis Center (MIAC AG) and Quantitative Biomedical
Imaging Group (qbig), Department of Biomedical Engineering, University of Basel,
Basel, Switzerland (M.D.)
| | - Anand Viswanathan
- From the J. Philip Kistler Stroke Research Center, Department of
Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass
(M.C.Z.Z., P.Y., L.S., D.S., S.J.v.V., M.R.E., A.C., S.M.G., A.V.); Center for
Imaging Sciences and Medical Physics, Department of Medical Imaging, Hematology
and Clinical Oncology, Ribeirão Preto Medical School, University of
São Paulo, 3900 Ten. Catão Roxo Street, Monte Alegre, Campus
Universitário, Ribeirão Preto, SP 14015-010, Brazil (M.C.Z.Z.);
Departments of Epidemiology and Radiology and Nuclear Medicine, Erasmus Medical
Center, Rotterdam, the Netherlands (P.Y.); Division of Neurology, Department of
Clinical Neurosciences, Geneva University Hospital, Faculty of Medicine,
University of Geneva, Geneva, Switzerland (L.S.); Institute of Cardiology,
Medical Academy, Lithuanian University of Health Sciences, Kaunas, Lithuania
(L.S.); and Medical Image Analysis Center (MIAC AG) and Quantitative Biomedical
Imaging Group (qbig), Department of Biomedical Engineering, University of Basel,
Basel, Switzerland (M.D.)
| |
Collapse
|
16
|
Zanon Zotin MC, Schoemaker D, Raposo N, Perosa V, Bretzner M, Sveikata L, Li Q, van Veluw SJ, Horn MJ, Etherton MR, Charidimou A, Gurol ME, Greenberg SM, Duering M, dos Santos AC, Pontes-Neto OM, Viswanathan A. Peak width of skeletonized mean diffusivity in cerebral amyloid angiopathy: Spatial signature, cognitive, and neuroimaging associations. Front Neurosci 2022; 16:1051038. [PMID: 36440281 PMCID: PMC9693722 DOI: 10.3389/fnins.2022.1051038] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2022] [Accepted: 10/25/2022] [Indexed: 11/13/2022] Open
Abstract
Background Peak width of skeletonized mean diffusivity (PSMD) is a promising diffusion tensor imaging (DTI) marker that shows consistent and strong cognitive associations in the context of different cerebral small vessel diseases (cSVD). Purpose Investigate whether PSMD (1) is higher in patients with Cerebral Amyloid Angiopathy (CAA) than those with arteriolosclerosis; (2) can capture the anteroposterior distribution of CAA-related abnormalities; (3) shows similar neuroimaging and cognitive associations in comparison to other classical DTI markers, such as average mean diffusivity (MD) and fractional anisotropy (FA). Materials and methods We analyzed cross-sectional neuroimaging and neuropsychological data from 90 non-demented memory-clinic subjects from a single center. Based on MRI findings, we classified them into probable-CAA (those that fulfilled the modified Boston criteria), subjects with MRI markers of cSVD not attributable to CAA (presumed arteriolosclerosis; cSVD), and subjects without evidence of cSVD on MRI (non-cSVD). We compared total and lobe-specific (frontal and occipital) DTI metrics values across the groups. We used linear regression models to investigate how PSMD, MD, and FA correlate with conventional neuroimaging markers of cSVD and cognitive scores in CAA. Results PSMD was comparable in probable-CAA (median 4.06 × 10–4 mm2/s) and cSVD (4.07 × 10–4 mm2/s) patients, but higher than in non-cSVD (3.30 × 10–4 mm2/s; p < 0.001) subjects. Occipital-frontal PSMD gradients were higher in probable-CAA patients, and we observed a significant interaction between diagnosis and region on PSMD values [F(2, 87) = 3.887, p = 0.024]. PSMD was mainly associated with white matter hyperintensity volume, whereas MD and FA were also associated with other markers, especially with the burden of perivascular spaces. PSMD correlated with worse executive function (β = −0.581, p < 0.001) and processing speed (β = −0.463, p = 0.003), explaining more variance than other MRI markers. MD and FA were not associated with performance in any cognitive domain. Conclusion PSMD is a promising biomarker of cognitive impairment in CAA that outperforms other conventional and DTI-based neuroimaging markers. Although global PSMD is similarly increased in different forms of cSVD, PSMD’s spatial variations could potentially provide insights into the predominant type of underlying microvascular pathology.
Collapse
Affiliation(s)
- Maria Clara Zanon Zotin
- J. Philip Kistler Stroke Research Center, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States
- Center for Imaging Sciences and Medical Physics, Department of Medical Imaging, Hematology and Clinical Oncology, Ribeirão Preto Medical School, University of São Paulo, Ribeirão Preto, Brazil
- *Correspondence: Maria Clara Zanon Zotin, ,
| | - Dorothee Schoemaker
- Department of Psychiatry, Harvard Medical School, Massachusetts General Hospital, Boston, MA, United States
| | - Nicolas Raposo
- Toulouse NeuroImaging Center, Université de Toulouse, Inserm, UPS, Toulouse, France
| | | | - Martin Bretzner
- J. Philip Kistler Stroke Research Center, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States
- University of Lille, Inserm, CHU Lille, U1172 - LilNCog (JPARC) - Lille Neurosciences & Cognition, Lille, France
| | - Lukas Sveikata
- J. Philip Kistler Stroke Research Center, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States
- Division of Neurology, Department of Clinical Neurosciences, Geneva University Hospitals, Geneva, Switzerland
- Institute of Cardiology, Medical Academy, Lithuanian University of Health Sciences, Kaunas, Lithuania
| | - Qi Li
- The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Susanne J. van Veluw
- J. Philip Kistler Stroke Research Center, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States
| | - Mitchell J. Horn
- J. Philip Kistler Stroke Research Center, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States
| | - Mark R. Etherton
- J. Philip Kistler Stroke Research Center, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States
| | - Andreas Charidimou
- J. Philip Kistler Stroke Research Center, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States
- Department of Neurology, Boston University School of Medicine, Boston University Medical Center, Boston, MA, United States
| | - M. Edip Gurol
- J. Philip Kistler Stroke Research Center, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States
| | - Steven M. Greenberg
- J. Philip Kistler Stroke Research Center, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States
| | - Marco Duering
- Department of Biomedical Engineering, Medical Imaging Analysis Center (MIAC), University of Basel, Basel, Switzerland
| | - Antonio Carlos dos Santos
- Center for Imaging Sciences and Medical Physics, Department of Medical Imaging, Hematology and Clinical Oncology, Ribeirão Preto Medical School, University of São Paulo, Ribeirão Preto, Brazil
| | - Octavio M. Pontes-Neto
- Department of Neuroscience and Behavioral Sciences, Ribeirão Preto Medical School, University of São Paulo, Ribeirão Preto, Brazil
| | - Anand Viswanathan
- J. Philip Kistler Stroke Research Center, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States
| |
Collapse
|
17
|
Sun Y, Hu Y, Qiu Y, Zhang Y, Jiang C, Lu P, Xu Q, Shi Y, Wei H, Zhou Y. Characterization of white matter over 1–2 years in small vessel disease using MR-based quantitative susceptibility mapping and free-water mapping. Front Aging Neurosci 2022; 14:998051. [PMID: 36247993 PMCID: PMC9562046 DOI: 10.3389/fnagi.2022.998051] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2022] [Accepted: 09/07/2022] [Indexed: 11/13/2022] Open
Abstract
PurposeThe aim of this study was to investigate alterations in white matter lesions (WMLs) and normal-appearing white matter (NAWM) with small vessel disease (SVD) over 1–2 years using quantitative susceptibility mapping (QSM) and free-water (FW) mapping.MethodsFifty-one SVD patients underwent MRI brain scans and neuropsychological testing both at baseline and follow-up. The main approach for treating these patients is the management of risk factors. Quantitative susceptibility (QS), fractional anisotropy (FA), mean diffusivity (MD), FW, FW-corrected FA (FAT), and FW-corrected MD (MDT) maps within WMLs and NAWM were generated. Furthermore, the JHU-ICBM-DTI label atlas was used as an anatomic guide, and the measurements of the segmented NAWMs were calculated. The average regional values were extracted, and a paired t-test was used to analyze the longitudinal change. Partial correlations were used to assess the relationship between the MRI indices changes (e.g., ΔQSfollowup − baseline/QSbaseline) and the cognitive function changes (e.g., ΔMoCAfollowup − baseline/MoCAbaseline).ResultsAfter SVD risk factor control, no gradual cognitive decline occurred during 1–2 years. However, we still found that the QS values (index of demyelination) increased in the NAWM at follow-up, especially in the NAWM part of the left superior frontal blade (SF), left occipital blade, right uncinate fasciculus, and right corticospinal tract (CST). FW (index of neuroinflammation/edema) analysis revealed that the follow-up group differed from the baseline group in the NAWM part of the right CST and inferior frontal blade (IF). Decreased FAT (index of axonal loss) was observed in the NAWM part of the right SF and IF at follow-up. In addition, the FAT changes in the NAWM part of the right IF were associated with overall cognitive performance changes. In contrast, no significant differences were found in the WMLs.ConclusionThe NAWM was still in the progressive injury process over time, while WMLs remained relatively stable, which supports the notion that SVD is a chronic progressive disease. The process of axonal loss in the NAWM part of the prefrontal lobe might be a biomarker of cognitive changes in the evolution of SVD.
Collapse
Affiliation(s)
- Yawen Sun
- Department of Radiology, School of Medicine, Ren Ji Hospital, Shanghai Jiao Tong University, Shanghai, China
| | - Ying Hu
- Department of Radiology, School of Medicine, Ren Ji Hospital, Shanghai Jiao Tong University, Shanghai, China
| | - Yage Qiu
- Department of Radiology, School of Medicine, Ren Ji Hospital, Shanghai Jiao Tong University, Shanghai, China
| | - Yuyao Zhang
- School of Information and Science and Technology, ShanghaiTech University, Shanghai, China
| | - Changhao Jiang
- School of Information and Science and Technology, ShanghaiTech University, Shanghai, China
| | - Peiwen Lu
- Department of Neurology, School of Medicine, Ren Ji Hospital, Shanghai Jiao Tong University, Shanghai, China
- Ren Ji-UNSW CHeBA Neurocognitive Center, School of Medicine, Ren Ji Hospital, Shanghai Jiao Tong University, Shanghai, China
| | - Qun Xu
- Department of Neurology, School of Medicine, Ren Ji Hospital, Shanghai Jiao Tong University, Shanghai, China
- Ren Ji-UNSW CHeBA Neurocognitive Center, School of Medicine, Ren Ji Hospital, Shanghai Jiao Tong University, Shanghai, China
- Department of Health Manage Center, School of Medicine, Ren Ji Hospital, Shanghai Jiao Tong University, Shanghai, China
| | - Yuting Shi
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Hongjiang Wei
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
- *Correspondence: Yan Zhou
| | - Yan Zhou
- Department of Radiology, School of Medicine, Ren Ji Hospital, Shanghai Jiao Tong University, Shanghai, China
- Hongjiang Wei
| |
Collapse
|
18
|
Shaikh I, Beaulieu C, Gee M, McCreary CR, Beaudin AE, Valdés-Cabrera D, Smith EE, Camicioli R. Diffusion tensor tractography of the fornix in cerebral amyloid angiopathy, mild cognitive impairment and Alzheimer's disease. Neuroimage Clin 2022; 34:103002. [PMID: 35413649 PMCID: PMC9010796 DOI: 10.1016/j.nicl.2022.103002] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2021] [Revised: 03/26/2022] [Accepted: 04/02/2022] [Indexed: 11/16/2022]
Abstract
The fornix was delineated with deterministic tractography from diffusion tensor images (DTI). Fornix diffusion changes were found in the fornix in CAA, AD and MCI compared to controls. Higher fornix diffusivity correlated with smaller hippocampal volume and larger ventricles. Fornix diffusion measures correlated with cognitive measures in the combined disease groups.
Purpose Cerebral amyloid angiopathy (CAA) is a common neuropathological finding and clinical entity that occurs independently and with co-existent Alzheimer’s disease (AD) and small vessel disease. We compared diffusion tensor imaging (DTI) metrics of the fornix, the primary efferent tract of the hippocampus between CAA, AD and Mild Cognitive Impairment (MCI) and healthy controls. Methods Sixty-eight healthy controls, 32 CAA, 21 AD, and 26 MCI patients were recruited at two centers. Diffusion tensor images were acquired at 3 T with high spatial resolution and fluid-attenuated inversion recovery (FLAIR) to suppress cerebrospinal fluid (CSF) and minimize partial volume effects on the fornix. The fornix was delineated with deterministic tractography to yield mean diffusivity (MD), axial diffusivity (AXD), radial diffusivity (RD), fractional anisotropy (FA) and tract volume. Volumetric measurements of the hippocampus, thalamus, and lateral ventricles were obtained using T1-weighted MRI. Results Diffusivity (MD, AXD, and RD) of the fornix was highest in AD followed by CAA compared to controls; the MCI group was not significantly different from controls. FA was similar between groups. Fornix tract volume was ∼ 30% lower for all three patient groups compared to controls, but not significantly different between the patient groups. Thalamic and hippocampal volumes were preserved in CAA, but lower in AD and MCI compared to controls. Lateral ventricular volumes were increased in CAA, AD and MCI. Global cognition, memory, and executive function all correlated negatively with fornix diffusivity across the combined clinical group. Conclusion There were significant diffusion changes of the fornix in CAA, AD and MCI compared to controls, despite relatively intact thalamic and hippocampal volumes in CAA, suggesting the mechanisms for fornix diffusion abnormalities may differ in CAA compared to AD and MCI.
Collapse
Affiliation(s)
- Ibrahim Shaikh
- Department of Medicine, Division of Neurology and Neuroscience and Mental Health Institute (NMHI), University of Alberta, Edmonton, AB, Canada; Department of Biomedical Engineering, University of Alberta, Edmonton, AB, Canada
| | - Christian Beaulieu
- Department of Biomedical Engineering, University of Alberta, Edmonton, AB, Canada
| | - Myrlene Gee
- Department of Medicine, Division of Neurology and Neuroscience and Mental Health Institute (NMHI), University of Alberta, Edmonton, AB, Canada
| | - Cheryl R McCreary
- Department of Radiology, University of Calgary, Calgary, AB, Canada; Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada; Department of Clinical Neurosciences, University of Calgary, Calgary, AB, Canada; Seaman Family MR Research Centre, Foothills Medical Centre, Alberta Health Services, Calgary, AB, Canada
| | - Andrew E Beaudin
- Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada; Department of Clinical Neurosciences, University of Calgary, Calgary, AB, Canada
| | - Diana Valdés-Cabrera
- Department of Biomedical Engineering, University of Alberta, Edmonton, AB, Canada
| | - Eric E Smith
- Department of Radiology, University of Calgary, Calgary, AB, Canada; Seaman Family MR Research Centre, Foothills Medical Centre, Alberta Health Services, Calgary, AB, Canada
| | - Richard Camicioli
- Department of Medicine, Division of Neurology and Neuroscience and Mental Health Institute (NMHI), University of Alberta, Edmonton, AB, Canada.
| |
Collapse
|
19
|
Freeze WM, Zanon Zotin MC, Scherlek AA, Perosa V, Auger CA, Warren AD, van der Weerd L, Schoemaker D, Horn MJ, Gurol ME, Gokcal E, Bacskai BJ, Viswanathan A, Greenberg SM, Reijmer YD, van Veluw SJ. Corpus callosum lesions are associated with worse cognitive performance in cerebral amyloid angiopathy. Brain Commun 2022; 4:fcac105. [PMID: 35611313 PMCID: PMC9123849 DOI: 10.1093/braincomms/fcac105] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2021] [Revised: 02/20/2022] [Accepted: 04/21/2022] [Indexed: 11/19/2022] Open
Abstract
The impact of vascular lesions on cognition is location dependent. Here, we assessed the contribution of small vessel disease lesions in the corpus callosum to vascular cognitive impairment in cerebral amyloid angiopathy, as a model for cerebral small vessel disease. Sixty-five patients with probable cerebral amyloid angiopathy underwent 3T magnetic resonance imaging, including a diffusion tensor imaging scan, and neuropsychological testing. Microstructural white-matter integrity was quantified by fractional anisotropy and mean diffusivity. Z-scores on individual neuropsychological tests were averaged into five cognitive domains: information processing speed, executive functioning, memory, language and visuospatial ability. Corpus callosum lesions were defined as haemorrhagic (microbleeds or larger bleeds) or ischaemic (microinfarcts, larger infarcts and diffuse fluid-attenuated inversion recovery hyperintensities). Associations between corpus callosum lesion presence, microstructural white-matter integrity and cognitive performance were examined with multiple regression models. The prevalence of corpus callosum lesions was confirmed in an independent cohort of memory clinic patients with and without cerebral amyloid angiopathy (n = 82). In parallel, we assessed corpus callosum lesions on ex vivo magnetic resonance imaging in cerebral amyloid angiopathy patients (n = 19) and controls (n = 5) and determined associated tissue abnormalities with histopathology. A total number of 21 corpus callosum lesions was found in 19/65 (29%) cerebral amyloid angiopathy patients. Corpus callosum lesion presence was associated with reduced microstructural white-matter integrity within the corpus callosum and in the whole-brain white matter. Patients with corpus callosum lesions performed significantly worse on all cognitive domains except language, compared with those without corpus callosum lesions after correcting for age, sex, education and time between magnetic resonance imaging and neuropsychological assessment. This association was independent of the presence of intracerebral haemorrhage, whole-brain fractional anisotropy and mean diffusivity, and white-matter hyperintensity volume and brain volume for the domains of information processing speed and executive functioning. In the memory clinic patient cohort, corpus callosum lesions were present in 14/54 (26%) patients with probable and 2/8 (25%) patients with possible cerebral amyloid angiopathy, and in 3/20 (15%) patients without cerebral amyloid angiopathy. In the ex vivo cohort, corpus callosum lesions were present in 10/19 (53%) patients and 2/5 (40%) controls. On histopathology, ischaemic corpus callosum lesions were associated with tissue loss and demyelination, which extended beyond the lesion core. Together, these data suggest that corpus callosum lesions are a frequent finding in cerebral amyloid angiopathy, and that they independently contribute to cognitive impairment through strategic microstructural disruption of white-matter tracts.
Collapse
Affiliation(s)
- Whitney M. Freeze
- Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
- Department of Neuropsychology and Psychiatry, Maastricht University, Maastricht, The Netherlands
| | - Maria Clara Zanon Zotin
- Department of Neurology, J. Philip Kistler Stroke Research Center, Massachusetts General Hospital, Boston, MA, USA
- Department of Medical Imaging, Hematology and Clinical Oncology, Ribeirão Preto Medical School, USP, SP, Brazil
| | - Ashley A. Scherlek
- MassGeneral Institute for Neurodegenerative Disease, Massachusetts General Hospital, Charlestown, MA 02129, USA
| | - Valentina Perosa
- Department of Neurology, J. Philip Kistler Stroke Research Center, Massachusetts General Hospital, Boston, MA, USA
| | - Corinne A. Auger
- MassGeneral Institute for Neurodegenerative Disease, Massachusetts General Hospital, Charlestown, MA 02129, USA
| | - Andrew D. Warren
- Department of Neurology, J. Philip Kistler Stroke Research Center, Massachusetts General Hospital, Boston, MA, USA
| | - Louise van der Weerd
- Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
| | | | - Mitchell J. Horn
- Department of Neurology, J. Philip Kistler Stroke Research Center, Massachusetts General Hospital, Boston, MA, USA
| | - M. Edip Gurol
- Department of Neurology, J. Philip Kistler Stroke Research Center, Massachusetts General Hospital, Boston, MA, USA
| | - Elif Gokcal
- Department of Neurology, J. Philip Kistler Stroke Research Center, Massachusetts General Hospital, Boston, MA, USA
| | - Brian J. Bacskai
- MassGeneral Institute for Neurodegenerative Disease, Massachusetts General Hospital, Charlestown, MA 02129, USA
| | - Anand Viswanathan
- Department of Neurology, J. Philip Kistler Stroke Research Center, Massachusetts General Hospital, Boston, MA, USA
| | - Steven M. Greenberg
- Department of Neurology, J. Philip Kistler Stroke Research Center, Massachusetts General Hospital, Boston, MA, USA
| | - Yael D. Reijmer
- Department of Neurology, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Susanne J. van Veluw
- Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
- Department of Neurology, J. Philip Kistler Stroke Research Center, Massachusetts General Hospital, Boston, MA, USA
- MassGeneral Institute for Neurodegenerative Disease, Massachusetts General Hospital, Charlestown, MA 02129, USA
| |
Collapse
|
20
|
van Veluw SJ, Arfanakis K, Schneider JA. Neuropathology of Vascular Brain Health: Insights From Ex Vivo Magnetic Resonance Imaging-Histopathology Studies in Cerebral Small Vessel Disease. Stroke 2022; 53:404-415. [PMID: 35000425 PMCID: PMC8830602 DOI: 10.1161/strokeaha.121.032608] [Citation(s) in RCA: 32] [Impact Index Per Article: 10.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Abstract
Sporadic cerebral small vessel disease (SVD) is a major contributor to vascular cognitive impairment and dementia in the aging human brain. On neuropathology, sporadic SVD is characterized by abnormalities to the small vessels of the brain predominantly in the form of cerebral amyloid angiopathy and arteriolosclerosis. These pathologies frequently coexist with Alzheimer disease changes, such as plaques and tangles, in a single brain. Conversely, during life, magnetic resonance imaging (MRI) only captures the larger manifestations of SVD in the form of parenchymal brain abnormalities. There appears to be a major knowledge gap regarding the underlying neuropathology of individual MRI-detectable SVD abnormalities. Ex vivo MRI in postmortem human brain tissue is a powerful tool to bridge this gap. This review summarizes current insights into the histopathologic correlations of MRI manifestations of SVD, their underlying cause, presumed pathophysiology, and associated secondary tissue injury. Moreover, we discuss the advantages and limitations of ex vivo MRI-guided histopathologic investigations and make recommendations for future studies.
Collapse
Affiliation(s)
- Susanne J. van Veluw
- J. Philip Kistler Stroke Research Center, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA,MassGeneral Institute for Neurodegenerative Disease, Massachusetts General Hospital, Charlestown, MA, USA,Department of Radiology, Leiden University Medical Center, Leiden, the Netherlands
| | - Konstantinos Arfanakis
- Department of Biomedical Engineering, Illinois Institute of Technology, Chicago, IL, USA,Rush Alzheimer’s Disease Center, Rush University Medical Center, Chicago, IL, USA
| | - Julie A. Schneider
- Rush Alzheimer’s Disease Center, Rush University Medical Center, Chicago, IL, USA,Departments of Pathology and Neurological Sciences, Rush University Medical Center, Chicago IL, USA
| |
Collapse
|
21
|
García-Morales V, González-Acedo A, Melguizo-Rodríguez L, Pardo-Moreno T, Costela-Ruiz VJ, Montiel-Troya M, Ramos-Rodríguez JJ. Current Understanding of the Physiopathology, Diagnosis and Therapeutic Approach to Alzheimer's Disease. Biomedicines 2021; 9:1910. [PMID: 34944723 PMCID: PMC8698840 DOI: 10.3390/biomedicines9121910] [Citation(s) in RCA: 37] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2021] [Revised: 12/08/2021] [Accepted: 12/10/2021] [Indexed: 02/06/2023] Open
Abstract
Alzheimer's disease (AD) is the most common cause of dementia. It is characterized by cognitive decline and progressive memory loss. The aim of this review was to update the state of knowledge on the pathophysiological mechanisms, diagnostic methods and therapeutic approach to AD. Currently, the amyloid cascade hypothesis remains the leading theory in the pathophysiology of AD. This hypothesis states that amyloid-β (Aβ) deposition triggers a chemical cascade of events leading to the development of AD dementia. The antemortem diagnosis of AD is still based on clinical parameters. Diagnostic procedures in AD include fluid-based biomarkers such as those present in cerebrospinal fluid and plasma or diagnostic imaging methods. Currently, the therapeutic armory available focuses on symptom control and is based on four pillars: pharmacological treatment where acetylcholinesterase inhibitors stand out; pharmacological treatment under investigation which includes drugs focused on the control of Aβ pathology and tau hyperphosphorylation; treatment focusing on risk factors such as diabetes; or nonpharmacological treatments aimed at preventing development of the disease or treating symptoms through occupational therapy or psychological help. AD remains a largely unknown disease. Further research is needed to identify new biomarkers and therapies that can prevent progression of the pathology.
Collapse
Affiliation(s)
- Victoria García-Morales
- Department of Biomedicine, Biotechnology and Public Health, Physiology Area, Faculty of Medicine, University of Cádiz, 11003 Cádiz, Spain;
| | - Anabel González-Acedo
- Biomedical Group (BIO277), Department of Nursing, Faculty of Health Sciences, University of Granada, 18016 Granada, Spain; (A.G.-A.); (V.J.C.-R.)
| | - Lucía Melguizo-Rodríguez
- Biomedical Group (BIO277), Department of Nursing, Faculty of Health Sciences, University of Granada, 18016 Granada, Spain; (A.G.-A.); (V.J.C.-R.)
- Instituto de Investigación Biosanitaria, Ibs Granada, 18012 Granada, Spain
| | - Teresa Pardo-Moreno
- Instituto Nacional de Gestión Sanitaria (INGESA), Primary Health Care, 51003 Ceuta, Spain;
| | - Víctor Javier Costela-Ruiz
- Biomedical Group (BIO277), Department of Nursing, Faculty of Health Sciences, University of Granada, 18016 Granada, Spain; (A.G.-A.); (V.J.C.-R.)
- Instituto de Investigación Biosanitaria, Ibs Granada, 18012 Granada, Spain
| | - María Montiel-Troya
- Department of Nursing, Faculty of Health Sciences (Ceuta), University of Granada, 51001 Ceuta, Spain;
| | - Juan José Ramos-Rodríguez
- Department of Physiology, Faculty of Health Sciences (Ceuta), University of Granada, 51001 Ceuta, Spain;
| |
Collapse
|
22
|
Li H, Zhang Q, Duan Q, Jin J, Hu F, Dang J, Zhang M. Brainstem Involvement in Amyotrophic Lateral Sclerosis: A Combined Structural and Diffusion Tensor MRI Analysis. Front Neurosci 2021; 15:675444. [PMID: 34149349 PMCID: PMC8206526 DOI: 10.3389/fnins.2021.675444] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2021] [Accepted: 04/12/2021] [Indexed: 12/13/2022] Open
Abstract
Introduction The brainstem is an important component in the pathology of amyotrophic lateral sclerosis (ALS). Although neuroimaging studies have shown multiple structural changes in ALS patients, few studies have investigated structural alterations in the brainstem. Herein, we compared the brainstem structure between patients with ALS and healthy controls. Methods A total of 33 patients with ALS and 33 healthy controls were recruited in this study. T1-weighted and diffusion tensor imaging (DTI) were acquired on a 3 Tesla magnetic resonance imaging (3T MRI) scanner. Volumetric and vertex-wised approaches were implemented to assess the differences in the brainstem’s morphological features between the two groups. An atlas-based region of interest (ROI) analysis was performed to compare the white matter integrity of the brainstem between the two groups. Additionally, a correlation analysis was used to evaluate the relationship between ALS clinical characteristics and structural features. Results Volumetric analyses showed no significant difference in the subregion volume of the brainstem between ALS patients and healthy controls. In the shape analyses, ALS patients had a local abnormal surface contraction in the ventral medulla oblongata and ventral pons. Compared with healthy controls, ALS patients showed significantly lower fractional anisotropy (FA) in the left corticospinal tract (CST) and bilateral frontopontine tracts (FPT) at the brainstem level, and higher radial diffusivity (RD) in bilateral CST and left FPT at the brainstem level by ROI analysis in DTI. Correlation analysis showed that disease severity was positively associated with FA in left CST and left FPT. Conclusion These findings suggest that the brainstem in ALS suffers atrophy, and degenerative processes in the brainstem may reflect disease severity in ALS. These findings may be helpful for further understanding of potential neural mechanisms in ALS.
Collapse
Affiliation(s)
- Haining Li
- Department of Medical Imaging, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Qiuli Zhang
- Department of Medical Imaging, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Qianqian Duan
- Department of Medical Imaging, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Jiaoting Jin
- Department of Neurology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Fangfang Hu
- Department of Neurology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Jingxia Dang
- Department of Neurology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Ming Zhang
- Department of Medical Imaging, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| |
Collapse
|
23
|
James SN, Nicholas JM, Lane CA, Parker TD, Lu K, Keshavan A, Buchanan SM, Keuss SE, Murray-Smith H, Wong A, Cash DM, Malone IB, Barnes J, Sudre CH, Coath W, Prosser L, Ourselin S, Modat M, Thomas DL, Cardoso J, Heslegrave A, Zetterberg H, Crutch SJ, Schott JM, Richards M, Fox NC. A population-based study of head injury, cognitive function and pathological markers. Ann Clin Transl Neurol 2021; 8:842-856. [PMID: 33694298 PMCID: PMC8045921 DOI: 10.1002/acn3.51331] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2021] [Accepted: 02/12/2021] [Indexed: 02/01/2023] Open
Abstract
Objective To assess associations between head injury (HI) with loss of consciousness (LOC), ageing and markers of later‐life cerebral pathology; and to explore whether those effects may help explain subtle cognitive deficits in dementia‐free individuals. Methods Participants (n = 502, age = 69–71) from the 1946 British Birth Cohort underwent cognitive testing (subtests of Preclinical Alzheimer Cognitive Composite), 18F‐florbetapir Aβ‐PET and MR imaging. Measures include Aβ‐PET status, brain, hippocampal and white matter hyperintensity (WMH) volumes, normal appearing white matter (NAWM) microstructure, Alzheimer’s disease (AD)‐related cortical thickness, and serum neurofilament light chain (NFL). LOC HI metrics include HI occurring: (i) >15 years prior to the scan (ii) anytime up to age 71. Results Compared to those with no evidence of an LOC HI, only those reporting an LOC HI>15 years prior (16%, n = 80) performed worse on cognitive tests at age 69–71, taking into account premorbid cognition, particularly on the digit‐symbol substitution test (DSST). Smaller brain volume (BV) and adverse NAWM microstructural integrity explained 30% and 16% of the relationship between HI and DSST, respectively. We found no evidence that LOC HI was associated with Aβ load, hippocampal volume, WMH volume, AD‐related cortical thickness or NFL (all p > 0.01). Interpretation Having a LOC HI aged 50’s and younger was linked with lower later‐life cognitive function at age ~70 than expected. This may reflect a damaging but small impact of HI; explained in part by smaller BV and different microstructure pathways but not via pathology related to AD (amyloid, hippocampal volume, AD cortical thickness) or ongoing neurodegeneration (serum NFL).
Collapse
Affiliation(s)
- Sarah-Naomi James
- MRC Unit for Lifelong Health and Ageing at UCL, University College London, London, United Kingdom.,Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Jennifer M Nicholas
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom.,Department of Medical Statistics, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Christopher A Lane
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Thomas D Parker
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Kirsty Lu
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Ashvini Keshavan
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Sarah M Buchanan
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Sarah E Keuss
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Heidi Murray-Smith
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Andrew Wong
- MRC Unit for Lifelong Health and Ageing at UCL, University College London, London, United Kingdom
| | - David M Cash
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Ian B Malone
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Josephine Barnes
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Carole H Sudre
- MRC Unit for Lifelong Health and Ageing at UCL, University College London, London, United Kingdom.,Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom.,School of Biomedical Engineering and Imaging Sciences, King's College London, Institute of Nuclear Medicine, University College London Hospitals, London, United Kingdom.,Centre for Medical Image Computing, Department of Computer Science, University College London, London, United Kingdom
| | - William Coath
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Lloyd Prosser
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Sebastien Ourselin
- School of Biomedical Engineering and Imaging Sciences, King's College London, Institute of Nuclear Medicine, University College London Hospitals, London, United Kingdom
| | - Marc Modat
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom.,School of Biomedical Engineering and Imaging Sciences, King's College London, Institute of Nuclear Medicine, University College London Hospitals, London, United Kingdom
| | - David L Thomas
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Jorge Cardoso
- School of Biomedical Engineering and Imaging Sciences, King's College London, Institute of Nuclear Medicine, University College London Hospitals, London, United Kingdom
| | - Amanda Heslegrave
- UK Dementia Research Institute at UCL, University College London, London, United Kingdom.,Department of Neurodegenerative Disease, UCL Institute of Neurology, London, United Kingdom
| | - Henrik Zetterberg
- UK Dementia Research Institute at UCL, University College London, London, United Kingdom.,Department of Neurodegenerative Disease, UCL Institute of Neurology, London, United Kingdom.,Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden.,Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Sebastian J Crutch
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Jonathan M Schott
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Marcus Richards
- MRC Unit for Lifelong Health and Ageing at UCL, University College London, London, United Kingdom
| | - Nick C Fox
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom.,UK Dementia Research Institute at UCL, University College London, London, United Kingdom
| |
Collapse
|
24
|
Raposo N, Zanon Zotin MC, Schoemaker D, Xiong L, Fotiadis P, Charidimou A, Pasi M, Boulouis G, Schwab K, Schirmer MD, Etherton MR, Gurol ME, Greenberg SM, Duering M, Viswanathan A. Peak Width of Skeletonized Mean Diffusivity as Neuroimaging Biomarker in Cerebral Amyloid Angiopathy. AJNR Am J Neuroradiol 2021; 42:875-881. [PMID: 33664113 DOI: 10.3174/ajnr.a7042] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2020] [Accepted: 11/20/2020] [Indexed: 12/19/2022]
Abstract
BACKGROUND AND PURPOSE Whole-brain network connectivity has been shown to be a useful biomarker of cerebral amyloid angiopathy and related cognitive impairment. We evaluated an automated DTI-based method, peak width of skeletonized mean diffusivity, in cerebral amyloid angiopathy, together with its association with conventional MRI markers and cognitive functions. MATERIALS AND METHODS We included 24 subjects (mean age, 74.7 [SD, 6.0] years) with probable cerebral amyloid angiopathy and mild cognitive impairment and 62 patients with MCI not attributable to cerebral amyloid angiopathy (non-cerebral amyloid angiopathy-mild cognitive impairment). We compared peak width of skeletonized mean diffusivity between subjects with cerebral amyloid angiopathy-mild cognitive impairment and non-cerebral amyloid angiopathy-mild cognitive impairment and explored its associations with cognitive functions and conventional markers of cerebral small-vessel disease, using linear regression models. RESULTS Subjects with Cerebral amyloid angiopathy-mild cognitive impairment showed increased peak width of skeletonized mean diffusivity in comparison to those with non-cerebral amyloid angiopathy-mild cognitive impairment (P < .001). Peak width of skeletonized mean diffusivity values were correlated with the volume of white matter hyperintensities in both groups. Higher peak width of skeletonized mean diffusivity was associated with worse performance in processing speed among patients with cerebral amyloid angiopathy, after adjusting for other MRI markers of cerebral small vessel disease. The peak width of skeletonized mean diffusivity did not correlate with cognitive functions among those with non-cerebral amyloid angiopathy-mild cognitive impairment. CONCLUSIONS Peak width of skeletonized mean diffusivity is altered in cerebral amyloid angiopathy and is associated with performance in processing speed. This DTI-based method may reflect the degree of white matter structural disruption in cerebral amyloid angiopathy and could be a useful biomarker for cognition in this population.
Collapse
Affiliation(s)
- N Raposo
- From the Stroke Research Center (N.R., M.C.Z.Z., D.S., L.X., P.F., A.C., K.S., M.D.S., M.R.E., M.E.G., S.M.G., A.V.), Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts .,Department of Neurology (N.R.), Centre Hospitalier Universitaire de Toulouse, Toulouse, France.,Toulouse NeuroImaging Center (N.R.), Université de Toulouse, Institut National de la Santé et de la Recherche Médicale, Toulouse, UPS, France
| | - M C Zanon Zotin
- From the Stroke Research Center (N.R., M.C.Z.Z., D.S., L.X., P.F., A.C., K.S., M.D.S., M.R.E., M.E.G., S.M.G., A.V.), Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts.,Center for Imaging Sciences and Medical Physics (M.C.Z.Z.). Department of Medical Imaging, Hematology and Clinical Oncology, Ribeirão Preto Medical School, University of São Paulo, Ribeirão Preto, São Paulo, Brazil;, Hospital das Clínicas da Faculdade de Medicina de Ribeirão Preto, Universidade de São Paulo, São Paulo, Brazil
| | - D Schoemaker
- From the Stroke Research Center (N.R., M.C.Z.Z., D.S., L.X., P.F., A.C., K.S., M.D.S., M.R.E., M.E.G., S.M.G., A.V.), Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
| | - L Xiong
- From the Stroke Research Center (N.R., M.C.Z.Z., D.S., L.X., P.F., A.C., K.S., M.D.S., M.R.E., M.E.G., S.M.G., A.V.), Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
| | - P Fotiadis
- From the Stroke Research Center (N.R., M.C.Z.Z., D.S., L.X., P.F., A.C., K.S., M.D.S., M.R.E., M.E.G., S.M.G., A.V.), Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
| | - A Charidimou
- From the Stroke Research Center (N.R., M.C.Z.Z., D.S., L.X., P.F., A.C., K.S., M.D.S., M.R.E., M.E.G., S.M.G., A.V.), Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
| | - M Pasi
- Department of Neurology (M.P.), Centre Hospitalier Universitaire de Lille, Lille, France
| | - G Boulouis
- Department of Neuroradiology (G.B.), Centre Hospitalier Sainte-Anne, Université Paris-Descartes, Paris, France
| | - K Schwab
- From the Stroke Research Center (N.R., M.C.Z.Z., D.S., L.X., P.F., A.C., K.S., M.D.S., M.R.E., M.E.G., S.M.G., A.V.), Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
| | - M D Schirmer
- From the Stroke Research Center (N.R., M.C.Z.Z., D.S., L.X., P.F., A.C., K.S., M.D.S., M.R.E., M.E.G., S.M.G., A.V.), Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts.,Computer Science and Artificial Intelligence Lab (M.D.S.), Massachusetts Institute of Technology, Boston, Massachusetts.,Department of Population Health Sciences (M.D.S.), German Center for Neurodegenerative Diseases, Bonn, Germany
| | - M R Etherton
- From the Stroke Research Center (N.R., M.C.Z.Z., D.S., L.X., P.F., A.C., K.S., M.D.S., M.R.E., M.E.G., S.M.G., A.V.), Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
| | - M E Gurol
- From the Stroke Research Center (N.R., M.C.Z.Z., D.S., L.X., P.F., A.C., K.S., M.D.S., M.R.E., M.E.G., S.M.G., A.V.), Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
| | - S M Greenberg
- From the Stroke Research Center (N.R., M.C.Z.Z., D.S., L.X., P.F., A.C., K.S., M.D.S., M.R.E., M.E.G., S.M.G., A.V.), Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
| | - M Duering
- Medical Image Analysis Center and Quantitative Biomedical Imaging Group (M.D.), Department of Biomedical Engineering, University of Basel, Basel, Switzerland
| | - A Viswanathan
- From the Stroke Research Center (N.R., M.C.Z.Z., D.S., L.X., P.F., A.C., K.S., M.D.S., M.R.E., M.E.G., S.M.G., A.V.), Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
| |
Collapse
|
25
|
Rotta J, Perosa V, Yakupov R, Kuijf HJ, Schreiber F, Dobisch L, Oltmer J, Assmann A, Speck O, Heinze HJ, Acosta-Cabronero J, Duzel E, Schreiber S. Detection of Cerebral Microbleeds With Venous Connection at 7-Tesla MRI. Neurology 2021; 96:e2048-e2057. [PMID: 33653897 DOI: 10.1212/wnl.0000000000011790] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2020] [Accepted: 01/28/2021] [Indexed: 12/15/2022] Open
Abstract
OBJECTIVE Cerebral microbleeds (MBs) are a common finding in patients with cerebral small vessel disease (CSVD) and Alzheimer disease as well as in healthy elderly people, but their pathophysiology remains unclear. To investigate a possible role of veins in the development of MBs, we performed an exploratory study, assessing in vivo presence of MBs with a direct connection to a vein. METHODS 7-Tesla (7T) MRI was conducted and MBs were counted on quantitative susceptibility mapping (QSM). A submillimeter resolution QSM-based venogram allowed identification of MBs with a direct spatial connection to a vein. RESULTS A total of 51 people (mean age [SD] 70.5 [8.6] years, 37% female) participated in the study: 20 had CSVD (cerebral amyloid angiopathy [CAA] with strictly lobar MBs [n = 8], hypertensive arteriopathy [HA] with strictly deep MBs [n = 5], or mixed lobar and deep MBs [n = 7], 72.4 [6.1] years, 30% female) and 31 were healthy controls (69.4 [9.9] years, 42% female). In our cohort, we counted a total of 96 MBs with a venous connection, representing 14% of all detected MBs on 7T QSM. Most venous MBs (86%, n = 83) were observed in lobar locations and all of these were cortical. Patients with CAA showed the highest ratio of venous to total MBs (19%) (HA = 9%, mixed = 18%, controls = 5%). CONCLUSION Our findings establish a link between cerebral MBs and the venous vasculature, pointing towards a possible contribution of veins to CSVD in general and to CAA in particular. Pathologic studies are needed to confirm our observations.
Collapse
Affiliation(s)
- Johanna Rotta
- From the Department of Neurology (J.R., V.P., F.S., A.A., H.-J.H., S.S.) and Institute of Physics (O.S.), Otto-von-Guericke University; Institute of Cognitive Neurology and Dementia Research (IKND) (V.P., R.Y., J.O., H.-J.H., E.D.), Magdeburg, Germany; J. Philip Kistler Stroke Research Center (V.P.), Massachusetts General Hospital, Boston; German Center for Neurodegenerative Diseases (DZNE) (R.Y., F.S., L.D., O.S., H.-J.H., E.D., S.S.), Magdeburg, Germany; Image Sciences Institute (H.J.K.), University Medical Center Utrecht, the Netherlands; Leibniz-Institute for Neurobiology (LIN) (O.S., H.-J.H., E.D.); Center for Behavioral Brain Sciences (CBBS) (O.S., H.-J.H., E.D., S.S.), Magdeburg, Germany; Tenoke Limited (J.A.-C.), Cambridge, UK; and Institute of Cognitive Neuroscience (E.D.), University College London, UK
| | - Valentina Perosa
- From the Department of Neurology (J.R., V.P., F.S., A.A., H.-J.H., S.S.) and Institute of Physics (O.S.), Otto-von-Guericke University; Institute of Cognitive Neurology and Dementia Research (IKND) (V.P., R.Y., J.O., H.-J.H., E.D.), Magdeburg, Germany; J. Philip Kistler Stroke Research Center (V.P.), Massachusetts General Hospital, Boston; German Center for Neurodegenerative Diseases (DZNE) (R.Y., F.S., L.D., O.S., H.-J.H., E.D., S.S.), Magdeburg, Germany; Image Sciences Institute (H.J.K.), University Medical Center Utrecht, the Netherlands; Leibniz-Institute for Neurobiology (LIN) (O.S., H.-J.H., E.D.); Center for Behavioral Brain Sciences (CBBS) (O.S., H.-J.H., E.D., S.S.), Magdeburg, Germany; Tenoke Limited (J.A.-C.), Cambridge, UK; and Institute of Cognitive Neuroscience (E.D.), University College London, UK.
| | - Renat Yakupov
- From the Department of Neurology (J.R., V.P., F.S., A.A., H.-J.H., S.S.) and Institute of Physics (O.S.), Otto-von-Guericke University; Institute of Cognitive Neurology and Dementia Research (IKND) (V.P., R.Y., J.O., H.-J.H., E.D.), Magdeburg, Germany; J. Philip Kistler Stroke Research Center (V.P.), Massachusetts General Hospital, Boston; German Center for Neurodegenerative Diseases (DZNE) (R.Y., F.S., L.D., O.S., H.-J.H., E.D., S.S.), Magdeburg, Germany; Image Sciences Institute (H.J.K.), University Medical Center Utrecht, the Netherlands; Leibniz-Institute for Neurobiology (LIN) (O.S., H.-J.H., E.D.); Center for Behavioral Brain Sciences (CBBS) (O.S., H.-J.H., E.D., S.S.), Magdeburg, Germany; Tenoke Limited (J.A.-C.), Cambridge, UK; and Institute of Cognitive Neuroscience (E.D.), University College London, UK
| | - Hugo J Kuijf
- From the Department of Neurology (J.R., V.P., F.S., A.A., H.-J.H., S.S.) and Institute of Physics (O.S.), Otto-von-Guericke University; Institute of Cognitive Neurology and Dementia Research (IKND) (V.P., R.Y., J.O., H.-J.H., E.D.), Magdeburg, Germany; J. Philip Kistler Stroke Research Center (V.P.), Massachusetts General Hospital, Boston; German Center for Neurodegenerative Diseases (DZNE) (R.Y., F.S., L.D., O.S., H.-J.H., E.D., S.S.), Magdeburg, Germany; Image Sciences Institute (H.J.K.), University Medical Center Utrecht, the Netherlands; Leibniz-Institute for Neurobiology (LIN) (O.S., H.-J.H., E.D.); Center for Behavioral Brain Sciences (CBBS) (O.S., H.-J.H., E.D., S.S.), Magdeburg, Germany; Tenoke Limited (J.A.-C.), Cambridge, UK; and Institute of Cognitive Neuroscience (E.D.), University College London, UK
| | - Frank Schreiber
- From the Department of Neurology (J.R., V.P., F.S., A.A., H.-J.H., S.S.) and Institute of Physics (O.S.), Otto-von-Guericke University; Institute of Cognitive Neurology and Dementia Research (IKND) (V.P., R.Y., J.O., H.-J.H., E.D.), Magdeburg, Germany; J. Philip Kistler Stroke Research Center (V.P.), Massachusetts General Hospital, Boston; German Center for Neurodegenerative Diseases (DZNE) (R.Y., F.S., L.D., O.S., H.-J.H., E.D., S.S.), Magdeburg, Germany; Image Sciences Institute (H.J.K.), University Medical Center Utrecht, the Netherlands; Leibniz-Institute for Neurobiology (LIN) (O.S., H.-J.H., E.D.); Center for Behavioral Brain Sciences (CBBS) (O.S., H.-J.H., E.D., S.S.), Magdeburg, Germany; Tenoke Limited (J.A.-C.), Cambridge, UK; and Institute of Cognitive Neuroscience (E.D.), University College London, UK
| | - Laura Dobisch
- From the Department of Neurology (J.R., V.P., F.S., A.A., H.-J.H., S.S.) and Institute of Physics (O.S.), Otto-von-Guericke University; Institute of Cognitive Neurology and Dementia Research (IKND) (V.P., R.Y., J.O., H.-J.H., E.D.), Magdeburg, Germany; J. Philip Kistler Stroke Research Center (V.P.), Massachusetts General Hospital, Boston; German Center for Neurodegenerative Diseases (DZNE) (R.Y., F.S., L.D., O.S., H.-J.H., E.D., S.S.), Magdeburg, Germany; Image Sciences Institute (H.J.K.), University Medical Center Utrecht, the Netherlands; Leibniz-Institute for Neurobiology (LIN) (O.S., H.-J.H., E.D.); Center for Behavioral Brain Sciences (CBBS) (O.S., H.-J.H., E.D., S.S.), Magdeburg, Germany; Tenoke Limited (J.A.-C.), Cambridge, UK; and Institute of Cognitive Neuroscience (E.D.), University College London, UK
| | - Jan Oltmer
- From the Department of Neurology (J.R., V.P., F.S., A.A., H.-J.H., S.S.) and Institute of Physics (O.S.), Otto-von-Guericke University; Institute of Cognitive Neurology and Dementia Research (IKND) (V.P., R.Y., J.O., H.-J.H., E.D.), Magdeburg, Germany; J. Philip Kistler Stroke Research Center (V.P.), Massachusetts General Hospital, Boston; German Center for Neurodegenerative Diseases (DZNE) (R.Y., F.S., L.D., O.S., H.-J.H., E.D., S.S.), Magdeburg, Germany; Image Sciences Institute (H.J.K.), University Medical Center Utrecht, the Netherlands; Leibniz-Institute for Neurobiology (LIN) (O.S., H.-J.H., E.D.); Center for Behavioral Brain Sciences (CBBS) (O.S., H.-J.H., E.D., S.S.), Magdeburg, Germany; Tenoke Limited (J.A.-C.), Cambridge, UK; and Institute of Cognitive Neuroscience (E.D.), University College London, UK
| | - Anne Assmann
- From the Department of Neurology (J.R., V.P., F.S., A.A., H.-J.H., S.S.) and Institute of Physics (O.S.), Otto-von-Guericke University; Institute of Cognitive Neurology and Dementia Research (IKND) (V.P., R.Y., J.O., H.-J.H., E.D.), Magdeburg, Germany; J. Philip Kistler Stroke Research Center (V.P.), Massachusetts General Hospital, Boston; German Center for Neurodegenerative Diseases (DZNE) (R.Y., F.S., L.D., O.S., H.-J.H., E.D., S.S.), Magdeburg, Germany; Image Sciences Institute (H.J.K.), University Medical Center Utrecht, the Netherlands; Leibniz-Institute for Neurobiology (LIN) (O.S., H.-J.H., E.D.); Center for Behavioral Brain Sciences (CBBS) (O.S., H.-J.H., E.D., S.S.), Magdeburg, Germany; Tenoke Limited (J.A.-C.), Cambridge, UK; and Institute of Cognitive Neuroscience (E.D.), University College London, UK
| | - Oliver Speck
- From the Department of Neurology (J.R., V.P., F.S., A.A., H.-J.H., S.S.) and Institute of Physics (O.S.), Otto-von-Guericke University; Institute of Cognitive Neurology and Dementia Research (IKND) (V.P., R.Y., J.O., H.-J.H., E.D.), Magdeburg, Germany; J. Philip Kistler Stroke Research Center (V.P.), Massachusetts General Hospital, Boston; German Center for Neurodegenerative Diseases (DZNE) (R.Y., F.S., L.D., O.S., H.-J.H., E.D., S.S.), Magdeburg, Germany; Image Sciences Institute (H.J.K.), University Medical Center Utrecht, the Netherlands; Leibniz-Institute for Neurobiology (LIN) (O.S., H.-J.H., E.D.); Center for Behavioral Brain Sciences (CBBS) (O.S., H.-J.H., E.D., S.S.), Magdeburg, Germany; Tenoke Limited (J.A.-C.), Cambridge, UK; and Institute of Cognitive Neuroscience (E.D.), University College London, UK
| | - Hans-Jochen Heinze
- From the Department of Neurology (J.R., V.P., F.S., A.A., H.-J.H., S.S.) and Institute of Physics (O.S.), Otto-von-Guericke University; Institute of Cognitive Neurology and Dementia Research (IKND) (V.P., R.Y., J.O., H.-J.H., E.D.), Magdeburg, Germany; J. Philip Kistler Stroke Research Center (V.P.), Massachusetts General Hospital, Boston; German Center for Neurodegenerative Diseases (DZNE) (R.Y., F.S., L.D., O.S., H.-J.H., E.D., S.S.), Magdeburg, Germany; Image Sciences Institute (H.J.K.), University Medical Center Utrecht, the Netherlands; Leibniz-Institute for Neurobiology (LIN) (O.S., H.-J.H., E.D.); Center for Behavioral Brain Sciences (CBBS) (O.S., H.-J.H., E.D., S.S.), Magdeburg, Germany; Tenoke Limited (J.A.-C.), Cambridge, UK; and Institute of Cognitive Neuroscience (E.D.), University College London, UK
| | - Julio Acosta-Cabronero
- From the Department of Neurology (J.R., V.P., F.S., A.A., H.-J.H., S.S.) and Institute of Physics (O.S.), Otto-von-Guericke University; Institute of Cognitive Neurology and Dementia Research (IKND) (V.P., R.Y., J.O., H.-J.H., E.D.), Magdeburg, Germany; J. Philip Kistler Stroke Research Center (V.P.), Massachusetts General Hospital, Boston; German Center for Neurodegenerative Diseases (DZNE) (R.Y., F.S., L.D., O.S., H.-J.H., E.D., S.S.), Magdeburg, Germany; Image Sciences Institute (H.J.K.), University Medical Center Utrecht, the Netherlands; Leibniz-Institute for Neurobiology (LIN) (O.S., H.-J.H., E.D.); Center for Behavioral Brain Sciences (CBBS) (O.S., H.-J.H., E.D., S.S.), Magdeburg, Germany; Tenoke Limited (J.A.-C.), Cambridge, UK; and Institute of Cognitive Neuroscience (E.D.), University College London, UK
| | - Emrah Duzel
- From the Department of Neurology (J.R., V.P., F.S., A.A., H.-J.H., S.S.) and Institute of Physics (O.S.), Otto-von-Guericke University; Institute of Cognitive Neurology and Dementia Research (IKND) (V.P., R.Y., J.O., H.-J.H., E.D.), Magdeburg, Germany; J. Philip Kistler Stroke Research Center (V.P.), Massachusetts General Hospital, Boston; German Center for Neurodegenerative Diseases (DZNE) (R.Y., F.S., L.D., O.S., H.-J.H., E.D., S.S.), Magdeburg, Germany; Image Sciences Institute (H.J.K.), University Medical Center Utrecht, the Netherlands; Leibniz-Institute for Neurobiology (LIN) (O.S., H.-J.H., E.D.); Center for Behavioral Brain Sciences (CBBS) (O.S., H.-J.H., E.D., S.S.), Magdeburg, Germany; Tenoke Limited (J.A.-C.), Cambridge, UK; and Institute of Cognitive Neuroscience (E.D.), University College London, UK
| | - Stefanie Schreiber
- From the Department of Neurology (J.R., V.P., F.S., A.A., H.-J.H., S.S.) and Institute of Physics (O.S.), Otto-von-Guericke University; Institute of Cognitive Neurology and Dementia Research (IKND) (V.P., R.Y., J.O., H.-J.H., E.D.), Magdeburg, Germany; J. Philip Kistler Stroke Research Center (V.P.), Massachusetts General Hospital, Boston; German Center for Neurodegenerative Diseases (DZNE) (R.Y., F.S., L.D., O.S., H.-J.H., E.D., S.S.), Magdeburg, Germany; Image Sciences Institute (H.J.K.), University Medical Center Utrecht, the Netherlands; Leibniz-Institute for Neurobiology (LIN) (O.S., H.-J.H., E.D.); Center for Behavioral Brain Sciences (CBBS) (O.S., H.-J.H., E.D., S.S.), Magdeburg, Germany; Tenoke Limited (J.A.-C.), Cambridge, UK; and Institute of Cognitive Neuroscience (E.D.), University College London, UK
| |
Collapse
|
26
|
Razek AAKA, Elsebaie NA. Imaging of vascular cognitive impairment. Clin Imaging 2021; 74:45-54. [PMID: 33434866 DOI: 10.1016/j.clinimag.2020.12.038] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2020] [Revised: 11/21/2020] [Accepted: 12/30/2020] [Indexed: 12/15/2022]
Abstract
Vascular cognitive impairment (VCI) is a major health challenge and represents the second most common cause of dementia. We review the updated imaging classification and imaging findings of different subtypes of VCI. We will focus on the magnetic resonance imaging (MRI) markers of each subtype and highlight the role of advanced MR imaging sequences in the evaluation of these patients. Small vessel dementia appears as white matter hyperintensity, lacunae, microinfarcts, and microbleeds. Large vessel dementia includes strategic infarction and multi-infarction dementias. Hypoperfusion dementia can be seen as watershed infarcts and cortical laminar necrosis. Hemorrhagic dementia results from cerebral amyloid angiopathy and cortical superficial siderosis. Hereditary forms of VCI, caused by gene mutations such as CADASIL, should be suspected when dementia presents in young patients. Mixed dementia is seen in patients with Alzheimer's disease and the coexistence of cerebrovascular disease.
Collapse
Affiliation(s)
- Ahmed Abdel Khalek Abdel Razek
- Department of Diagnostic Radiology, Mansoura Faculty of Medicine, Mansoura, Egypt; Department of Radiology, Alexandria Faculty of Medicine, Alexandria, Egypt.
| | - Nermeen A Elsebaie
- Department of Diagnostic Radiology, Mansoura Faculty of Medicine, Mansoura, Egypt; Department of Radiology, Alexandria Faculty of Medicine, Alexandria, Egypt.
| |
Collapse
|
27
|
Xiong L, Charidimou A, Pasi M, Boulouis G, Pongpitakmetha T, Schirmer MD, Singh S, Benson E, Gurol EM, Rosand J, Greenberg SM, Biffi A, Viswanathan A. Predictors for Late Post-Intracerebral Hemorrhage Dementia in Patients with Probable Cerebral Amyloid Angiopathy. J Alzheimers Dis 2020; 71:435-442. [PMID: 31403947 DOI: 10.3233/jad-190346] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/15/2023]
Abstract
BACKGROUND AND OBJECTIVE Cerebral amyloid angiopathy (CAA) accounts for the majority of lobar intracerebral hemorrhage (ICH); however, the risk factors for dementia conversion after ICH occurrence in CAA patients are unknown, especially in the long-term period after ICH. Therefore, we aimed to unravel the predictors for late post-ICH dementia (6 months after ICH event) in probable CAA patients. METHODS From a large consecutive MRI prospective cohort of spontaneous ICH (2006-2017), we identified probable CAA patients (modified Boston criteria) without dementia 6 months post-ICH. Cognitive outcome during follow-up was determined based on the information from standardized clinical visit notes. We used Cox regression analysis to investigate the association between baseline demographic characteristics, past medical history, MRI biomarkers, and late post-ICH dementia conversion (dementia occurred after 6 months). RESULTS Among 97 non-demented lobar ICH patients with probable CAA, 25 patients (25.8%) developed dementia during a median follow-up time of 2.5 years (IQR 1.5-3.8 years). Pre-existing mild cognitive impairment, increased white matter hyperintensities (WMH) burden, the presence of disseminated cortical superficial siderosis (cSS), and higher total small vessel disease score for CAA were all independent predictors for late dementia conversion. CONCLUSION In probable CAA patients presenting with lobar ICH, high WMH burden and presence of disseminated cSS are useful neuroimaging biomarkers for dementia risk stratification. These findings have implications for clinical practice and future trial design.
Collapse
Affiliation(s)
- Li Xiong
- Department of Neurology, Massachusetts General Hospital Stroke Research Center, Harvard Medical School, Boston, MA, USA
| | - Andreas Charidimou
- Department of Neurology, Massachusetts General Hospital Stroke Research Center, Harvard Medical School, Boston, MA, USA
| | - Marco Pasi
- Department of Neurology, Massachusetts General Hospital Stroke Research Center, Harvard Medical School, Boston, MA, USA
| | - Gregoire Boulouis
- Centre Hospitalier Sainte-Anne, Université Paris Descartes, Paris, France
| | - Thanakit Pongpitakmetha
- Department of Neurology, Massachusetts General Hospital Stroke Research Center, Harvard Medical School, Boston, MA, USA.,Department of Pharmacology, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand
| | - Markus D Schirmer
- Department of Neurology, Massachusetts General Hospital Stroke Research Center, Harvard Medical School, Boston, MA, USA.,Computer Science and Artificial Intelligence Lab, Massachusetts Institute of Technology, Boston, MA, USA.,Department of Population Health Sciences, German Centre for Neurodegenerative Diseases (DZNE), Germany
| | - Sanjula Singh
- Department of Neurology, Massachusetts General Hospital Stroke Research Center, Harvard Medical School, Boston, MA, USA
| | - Emily Benson
- Department of Neurology, Massachusetts General Hospital Stroke Research Center, Harvard Medical School, Boston, MA, USA
| | - Edip M Gurol
- Department of Neurology, Massachusetts General Hospital Stroke Research Center, Harvard Medical School, Boston, MA, USA
| | - Jonathan Rosand
- Department of Neurology, Massachusetts General Hospital Stroke Research Center, Harvard Medical School, Boston, MA, USA
| | - Steven M Greenberg
- Department of Neurology, Massachusetts General Hospital Stroke Research Center, Harvard Medical School, Boston, MA, USA
| | - Alessandro Biffi
- Department of Neurology, Massachusetts General Hospital Stroke Research Center, Harvard Medical School, Boston, MA, USA
| | - Anand Viswanathan
- Department of Neurology, Massachusetts General Hospital Stroke Research Center, Harvard Medical School, Boston, MA, USA
| |
Collapse
|
28
|
Liu JY, Zhou YJ, Zhai FF, Han F, Zhou LX, Ni J, Yao M, Zhang S, Jin Z, Cui L, Zhu YC. Cerebral Microbleeds Are Associated with Loss of White Matter Integrity. AJNR Am J Neuroradiol 2020; 41:1397-1404. [PMID: 32719091 DOI: 10.3174/ajnr.a6622] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2020] [Accepted: 05/01/2020] [Indexed: 11/07/2022]
Abstract
BACKGROUND AND PURPOSE Previous studies have shown that diffusion tensor imaging suggests a diffuse loss of white matter integrity in people with white matter hyperintensities or lacunes. The purpose of this study was to investigate whether the presence of cerebral microbleeds and their distribution are related to the integrity of white matter microstructures. MATERIALS AND METHODS The study comprised 982 participants who underwent brain MR imaging to determine microbleed status. The cross-sectional relation between microbleeds and the microstructural integrity of the white matter was assessed by 2 statistical methods: a multilinear regression model based on the average DTI parameters of normal-appearing white matter and Tract-Based Spatial Statistics analysis, a tract-based voxelwise analysis. Fiber tractography was used to spatially describe the microstructural abnormalities along WM tracts containing a cerebral microbleed. RESULTS The presence of cerebral microbleeds was associated with lower mean fractional anisotropy and higher mean diffusivity, axial diffusivity, and radial diffusivity, and the association remained when cardiovascular risk factors and cerebral small-vessel disease markers were further adjusted. Tract-Based Spatial Statistics analysis indicated strictly lobar cerebral microbleeds associated with lower fractional anisotropy, higher mean diffusivity, and higher radial diffusivity in the internal capsule and corpus callosum after adjusting other cerebral small-vessel disease markers, while only a few voxels remained associated with deep cerebral microbleeds. Diffusion abnormalities gradients along WM tracts containing a cerebral microbleed were not found in fiber tractography analysis. CONCLUSIONS Cerebral microbleeds are associated with widely distributed changes in white matter, despite their focal appearance on SWI.
Collapse
Affiliation(s)
- J-Y Liu
- From the Departments of Neurology (J.-Y.L., Y.-J.Z., F.-F.Z., F.H., L.-X.Z., J.N., M.Y., L.C., Y.-C.Z.), Radiology (Z.J.), and Cardiology (S.Z.), Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Science, Beijing, China
| | - Y-J Zhou
- From the Departments of Neurology (J.-Y.L., Y.-J.Z., F.-F.Z., F.H., L.-X.Z., J.N., M.Y., L.C., Y.-C.Z.), Radiology (Z.J.), and Cardiology (S.Z.), Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Science, Beijing, China
| | - F-F Zhai
- From the Departments of Neurology (J.-Y.L., Y.-J.Z., F.-F.Z., F.H., L.-X.Z., J.N., M.Y., L.C., Y.-C.Z.), Radiology (Z.J.), and Cardiology (S.Z.), Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Science, Beijing, China
| | - F Han
- From the Departments of Neurology (J.-Y.L., Y.-J.Z., F.-F.Z., F.H., L.-X.Z., J.N., M.Y., L.C., Y.-C.Z.), Radiology (Z.J.), and Cardiology (S.Z.), Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Science, Beijing, China
| | - L-X Zhou
- From the Departments of Neurology (J.-Y.L., Y.-J.Z., F.-F.Z., F.H., L.-X.Z., J.N., M.Y., L.C., Y.-C.Z.), Radiology (Z.J.), and Cardiology (S.Z.), Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Science, Beijing, China
| | - J Ni
- From the Departments of Neurology (J.-Y.L., Y.-J.Z., F.-F.Z., F.H., L.-X.Z., J.N., M.Y., L.C., Y.-C.Z.), Radiology (Z.J.), and Cardiology (S.Z.), Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Science, Beijing, China
| | - M Yao
- From the Departments of Neurology (J.-Y.L., Y.-J.Z., F.-F.Z., F.H., L.-X.Z., J.N., M.Y., L.C., Y.-C.Z.), Radiology (Z.J.), and Cardiology (S.Z.), Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Science, Beijing, China
| | - S Zhang
- From the Departments of Neurology (J.-Y.L., Y.-J.Z., F.-F.Z., F.H., L.-X.Z., J.N., M.Y., L.C., Y.-C.Z.), Radiology (Z.J.), and Cardiology (S.Z.), Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Science, Beijing, China
| | - Z Jin
- From the Departments of Neurology (J.-Y.L., Y.-J.Z., F.-F.Z., F.H., L.-X.Z., J.N., M.Y., L.C., Y.-C.Z.), Radiology (Z.J.), and Cardiology (S.Z.), Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Science, Beijing, China
| | - L Cui
- From the Departments of Neurology (J.-Y.L., Y.-J.Z., F.-F.Z., F.H., L.-X.Z., J.N., M.Y., L.C., Y.-C.Z.), Radiology (Z.J.), and Cardiology (S.Z.), Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Science, Beijing, China
| | - Y-C Zhu
- From the Departments of Neurology (J.-Y.L., Y.-J.Z., F.-F.Z., F.H., L.-X.Z., J.N., M.Y., L.C., Y.-C.Z.), Radiology (Z.J.), and Cardiology (S.Z.), Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Science, Beijing, China.
| |
Collapse
|
29
|
Ter Telgte A, Scherlek AA, Reijmer YD, van der Kouwe AJ, van Harten T, Duering M, Bacskai BJ, de Leeuw FE, Frosch MP, Greenberg SM, van Veluw SJ. Histopathology of diffusion-weighted imaging-positive lesions in cerebral amyloid angiopathy. Acta Neuropathol 2020; 139:799-812. [PMID: 32108259 DOI: 10.1007/s00401-020-02140-y] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2019] [Revised: 01/25/2020] [Accepted: 02/21/2020] [Indexed: 11/24/2022]
Abstract
Small subclinical hyperintense lesions are frequently encountered on brain diffusion-weighted imaging (DWI) scans of patients with cerebral amyloid angiopathy (CAA). Interpretation of these DWI+ lesions, however, has been limited by absence of histopathological examination. We aimed to determine whether DWI+ lesions represent acute microinfarcts on histopathology in brains with advanced CAA, using a combined in vivo MRI-ex vivo MRI-histopathology approach. We first investigated the histopathology of a punctate cortical DWI+ lesion observed on clinical in vivo MRI 7 days prior to death in a CAA case. Subsequently, we assessed the use of ex vivo DWI to identify similar punctate cortical lesions post-mortem. Intact formalin-fixed hemispheres of 12 consecutive cases with CAA and three non-CAA controls were subjected to high-resolution 3 T ex vivo DWI and T2 imaging. Small cortical lesions were classified as either DWI+/T2+ or DWI-/T2+. A representative subset of lesions from three CAA cases was selected for detailed histopathological examination. The DWI+ lesion observed on in vivo MRI could be matched to an area with evidence of recent ischemia on histopathology. Ex vivo MRI of the intact hemispheres revealed a total of 130 DWI+/T2+ lesions in 10/12 CAA cases, but none in controls (p = 0.022). DWI+/T2+ lesions examined histopathologically proved to be acute microinfarcts (classification accuracy 100%), characterized by presence of eosinophilic neurons on hematoxylin and eosin and absence of reactive astrocytes on glial fibrillary acidic protein-stained sections. In conclusion, we suggest that small DWI+ lesions in CAA represent acute microinfarcts. Furthermore, our findings support the use of ex vivo DWI as a method to detect acute microinfarcts post-mortem, which may benefit future histopathological investigations on the etiology of microinfarcts.
Collapse
Affiliation(s)
- Annemieke Ter Telgte
- MassGeneral Institute for Neurodegenerative Disease, Massachusetts General Hospital and Harvard Medical School, 114 16th Street, Charlestown, MA, 02129, USA
- Department of Neurology, J. Philip Kistler Stroke Research Center, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Ashley A Scherlek
- MassGeneral Institute for Neurodegenerative Disease, Massachusetts General Hospital and Harvard Medical School, 114 16th Street, Charlestown, MA, 02129, USA
| | - Yael D Reijmer
- Department of Neurology, J. Philip Kistler Stroke Research Center, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Department of Neurology, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Andre J van der Kouwe
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
| | - Thijs van Harten
- Department of Neurology, J. Philip Kistler Stroke Research Center, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Marco Duering
- Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands
- Institute for Stroke and Dementia Research (ISD), University Hospital LMU Munich, Munich, Germany
- Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
| | - Brian J Bacskai
- MassGeneral Institute for Neurodegenerative Disease, Massachusetts General Hospital and Harvard Medical School, 114 16th Street, Charlestown, MA, 02129, USA
| | - Frank-Erik de Leeuw
- Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Matthew P Frosch
- MassGeneral Institute for Neurodegenerative Disease, Massachusetts General Hospital and Harvard Medical School, 114 16th Street, Charlestown, MA, 02129, USA
- Neuropathology Service, C.S. Kubik Laboratory for Neuropathology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Steven M Greenberg
- Department of Neurology, J. Philip Kistler Stroke Research Center, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Susanne J van Veluw
- MassGeneral Institute for Neurodegenerative Disease, Massachusetts General Hospital and Harvard Medical School, 114 16th Street, Charlestown, MA, 02129, USA.
- Department of Neurology, J. Philip Kistler Stroke Research Center, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
| |
Collapse
|
30
|
Kozberg MG, van Veluw SJ, Frosch MP, Greenberg SM. Hereditary cerebral amyloid angiopathy, Piedmont-type mutation. NEUROLOGY-GENETICS 2020; 6:e411. [PMID: 32337337 PMCID: PMC7164975 DOI: 10.1212/nxg.0000000000000411] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/27/2019] [Accepted: 01/27/2020] [Indexed: 11/30/2022]
Abstract
Objective We present here a case report of a patient with a family history of intracerebral hemorrhages (ICHs) who presented with multiple large lobar hemorrhages in rapid succession, with cognitive sparing, who was found to have a mutation in the β-amyloid coding sequence of amyloid precursor protein (Leu705Val), termed the Piedmont-type mutation, the second ever reported case of this form of hereditary cerebral amyloid angiopathy (CAA). Methods Targeted pathologic examination was performed aided by the use of ex vivo MRI. Results Severe CAA was observed mainly involving the leptomeningeal vessels and, to a far lesser extent, cortical vessels, with no amyloid plaques or neurofibrillary tangles. Conclusions This leptomeningeal pattern of β-amyloid deposition coupled with multiple large hemorrhages demonstrates unique pathophysiologic characteristics of CAA associated with the Piedmont-type mutation, suggesting a potential association between leptomeningeal CAA and larger ICHs.
Collapse
Affiliation(s)
- Mariel G Kozberg
- MassGeneral Institute for Neurodegenerative Disease (M.G.K., S.J.v.V.), Massachusetts General Hospital and Harvard Medical School, Charlestown; Department of Neurology (M.G.K., S.J.v.V., S.M.G.), Massachusetts General Hospital, Boston; Department of Neurology (M.G.K.), Brigham and Women's Hospital, Boston; J. Philip Kistler Stroke Research Center (S.J.v.V., S.M.G.), Massachusetts General Hospital and Harvard Medical School, Boston; and Neuropathology Service, C. S. Kubik Laboratory for Neuropathology (M.P.F), Massachusetts General Hospital and Harvard Medical School, Boston
| | - Susanne J van Veluw
- MassGeneral Institute for Neurodegenerative Disease (M.G.K., S.J.v.V.), Massachusetts General Hospital and Harvard Medical School, Charlestown; Department of Neurology (M.G.K., S.J.v.V., S.M.G.), Massachusetts General Hospital, Boston; Department of Neurology (M.G.K.), Brigham and Women's Hospital, Boston; J. Philip Kistler Stroke Research Center (S.J.v.V., S.M.G.), Massachusetts General Hospital and Harvard Medical School, Boston; and Neuropathology Service, C. S. Kubik Laboratory for Neuropathology (M.P.F), Massachusetts General Hospital and Harvard Medical School, Boston
| | - Matthew P Frosch
- MassGeneral Institute for Neurodegenerative Disease (M.G.K., S.J.v.V.), Massachusetts General Hospital and Harvard Medical School, Charlestown; Department of Neurology (M.G.K., S.J.v.V., S.M.G.), Massachusetts General Hospital, Boston; Department of Neurology (M.G.K.), Brigham and Women's Hospital, Boston; J. Philip Kistler Stroke Research Center (S.J.v.V., S.M.G.), Massachusetts General Hospital and Harvard Medical School, Boston; and Neuropathology Service, C. S. Kubik Laboratory for Neuropathology (M.P.F), Massachusetts General Hospital and Harvard Medical School, Boston
| | - Steven M Greenberg
- MassGeneral Institute for Neurodegenerative Disease (M.G.K., S.J.v.V.), Massachusetts General Hospital and Harvard Medical School, Charlestown; Department of Neurology (M.G.K., S.J.v.V., S.M.G.), Massachusetts General Hospital, Boston; Department of Neurology (M.G.K.), Brigham and Women's Hospital, Boston; J. Philip Kistler Stroke Research Center (S.J.v.V., S.M.G.), Massachusetts General Hospital and Harvard Medical School, Boston; and Neuropathology Service, C. S. Kubik Laboratory for Neuropathology (M.P.F), Massachusetts General Hospital and Harvard Medical School, Boston
| |
Collapse
|
31
|
Neurovascular unit dysregulation, white matter disease, and executive dysfunction: the shared triad of vascular cognitive impairment and Alzheimer disease. GeroScience 2020; 42:445-465. [PMID: 32002785 DOI: 10.1007/s11357-020-00164-6] [Citation(s) in RCA: 55] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2019] [Accepted: 01/22/2020] [Indexed: 01/07/2023] Open
Abstract
Executive dysfunction is the most important predictor for loss of independence in dementia. As executive function involves the coordination of distributed cerebral functions, executive function requires healthy white matter. However, white matter is highly vulnerable to cerebrovascular insults, with executive dysfunction being a core feature of vascular cognitive impairment (VCI). At the same time, cerebrovascular pathology, white matter disease, and executive dysfunction are all increasingly recognized as features of Alzheimer disease (AD). Recent studies have characterized the crucial role of glial cells in the pathological changes observed in both VCI and AD. In comorbid VCI and AD, the glial cells of the neurovascular unit (NVU) emerge as important therapeutic targets for the preservation of white matter integrity and executive function. Our synthesis from current research identifies dysregulation of the NVU, white matter disease, and executive dysfunction as a fundamental triad that is common to both VCI and AD. Further study of this triad will be critical for advancing the prevention and management of dementia.
Collapse
|
32
|
Greenberg SM, Bacskai BJ, Hernandez-Guillamon M, Pruzin J, Sperling R, van Veluw SJ. Cerebral amyloid angiopathy and Alzheimer disease - one peptide, two pathways. Nat Rev Neurol 2020; 16:30-42. [PMID: 31827267 PMCID: PMC7268202 DOI: 10.1038/s41582-019-0281-2] [Citation(s) in RCA: 510] [Impact Index Per Article: 102.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/11/2019] [Indexed: 12/22/2022]
Abstract
The shared role of amyloid-β (Aβ) deposition in cerebral amyloid angiopathy (CAA) and Alzheimer disease (AD) is arguably the clearest instance of crosstalk between neurodegenerative and cerebrovascular processes. The pathogenic pathways of CAA and AD intersect at the levels of Aβ generation, its circulation within the interstitial fluid and perivascular drainage pathways and its brain clearance, but diverge in their mechanisms of brain injury and disease presentation. Here, we review the evidence for and the pathogenic implications of interactions between CAA and AD. Both pathologies seem to be driven by impaired Aβ clearance, creating conditions for a self-reinforcing cycle of increased vascular Aβ, reduced perivascular clearance and further CAA and AD progression. Despite the close relationship between vascular and plaque Aβ deposition, several factors favour one or the other, such as the carboxy-terminal site of the peptide and specific co-deposited proteins. Amyloid-related imaging abnormalities that have been seen in trials of anti-Aβ immunotherapy are another probable intersection between CAA and AD, representing overload of perivascular clearance pathways and the effects of removing Aβ from CAA-positive vessels. The intersections between CAA and AD point to a crucial role for improving vascular function in the treatment of both diseases and indicate the next steps necessary for identifying therapies.
Collapse
Affiliation(s)
- Steven M Greenberg
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
| | - Brian J Bacskai
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Mar Hernandez-Guillamon
- Neurovascular Research Laboratory, Institut de Recerca, Hospital Vall d'Hebron, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Jeremy Pruzin
- Center for Alzheimer Research and Treatment, Brigham & Women's Hospital, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Reisa Sperling
- Center for Alzheimer Research and Treatment, Brigham & Women's Hospital, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Susanne J van Veluw
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| |
Collapse
|
33
|
Planas AM. Top ten discoveries of the year: Neurovascular disease. FREE NEUROPATHOLOGY 2020; 1:5. [PMID: 37283688 PMCID: PMC10209999 DOI: 10.17879/freeneuropathology-2020-2615] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Received: 01/09/2020] [Accepted: 01/25/2020] [Indexed: 06/08/2023]
Abstract
The aim of this review is to highlight novel findings in 2019 in the area of neurovascular disease. Experimental studies have provided insight into disease development, molecular determinants of pathology, and putative novel therapeutic targets. Studies in genetic experimental models as well as monogenic forms of human cerebrovascular diseases identified pathogenic molecules that may also be relevant to sporadic cases. There have been advances in understanding the development of cerebral cavernous angiomas and arteriovenous malformations, and putative curative treatments have been suggested from experimental models. Key pathogenic pathways involved in vessel calcification and stiffness have also been identified. At the cellular level, studies showed that proper function of endothelial and mural cells, particularly pericytes, is crucial to ensure full endothelial differentiation and blood-brain barrier integrity. Moreover, recent discoveries support the existence of a homeostatic crosstalk between vascular cells and other neural cells, including neurons. Cerebrovascular diseases are strongly associated with inflammation. Beyond pathogenic roles of specific components of the inflammatory response, new discoveries showed interesting interactions between inflammatory molecules and regulators of vascular function. Clinical investigation on cerebrovascular diseases has progressed by combining advanced imaging and genome-wide association studies. Finally, vascular cognitive impairment and dementia are receiving increasing attention. Recent findings suggest that high-salt intake may cause cerebrovascular dysfunction and cognitive impairment independent of hypoperfusion and hypertension. These and other recent reports will surely inspire further research in the field of cerebrovascular disease that will hopefully contribute to improved prevention and treatment.
Collapse
Affiliation(s)
- Anna M Planas
- Department of Brain Ischemia and Neurodegeneration, Spanish National Research Council (CSIC), Barcelona, Spain
| |
Collapse
|
34
|
van Veluw SJ, Scherlek AA, Freeze WM, Ter Telgte A, van der Kouwe AJ, Bacskai BJ, Frosch MP, Greenberg SM. Different microvascular alterations underlie microbleeds and microinfarcts. Ann Neurol 2019; 86:279-292. [PMID: 31152566 DOI: 10.1002/ana.25512] [Citation(s) in RCA: 52] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2019] [Revised: 05/29/2019] [Accepted: 05/29/2019] [Indexed: 11/08/2022]
Abstract
OBJECTIVE Cerebral amyloid angiopathy (CAA) is characterized by the accumulation of amyloid β (Aβ) in the walls of cortical vessels and the accrual of microbleeds and microinfarcts over time. The relationship between CAA severity and microbleeds and microinfarcts as well as the sequence of events that lead to lesion formation remain poorly understood. METHODS We scanned intact formalin-fixed hemispheres of 12 CAA cases with magnetic resonance imaging (MRI), followed by histopathological examination in predefined areas and serial sectioning in targeted areas with multiple lesions. RESULTS In total, 1,168 cortical microbleeds and 472 cortical microinfarcts were observed on ex vivo MRI. Increasing CAA severity at the whole-brain or regional level was not associated with the number of microbleeds or microinfarcts. However, locally, the density of Aβ-positive cortical vessels was lower surrounding a microbleed compared to a simulated control lesion, and higher surrounding microinfarcts. Serial sectioning revealed that for (n = 28) microbleeds, both Aβ (4%) and smooth muscle cells (4%) were almost never present in the vessel wall at the site of bleeding, but Aβ was frequently observed upstream or downstream (71%), as was extensive fibrin(ogen) buildup (87%). In contrast, for (n = 22) microinfarcts, vascular Aβ was almost always observed at the core of the lesion (91%, p < 0.001) as well as upstream or downstream (82%), but few vessels associated with microinfarcts had intact smooth muscle cells (9%). INTERPRETATION These observations provide a model for how a single neuropathologic process such as CAA may result in hemorrhagic or ischemic brain lesions potentially through 2 different mechanistic pathways. ANN NEUROL 2019;86:279-292.
Collapse
Affiliation(s)
- Susanne J van Veluw
- MassGeneral Institute for Neurodegenerative Disease, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA.,J. Philip Kistler Stroke Research Center, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA
| | - Ashley A Scherlek
- MassGeneral Institute for Neurodegenerative Disease, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA
| | - Whitney M Freeze
- MassGeneral Institute for Neurodegenerative Disease, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA.,Department of Psychiatry and Neuropsychology, Maastricht University, School for Mental Health and Neuroscience, Alzheimer Center Limburg, Maastricht, the Netherlands
| | - Annemieke Ter Telgte
- MassGeneral Institute for Neurodegenerative Disease, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA.,Department of Neurology, Donders Institute for Brain, Cognition, and Behavior, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Andre J van der Kouwe
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA
| | - Brian J Bacskai
- MassGeneral Institute for Neurodegenerative Disease, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA
| | - Matthew P Frosch
- MassGeneral Institute for Neurodegenerative Disease, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA.,Neuropathology Service, C. S. Kubik Laboratory for Neuropathology, Massachusetts General Hospital and Harvard Medical School, Boston, MA
| | - Steven M Greenberg
- J. Philip Kistler Stroke Research Center, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA
| |
Collapse
|