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Kancheva AK, Wardlaw JM, Lyall DM, Quinn TJ. Clinical Phenotypes Associated With Cerebral Small Vessel Disease: An Overview of Systematic Reviews. Neurology 2024; 102:e209267. [PMID: 38552192 DOI: 10.1212/wnl.0000000000209267] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2023] [Accepted: 01/18/2024] [Indexed: 04/02/2024] Open
Abstract
BACKGROUND AND OBJECTIVES Cerebral small vessel disease (cSVD) causes lacunar and hemorrhagic stroke and is an important contributor to vascular cognitive impairment. Other potential physical and psychological consequences of cSVD have been described across various body systems. Descriptions of cSVD are available in journals specific to those individual body systems, but a comprehensive assessment of clinical manifestations across this disparate literature is lacking. We conducted an overview of systematic reviews describing clinical cSVD phenotypes. METHODS We searched multidisciplinary databases from inception to December 2023. We included reviews describing concurrent clinical phenotypes in individuals with neuroimaging evidence of cSVD, defined using the STandards for ReportIng Vascular changes on nEuroimaging criteria. We broadly classified phenotypes into cognitive, mood and neuropsychiatric, respiratory, cardiovascular, renal-urinary, peripheral nervous system, locomotor, and gastrointestinal. We included both studies assessing multiple cSVD features and studies examining individual cSVD markers. We extracted risk factor-adjusted effect estimates, where possible, and assessed methodologic quality using the Assessment of Multiple Systematic Reviews-2 tool. RESULTS After screening 6,156 publications, we included 24 systematic reviews reporting on 685 original studies and 1,135,943 participants. Cognitive and neuropsychiatric phenotypes were examined most often, particularly in relation to white matter hyperintensities (range of risk ratios [RRs] for cognitive phenotypes 1.21-1.49, range of 95% CI 1.01-1.84; for neuropsychiatric, RR 1.02-5.71, 95% CI 0.96-19.69). Two reviews focused solely on perivascular spaces. No reviews assessed lacunes or small subcortical infarcts separately from other cSVD features. Reviews on peripheral nervous system, urinary, or gastrointestinal phenotypes were lacking. Fourteen reviews had high methodologic quality, 5 had moderate quality, and 5 had low quality. Heterogeneity in cSVD definitions and phenotypic assessments was substantial. DISCUSSION Neuroimaging markers of cSVD are associated with various clinical manifestations, suggesting a multisystem phenotype. However, features classically associated with cSVD, for example, gait, had limited supporting evidence, and for many body systems, there were no available reviews. Similarly, while white matter hyperintensities were relatively well studied, there were limited data on phenotypes associated with other cSVD features. Future studies should characterize the full clinical spectrum of cSVD and explore clinical associations beyond neurocognitive and neuropsychiatric presentations.
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Affiliation(s)
- Angelina K Kancheva
- From the School of Cardiovascular and Metabolic Health (A.K.K., T.J.Q.), University of Glasgow; Centre for Clinical Brain Sciences (J.M.W.), University of Edinburgh; and School of Health & Wellbeing (D.M.L.), University of Glasgow, United Kingdom
| | - Joanna M Wardlaw
- From the School of Cardiovascular and Metabolic Health (A.K.K., T.J.Q.), University of Glasgow; Centre for Clinical Brain Sciences (J.M.W.), University of Edinburgh; and School of Health & Wellbeing (D.M.L.), University of Glasgow, United Kingdom
| | - Donald M Lyall
- From the School of Cardiovascular and Metabolic Health (A.K.K., T.J.Q.), University of Glasgow; Centre for Clinical Brain Sciences (J.M.W.), University of Edinburgh; and School of Health & Wellbeing (D.M.L.), University of Glasgow, United Kingdom
| | - Terence J Quinn
- From the School of Cardiovascular and Metabolic Health (A.K.K., T.J.Q.), University of Glasgow; Centre for Clinical Brain Sciences (J.M.W.), University of Edinburgh; and School of Health & Wellbeing (D.M.L.), University of Glasgow, United Kingdom
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Taghvaei M, Mechanic-Hamilton DJ, Sadaghiani S, Shakibajahromi B, Dolui S, Das S, Brown C, Tackett W, Khandelwal P, Cook P, Shinohara RT, Yushkevich P, Bassett DS, Wolk DA, Detre JA. Impact of white matter hyperintensities on structural connectivity and cognition in cognitively intact ADNI participants. Neurobiol Aging 2024; 135:79-90. [PMID: 38262221 PMCID: PMC10872454 DOI: 10.1016/j.neurobiolaging.2023.10.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2023] [Revised: 10/19/2023] [Accepted: 10/22/2023] [Indexed: 01/25/2024]
Abstract
We used indirect brain mapping with virtual lesion tractography to test the hypothesis that the extent of white matter tract disconnection due to white matter hyperintensities (WMH) is associated with corresponding tract-specific cognitive performance decrements. To estimate tract disconnection, WMH masks were extracted from FLAIR MRI data of 481 cognitively intact participants in the Alzheimer's Disease Neuroimaging Initiative (ADNI) and used as regions of avoidance for fiber tracking in diffusion MRI data from 50 healthy young participants from the Human Connectome Project. Estimated tract disconnection in the right inferior fronto-occipital fasciculus, right frontal aslant tract, and right superior longitudinal fasciculus mediated the effects of WMH volume on executive function. Estimated tract disconnection in the left uncinate fasciculus mediated the effects of WMH volume on memory and in the right frontal aslant tract on language. In a subset of ADNI control participants with amyloid data, positive status increased the probability of periventricular WMH and moderated the relationship between WMH burden and tract disconnection in executive function performance.
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Affiliation(s)
- Mohammad Taghvaei
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA
| | | | | | | | - Sudipto Dolui
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA
| | - Sandhitsu Das
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA
| | - Christopher Brown
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA
| | - William Tackett
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA
| | - Pulkit Khandelwal
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA
| | - Philip Cook
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA
| | - Russell T Shinohara
- Penn Statistics in Imaging and Visualization Center, Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia, PA, USA
| | - Paul Yushkevich
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA
| | - Danielle S Bassett
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, USA
| | - David A Wolk
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA
| | - John A Detre
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA.
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Jochems ACC, Muñoz Maniega S, Clancy U, Arteaga C, Jaime Garcia D, Chappell FM, Hewins W, Locherty R, Backhouse EV, Barclay G, Jardine C, McIntyre D, Gerrish I, Kampaite A, Sakka E, Valdés Hernández M, Wiseman S, Bastin ME, Stringer MS, Thrippleton MJ, Doubal FN, Wardlaw JM. Magnetic Resonance Imaging Tissue Signatures Associated With White Matter Changes Due to Sporadic Cerebral Small Vessel Disease Indicate That White Matter Hyperintensities Can Regress. J Am Heart Assoc 2024; 13:e032259. [PMID: 38293936 PMCID: PMC11056146 DOI: 10.1161/jaha.123.032259] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/25/2023] [Accepted: 12/21/2023] [Indexed: 02/01/2024]
Abstract
BACKGROUND White matter hyperintensities (WMHs) might regress and progress contemporaneously, but we know little about underlying mechanisms. We examined WMH change and underlying quantitative magnetic resonance imaging tissue measures over 1 year in patients with minor ischemic stroke with sporadic cerebral small vessel disease. METHODS AND RESULTS We defined areas of stable normal-appearing white matter, stable WMHs, progressing and regressing WMHs based on baseline and 1-year brain magnetic resonance imaging. In these areas we assessed tissue characteristics with quantitative T1, fractional anisotropy (FA), mean diffusivity (MD), and neurite orientation dispersion and density imaging (baseline only). We compared tissue signatures cross-sectionally between areas, and longitudinally within each area. WMH change masks were available for N=197. Participants' mean age was 65.61 years (SD, 11.10), 59% had a lacunar infarct, and 68% were men. FA and MD were available for N=195, quantitative T1 for N=182, and neurite orientation dispersion and density imaging for N=174. Cross-sectionally, all 4 tissue classes differed for FA, MD, T1, and Neurite Density Index. Longitudinally, in regressing WMHs, FA increased with little change in MD and T1 (difference estimate, 0.011 [95% CI, 0.006-0.017]; -0.002 [95% CI, -0.008 to 0.003] and -0.003 [95% CI, -0.009 to 0.004]); in progressing and stable WMHs, FA decreased (-0.022 [95% CI, -0.027 to -0.017] and -0.009 [95% CI, -0.011 to -0.006]), whereas MD and T1 increased (progressing WMHs, 0.057 [95% CI, 0.050-0.063], 0.058 [95% CI, 0.050 -0.066]; stable WMHs, 0.054 [95% CI, 0.045-0.063], 0.049 [95% CI, 0.039-0.058]); and in stable normal-appearing white matter, MD increased (0.004 [95% CI, 0.003-0.005]), whereas FA and T1 slightly decreased and increased (-0.002 [95% CI, -0.004 to -0.000] and 0.005 [95% CI, 0.001-0.009]). CONCLUSIONS Quantitative magnetic resonance imaging shows that WMHs that regress have less abnormal microstructure at baseline than stable WMHs and follow trajectories indicating tissue improvement compared with stable and progressing WMHs.
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Affiliation(s)
- Angela C. C. Jochems
- Centre for Clinical Brain SciencesUniversity of EdinburghEdinburghUnited Kingdom
- UK Dementia Research Institute at the University of EdinburghEdinburghUnited Kingdom
| | - Susana Muñoz Maniega
- Centre for Clinical Brain SciencesUniversity of EdinburghEdinburghUnited Kingdom
- UK Dementia Research Institute at the University of EdinburghEdinburghUnited Kingdom
| | - Una Clancy
- Centre for Clinical Brain SciencesUniversity of EdinburghEdinburghUnited Kingdom
- UK Dementia Research Institute at the University of EdinburghEdinburghUnited Kingdom
| | - Carmen Arteaga
- Centre for Clinical Brain SciencesUniversity of EdinburghEdinburghUnited Kingdom
- UK Dementia Research Institute at the University of EdinburghEdinburghUnited Kingdom
| | - Daniela Jaime Garcia
- Centre for Clinical Brain SciencesUniversity of EdinburghEdinburghUnited Kingdom
- UK Dementia Research Institute at the University of EdinburghEdinburghUnited Kingdom
| | - Francesca M. Chappell
- Centre for Clinical Brain SciencesUniversity of EdinburghEdinburghUnited Kingdom
- UK Dementia Research Institute at the University of EdinburghEdinburghUnited Kingdom
| | - Will Hewins
- Centre for Clinical Brain SciencesUniversity of EdinburghEdinburghUnited Kingdom
- UK Dementia Research Institute at the University of EdinburghEdinburghUnited Kingdom
| | - Rachel Locherty
- Centre for Clinical Brain SciencesUniversity of EdinburghEdinburghUnited Kingdom
- UK Dementia Research Institute at the University of EdinburghEdinburghUnited Kingdom
| | - Ellen V. Backhouse
- Centre for Clinical Brain SciencesUniversity of EdinburghEdinburghUnited Kingdom
- UK Dementia Research Institute at the University of EdinburghEdinburghUnited Kingdom
| | - Gayle Barclay
- Edinburgh Imaging Facility, Royal Infirmary of EdinburghEdinburghUnited Kingdom
| | - Charlotte Jardine
- Edinburgh Imaging Facility, Royal Infirmary of EdinburghEdinburghUnited Kingdom
| | - Donna McIntyre
- Edinburgh Imaging Facility, Royal Infirmary of EdinburghEdinburghUnited Kingdom
| | - Iona Gerrish
- Edinburgh Imaging Facility, Royal Infirmary of EdinburghEdinburghUnited Kingdom
| | - Agniete Kampaite
- Centre for Clinical Brain SciencesUniversity of EdinburghEdinburghUnited Kingdom
| | - Eleni Sakka
- Centre for Clinical Brain SciencesUniversity of EdinburghEdinburghUnited Kingdom
| | - Maria Valdés Hernández
- Centre for Clinical Brain SciencesUniversity of EdinburghEdinburghUnited Kingdom
- UK Dementia Research Institute at the University of EdinburghEdinburghUnited Kingdom
| | - Stewart Wiseman
- Centre for Clinical Brain SciencesUniversity of EdinburghEdinburghUnited Kingdom
- UK Dementia Research Institute at the University of EdinburghEdinburghUnited Kingdom
| | - Mark E. Bastin
- Centre for Clinical Brain SciencesUniversity of EdinburghEdinburghUnited Kingdom
| | - Michael S. Stringer
- Centre for Clinical Brain SciencesUniversity of EdinburghEdinburghUnited Kingdom
- UK Dementia Research Institute at the University of EdinburghEdinburghUnited Kingdom
| | - Michael J. Thrippleton
- Centre for Clinical Brain SciencesUniversity of EdinburghEdinburghUnited Kingdom
- UK Dementia Research Institute at the University of EdinburghEdinburghUnited Kingdom
- Edinburgh Imaging Facility, Royal Infirmary of EdinburghEdinburghUnited Kingdom
| | - Fergus N. Doubal
- Centre for Clinical Brain SciencesUniversity of EdinburghEdinburghUnited Kingdom
- UK Dementia Research Institute at the University of EdinburghEdinburghUnited Kingdom
| | - Joanna M. Wardlaw
- Centre for Clinical Brain SciencesUniversity of EdinburghEdinburghUnited Kingdom
- UK Dementia Research Institute at the University of EdinburghEdinburghUnited Kingdom
- Edinburgh Imaging Facility, Royal Infirmary of EdinburghEdinburghUnited Kingdom
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Iandolo R, Avci E, Bommarito G, Sandvig I, Rohweder G, Sandvig A. Characterizing upper extremity fine motor function in the presence of white matter hyperintensities: A 7 T MRI cross-sectional study in older adults. Neuroimage Clin 2024; 41:103569. [PMID: 38281363 PMCID: PMC10839532 DOI: 10.1016/j.nicl.2024.103569] [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: 07/10/2023] [Revised: 01/19/2024] [Accepted: 01/21/2024] [Indexed: 01/30/2024]
Abstract
BACKGROUND White matter hyperintensities (WMH) are a prevalent radiographic finding in the aging brain studies. Research on WMH association with motor impairment is mostly focused on the lower-extremity function and further investigation on the upper-extremity is needed. How different degrees of WMH burden impact the network of activation recruited during upper limb motor performance could provide further insight on the complex mechanisms of WMH pathophysiology and its interaction with aging and neurological disease processes. METHODS 40 healthy elderly subjects without a neurological/psychiatric diagnosis were included in the study (16F, mean age 69.3 years). All subjects underwent ultra-high field 7 T MRI including structural and finger tapping task-fMRI. First, we quantified the WMH lesion load and its spatial distribution. Secondly, we performed a data-driven stratification of the subjects according to their periventricular and deep WMH burdens. Thirdly, we investigated the distribution of neural recruitment and the corresponding activity assessed through BOLD signal changes among different brain regions for groups of subjects. We clustered the degree of WMH based on location, numbers, and volume into three categories; ranging from mild, moderate, and severe. Finally, we explored how the spatial distribution of WMH, and activity elicited during task-fMRI relate to motor function, measured with the 9-Hole Peg Test. RESULTS Within our population, we found three subgroups of subjects, partitioned according to their periventricular and deep WMH lesion load. We found decreased activity in several frontal and cingulate cortex areas in subjects with a severe WMH burden. No statistically significant associations were found when performing the brain-behavior statistical analysis for structural or functional data. CONCLUSION WMH burden has an effect on brain activity during fine motor control and the activity changes are associated with varying degrees of the total burden and distributions of WMH lesions. Collectively, our results shed new light on the potential impact of WMH on motor function in the context of aging and neurodegeneration.
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Affiliation(s)
- Riccardo Iandolo
- Department of Neuromedicine and Movement Science, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology (NTNU), Trondheim, Norway.
| | - Esin Avci
- Department of Neuromedicine and Movement Science, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology (NTNU), Trondheim, Norway.
| | - Giulia Bommarito
- Department of Clinical Neurosciences, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Ioanna Sandvig
- Department of Neuromedicine and Movement Science, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
| | - Gitta Rohweder
- Department of Neuromedicine and Movement Science, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology (NTNU), Trondheim, Norway; Stroke Unit, Department of Medicine, St Olav's University Hospital, Trondheim, Norway
| | - Axel Sandvig
- Department of Neuromedicine and Movement Science, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology (NTNU), Trondheim, Norway; Department of Neurology and Clinical Neurophysiology, St. Olav's University Hospital, Trondheim, Norway; Department of Clinical Neurosciences, Division of Neuro, Head and Neck, Umeå University Hospital, Umeå, Sweden; Department of Community Medicine and Rehabilitation, Umeå University Hospital, Umeå, Sweden.
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5
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Caçoilo A, Dortdivanlioglu B, Rusinek H, Weickenmeier J. A multiphysics model to predict periventricular white matter hyperintensity growth during healthy brain aging. BRAIN MULTIPHYSICS 2023; 5:100072. [PMID: 37546181 PMCID: PMC10399513 DOI: 10.1016/j.brain.2023.100072] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/08/2023] Open
Abstract
Periventricular white matter hyperintensities (WMH) are a common finding in medical images of the aging brain and are associated with white matter damage resulting from cerebral small vessel disease, white matter inflammation, and a degeneration of the lateral ventricular wall. Despite extensive work, the etiology of periventricular WMHs remains unclear. We pose that there is a strong coupling between age-related ventricular expansion and the degeneration of the ventricular wall which leads to a dysregulated fluid exchange across this brain-fluid barrier. Here, we present a multiphysics model that couples cerebral atrophy-driven ventricular wall loading with periventricular WMH formation and progression. We use patient data to create eight 2D finite element models and demonstrate the predictive capabilities of our damage model. Our simulations show that we accurately capture the spatiotemporal features of periventricular WMH growth. For one, we observe that damage appears first in both the anterior and posterior horns and then spreads into deeper white matter tissue. For the other, we note that it takes up to 12 years before periventricular WMHs first appear and derive an average annualized periventricular WMH damage growth rate of 15.2 ± 12.7 mm2/year across our models. A sensitivity analysis demonstrated that our model parameters provide sufficient sensitivity to rationalize subject-specific differences with respect to onset time and damage growth. Moreover, we show that the septum pellucidum, a membrane that separates the left and right lateral ventricles, delays the onset of periventricular WMHs at first, but leads to a higher WMH load in the long-term.
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Affiliation(s)
- Andreia Caçoilo
- Department of Mechanical Engineering, Stevens Institute of Technology, Hoboken, NJ 07030, United States of America
| | - Berkin Dortdivanlioglu
- Civil, Architectural, and Environmental Engineering, The University of Texas at Austin, Austin, TX 78712, United States of America
| | - Henry Rusinek
- Department of Radiology, New York University Grossman School of Medicine, New York, NY 10016, United States of America
| | - Johannes Weickenmeier
- Department of Mechanical Engineering, Stevens Institute of Technology, Hoboken, NJ 07030, United States of America
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Taghvaei M, Cook P, Sadaghiani S, Shakibajahromi B, Tackett W, Dolui S, De D, Brown C, Khandelwal P, Yushkevich P, Das S, Wolk DA, Detre JA. Young versus older subject diffusion magnetic resonance imaging data for virtual white matter lesion tractography. Hum Brain Mapp 2023; 44:3943-3953. [PMID: 37148501 PMCID: PMC10258527 DOI: 10.1002/hbm.26326] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2022] [Revised: 04/12/2023] [Accepted: 04/17/2023] [Indexed: 05/08/2023] Open
Abstract
White matter hyperintensity (WMH) lesions on T2 fluid-attenuated inversion recovery (FLAIR) magnetic resonance imaging (MRI) and changes in adjacent normal-appearing white matter can disrupt computerized tract reconstruction and result in inaccurate measures of structural brain connectivity. The virtual lesion approach provides an alternative strategy for estimating structural connectivity changes due to WMH. To assess the impact of using young versus older subject diffusion MRI data for virtual lesion tractography, we leveraged recently available diffusion MRI data from the Human Connectome Project (HCP) Lifespan database. Neuroimaging data from 50 healthy young (39.2 ± 1.6 years) and 46 healthy older (74.2 ± 2.5 years) subjects were obtained from the publicly available HCP-Aging database. Three WMH masks with low, moderate, and high lesion burdens were extracted from the WMH lesion frequency map of locally acquired FLAIR MRI data. Deterministic tractography was conducted to extract streamlines in 21 WM bundles with and without the WMH masks as regions of avoidance in both young and older cohorts. For intact tractography without virtual lesion masks, 7 out of 21 WM pathways showed a significantly lower number of streamlines in older subjects compared to young subjects. A decrease in streamline count with higher native lesion burden was found in corpus callosum, corticostriatal tract, and fornix pathways. Comparable percentages of affected streamlines were obtained in young and older groups with virtual lesion tractography using the three WMH lesion masks of increasing severity. We conclude that using normative diffusion MRI data from young subjects for virtual lesion tractography of WMH is, in most cases, preferable to using age-matched normative data.
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Affiliation(s)
- Mohammad Taghvaei
- Department of NeurologyUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Philip Cook
- Department of RadiologyUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Shokufeh Sadaghiani
- Department of NeurologyUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | | | - William Tackett
- Department of NeurologyUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Sudipto Dolui
- Department of RadiologyUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Debarun De
- Department of Computer EngineeringUniversity of IllinoisUrbanaIllinoisUSA
| | - Christopher Brown
- Department of NeurologyUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Pulkit Khandelwal
- Department of BioengineeringUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Paul Yushkevich
- Department of RadiologyUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Sandhitsu Das
- Department of NeurologyUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - David A. Wolk
- Department of NeurologyUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - John A. Detre
- Department of NeurologyUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
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Caçoilo A, Rusinek H, Weickenmeier J. 3D finite-element brain modeling of lateral ventricular wall loading to rationalize periventricular white matter hyperintensity locations. ENGINEERING WITH COMPUTERS 2022; 38:3939-3955. [PMID: 37485473 PMCID: PMC10361695 DOI: 10.1007/s00366-022-01700-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/10/2021] [Accepted: 06/19/2022] [Indexed: 07/25/2023]
Abstract
Aging-related periventricular white matter hyperintensities (pvWMHs) are a common observation in medical images of the aging brain. The underlying tissue damage is part of the complex pathophysiology associated with age-related microstructural changes and cognitive decline. PvWMH formation is linked to blood-brain barrier dysfunction from cerebral small vessel disease as well as the accumulation of cerebrospinal fluid in periventricular tissue due to progressive denudation of the ventricular wall. In need of a unifying theory for pvWMH etiology, image-based finite-element modeling is used to demonstrate that ventricular expansion from age-related cerebral atrophy and hemodynamic loading leads to maximum mechanical loading of the ventricular wall in the same locations that show pvWMHs. Ventricular inflation, induced via pressurization of the ventricular wall, creates significant ventricular wall stretch and stress on the ependymal cells lining the wall, that are linked to cerebrospinal fluid leaking from the lateral ventricles into periventricular white matter tissue. Eight anatomically accurate 3D brain models of cognitively healthy subjects with a wide range of ventricular shapes are created. For all models, our simulations show that mechanomarkers of mechanical wall loading are consistently highest in pvWMHs locations (p < 0.05). Maximum principal strain, the ependymal cell thinning ratio, and wall curvature are on average 14%, 8%, and 24% higher in pvWMH regions compared to the remaining ventricular wall, respectively. Computational modeling provides a powerful framework to systematically study pvWMH formation and growth with the goal to develop pharmacological interventions in the future.
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Affiliation(s)
- Andreia Caçoilo
- Department of Mechanical Engineering, Stevens Institute of Technology, Hoboken, NJ 07030, USA
| | - Henry Rusinek
- Department of Radiology, New York University Grossman School of Medicine, New York, NY 10016, USA
| | - Johannes Weickenmeier
- Department of Mechanical Engineering, Stevens Institute of Technology, Hoboken, NJ 07030, USA
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Ferris J, Greeley B, Yeganeh NM, Rinat S, Ramirez J, Black S, Boyd L. Exploring biomarkers of processing speed and executive function: The role of the anterior thalamic radiations. Neuroimage Clin 2022; 36:103174. [PMID: 36067614 PMCID: PMC9460835 DOI: 10.1016/j.nicl.2022.103174] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2022] [Revised: 08/08/2022] [Accepted: 08/27/2022] [Indexed: 12/14/2022]
Abstract
INTRODUCTION Processing speed and executive function are often impaired after stroke and in typical aging. However, there are no reliable neurological markers of these cognitive impairments. The trail making test (TMT) is a common index of processing speed and executive function. Here, we tested candidate MRI markers of TMT performance in a cohort of older adults and individuals with chronic stroke. METHODS In 61 older adults and 32 individuals with chronic stroke, we indexed white matter structure with region-specific lesion load (of white matter hyperintensities (WMHs) and stroke lesions) and diffusion tensor imaging (DTI) from four regions related to TMT performance: the anterior thalamic radiations (ATR), superior longitudinal fasciculus (SLF), forceps minor, and cholinergic pathways. Regression modelling was used to identify the marker(s) that explained the most variance in TMT performance. RESULTS DTI metrics of the ATR related to processing speed in both the older adult (TMT A: β = -3.431, p < 0.001) and chronic stroke (TMT A: β = 11.282, p < 0.001) groups. In the chronic stroke group executive function was best predicted by a combination of ATR and forceps minor DTI metrics (TMT B: adjustedR2 = 0.438, p < 0.001); no significant predictors of executive function (TMT B) emerged in the older adult group. No imaging metrics related to set shifting (TMT B-A). Regional DTI metrics predicted TMT performance above and beyond whole-brain stroke and WMH volumes and removing whole-brain lesion volumes improved model fits. CONCLUSIONS In this comprehensive assessment of candidate imaging markers, we demonstrate an association between ATR microstructure and processing speed and executive function performance. Regional DTI metrics provided better predictors of cognitive performance than whole-brain lesion volumes or regional lesion load, emphasizing the importance of lesion location in understanding cognition. We propose ATR DTI metrics as novel candidate imaging biomarker of post-stroke cognitive impairment.
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Affiliation(s)
- Jennifer Ferris
- Department of Physical Therapy, University of British Columbia, Vancouver, Canada,Graduate Programs in Rehabilitation Sciences, University of British Columbia, Vancouver, Canada
| | - Brian Greeley
- Department of Physical Therapy, University of British Columbia, Vancouver, Canada
| | - Negin Motamed Yeganeh
- Djavad Mowafaghian Centre for Brain Health, University of British Columbia, Vancouver, Canada
| | - Shie Rinat
- Department of Physical Therapy, University of British Columbia, Vancouver, Canada,Graduate Programs in Rehabilitation Sciences, University of British Columbia, Vancouver, Canada
| | - Joel Ramirez
- LC Campbell Cognitive Neurology Research Unit, Dr Sandra Black Centre for Brain Resilience and Recovery, Toronto, Canada,Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, University of Toronto, Toronto, Canada
| | - Sandra Black
- LC Campbell Cognitive Neurology Research Unit, Dr Sandra Black Centre for Brain Resilience and Recovery, Toronto, Canada,Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, University of Toronto, Toronto, Canada
| | - Lara Boyd
- Department of Physical Therapy, University of British Columbia, Vancouver, Canada,Graduate Programs in Rehabilitation Sciences, University of British Columbia, Vancouver, Canada,Djavad Mowafaghian Centre for Brain Health, University of British Columbia, Vancouver, Canada,Corresponding author at: University of British Columbia, 212-2177 Wesbrook Mall, Vancouver, British Columbia V6T 2B5, Canada.
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9
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Ferris JK, Greeley B, Vavasour IM, Kraeutner SN, Rinat S, Ramirez J, Black SE, Boyd LA. In vivo myelin imaging and tissue microstructure in white matter hyperintensities and perilesional white matter. Brain Commun 2022; 4:fcac142. [PMID: 35694147 PMCID: PMC9178967 DOI: 10.1093/braincomms/fcac142] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2022] [Revised: 03/28/2022] [Accepted: 05/26/2022] [Indexed: 11/12/2022] Open
Abstract
White matter hyperintensities negatively impact white matter structure and relate to cognitive decline in aging. Diffusion tensor imaging detects changes to white matter microstructure, both within the white matter hyperintensity and extending into surrounding (perilesional) normal-appearing white matter. However, diffusion tensor imaging markers are not specific to tissue components, complicating the interpretation of previous microstructural findings. Myelin water imaging is a novel imaging technique that provides specific markers of myelin content (myelin water fraction) and interstitial fluid (geometric mean T2). Here we combined diffusion tensor imaging and myelin water imaging to examine tissue characteristics in white matter hyperintensities and perilesional white matter in 80 individuals (47 older adults and 33 individuals with chronic stroke). To measure perilesional normal-appearing white matter, white matter hyperintensity masks were dilated in 2 mm segments up to 10 mm in distance from the white matter hyperintensity. Fractional anisotropy, mean diffusivity, myelin water fraction, and geometric mean T2 were extracted from white matter hyperintensities and perilesional white matter. We observed a spatial gradient of higher mean diffusivity and geometric mean T2, and lower fractional anisotropy, in the white matter hyperintensity and perilesional white matter. In the chronic stroke group, myelin water fraction was reduced in the white matter hyperintensity but did not show a spatial gradient in perilesional white matter. Across the entire sample, white matter metrics within the white matter hyperintensity related to whole-brain white matter hyperintensity volume; with increasing white matter hyperintensity volume there was increased mean diffusivity and geometric mean T2, and decreased myelin water fraction in the white matter hyperintensity. Normal-appearing white matter adjacent to white matter hyperintensities exhibits characteristics of a transitional stage between healthy white matter and white matter hyperintensities. This effect was observed in markers sensitive to interstitial fluid, but not in myelin water fraction, the specific marker of myelin concentration. Within the white matter hyperintensity, interstitial fluid was higher and myelin concentration was lower in individuals with more severe cerebrovascular disease. Our data suggests white matter hyperintensities have penumbra-like effects in perilesional white matter that specifically reflect increased interstitial fluid, with no changes to myelin concentration. In contrast, within the white matter hyperintensity there are varying levels of demyelination, which vary based on the severity of cerebrovascular disease. Diffusion tensor imaging and myelin imaging may be useful clinical markers to predict white matter hyperintensity formation, and to stage neuronal damage within white matter hyperintensities.
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Affiliation(s)
- Jennifer K. Ferris
- University of British Columbia Graduate Programs in Rehabilitation Sciences, , Vancouver, Canada
| | - Brian Greeley
- University of British Columbia Department of Physical Therapy, , Vancouver, Canada
| | - Irene M. Vavasour
- The University of British Columbia Department of Radiology, , Vancouver, Canada
- University of British Columbia UBC MRI Research Centre, Faculty of Medicine, , Vancouver, Canada
| | - Sarah N. Kraeutner
- University of British Columbia Department of Psychology, , Okanagan, Kelowna, Canada
| | - Shie Rinat
- University of British Columbia Graduate Programs in Rehabilitation Sciences, , Vancouver, Canada
| | - Joel Ramirez
- LC Campbell Cognitive Neurology Research Unit, Dr Sandra Black Centre for Brain Resilience and Recovery , Toronto, Canada
- Sunnybrook Research Institute, University of Toronto Hurvitz Brain Sciences Research Program, , Toronto, Canada
| | - Sandra E. Black
- LC Campbell Cognitive Neurology Research Unit, Dr Sandra Black Centre for Brain Resilience and Recovery , Toronto, Canada
- Sunnybrook Research Institute, University of Toronto Hurvitz Brain Sciences Research Program, , Toronto, Canada
| | - Lara A. Boyd
- University of British Columbia Graduate Programs in Rehabilitation Sciences, , Vancouver, Canada
- University of British Columbia Department of Physical Therapy, , Vancouver, Canada
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10
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Dounavi ME, Low A, Muniz-Terrera G, Ritchie K, Ritchie CW, Su L, Markus HS, O’Brien JT. Fluid-attenuated inversion recovery magnetic resonance imaging textural features as sensitive markers of white matter damage in midlife adults. Brain Commun 2022; 4:fcac116. [PMID: 35611309 PMCID: PMC9123845 DOI: 10.1093/braincomms/fcac116] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2021] [Revised: 01/28/2022] [Accepted: 05/04/2022] [Indexed: 11/18/2022] Open
Abstract
White matter hyperintensities are common radiological findings in ageing and a typical manifestation of cerebral small vessel disease. White matter hyperintensity burden is evaluated by quantifying their volume; however, subtle changes in the white matter may not be captured by white matter hyperintensity volumetry. In this cross-sectional study, we investigated whether magnetic resonance imaging texture of both white matter hyperintensities and normal appearing white matter was associated with reaction time, white matter hyperintensity volume and dementia risk in a midlife cognitively normal population. Data from 183 cognitively healthy midlife adults from the PREVENT-Dementia study (mean age 51.9 ± 5.4; 70% females) were analysed. White matter hyperintensities were segmented from 3 Tesla fluid-attenuated inversion recovery scans using a semi-automated approach. The fluid-attenuated inversion recovery images were bias field corrected and textural features (intensity mean and standard deviation, contrast, energy, entropy, homogeneity) were calculated in white matter hyperintensities and normal appearing white matter based on generated textural maps. Textural features were analysed for associations with white matter hyperintensity volume, reaction time and the Cardiovascular Risk Factors, Aging and Dementia risk score using linear regression models adjusting for age and sex. The extent of normal appearing white matter surrounding white matter hyperintensities demonstrating similar textural associations to white matter hyperintensities was further investigated by defining layers surrounding white matter hyperintensities at increments of 0.86 mm thickness. Lower mean intensity within white matter hyperintensities was a significant predictor of longer reaction time (t = −3.77, P < 0.01). White matter hyperintensity volume was predicted by textural features within white matter hyperintensities and normal appearing white matter, albeit in opposite directions. A white matter area extending 2.5 – 3.5 mm further from the white matter hyperintensities demonstrated similar associations. White matter hyperintensity volume was not related to reaction time, although interaction analysis revealed that participants with high white matter hyperintensity burden and less homogeneous white matter hyperintensity texture demonstrated slower reaction time. Higher Cardiovascular Risk Factors, Aging, and Dementia score was associated with a heterogeneous normal appearing white matter intensity pattern. Overall, greater homogeneity within white matter hyperintensities and a more heterogeneous normal appearing white matter intensity profile were connected to a higher white matter hyperintensity burden, while heterogeneous intensity was related to prolonged reaction time (white matter hyperintensities of larger volume) and dementia risk (normal appearing white matter). Our results suggest that the quantified textural measures extracted from widely used clinical scans, might capture underlying microstructural damage and might be more sensitive to early pathological changes compared to white matter hyperintensity volumetry.
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Affiliation(s)
- Maria-Eleni Dounavi
- Department of Psychiatry, School of Clinical Medicine, University of Cambridge, United Kingdom
| | - Audrey Low
- Department of Psychiatry, School of Clinical Medicine, University of Cambridge, United Kingdom
| | | | - Karen Ritchie
- Centre for Dementia Prevention, University of Edinburgh, Edinburgh, United Kingdom
- INM, Univ Montpellier, INSERM, Montpellier, France
| | - Craig W. Ritchie
- Centre for Dementia Prevention, University of Edinburgh, Edinburgh, United Kingdom
| | - Li Su
- Department of Psychiatry, School of Clinical Medicine, University of Cambridge, United Kingdom
- Department of Neuroscience, University of Sheffield, Sheffield, United Kingdom
| | - Hugh S. Markus
- Department of Clinical Neurosciences, University of Cambridge, United Kingdom
| | - John T. O’Brien
- Department of Psychiatry, School of Clinical Medicine, University of Cambridge, United Kingdom
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11
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Cox SR, Deary IJ. Brain and cognitive ageing: The present, and some predictions (…about the future). AGING BRAIN 2022; 2:100032. [PMID: 36908875 PMCID: PMC9997131 DOI: 10.1016/j.nbas.2022.100032] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2022] [Revised: 01/18/2022] [Accepted: 01/31/2022] [Indexed: 11/26/2022] Open
Abstract
Experiencing decline in one's cognitive abilities is among the most feared aspects of growing old [53]. Age-related cognitive decline carries a huge personal, societal, and financial cost both in pathological ageing (such as dementias) and also within the non-clinical majority of the population. A projected 152 million people worldwide will suffer from dementia by 2050 [3]. The early stages of cognitive decline are much more prevalent than dementia, and can still impose serious limitations of performance on everyday activities, independence, and quality of life in older age [5], [60], [80]. Cognitive decline also predicts poorer health, adherence to medical regimens, and financial decision-making, and can herald dementia, illness, and death [6], [40]. Of course, when seeking to understand why some people experience more severe cognitive ageing than others, researchers have turned to the organ of thinking for clues about the nature, possible mechanisms, and determinants that might underpin more and less successful cognitive agers. However, that organ is relatively inaccessible, a limitation partly alleviated by advances in neuroimaging. Here we discuss lessons for cognitive and brain ageing that have come from neuroimaging research (especially structural brain imaging), what neuroimaging still has left to teach us, and our views on possible ways forward in this multidisciplinary field.
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Affiliation(s)
- Simon R. Cox
- Lothian Birth Cohorts, Department of Psychology, The University of Edinburgh, UK
- Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) Collaboration, Edinburgh, UK
| | - Ian J. Deary
- Lothian Birth Cohorts, Department of Psychology, The University of Edinburgh, UK
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12
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Wardlaw JM, Benveniste H, Williams A. Cerebral Vascular Dysfunctions Detected in Human Small Vessel Disease and Implications for Preclinical Studies. Annu Rev Physiol 2022; 84:409-434. [PMID: 34699267 DOI: 10.1146/annurev-physiol-060821-014521] [Citation(s) in RCA: 30] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Cerebral small vessel disease (SVD) is highly prevalent and a common cause of ischemic and hemorrhagic stroke and dementia, yet the pathophysiology is poorly understood. Its clinical expression is highly varied, and prognostic implications are frequently overlooked in clinics; thus, treatment is currently confined to vascular risk factor management. Traditionally, SVD is considered the small vessel equivalent of large artery stroke (occlusion, rupture), but data emerging from human neuroimaging and genetic studies refute this, instead showing microvessel endothelial dysfunction impacting on cell-cell interactions and leading to brain damage. These dysfunctions reflect defects that appear to be inherited and secondary to environmental exposures, including vascular risk factors. Interrogation in preclinical models shows consistent and converging molecular and cellular interactions across the endothelial-glial-neural unit that increasingly explain the human macroscopic observations and identify common patterns of pathology despite different triggers. Importantly, these insights may offer new targets for therapeutic intervention focused on restoring endothelial-glial physiology.
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Affiliation(s)
- Joanna M Wardlaw
- Division of Neuroimaging Sciences, Centre for Clinical Brain Sciences; UK Dementia Research Institute; and Edinburgh Imaging, University of Edinburgh, Edinburgh, United Kingdom;
| | - Helene Benveniste
- Department of Anesthesiology, Yale School of Medicine, New Haven, Connecticut, USA
| | - Anna Williams
- Centre for Regenerative Medicine, Institute for Regeneration and Repair, University of Edinburgh, Edinburgh, United Kingdom
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13
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Deary IJ, Cox SR, Hill WD. Genetic variation, brain, and intelligence differences. Mol Psychiatry 2022; 27:335-353. [PMID: 33531661 PMCID: PMC8960418 DOI: 10.1038/s41380-021-01027-y] [Citation(s) in RCA: 38] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/23/2020] [Revised: 12/28/2020] [Accepted: 01/11/2021] [Indexed: 01/30/2023]
Abstract
Individual differences in human intelligence, as assessed using cognitive test scores, have a well-replicated, hierarchical phenotypic covariance structure. They are substantially stable across the life course, and are predictive of educational, social, and health outcomes. From this solid phenotypic foundation and importance for life, comes an interest in the environmental, social, and genetic aetiologies of intelligence, and in the foundations of intelligence differences in brain structure and functioning. Here, we summarise and critique the last 10 years or so of molecular genetic (DNA-based) research on intelligence, including the discovery of genetic loci associated with intelligence, DNA-based heritability, and intelligence's genetic correlations with other traits. We summarise new brain imaging-intelligence findings, including whole-brain associations and grey and white matter associations. We summarise regional brain imaging associations with intelligence and interpret these with respect to theoretical accounts. We address research that combines genetics and brain imaging in studying intelligence differences. There are new, though modest, associations in all these areas, and mechanistic accounts are lacking. We attempt to identify growing points that might contribute toward a more integrated 'systems biology' account of some of the between-individual differences in intelligence.
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Affiliation(s)
- Ian J. Deary
- grid.4305.20000 0004 1936 7988Lothian Birth Cohorts group, Department of Psychology, University of Edinburgh, 7 George Square, Edinburgh, EH8 9JZ UK
| | - Simon R. Cox
- grid.4305.20000 0004 1936 7988Lothian Birth Cohorts group, Department of Psychology, University of Edinburgh, 7 George Square, Edinburgh, EH8 9JZ UK
| | - W. David Hill
- grid.4305.20000 0004 1936 7988Lothian Birth Cohorts group, Department of Psychology, University of Edinburgh, 7 George Square, Edinburgh, EH8 9JZ UK
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14
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McCook O, Scheuerle A, Denoix N, Kapapa T, Radermacher P, Merz T. Localization of the hydrogen sulfide and oxytocin systems at the depth of the sulci in a porcine model of acute subdural hematoma. Neural Regen Res 2021; 16:2376-2382. [PMID: 33907009 PMCID: PMC8374554 DOI: 10.4103/1673-5374.313018] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2020] [Revised: 11/17/2020] [Accepted: 12/10/2020] [Indexed: 11/24/2022] Open
Abstract
In the porcine model discussed in this review, the acute subdural hematoma was induced by subdural injection of autologous blood over the left parietal cortex, which led to a transient elevation of the intracerebral pressure, measured by bilateral neuromonitoring. The hematoma-induced brain injury was associated with albumin extravasation, oxidative stress, reactive astrogliosis and microglial activation in the ipsilateral hemisphere. Further proteins and injury markers were validated to be used for immunohistochemistry of porcine brain tissue. The cerebral expression patterns of oxytocin, oxytocin receptor, cystathionine-γ-lyase and cystathionine-β-synthase were particularly interesting: these four proteins all co-localized at the base of the sulci, where pressure-induced brain injury elicits maximum stress. In this context, the pig is a very relevant translational model in contrast to the rodent brain. The structure of the porcine brain is very similar to the human: the presence of gyri and sulci (gyrencephalic brain), white matter to grey matter proportion and tentorium cerebelli. Thus, pressure-induced injury in the porcine brain, unlike in the rodent brain, is reflective of the human pathophysiology.
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Affiliation(s)
- Oscar McCook
- Institute for Anesthesiological Pathophysiology and Process Engineering, Ulm University Medical Center, Ulm, Germany
| | - Angelika Scheuerle
- Department of Neuropathology, Ulm University Medical Center, Günzburg, Germany
| | - Nicole Denoix
- Institute for Anesthesiological Pathophysiology and Process Engineering, Ulm University Medical Center, Ulm, Germany
- Clinic for Psychosomatic Medicine and Psychotherapy, Ulm University Medical Center, Ulm, Germany
| | - Thomas Kapapa
- Department of Neurosurgery, Ulm University Medical Center, Ulm, Germany
| | - Peter Radermacher
- Institute for Anesthesiological Pathophysiology and Process Engineering, Ulm University Medical Center, Ulm, Germany
| | - Tamara Merz
- Institute for Anesthesiological Pathophysiology and Process Engineering, Ulm University Medical Center, Ulm, Germany
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15
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Shirazi Y, Oghabian MA, Batouli SAH. Along-tract analysis of the white matter is more informative about brain ageing, compared to whole-tract analysis. Clin Neurol Neurosurg 2021; 211:107048. [PMID: 34826755 DOI: 10.1016/j.clineuro.2021.107048] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2021] [Revised: 10/25/2021] [Accepted: 11/14/2021] [Indexed: 11/30/2022]
Abstract
Diffusion Tensor Imaging (DTI) enabled the investigation of brain White Matter (WM), both qualitatively to study the macrostructure, and quantitatively to study the microstructure. The quantitative analyses are mostly performed at the whole-tract level, i.e., providing one measure of interest per tract; however, along-tract approaches may provide finer details of the quality of the WM tracts. In this study, using the DWI data collected from 40 young and 40 old individuals, we compared the DTI measures of FA, MD, AD, and RD, estimated by both whole-tract and along-tract approaches in 18 WM bundles, between the two groups. The results of the whole-tract quantitative analysis showed a statistically significant (p-FWER < 0.05) difference between the old and young groups in 6 tracts for FA, 8 tracts for MD, 1 tract for AD, and 7 tracts for RD. On the contrary, the along-tract approach showed differences between the two groups in 10 tracts for FA, 14 tracts for MD, 8 tracts for AD, and 11 tracts for RD. All the differences between the along-tract measures of the two groups had a large effect size (Cohen'd > 0.80). This study showed that the along-tract approach for the analysis of brain WM reveals changes in some WM tracts which had not shown any changes in the whole-tract approach, and therefore this finding emphasizes the utilization of the along-tract approach along with the whole-tract method for a more accurate study of the brain WM.
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Affiliation(s)
- Yasin Shirazi
- Medical Physics and Biomedical Engineering Department, Tehran University of Medical Sciences, Tehran, Iran
| | - Mohammad Ali Oghabian
- Medical Physics and Biomedical Engineering Department, Tehran University of Medical Sciences, Tehran, Iran; Neuroimaging and Analysis Group, Research Center for Molecular and Cellular Imaging, Tehran University of Medical Sciences, Tehran, Iran
| | - Seyed Amir Hossein Batouli
- Neuroimaging and Analysis Group, Research Center for Molecular and Cellular Imaging, Tehran University of Medical Sciences, Tehran, Iran; Department of Neuroscience and addiction Studies, School of Advanced Technologies in Medicine, Tehran University of Medical Sciences, Tehran, Iran.
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16
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Xu Z, Li F, Xing D, Song H, Chen J, Duan Y, Yang B. A Novel Imaging Biomarker for Cerebral Small Vessel Disease Associated With Cognitive Impairment: The Deep-Medullary-Veins Score. Front Aging Neurosci 2021; 13:720481. [PMID: 34759812 PMCID: PMC8572877 DOI: 10.3389/fnagi.2021.720481] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2021] [Accepted: 10/04/2021] [Indexed: 11/13/2022] Open
Abstract
Objective: To explore the biomarkers of cerebral small vessel disease (CSVD) associated with cognitive impairment. Methods: A total of 69 patients with CSVD were enrolled in the study, and baseline clinical and imaging data were reviewed retrospectively. The following neuroimaging biomarkers of CSVD were identified: high-grade white matter hyperintensity (HWMH), cerebral microbleeds (CMB), enlarged perivascular space (PVS), and lacunar infarct (LI). A total score for CSVD was calculated. The deep medullary veins (DMVs) were divided into six segments according to the regional anatomy. The total DMV score (0–18) was derived from the sum of the scores of the six individual segments, the scores of which ranged from 0 to 3, for a semiquantitative assessment of the DMV that was based on segmental continuity and visibility. Results: The DMV score, patient age, and total CSVD score were independently associated with the presence or absence of cognitive impairment in patients with CSVD (P < 0.05). By integrating patient age and the total CSVD and DMV scores, the area under the curve of the receiver operating characteristic curve (AUROC) for predicting CSVD associated with cognitive impairment was 0.885, and the sensitivity and specificity were 64.71 and 94.23%, respectively. Conclusions: The DMV score may be a novel imaging biomarker for CSVD associated with cognitive impairment. The integration of the DMV score with age and total CSVD score should increase the predictive value of the DMV score for CSVD associated with cognitive impairment.
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Affiliation(s)
- Zhihua Xu
- Department of Radiology, Tongde Hospital of Zhejiang Province, Hangzhou, China.,Center for Neuroimaging, Department of Radiology, General Hospital of Northern Theater Command, Shenyang, China
| | - Fangfei Li
- Center for Neuroimaging, Department of Radiology, General Hospital of Northern Theater Command, Shenyang, China.,General Hospital of Northern Theater Command Training Base for Graduate, Dalian Medical University, Shenyang, China
| | - Dengxiang Xing
- Center for Medical Data, General Hospital of Northern Theater Command, Shenyang, China
| | - Hongyan Song
- Center for Neuroimaging, Department of Radiology, General Hospital of Northern Theater Command, Shenyang, China
| | - Jingshu Chen
- Center for Neuroimaging, Department of Radiology, General Hospital of Northern Theater Command, Shenyang, China
| | - Yang Duan
- Center for Neuroimaging, Department of Radiology, General Hospital of Northern Theater Command, Shenyang, China.,General Hospital of Northern Theater Command Training Base for Graduate, Dalian Medical University, Shenyang, China.,General Hospital of Northern Theater Command Training Base for Graduate, Jinzhou Medical University, Shenyang, China.,General Hospital of Northern Theater Command Training Base for Graduate, China Medical University, Shenyang, China
| | - Benqiang Yang
- General Hospital of Northern Theater Command Training Base for Graduate, China Medical University, Shenyang, China.,Department of Radiology, General Hospital of Northern Theater Command, Shenyang, China
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17
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Cerebral small vessel disease burden and longitudinal cognitive decline from age 73 to 82: the Lothian Birth Cohort 1936. Transl Psychiatry 2021; 11:376. [PMID: 34226517 PMCID: PMC8257729 DOI: 10.1038/s41398-021-01495-4] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/19/2021] [Revised: 06/14/2021] [Accepted: 06/22/2021] [Indexed: 12/15/2022] Open
Abstract
Slowed processing speed is considered a hallmark feature of cognitive decline in cerebral small vessel disease (SVD); however, it is unclear whether SVD's association with slowed processing might be due to its association with overall declining general cognitive ability. We quantified the total MRI-visible SVD burden of 540 members of the Lothian Birth Cohort 1936 (age: 72.6 ± 0.7 years; 47% female). Using latent growth curve modelling, we tested associations between total SVD burden at mean age 73 and changes in general cognitive ability, processing speed, verbal memory and visuospatial ability, measured at age 73, 76, 79 and 82. Covariates included age, sex, vascular risk and childhood cognitive ability. In the fully adjusted models, greater SVD burden was associated with greater declines in general cognitive ability (standardised β: -0.201; 95% CI: [-0.36, -0.04]; pFDR = 0.022) and processing speed (-0.222; [-0.40, -0.04]; pFDR = 0.022). SVD burden accounted for between 4 and 5% of variance in declines of general cognitive ability and processing speed. After accounting for the covariance between tests of processing speed and general cognitive ability, only SVD's association with greater decline in general cognitive ability remained significant, prior to FDR correction (-0.222; [-0.39, -0.06]; p = 0.008; pFDR = 0.085). Our findings do not support the notion that SVD has a specific association with declining processing speed, independent of decline in general cognitive ability (which captures the variance shared across domains of cognitive ability). The association between SVD burden and declining general cognitive ability supports the notion of SVD as a diffuse, whole-brain disease and suggests that trials monitoring SVD-related cognitive changes should consider domain-specific changes in the context of overall, general cognitive decline.
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18
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Brandhofe A, Stratmann C, Schüre JR, Pilatus U, Hattingen E, Deichmann R, Nöth U, Wagner M, Gracien RM, Seiler A. T 2 relaxation time of the normal-appearing white matter is related to the cognitive status in cerebral small vessel disease. J Cereb Blood Flow Metab 2021; 41:1767-1777. [PMID: 33327818 PMCID: PMC8221761 DOI: 10.1177/0271678x20972511] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
Abstract
Previous diffusion tensor imaging (DTI) studies indicate that impaired microstructural integrity of the normal-appearing white matter (NAWM) is related to cognitive impairment in cerebral small vessel disease (SVD). This study aimed to investigate whether quantitative T2 relaxometry is a suitable imaging biomarker for the assessment of tissue changes related to cognitive abnormalities in patients with SVD. 39 patients and 18 age-matched healthy control subjects underwent 3 T magnetic resonance imaging (MRI) with T2-weighted multiple spin echo sequences for T2 relaxometry and DTI sequences, as well as comprehensive cognitive assessment. Averaged quantitative T2, fractional anisotropy (FA) and mean diffusivity (MD) were determined in the NAWM and related to cognitive parameters controlling for age, normalized brain volume, white matter hyperintensity volume and other conventional SVD markers. In SVD patients, quantitative T2 values were significantly increased compared to controls (p = 0.002) and significantly negatively correlated with the global cognitive performance (r= -0.410, p = 0.014) and executive function (r= -0.399, p = 0.016). DTI parameters did not correlate with cognitive function. T2 relaxometry of the NAWM seems to be sensitive to microstructural tissue damage associated with cognitive impairment in SVD and might be a promising imaging biomarker for evaluation of disease progression and possible effects of therapeutic interventions.
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Affiliation(s)
- Annemarie Brandhofe
- Department of Neurology, Goethe University Frankfurt, Frankfurt, Germany.,Brain Imaging Center, Goethe University Frankfurt, Frankfurt, Germany
| | - Christoph Stratmann
- Department of Neurology, Goethe University Frankfurt, Frankfurt, Germany.,Institute of Neuroradiology, Goethe University Frankfurt, Frankfurt, Germany
| | - Jan-Rüdiger Schüre
- Institute of Neuroradiology, Goethe University Frankfurt, Frankfurt, Germany
| | - Ulrich Pilatus
- Institute of Neuroradiology, Goethe University Frankfurt, Frankfurt, Germany
| | - Elke Hattingen
- Institute of Neuroradiology, Goethe University Frankfurt, Frankfurt, Germany
| | - Ralf Deichmann
- Brain Imaging Center, Goethe University Frankfurt, Frankfurt, Germany
| | - Ulrike Nöth
- Brain Imaging Center, Goethe University Frankfurt, Frankfurt, Germany
| | - Marlies Wagner
- Institute of Neuroradiology, Goethe University Frankfurt, Frankfurt, Germany
| | - René-Maxime Gracien
- Department of Neurology, Goethe University Frankfurt, Frankfurt, Germany.,Brain Imaging Center, Goethe University Frankfurt, Frankfurt, Germany
| | - Alexander Seiler
- Department of Neurology, Goethe University Frankfurt, Frankfurt, Germany.,Brain Imaging Center, Goethe University Frankfurt, Frankfurt, Germany
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19
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Li Z, Dolui S, Habes M, Bassett DS, Wolk D, Detre JA. Predicted disconnectome associated with progressive periventricular white matter ischemia. CEREBRAL CIRCULATION - COGNITION AND BEHAVIOR 2021; 2:100022. [PMID: 36324715 PMCID: PMC9616229 DOI: 10.1016/j.cccb.2021.100022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/15/2020] [Revised: 06/28/2021] [Accepted: 06/29/2021] [Indexed: 11/21/2022]
Abstract
We used a virtual lesion DTI fiber tracking approach with healthy subject DTI data and simulated periventricular white matter (PVWM) lesion masks to predict the sequence of connectivity changes associated with progressive PVWM ischemia. We found that the optic radiations, inferior fronto-occipital fasciculus, inferior longitudinal fasciculus, corpus callosum, temporopontine tract and fornix were affected in early simulated ischemic injury, and that the connectivity of subcortical, cerebellar, and visual regions were significantly disrupted with increasing simulated lesion severity. The results of this study provide insights into the spatial-temporal changes of the brain structural connectome under progressive PVWM ischemia. The virtual lesion approach provides a meaningful proxy to the spatial-temporal changes of the brain's structural connectome and can be used to further characterize the cognitive sequelae of progressive PVWM ischemia in both normal aging and dementia.
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Affiliation(s)
- Zhengjun Li
- Departments of Neurology, University of Pennsylvania, 3W Gates Pavilion, 3400 Spruce Street, Philadelphia, PA 19104, USA
- Bioengineering, USA
- Physics & Astronomy, USA
- Electrical and Systems Engineering, University of Pennsylvania Perelman School of Medicine, USA
| | - Sudipto Dolui
- Radiology, USA
- Bioengineering, USA
- Physics & Astronomy, USA
- Electrical and Systems Engineering, University of Pennsylvania Perelman School of Medicine, USA
| | - Mohamad Habes
- Departments of Neurology, University of Pennsylvania, 3W Gates Pavilion, 3400 Spruce Street, Philadelphia, PA 19104, USA
- Radiology, USA
- Bioengineering, USA
- Physics & Astronomy, USA
- Electrical and Systems Engineering, University of Pennsylvania Perelman School of Medicine, USA
- Biggs institute neuroimaging core (BINC), Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Sciences Center, USA
| | - Danielle S. Bassett
- Departments of Neurology, University of Pennsylvania, 3W Gates Pavilion, 3400 Spruce Street, Philadelphia, PA 19104, USA
- Psychiatry, USA
- Bioengineering, USA
- Physics & Astronomy, USA
- Electrical and Systems Engineering, University of Pennsylvania Perelman School of Medicine, USA
- The Santa Fe Institute, USA
| | - David Wolk
- Departments of Neurology, University of Pennsylvania, 3W Gates Pavilion, 3400 Spruce Street, Philadelphia, PA 19104, USA
- Bioengineering, USA
- Physics & Astronomy, USA
- Electrical and Systems Engineering, University of Pennsylvania Perelman School of Medicine, USA
| | - John A. Detre
- Departments of Neurology, University of Pennsylvania, 3W Gates Pavilion, 3400 Spruce Street, Philadelphia, PA 19104, USA
- Radiology, USA
- Bioengineering, USA
- Physics & Astronomy, USA
- Electrical and Systems Engineering, University of Pennsylvania Perelman School of Medicine, USA
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20
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Hamilton OKL, Backhouse EV, Janssen E, Jochems ACC, Maher C, Ritakari TE, Stevenson AJ, Xia L, Deary IJ, Wardlaw JM. Cognitive impairment in sporadic cerebral small vessel disease: A systematic review and meta-analysis. Alzheimers Dement 2021; 17:665-685. [PMID: 33185327 PMCID: PMC8593445 DOI: 10.1002/alz.12221] [Citation(s) in RCA: 93] [Impact Index Per Article: 31.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2020] [Revised: 02/08/2020] [Accepted: 05/10/2020] [Indexed: 01/09/2023]
Abstract
This paper is a proposal for an update on the characterization of cognitive impairments associated with sporadic cerebral small vessel disease (SVD). We pose a series of questions about the nature of SVD-related cognitive impairments and provide answers based on a comprehensive review and meta-analysis of published data from 69 studies. Although SVD is thought primarily to affect executive function and processing speed, we hypothesize that SVD affects all major domains of cognitive ability. We also identify low levels of education as a potentially modifiable risk factor for SVD-related cognitive impairment. Therefore, we propose the use of comprehensive cognitive assessments and the measurement of educational level both in clinics and research settings, and suggest several recommendations for future research.
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Affiliation(s)
- Olivia KL Hamilton
- Centre for Clinical Brain Sciences, University of Edinburgh, Chancellor’s Building, 49 Little France Crescent, Edinburgh, UK, EH16 4SB
- Dementia Research Institute, University of Edinburgh, Chancellor’s Building, 49 Little France Crescent, Edinburgh, UK, EH16 4SB
- Lothian Birth Cohorts, University of Edinburgh, 7 George Square, Edinburgh, UK, EH8 9JZ
| | - Ellen V Backhouse
- Centre for Clinical Brain Sciences, University of Edinburgh, Chancellor’s Building, 49 Little France Crescent, Edinburgh, UK, EH16 4SB
- Dementia Research Institute, University of Edinburgh, Chancellor’s Building, 49 Little France Crescent, Edinburgh, UK, EH16 4SB
| | - Esther Janssen
- Centre for Clinical Brain Sciences, University of Edinburgh, Chancellor’s Building, 49 Little France Crescent, Edinburgh, UK, EH16 4SB
- Dementia Research Institute, University of Edinburgh, Chancellor’s Building, 49 Little France Crescent, Edinburgh, UK, EH16 4SB
| | - Angela CC Jochems
- Centre for Clinical Brain Sciences, University of Edinburgh, Chancellor’s Building, 49 Little France Crescent, Edinburgh, UK, EH16 4SB
- Dementia Research Institute, University of Edinburgh, Chancellor’s Building, 49 Little France Crescent, Edinburgh, UK, EH16 4SB
| | - Caragh Maher
- Centre for Clinical Brain Sciences, University of Edinburgh, Chancellor’s Building, 49 Little France Crescent, Edinburgh, UK, EH16 4SB
- Dementia Research Institute, University of Edinburgh, Chancellor’s Building, 49 Little France Crescent, Edinburgh, UK, EH16 4SB
| | - Tuula E Ritakari
- Centre for Clinical Brain Sciences, University of Edinburgh, Chancellor’s Building, 49 Little France Crescent, Edinburgh, UK, EH16 4SB
- Dementia Research Institute, University of Edinburgh, Chancellor’s Building, 49 Little France Crescent, Edinburgh, UK, EH16 4SB
| | - Anna J Stevenson
- Dementia Research Institute, University of Edinburgh, Chancellor’s Building, 49 Little France Crescent, Edinburgh, UK, EH16 4SB
- Centre for Genomic and Experimental Medicine, MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital Campus, Crewe Road, Edinburgh, UK, EH4 2XU
- Centre for Discovery Brain Sciences, University of Edinburgh, Hugh Robson Building, 15 George Square, Edinburgh, UK, EH8 9XD
| | - Lihua Xia
- Department of Psychology, University of Edinburgh, 7 George Square, Edinburgh, UK, EH8 9JZ
| | - Ian J Deary
- Lothian Birth Cohorts, University of Edinburgh, 7 George Square, Edinburgh, UK, EH8 9JZ
- Department of Psychology, University of Edinburgh, 7 George Square, Edinburgh, UK, EH8 9JZ
| | - Joanna M Wardlaw
- Centre for Clinical Brain Sciences, University of Edinburgh, Chancellor’s Building, 49 Little France Crescent, Edinburgh, UK, EH16 4SB
- Dementia Research Institute, University of Edinburgh, Chancellor’s Building, 49 Little France Crescent, Edinburgh, UK, EH16 4SB
- Lothian Birth Cohorts, University of Edinburgh, 7 George Square, Edinburgh, UK, EH8 9JZ
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21
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Liu Y, Xia Y, Wang X, Wang Y, Zhang D, Nguchu BA, He J, Wang Y, Yang L, Wang Y, Ying Y, Liang X, Zhao Q, Wu J, Liang Z, Ding D, Dong Q, Qiu B, Cheng X, Gao JH. White matter hyperintensities induce distal deficits in the connected fibers. Hum Brain Mapp 2021; 42:1910-1919. [PMID: 33417309 PMCID: PMC7978134 DOI: 10.1002/hbm.25338] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2020] [Revised: 12/20/2020] [Accepted: 12/25/2020] [Indexed: 12/20/2022] Open
Abstract
White matter hyperintensities (WMH) are common in elderly individuals and cause brain network deficits. However, it is still unclear how the global brain network is affected by the focal WMH. We aimed to investigate the diffusion of WMH-related deficits along the connecting white matters (WM). Brain magnetic resonance imaging data and neuropsychological evaluations of 174 participants (aged 74 ± 5 years) were collected and analyzed. For each participant, WMH lesions were segmented using a deep learning method, and 18 major WM tracts were reconstructed using automated quantitative tractography. The diffusion characteristics of distal WM tracts (with the WMH penumbra excluded) were calculated. Multivariable linear regression analysis was performed. We found that a high burden of tract-specific WMH was related to worse diffusion characteristics of distal WM tracts in a wide range of WM tracts, including the forceps major (FMA), forceps minor (FMI), anterior thalamic radiation (ATR), cingulum cingulate gyrus (CCG), corticospinal tract (CST), inferior longitudinal fasciculus (ILF), superior longitudinal fasciculus-parietal (SLFP), superior longitudinal fasciculus-temporal (SLFT), and uncinate fasciculus (UNC). Furthermore, a higher mean diffusivity (MD) of distal tracts was linked to worse attention and executive function in the FMI, right CCG, left ILF, SLFP, SLFT, and UNC. The effect of WMH on the microstructural integrity of WM tracts may propagate along tracts to distal regions beyond the penumbra and might eventually affect attention and executive function.
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Affiliation(s)
- Yanpeng Liu
- Hefei National Lab for Physical Sciences at the Microscale and the Centers for Biomedical Engineering, University of Science and Technology of China, Hefei, China
| | - Yiwei Xia
- Department of Neurology, National Clinical Research Centre for Aging and Medicine, Huashan Hospital, State Key Laboratory of Medical Neurobiology, Fudan University, Shanghai, China
| | - Xiaoxiao Wang
- Hefei National Lab for Physical Sciences at the Microscale and the Centers for Biomedical Engineering, University of Science and Technology of China, Hefei, China
| | - Yanming Wang
- Hefei National Lab for Physical Sciences at the Microscale and the Centers for Biomedical Engineering, University of Science and Technology of China, Hefei, China
| | - Du Zhang
- Hefei National Lab for Physical Sciences at the Microscale and the Centers for Biomedical Engineering, University of Science and Technology of China, Hefei, China
| | - Benedictor Alexander Nguchu
- Hefei National Lab for Physical Sciences at the Microscale and the Centers for Biomedical Engineering, University of Science and Technology of China, Hefei, China
| | - Jiajie He
- Hefei National Lab for Physical Sciences at the Microscale and the Centers for Biomedical Engineering, University of Science and Technology of China, Hefei, China
| | - Yi Wang
- Department of Neurology, National Clinical Research Centre for Aging and Medicine, Huashan Hospital, State Key Laboratory of Medical Neurobiology, Fudan University, Shanghai, China
| | - Lumeng Yang
- Department of Neurology, National Clinical Research Centre for Aging and Medicine, Huashan Hospital, State Key Laboratory of Medical Neurobiology, Fudan University, Shanghai, China
| | - Yiqing Wang
- Department of Neurology, National Clinical Research Centre for Aging and Medicine, Huashan Hospital, State Key Laboratory of Medical Neurobiology, Fudan University, Shanghai, China
| | - Yunqing Ying
- Department of Neurology, National Clinical Research Centre for Aging and Medicine, Huashan Hospital, State Key Laboratory of Medical Neurobiology, Fudan University, Shanghai, China
| | - Xiaoniu Liang
- Institute of Neurology, National Clinical Research Centre for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai, China
| | - Qianhua Zhao
- Institute of Neurology, National Clinical Research Centre for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai, China
| | - Jianjun Wu
- Department of Neurology, National Clinical Research Centre for Aging and Medicine, Huashan Hospital, State Key Laboratory of Medical Neurobiology, Fudan University, Shanghai, China.,Department of Neurology, Jing'an District Center Hospital, Shanghai, China
| | - Zonghui Liang
- Department of Radiology, Jing'an District Center Hospital, Shanghai, China
| | - Ding Ding
- Institute of Neurology, National Clinical Research Centre for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai, China
| | - Qiang Dong
- Department of Neurology, National Clinical Research Centre for Aging and Medicine, Huashan Hospital, State Key Laboratory of Medical Neurobiology, Fudan University, Shanghai, China
| | - Bensheng Qiu
- Hefei National Lab for Physical Sciences at the Microscale and the Centers for Biomedical Engineering, University of Science and Technology of China, Hefei, China
| | - Xin Cheng
- Department of Neurology, National Clinical Research Centre for Aging and Medicine, Huashan Hospital, State Key Laboratory of Medical Neurobiology, Fudan University, Shanghai, China
| | - Jia-Hong Gao
- Hefei National Lab for Physical Sciences at the Microscale and the Centers for Biomedical Engineering, University of Science and Technology of China, Hefei, China.,Center for MRI Research and Beijing City Key Lab for Medical Physics and Engineering, Peking University, Beijing, China.,McGovern Institute for Brain Research, Peking University, Beijing, China
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22
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Valdés Hernández MDC, Smith K, Bastin ME, Nicole Amft E, Ralston SH, Wardlaw JM, Wiseman SJ. Brain network reorganisation and spatial lesion distribution in systemic lupus erythematosus. Lupus 2020; 30:285-298. [PMID: 33307988 PMCID: PMC7854491 DOI: 10.1177/0961203320979045] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
Abstract
Objective This work investigates network organisation of brain structural connectivity
in systemic lupus erythematosus (SLE) relative to healthy controls and its
putative association with lesion distribution and disease indicators. Methods White matter hyperintensity (WMH) segmentation and connectomics were
performed in 47 patients with SLE and 47 healthy age-matched controls from
structural and diffusion MRI data. Network nodes were divided into
hierarchical tiers based on numbers of connections. Results were compared
between patients and controls to assess for differences in brain network
organisation. Voxel-based analyses of the spatial distribution of WMH in
relation to network measures and SLE disease indicators were conducted. Results Despite inter-individual differences in brain network organization observed
across the study sample, the connectome networks of SLE patients had larger
proportion of connections in the peripheral nodes. SLE patients had
statistically larger numbers of links in their networks with generally
larger fractional anisotropy weights (i.e. a measure of white matter
integrity) and less tendency to aggregate than those of healthy controls.
The voxels exhibiting connectomic differences were coincident with WMH
clusters, particularly the left hemisphere’s intersection between the
anterior limb of the internal and external capsules. Moreover, these voxels
also associated more strongly with disease indicators. Conclusion Our results indicate network differences reflective of compensatory
reorganization of the neural circuits, reflecting adaptive or extended
neuroplasticity in SLE.
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Affiliation(s)
- Maria Del C Valdés Hernández
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK.,UK Dementia Research Institute, University of Edinburgh, Edinburgh, UK
| | - Keith Smith
- Usher Institute for Population Health Science and Informatics, University of Edinburgh, Edinburgh, UK.,Health Data Research UK, London, UK
| | - Mark E Bastin
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - E Nicole Amft
- University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK
| | - Stuart H Ralston
- Centre for Genomic and Experimental Medicine, University of Edinburgh, Edinburgh, UK
| | - Joanna M Wardlaw
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK.,UK Dementia Research Institute, University of Edinburgh, Edinburgh, UK
| | - Stewart J Wiseman
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK.,UK Dementia Research Institute, University of Edinburgh, Edinburgh, UK
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23
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Mito R, Dhollander T, Xia Y, Raffelt D, Salvado O, Churilov L, Rowe CC, Brodtmann A, Villemagne VL, Connelly A. In vivo microstructural heterogeneity of white matter lesions in healthy elderly and Alzheimer's disease participants using tissue compositional analysis of diffusion MRI data. Neuroimage Clin 2020; 28:102479. [PMID: 33395971 PMCID: PMC7652769 DOI: 10.1016/j.nicl.2020.102479] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2020] [Revised: 09/25/2020] [Accepted: 10/19/2020] [Indexed: 12/13/2022]
Abstract
White matter hyperintensities (WMH) are regions of high signal intensity typically identified on fluid attenuated inversion recovery (FLAIR). Although commonly observed in elderly individuals, they are more prevalent in Alzheimer's disease (AD) patients. Given that WMH appear relatively homogeneous on FLAIR, they are commonly partitioned into location- or distance-based classes when investigating their relevance to disease. Since pathology indicates that such lesions are often heterogeneous, probing their microstructure in vivo may provide greater insight than relying on such arbitrary classification schemes. In this study, we investigated WMH in vivo using an advanced diffusion MRI method known as single-shell 3-tissue constrained spherical deconvolution (SS3T-CSD), which models white matter microstructure while accounting for grey matter and CSF compartments. Diffusion MRI data and FLAIR images were obtained from AD (n = 48) and healthy elderly control (n = 94) subjects. WMH were automatically segmented, and classified: (1) as either periventricular or deep; or (2) into three distance-based contours from the ventricles. The 3-tissue profile of WMH enabled their characterisation in terms of white matter-, grey matter-, and fluid-like characteristics of the diffusion signal. Our SS3T-CSD findings revealed substantial heterogeneity in the 3-tissue profile of WMH, both within lesions and across the various classes. Moreover, this heterogeneity information indicated that the use of different commonly used WMH classification schemes can result in different disease-based conclusions. We conclude that future studies of WMH in AD would benefit from inclusion of microstructural information when characterising lesions, which we demonstrate can be performed in vivo using SS3T-CSD.
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Affiliation(s)
- Remika Mito
- Florey Institute of Neuroscience and Mental Health, Melbourne, Victoria, Australia; Florey Department of Neuroscience and Mental Health, University of Melbourne, Melbourne, Victoria, Australia.
| | - Thijs Dhollander
- Florey Institute of Neuroscience and Mental Health, Melbourne, Victoria, Australia; Florey Department of Neuroscience and Mental Health, University of Melbourne, Melbourne, Victoria, Australia; Developmental Imaging, Murdoch Children's Research Institute, Melbourne, Victoria, Australia
| | - Ying Xia
- CSIRO, Health & Biosecurity, The Australian eHealth Research Centre, Brisbane, Queensland, Australia
| | - David Raffelt
- Florey Institute of Neuroscience and Mental Health, Melbourne, Victoria, Australia
| | - Olivier Salvado
- CSIRO, Health & Biosecurity, The Australian eHealth Research Centre, Brisbane, Queensland, Australia; CSIRO Data61, Sydney, New South Wales, Australia
| | - Leonid Churilov
- Florey Institute of Neuroscience and Mental Health, Melbourne, Victoria, Australia; Department of Medicine, Austin Health, University of Melbourne, Victoria, Australia
| | - Christopher C Rowe
- Florey Institute of Neuroscience and Mental Health, Melbourne, Victoria, Australia; Department of Medicine, Austin Health, University of Melbourne, Victoria, Australia; Department of Molecular Imaging & Therapy, Centre for PET, Austin Health, Heidelberg, Victoria, Australia
| | - Amy Brodtmann
- Florey Institute of Neuroscience and Mental Health, Melbourne, Victoria, Australia; Florey Department of Neuroscience and Mental Health, University of Melbourne, Melbourne, Victoria, Australia; Eastern Clinical Research Unit, Monash University, Box Hill Hospital, Melbourne, Victoria, Australia
| | - Victor L Villemagne
- Florey Institute of Neuroscience and Mental Health, Melbourne, Victoria, Australia; Department of Medicine, Austin Health, University of Melbourne, Victoria, Australia; Department of Molecular Imaging & Therapy, Centre for PET, Austin Health, Heidelberg, Victoria, Australia
| | - Alan Connelly
- Florey Institute of Neuroscience and Mental Health, Melbourne, Victoria, Australia; Florey Department of Neuroscience and Mental Health, University of Melbourne, Melbourne, Victoria, Australia
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24
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Denoix N, Merz T, Unmuth S, Hoffmann A, Nespoli E, Scheuerle A, Huber-Lang M, Gündel H, Waller C, Radermacher P, McCook O. Cerebral Immunohistochemical Characterization of the H 2S and the Oxytocin Systems in a Porcine Model of Acute Subdural Hematoma. Front Neurol 2020; 11:649. [PMID: 32754111 PMCID: PMC7358568 DOI: 10.3389/fneur.2020.00649] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2020] [Accepted: 06/02/2020] [Indexed: 12/11/2022] Open
Abstract
The hydrogen sulfide (H2S) and the oxytocin/oxytocin receptor (OT/OTR) systems interact in trauma and are implicated in vascular protection and regulation of fluid homeostasis. Acute brain injury is associated with pressure-induced edema formation, blood brain barrier disruption, and neuro-inflammation. The similarities in brain anatomy: size, gyrencephalic organization, skull structure, may render the pig a highly relevant model for translational medicine. Cerebral biomarkers for pigs for pathophysiological changes and neuro-inflammation are limited. The current study aims to characterize the localization of OT/OTR and the endogenous H2S producing enzymes together with relevant neuro-inflammatory markers on available porcine brain tissue from an acute subdural hematoma (ASDH) model. In a recent pilot study, anesthetized pigs underwent ASDH by injection of 20 mL of autologous blood above the left parietal cortex and were resuscitated with neuro-intensive care measures. After 54 h of intensive care, the animals were sacrificed, the brain was removed and analyzed via immunohistochemistry. The endogenous H2S producing enzymes cystathionine-ɤ-lyase (CSE) and cystathionine-β-synthase (CBS), the OTR, and OT were localized in neurons, vasculature and parenchyma at the base of sulci, where pressure-induced injury leads to maximal stress in the gyrencephalic brain. The pathophysiological changes in response to brain injury in humans and pigs, we show here, are comparable. We additionally identified modulators of brain injury to further characterize the pathophysiology of ASDH and which may indicate future therapeutic approaches.
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Affiliation(s)
- Nicole Denoix
- Clinic for Psychosomatic Medicine and Psychotherapy, Ulm University Medical Center, Ulm, Germany.,Institute for Anesthesiological Pathophysiology and Process Engineering, Ulm University Medical Center, Ulm, Germany
| | - Tamara Merz
- Institute for Anesthesiological Pathophysiology and Process Engineering, Ulm University Medical Center, Ulm, Germany
| | - Sarah Unmuth
- Institute for Anesthesiological Pathophysiology and Process Engineering, Ulm University Medical Center, Ulm, Germany
| | - Andrea Hoffmann
- Institute for Anesthesiological Pathophysiology and Process Engineering, Ulm University Medical Center, Ulm, Germany
| | - Ester Nespoli
- Department of Neurology, Molecular and Translational Neuroscience, Ulm University, Ulm, Germany
| | - Angelika Scheuerle
- Department of Neuropathology, Institute for Pathology, Ulm University Medical Center, Ulm, Germany
| | - Markus Huber-Lang
- Institute for Clinical and Experimental Trauma Immunology, Ulm University Medical Center, Ulm, Germany
| | - Harald Gündel
- Clinic for Psychosomatic Medicine and Psychotherapy, Ulm University Medical Center, Ulm, Germany
| | - Christiane Waller
- Department of Psychosomatic Medicine and Psychotherapy, Nuremberg General Hospital, Paracelsus Medical University, Nuremberg, Germany
| | - Peter Radermacher
- Institute for Anesthesiological Pathophysiology and Process Engineering, Ulm University Medical Center, Ulm, Germany
| | - Oscar McCook
- Institute for Anesthesiological Pathophysiology and Process Engineering, Ulm University Medical Center, Ulm, Germany
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25
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Rizvi B, Lao PJ, Colón J, Hale C, Igwe KC, Narkhede A, Budge M, Manly JJ, Schupf N, Brickman AM. Tract-defined regional white matter hyperintensities and memory. NEUROIMAGE-CLINICAL 2019; 25:102143. [PMID: 31887716 PMCID: PMC6939088 DOI: 10.1016/j.nicl.2019.102143] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/21/2019] [Revised: 12/13/2019] [Accepted: 12/21/2019] [Indexed: 01/08/2023]
Abstract
White matter hyperintensity volume in association and projection tracts was related to memory in older adults. The relationship of WMH volumes in association and projection tracts with cognition was specific to memory, and not to a global cognition measure that excluded memory. Within projection tracts, WMH volumes affecting the anterior thalamic and the corticospinal tracts were most reliably associated with poorer memory. Within association tracts, WMH volume affecting the inferior fronto-occipital fasciculus, the superior longitudinal fasciculus, and the uncinate fasciculus were most reliably associated with poorer memory.
White matter hyperintensities (WMH) are common radiological findings among older adults and strong predictors of age-related cognitive decline. Recent work has implicated WMH in the pathogenesis and symptom presentation of Alzheimer's disease (AD), which is characterized clinically primarily by a deficit in memory. The severity of WMH volume is typically quantified globally or by lobe, whereas white matter itself is organized by tracts and fiber classes. We derived WMH volumes within white matter tract classes, including association, projection, and commissural tracts, in 519 older adults and tested whether WMH volume within specific fiber classes is related to memory performance. We found that increased association and projection tract defined WMH volumes were related to worse memory function but not to a global cognition summary score that excluded memory. We conclude that macrostructural damage to association and projection tracts, manifesting as WMH, may result in memory decline among older adults.
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Affiliation(s)
- Batool Rizvi
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, College of Physicians and Surgeons, Columbia University, New York, NY 10032, United States
| | - Patrick J Lao
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, College of Physicians and Surgeons, Columbia University, New York, NY 10032, United States
| | - Juliet Colón
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, College of Physicians and Surgeons, Columbia University, New York, NY 10032, United States
| | - Christiane Hale
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, College of Physicians and Surgeons, Columbia University, New York, NY 10032, United States
| | - Kay C Igwe
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, College of Physicians and Surgeons, Columbia University, New York, NY 10032, United States
| | - Atul Narkhede
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, College of Physicians and Surgeons, Columbia University, New York, NY 10032, United States
| | - Mariana Budge
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, College of Physicians and Surgeons, Columbia University, New York, NY 10032, United States
| | - Jennifer J Manly
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, College of Physicians and Surgeons, Columbia University, New York, NY 10032, United States; Gertrude H. Sergievsky Center, College of Physicians and Surgeons, Columbia University, New York, NY 10032, United States; Department of Neurology, College of Physicians and Surgeons, Columbia University, New York, NY 10032, United States
| | - Nicole Schupf
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, College of Physicians and Surgeons, Columbia University, New York, NY 10032, United States; Gertrude H. Sergievsky Center, College of Physicians and Surgeons, Columbia University, New York, NY 10032, United States; Department of Neurology, College of Physicians and Surgeons, Columbia University, New York, NY 10032, United States; Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY 10032, United States
| | - Adam M Brickman
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, College of Physicians and Surgeons, Columbia University, New York, NY 10032, United States; Gertrude H. Sergievsky Center, College of Physicians and Surgeons, Columbia University, New York, NY 10032, United States; Department of Neurology, College of Physicians and Surgeons, Columbia University, New York, NY 10032, United States.
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26
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Sartoretti E, Sartoretti T, Wyss M, Becker AS, Schwenk Á, van Smoorenburg L, Najafi A, Binkert C, Thoeny HC, Zhou J, Jiang S, Graf N, Czell D, Sartoretti-Schefer S, Reischauer C. Amide Proton Transfer Weighted Imaging Shows Differences in Multiple Sclerosis Lesions and White Matter Hyperintensities of Presumed Vascular Origin. Front Neurol 2019; 10:1307. [PMID: 31920930 PMCID: PMC6914856 DOI: 10.3389/fneur.2019.01307] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2019] [Accepted: 11/26/2019] [Indexed: 01/14/2023] Open
Abstract
Objectives: To assess the ability of 3D amide proton transfer weighted (APTw) imaging based on magnetization transfer analysis to discriminate between multiple sclerosis lesions (MSL) and white matter hyperintensities of presumed vascular origin (WMH) and to compare APTw signal intensity of healthy white matter (healthy WM) with APTw signal intensity of MSL and WHM. Materials and Methods: A total of 27 patients (16 female, 11 males, mean age 39.6 years) with multiple sclerosis, 35 patients (17 females, 18 males, mean age 66.6 years) with small vessel disease (SVD) and 20 healthy young volunteers (9 females, 11 males, mean age 29 years) were included in the MSL, the WMH, and the healthy WM group. MSL and WMH were segmented on fluid attenuated inversion recovery (FLAIR) images underlaid onto APTw images. Histogram parameters (mean, median, 10th, 25th, 75th, 90th percentile) were calculated. Mean APTw signal intensity values in healthy WM were defined by "Region of interest" (ROI) measurements. Wilcoxon rank sum tests and receiver operating characteristics (ROC) curve analyses of clustered data were applied. Results: All histogram parameters except the 75 and 90th percentile were significantly different between MSL and WMH (p = 0.018-p = 0.034). MSL presented with higher median values in all parameters. The histogram parameters offered only low diagnostic performance in discriminating between MSL and WMH. The 10th percentile yielded the highest diagnostic performance with an AUC of 0.6245 (95% CI: [0.532, 0.717]). Mean APTw signal intensity values of MSL were significantly higher than mean values of healthy WM (p = 0.005). The mean values of WMH did not differ significantly from the values of healthy WM (p = 0.345). Conclusions: We found significant differences in APTw signal intensity, based on straightforward magnetization transfer analysis, between MSL and WMH and between MSL and healthy WM. Low AUC values from ROC analyses, however, suggest that it may be challenging to determine type of lesion with APTw imaging. More advanced analysis of the APT CEST signal may be helpful for further differentiation of MSL and WMH.
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Affiliation(s)
| | - Thomas Sartoretti
- Laboratory of Translational Nutrition Biology, Department of Health Sciences and Technology, ETH Zurich, Schwerzenbach, Switzerland
| | - Michael Wyss
- Institute of Radiology, Kantonsspital Winterthur, Winterthur, Switzerland.,Philips Healthsystems, Zurich, Switzerland
| | - Anton S Becker
- Laboratory of Translational Nutrition Biology, Department of Health Sciences and Technology, ETH Zurich, Schwerzenbach, Switzerland.,Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, University of Zurich, Zurich, Switzerland.,Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, United States
| | - Árpád Schwenk
- Institute of Radiology, Kantonsspital Winterthur, Winterthur, Switzerland
| | | | - Arash Najafi
- Institute of Radiology, Kantonsspital Winterthur, Winterthur, Switzerland
| | - Christoph Binkert
- Institute of Radiology, Kantonsspital Winterthur, Winterthur, Switzerland
| | - Harriet C Thoeny
- Department of Medicine, University of Fribourg, Fribourg, Switzerland.,Department of Radiology, HFR Fribourg-Hôpital Cantonal, Fribourg, Switzerland
| | - Jinyuan Zhou
- Division of MR Research, Department of Radiology, Johns Hopkins University, Baltimore, MD, United States
| | - Shanshan Jiang
- Division of MR Research, Department of Radiology, Johns Hopkins University, Baltimore, MD, United States
| | | | - David Czell
- Department of Neurology, Spital Linth, Uznach, Switzerland
| | | | - Carolin Reischauer
- Department of Medicine, University of Fribourg, Fribourg, Switzerland.,Department of Radiology, HFR Fribourg-Hôpital Cantonal, Fribourg, Switzerland
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Wang S, Jiaerken Y, Yu X, Shen Z, Luo X, Hong H, Sun J, Xu X, Zhang R, Zhou Y, Lou M, Huang P, Zhang M. Understanding the association between psychomotor processing speed and white matter hyperintensity: A comprehensive multi-modality MR imaging study. Hum Brain Mapp 2019; 41:605-616. [PMID: 31675160 PMCID: PMC7267958 DOI: 10.1002/hbm.24826] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2019] [Revised: 09/22/2019] [Accepted: 10/02/2019] [Indexed: 01/01/2023] Open
Abstract
Cognitive processing speed is crucial for human cognition and declines with aging. White matter hyperintensity (WMH), a common sign of WM vascular damage in the elderly, is closely related to slower psychomotor processing speed. In this study, we investigated the association between WMH and psychomotor speed changes through a comprehensive assessment of brain structural and functional features. Multi-modal MRIs were acquired from 60 elderly adults. Psychomotor processing speeds were assessed using the Trail Making Test Part A (TMT-A). Linear regression analyses were performed to assess the associations between TMT-A and brain features, including WMH volumes in five cerebral regions, diffusivity parameters in the major WM tracts, regional gray matter volume, and brain activities across the whole brain. Hierarchical regression analysis was used to demonstrate the contribution of each index to slower psychomotor processing speed. Linear regression analysis demonstrated that WMH volume in the occipital lobe and fractional anisotropy of the forceps major, an occipital association tract, were associated with TMT-A. Besides, resting-state brain activities in the visual cortex connected to the forceps major were associated with TMT-A. Hierarchical regression showed fractional anisotropy of the forceps major and regional brain activities were significant predictors of TMT-A. The occurrence of WMH, combined with the disruption of passing-through fiber integrity and altered functional activities in areas connected by this fiber, are associated with a decline of psychomotor processing speed. While the causal relationship of this WMH-Tract-Function-Behavior link requires further investigation, this study enhances our understanding of these complex mechanisms.
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Affiliation(s)
- Shuyue Wang
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Yeerfan Jiaerken
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Xinfeng Yu
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Zhujing Shen
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Xiao Luo
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Hui Hong
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Jianzhong Sun
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Xiaojun Xu
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Ruiting Zhang
- Department of Neurology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Ying Zhou
- Department of Neurology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Min Lou
- Department of Neurology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Peiyu Huang
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Minming Zhang
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
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