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Ressa H, Newman BT, Jacokes Z, McPartland JC, Kleinhans NM, Druzgal TJ, Pelphrey KA, Van Horn JD. Widespread Associations between Behavioral Metrics and Brain Microstructure in ASD. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.09.04.611183. [PMID: 39282332 PMCID: PMC11398530 DOI: 10.1101/2024.09.04.611183] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 09/22/2024]
Abstract
Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by deficits in social communication and repetitive behaviors. A diagnosis of ASD is provided by a clinician following cognitive and behavioral evaluations, but there is currently no biomarker associating these metrics with neurological changes. Our lab has previously found that g-ratio, the proportion of axon width to myelin diameter, and axonal conduction velocity, which is associated with the capacity of an axon to carry information, are both decreased in ASD individuals. By associating these differences with performance on cognitive and behavioral tests, we can evaluate which tests most reveal changes in the brain. Analyzing 273 participants (148 with ASD) ages 8-to-17 (49% female) through an NIH-sponsored Autism Centers of Excellence (ACE) network (Grant#: MH100028), we observe widespread associations between behavioral and cognitive evaluations of autism and between behavioral and microstructural metrics. Analyzing data from all participants, conduction velocity but not g-ratio was significantly associated with many behavioral metrics. However, this pattern was reversed when looking solely at ASD participants. This reversal may suggest that the mechanism underlying differences between autistic and non-autistic individuals may be distinct from the mechanism underlying ASD behavioral severity. Two additional machine learning cluster analyses applied to neuroimaging data reinforce the association between neuroimaging and behavioral metrics and suggest that age-related maturation of brain metrics may drive changes in ASD behavior. By associating neuroimaging metrics with ASD, it may be possible to measure and identify individuals at high risk of ASD before behavioral tests can detect them. Significance Statement This study establishes numerous relationships between multiple behavioral, language, and social metrics in ASD. Subsequently, this study is the first to then show associations between diffusion microstructure and subscales of behavioral assessments. Limited associations of these behaviors with conduction velocity may indicate that axonal diameter is a predominating factor in characterizing ASD over other metrics, such as myelination, however within ASD subjects the g-ratio is more closely related to behavioral metrics, suggesting a potential role for myelination in ASD severity. These findings suggest that some subscales and metrics more accurately capture behaviors associated neurologically with ASD than others, including composite scores, demonstrating the potential to identify children at high risk for ASD at an earlier age.
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Bachmann D, von Rickenbach B, Buchmann A, Hüllner M, Zuber I, Studer S, Saake A, Rauen K, Gruber E, Nitsch RM, Hock C, Treyer V, Gietl A. White matter hyperintensity patterns: associations with comorbidities, amyloid, and cognition. Alzheimers Res Ther 2024; 16:67. [PMID: 38561806 PMCID: PMC10983708 DOI: 10.1186/s13195-024-01435-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2023] [Accepted: 03/23/2024] [Indexed: 04/04/2024]
Abstract
BACKGROUND White matter hyperintensities (WMHs) are often measured globally, but spatial patterns of WMHs could underlie different risk factors and neuropathological and clinical correlates. We investigated the spatial heterogeneity of WMHs and their association with comorbidities, Alzheimer's disease (AD) risk factors, and cognition. METHODS In this cross-sectional study, we studied 171 cognitively unimpaired (CU; median age: 65 years, range: 50 to 89) and 51 mildly cognitively impaired (MCI; median age: 72, range: 53 to 89) individuals with available amyloid (18F-flutementamol) PET and FLAIR-weighted images. Comorbidities were assessed using the Cumulative Illness Rating Scale (CIRS). Each participant's white matter was segmented into 38 parcels, and WMH volume was calculated in each parcel. Correlated principal component analysis was applied to the parceled WMH data to determine patterns of WMH covariation. Adjusted and unadjusted linear regression models were used to investigate associations of component scores with comorbidities and AD-related factors. Using multiple linear regression, we tested whether WMH component scores predicted cognitive performance. RESULTS Principal component analysis identified four WMH components that broadly describe FLAIR signal hyperintensities in posterior, periventricular, and deep white matter regions, as well as basal ganglia and thalamic structures. In CU individuals, hypertension was associated with all patterns except the periventricular component. MCI individuals showed more diverse associations. The posterior and deep components were associated with renal disorders, the periventricular component was associated with increased amyloid, and the subcortical gray matter structures was associated with sleep disorders, endocrine/metabolic disorders, and increased amyloid. In the combined sample (CU + MCI), the main effects of WMH components were not associated with cognition but predicted poorer episodic memory performance in the presence of increased amyloid. No interaction between hypertension and the number of comorbidities on component scores was observed. CONCLUSION Our study underscores the significance of understanding the regional distribution patterns of WMHs and the valuable insights that risk factors can offer regarding their underlying causes. Moreover, patterns of hyperintensities in periventricular regions and deep gray matter structures may have more pronounced cognitive implications, especially when amyloid pathology is also present.
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Affiliation(s)
- Dario Bachmann
- Institute for Regenerative Medicine, University of Zurich, Campus Schlieren, Wagistrasse 12, 8952, Zurich, Schlieren, Switzerland.
- Department of Health Sciences and Technology, ETH Zürich, 8093, Zurich, Switzerland.
| | | | - Andreas Buchmann
- Institute for Regenerative Medicine, University of Zurich, Campus Schlieren, Wagistrasse 12, 8952, Zurich, Schlieren, Switzerland
| | - Martin Hüllner
- Department of Nuclear Medicine, University Hospital of Zurich, University of Zurich, 8091, Zurich, Switzerland
| | - Isabelle Zuber
- Institute for Regenerative Medicine, University of Zurich, Campus Schlieren, Wagistrasse 12, 8952, Zurich, Schlieren, Switzerland
| | - Sandro Studer
- Institute for Regenerative Medicine, University of Zurich, Campus Schlieren, Wagistrasse 12, 8952, Zurich, Schlieren, Switzerland
| | - Antje Saake
- Institute for Regenerative Medicine, University of Zurich, Campus Schlieren, Wagistrasse 12, 8952, Zurich, Schlieren, Switzerland
| | - Katrin Rauen
- Institute for Regenerative Medicine, University of Zurich, Campus Schlieren, Wagistrasse 12, 8952, Zurich, Schlieren, Switzerland
- Department of Geriatric Psychiatry, Psychiatric Hospital Zurich, 8032, Zurich, Switzerland
- Neuroscience Center Zurich, University of Zurich, 8057, Zurich, Switzerland
| | - Esmeralda Gruber
- Institute for Regenerative Medicine, University of Zurich, Campus Schlieren, Wagistrasse 12, 8952, Zurich, Schlieren, Switzerland
| | - Roger M Nitsch
- Institute for Regenerative Medicine, University of Zurich, Campus Schlieren, Wagistrasse 12, 8952, Zurich, Schlieren, Switzerland
- Neurimmune AG, 8952, Zurich, Schlieren, Switzerland
| | - Christoph Hock
- Institute for Regenerative Medicine, University of Zurich, Campus Schlieren, Wagistrasse 12, 8952, Zurich, Schlieren, Switzerland
- Neurimmune AG, 8952, Zurich, Schlieren, Switzerland
| | - Valerie Treyer
- Institute for Regenerative Medicine, University of Zurich, Campus Schlieren, Wagistrasse 12, 8952, Zurich, Schlieren, Switzerland
- Department of Nuclear Medicine, University Hospital of Zurich, University of Zurich, 8091, Zurich, Switzerland
| | - Anton Gietl
- Institute for Regenerative Medicine, University of Zurich, Campus Schlieren, Wagistrasse 12, 8952, Zurich, Schlieren, Switzerland
- Department of Geriatric Psychiatry, Psychiatric Hospital Zurich, 8032, Zurich, Switzerland
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Badji A, Cedres N, Muehlboeck JS, Khan W, Dhollander T, Barroso J, Ferreira D, Westman E. In vivo microstructural heterogeneity of white matter and cognitive correlates in aging using tissue compositional analysis of diffusion magnetic resonance imaging. Hum Brain Mapp 2024; 45:e26618. [PMID: 38414286 PMCID: PMC10899800 DOI: 10.1002/hbm.26618] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2023] [Revised: 12/03/2023] [Accepted: 12/24/2023] [Indexed: 02/29/2024] Open
Abstract
BACKGROUND Age-related cognitive decline is linked to changes in the brain, particularly the deterioration of white matter (WM) microstructure that accelerates after the age of 60. WM deterioration is associated with mild cognitive impairment and dementia, but the origin and role of white matter signal abnormalities (WMSA) seen in standard MRI remain debated due to their heterogeneity. This study explores the potential of single-shell 3-tissue constrained spherical deconvolution (SS3T-CSD), a novel technique that models diffusion data in terms of gray matter (TG ), white matter (Tw ), and cerebrospinal fluid (TC ), to differentiate WMSA from normal-appearing white matter and better understand the interplay between changes in WM microstructure and decline in cognition. METHODS A total of 189 individuals from the GENIC cohort were included. MRI data, including T1-weighted and diffusion images, were obtained. Preprocessing steps were performed on the diffusion MRI data, followed by the SS3T-CSD. WMSA were segmented using FreeSurfer. Statistical analyses were conducted to assess the association between age, WMSA volume, 3-tissue signal fractions (Tw , TG , and TC ), and neuropsychological variables. RESULTS Participants above 60 years old showed worse cognitive performance and processing speed compared to those below 60 (p < .001). Age was negatively associated with Tw in normal-appearing white matter (p < .001) and positively associated with TG in both WMSA (p < .01) and normal-appearing white matter (p < .001). Age was also significantly associated with WMSA volume (p < .001). Higher processing speed was associated with lower Tw and higher TG , in normal-appearing white matter (p < .01 and p < .001, respectively), as well as increased WMSA volume (p < .001). Similarly, lower MMSE scores correlated with lower Tw and higher TG in normal-appearing white matter (p < .05). High cholesterol and hypertension were associated with higher WMSA volume (p < .05). CONCLUSION The microstructural heterogeneity within normal-appearing white matter and WMSA is associated with increasing age and cognitive variation, in cognitively unimpaired individuals. Furthermore, the 3-tissue signal fractions are more specific to potential white matter alterations than conventional MRI measures such as WMSA volume. These findings also support the view that the WMSA volumes may be more influenced by vascular risk factors than the 3-tissue metrics. Finally, the 3-tissue metrics were able to capture associations with cognitive tests and therefore capable of capturing subtle pathological changes in the brain in individuals who are still within the normal range of cognitive performance.
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Affiliation(s)
- Atef Badji
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
- Theme Inflammation and Aging, Karolinska University Hospital, Stockholm, Sweden
| | - Nira Cedres
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
- Facultad de Ciencias de la Salud, Universidad Fernando Pessoa Canarias, Las Palmas de Gran Canaria, España
| | - J-Sebastian Muehlboeck
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
| | - Wasim Khan
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
| | - Thijs Dhollander
- Murdoch Children's Research Institute, Melbourne, Victoria, Australia
| | - Jose Barroso
- Facultad de Ciencias de la Salud, Universidad Fernando Pessoa Canarias, Las Palmas de Gran Canaria, España
| | - Daniel Ferreira
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
- Facultad de Ciencias de la Salud, Universidad Fernando Pessoa Canarias, Las Palmas de Gran Canaria, España
| | - Eric Westman
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
- Department of Neuroimaging, Centre for Neuroimaging Sciences, Institute of Psychiatry, Psychology, and Neuroscience, King's College London, London, UK
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Newman BT, Jacokes Z, Venkadesh S, Webb SJ, Kleinhans NM, McPartland JC, Druzgal TJ, Pelphrey KA, Van Horn JD. Conduction Velocity, G-ratio, and Extracellular Water as Microstructural Characteristics of Autism Spectrum Disorder. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.07.23.550166. [PMID: 37546913 PMCID: PMC10402058 DOI: 10.1101/2023.07.23.550166] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/08/2023]
Abstract
The neuronal differences contributing to the etiology of autism spectrum disorder (ASD) are still not well defined. Previous studies have suggested that myelin and axons are disrupted during development in ASD. By combining structural and diffusion MRI techniques, myelin and axons can be assessed using extracellular water, aggregate g-ratio, and a novel metric termed aggregate conduction velocity, which is related to the capacity of the axon to carry information. In this study, several innovative cellular microstructural methods, as measured from magnetic resonance imaging (MRI), are combined to characterize differences between ASD and typically developing adolescent participants in a large cohort. We first examine the relationship between each metric, including microstructural measurements of axonal and intracellular diffusion and the T1w/T2w ratio. We then demonstrate the sensitivity of these metrics by characterizing differences between ASD and neurotypical participants, finding widespread increases in extracellular water in the cortex and decreases in aggregate g-ratio and aggregate conduction velocity throughout the cortex, subcortex, and white matter skeleton. We finally provide evidence that these microstructural differences are associated with higher scores on the Social Communication Questionnaire (SCQ) a commonly used diagnostic tool to assess ASD. This study is the first to reveal that ASD involves MRI-measurable in vivo differences of myelin and axonal development with implications for neuronal and behavioral function. We also introduce a novel neuroimaging metric, aggregate conduction velocity, that is highly sensitive to these changes. We conclude that ASD may be characterized by otherwise intact structural connectivity but that functional connectivity may be attenuated by network properties affecting neural transmission speed. This effect may explain the putative reliance on local connectivity in contrast to more distal connectivity observed in ASD.
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Affiliation(s)
- Benjamin T. Newman
- Department of Psychology, University of Virginia, Gilmer Hall, Charlottesville, VA 22903
- UVA School of Medicine, University of Virginia, 560 Ray Hunt Drive, Charlottesville, VA 22903
| | - Zachary Jacokes
- School of Data Science, University of Virginia, Elson Building, Charlottesville, VA 22903
| | - Siva Venkadesh
- Department of Psychology, University of Virginia, Gilmer Hall, Charlottesville, VA 22903
| | - Sara J. Webb
- Department of Psychiatry and Behavioral Science, University of Washington, Seattle WA USA 98195
- Seattle Children’s Research Institute, 1920 Terry Ave, Building Cure-03, Seattle WA 98101
| | - Natalia M. Kleinhans
- Department of Radiology, Integrated Brain Imaging Center, University of Washington, 1959 NE Pacific St Seattle, WA 98195
| | - James C. McPartland
- Yale Child Study Center, 230 South Frontage Road, New Haven, CT 06520
- Yale Center for Brain and Mind Health, 40 Temple Street, Suite 6A, New Haven, CT, 06520
| | - T. Jason Druzgal
- UVA School of Medicine, University of Virginia, 560 Ray Hunt Drive, Charlottesville, VA 22903
| | - Kevin A. Pelphrey
- UVA School of Medicine, University of Virginia, 560 Ray Hunt Drive, Charlottesville, VA 22903
| | - John Darrell Van Horn
- Department of Psychology, University of Virginia, Gilmer Hall, Charlottesville, VA 22903
- School of Data Science, University of Virginia, Elson Building, Charlottesville, VA 22903
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Chen Y, Wang Y, Song Z, Fan Y, Gao T, Tang X. Abnormal white matter changes in Alzheimer's disease based on diffusion tensor imaging: A systematic review. Ageing Res Rev 2023; 87:101911. [PMID: 36931328 DOI: 10.1016/j.arr.2023.101911] [Citation(s) in RCA: 15] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2022] [Revised: 03/01/2023] [Accepted: 03/13/2023] [Indexed: 03/17/2023]
Abstract
Alzheimer's disease (AD) is a degenerative neurological disease in elderly individuals. Subjective cognitive decline (SCD), mild cognitive impairment (MCI) and further development to dementia (d-AD) are considered to be major stages of the progressive pathological development of AD. Diffusion tensor imaging (DTI), one of the most important modalities of MRI, can describe the microstructure of white matter through its tensor model. It is widely used in understanding the central nervous system mechanism and finding appropriate potential biomarkers for the early stages of AD. Based on the multilevel analysis methods of DTI (voxelwise, fiberwise and networkwise), we summarized that AD patients mainly showed extensive microstructural damage, structural disconnection and topological abnormalities in the corpus callosum, fornix, and medial temporal lobe, including the hippocampus and cingulum. The diffusion features and structural connectomics of specific regions can provide information for the early assisted recognition of AD. The classification accuracy of SCD and normal controls can reach 92.68% at present. And due to the further changes of brain structure and function, the classification accuracy of MCI, d-AD and normal controls can reach more than 97%. Finally, we summarized the limitations of current DTI-based AD research and propose possible future research directions.
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Affiliation(s)
- Yu Chen
- School of Medical Technology, Beijing Institute of Technology, Beijing 100081, China
| | - Yifei Wang
- School of Life Science, Beijing Institute of Technology, Beijing 100081, China
| | - Zeyu Song
- School of Medical Technology, Beijing Institute of Technology, Beijing 100081, China
| | - Yingwei Fan
- School of Medical Technology, Beijing Institute of Technology, Beijing 100081, China
| | - Tianxin Gao
- School of Life Science, Beijing Institute of Technology, Beijing 100081, China.
| | - Xiaoying Tang
- School of Medical Technology, Beijing Institute of Technology, Beijing 100081, China; School of Life Science, Beijing Institute of Technology, Beijing 100081, China.
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Chary K, Manninen E, Claessens J, Ramirez-Manzanares A, Gröhn O, Sierra A. Diffusion MRI approaches for investigating microstructural complexity in a rat model of traumatic brain injury. Sci Rep 2023; 13:2219. [PMID: 36755032 PMCID: PMC9908904 DOI: 10.1038/s41598-023-29010-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2022] [Accepted: 01/30/2023] [Indexed: 02/10/2023] Open
Abstract
Our study explores the potential of conventional and advanced diffusion MRI techniques including diffusion tensor imaging (DTI), and single-shell 3-tissue constrained spherical deconvolution (SS3T-CSD) to investigate complex microstructural changes following severe traumatic brain injury in rats at a chronic phase. Rat brains after sham-operation or lateral fluid percussion (LFP) injury were scanned ex vivo in a 9.4 T scanner. Our region-of-interest-based approach of tensor-, and SS3T-CSD derived fixel-, 3-tissue signal fraction maps were sensitive to changes in both white matter (WM) and grey matter (GM) areas. Tensor-based measures, such as fractional anisotropy (FA) and radial diffusivity (RD), detected more changes in WM and GM areas as compared to fixel-based measures including apparent fiber density (AFD), peak FOD amplitude and primary fiber bundle density, while 3-tissue signal fraction maps revealed distinct changes in WM, GM, and phosphate-buffered saline (PBS) fractions highlighting the complex tissue microstructural alterations post-trauma. Track-weighted imaging demonstrated changes in track morphology including reduced curvature and average pathlength distal from the primary lesion in severe TBI rats. In histological analysis, changes in the diffusion MRI measures could be associated to decreased myelin density, loss of myelinated axons, and increased cellularity, revealing progressive microstructural alterations in these brain areas five months after injury. Overall, this study highlights the use of combined conventional and advanced diffusion MRI measures to obtain more precise insights into the complex tissue microstructural alterations in chronic phase of severe brain injury.
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Affiliation(s)
- Karthik Chary
- A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, P.O. Box 1627, 70211, Neulaniementie 2, Kuopio, Finland
- Department of Radiology, University of Cambridge, Cambridge, UK
| | - Eppu Manninen
- A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, P.O. Box 1627, 70211, Neulaniementie 2, Kuopio, Finland
| | - Jade Claessens
- A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, P.O. Box 1627, 70211, Neulaniementie 2, Kuopio, Finland
| | | | - Olli Gröhn
- A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, P.O. Box 1627, 70211, Neulaniementie 2, Kuopio, Finland
| | - Alejandra Sierra
- A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, P.O. Box 1627, 70211, Neulaniementie 2, Kuopio, Finland.
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7
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Giraldo DL, Smith RE, Struyfs H, Niemantsverdriet E, De Roeck E, Bjerke M, Engelborghs S, Romero E, Sijbers J, Jeurissen B. Investigating Tissue-Specific Abnormalities in Alzheimer's Disease with Multi-Shell Diffusion MRI. J Alzheimers Dis 2022; 90:1771-1791. [PMID: 36336929 PMCID: PMC9789487 DOI: 10.3233/jad-220551] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
BACKGROUND Most studies using diffusion-weighted MRI (DW-MRI) in Alzheimer's disease (AD) have focused their analyses on white matter (WM) microstructural changes using the diffusion (kurtosis) tensor model. Although recent works have addressed some limitations of the tensor model, such as the representation of crossing fibers and partial volume effects with cerebrospinal fluid (CSF), the focus remains in modeling and analyzing the WM. OBJECTIVE In this work, we present a brain analysis approach for DW-MRI that disentangles multiple tissue compartments as well as micro- and macroscopic effects to investigate differences between groups of subjects in the AD continuum and controls. METHODS By means of the multi-tissue constrained spherical deconvolution of multi-shell DW-MRI, underlying brain tissue is modeled with a WM fiber orientation distribution function along with the contributions of gray matter (GM) and CSF to the diffusion signal. From this multi-tissue model, a set of measures capturing tissue diffusivity properties and morphology are extracted. Group differences were interrogated following fixel-, voxel-, and tensor-based morphometry approaches while including strong FWE control across multiple comparisons. RESULTS Abnormalities related to AD stages were detected in WM tracts including the splenium, cingulum, longitudinal fasciculi, and corticospinal tract. Changes in tissue composition were identified, particularly in the medial temporal lobe and superior longitudinal fasciculus. CONCLUSION This analysis framework constitutes a comprehensive approach allowing simultaneous macro and microscopic assessment of WM, GM, and CSF, from a single DW-MRI dataset.
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Affiliation(s)
- Diana L. Giraldo
- Computer Imaging and Medical Applications Laboratory - Cim@Lab, Universidad Nacional de Colombia, Bogotá, Colombia,imec-Vision Lab, Department of Physics, University of Antwerp, Antwerp, Belgium,μNEURO Research Center of Excellence, University of Antwerp, Antwerp, Belgium
| | - Robert E. Smith
- The Florey Institute of Neuroscience and Mental Health, Heidelberg, VIC, Australia,The Florey Department of Neuroscience and Mental Health, The University of Melbourne, Parkville, VIC, Australia
| | - Hanne Struyfs
- Reference Center for Biological Markers of Dementia (BIODEM), Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
| | - Ellis Niemantsverdriet
- Reference Center for Biological Markers of Dementia (BIODEM), Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
| | - Ellen De Roeck
- Reference Center for Biological Markers of Dementia (BIODEM), Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium,Department of Neurology and Memory Clinic, Hospital Network Antwerp (ZNA) Middelheim and Hoge Beuken, Antwerp, Belgium
| | - Maria Bjerke
- Reference Center for Biological Markers of Dementia (BIODEM), Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium,Laboratory of Neurochemistry, Department of Clinical Chemistry, and Center for Neurosciences (C4N), Universitair Ziekenhuis Brussel, Vrije Universiteit Brussel (VUB), Brussels, Belgium
| | - Sebastiaan Engelborghs
- Reference Center for Biological Markers of Dementia (BIODEM), Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium,Department of Neurology, and Center for Neurosciences (C4N), Universitair Ziekenhuis Brussel, Vrije Universiteit Brussel (VUB), Brussels, Belgium
| | - Eduardo Romero
- Computer Imaging and Medical Applications Laboratory - Cim@Lab, Universidad Nacional de Colombia, Bogotá, Colombia
| | - Jan Sijbers
- imec-Vision Lab, Department of Physics, University of Antwerp, Antwerp, Belgium,μNEURO Research Center of Excellence, University of Antwerp, Antwerp, Belgium
| | - Ben Jeurissen
- imec-Vision Lab, Department of Physics, University of Antwerp, Antwerp, Belgium,μNEURO Research Center of Excellence, University of Antwerp, Antwerp, Belgium,Lab for Equilibrium Investigations and Aerospace, Department of Physics, University of Antwerp, Antwerp, Belgium,Correspondence to: Ben Jeurissen, PhD, imec - Vision Lab, Department of Physics, University of Antwerp (CDE), Universiteitsplein 1, Building N, 2610 Antwerp, Belgium. Tel.: +32 3 265 24 77; E-mail:
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8
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Manners DN, Gramegna LL, La Morgia C, Sighinolfi G, Fiscone C, Carbonelli M, Romagnoli M, Carelli V, Tonon C, Lodi R. Multishell Diffusion MR Tractography Yields Morphological and Microstructural Information of the Anterior Optic Pathway: A Proof-of-Concept Study in Patients with Leber’s Hereditary Optic Neuropathy. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:ijerph19116914. [PMID: 35682499 PMCID: PMC9180110 DOI: 10.3390/ijerph19116914] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/31/2022] [Revised: 05/23/2022] [Accepted: 05/27/2022] [Indexed: 12/04/2022]
Abstract
Tractography based on multishell diffusion-weighted magnetic resonance imaging (DWI) can be used to estimate the course of myelinated white matter tracts and nerves, yielding valuable information regarding normal anatomy and variability. DWI is sensitive to the local tissue microstructure, so tractography can be used to estimate tissue properties within nerve tracts at a resolution of millimeters. This study aimed to test the applicability of the method using a disease with a well-established pattern of myelinated nerve involvement. Eight patients with LHON and 13 age-matched healthy controls underwent tractography of the anterior optic pathway. Diffusion parameters were compared between groups, and for the patient group correlated with clinical/ophthalmological parameters. Tractography established the course of the anterior optic pathway in both patients and controls. Localized changes in fractional anisotropy were observed, and related to estimates of different tissue compartments within the nerve and tract. The proportion of different compartments correlated with markers of disease severity. The method described allows both anatomical localization and tissue characterization in vivo, permitting both visualization of variation at the individual level and statistical inference at the group level. It provides a valuable adjunct to ex vivo anatomical and histological study of normal variation and disease processes.
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Affiliation(s)
- David Neil Manners
- Department of Biomedical and Neuromotor Sciences (DIBINEM), University of Bologna, 40138 Bologna, Italy; (L.L.G.); (G.S.); (C.F.); (M.C.); (V.C.); (C.T.); (R.L.)
- Correspondence:
| | - Laura Ludovica Gramegna
- Department of Biomedical and Neuromotor Sciences (DIBINEM), University of Bologna, 40138 Bologna, Italy; (L.L.G.); (G.S.); (C.F.); (M.C.); (V.C.); (C.T.); (R.L.)
- IRCCS Istituto delle Scienze Neurologiche di Bologna, Bellaria Hospital, 40139 Bologna, Italy; (C.L.M.); (M.R.)
| | - Chiara La Morgia
- IRCCS Istituto delle Scienze Neurologiche di Bologna, Bellaria Hospital, 40139 Bologna, Italy; (C.L.M.); (M.R.)
| | - Giovanni Sighinolfi
- Department of Biomedical and Neuromotor Sciences (DIBINEM), University of Bologna, 40138 Bologna, Italy; (L.L.G.); (G.S.); (C.F.); (M.C.); (V.C.); (C.T.); (R.L.)
| | - Cristiana Fiscone
- Department of Biomedical and Neuromotor Sciences (DIBINEM), University of Bologna, 40138 Bologna, Italy; (L.L.G.); (G.S.); (C.F.); (M.C.); (V.C.); (C.T.); (R.L.)
| | - Michele Carbonelli
- Department of Biomedical and Neuromotor Sciences (DIBINEM), University of Bologna, 40138 Bologna, Italy; (L.L.G.); (G.S.); (C.F.); (M.C.); (V.C.); (C.T.); (R.L.)
| | - Martina Romagnoli
- IRCCS Istituto delle Scienze Neurologiche di Bologna, Bellaria Hospital, 40139 Bologna, Italy; (C.L.M.); (M.R.)
| | - Valerio Carelli
- Department of Biomedical and Neuromotor Sciences (DIBINEM), University of Bologna, 40138 Bologna, Italy; (L.L.G.); (G.S.); (C.F.); (M.C.); (V.C.); (C.T.); (R.L.)
- IRCCS Istituto delle Scienze Neurologiche di Bologna, Bellaria Hospital, 40139 Bologna, Italy; (C.L.M.); (M.R.)
| | - Caterina Tonon
- Department of Biomedical and Neuromotor Sciences (DIBINEM), University of Bologna, 40138 Bologna, Italy; (L.L.G.); (G.S.); (C.F.); (M.C.); (V.C.); (C.T.); (R.L.)
- IRCCS Istituto delle Scienze Neurologiche di Bologna, Bellaria Hospital, 40139 Bologna, Italy; (C.L.M.); (M.R.)
| | - Raffaele Lodi
- Department of Biomedical and Neuromotor Sciences (DIBINEM), University of Bologna, 40138 Bologna, Italy; (L.L.G.); (G.S.); (C.F.); (M.C.); (V.C.); (C.T.); (R.L.)
- IRCCS Istituto delle Scienze Neurologiche di Bologna, Bellaria Hospital, 40139 Bologna, Italy; (C.L.M.); (M.R.)
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9
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Kelly C, Dhollander T, Harding IH, Khan W, Beare R, Cheong JL, Doyle LW, Seal M, Thompson DK, Inder TE, Anderson PJ. Brain tissue microstructural and free-water composition 13 years after very preterm birth. Neuroimage 2022; 254:119168. [PMID: 35367651 DOI: 10.1016/j.neuroimage.2022.119168] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2021] [Revised: 02/27/2022] [Accepted: 03/30/2022] [Indexed: 12/20/2022] Open
Abstract
There have been many studies demonstrating children born very preterm exhibit brain white matter microstructural alterations, which have been related to neurodevelopmental difficulties. These prior studies have often been based on diffusion MRI modelling and analysis techniques, which commonly focussed on white matter microstructural properties in very preterm-born children. However, there have been relatively fewer studies investigating the free-water content of the white matter, and also the microstructure and free-water content of the cortical grey matter, in very preterm-born children. These biophysical properties of the brain change rapidly during fetal and neonatal brain development, and therefore such properties are likely also adversely affected by very preterm birth. In this study, we investigated the relationship of very preterm birth (<30 weeks' gestation) to both white matter and cortical grey matter microstructure and free-water content in childhood using advanced diffusion MRI analyses. A total of 130 very preterm participants and 45 full-term control participants underwent diffusion MRI at age 13 years. Diffusion tissue signal fractions derived by Single-Shell 3-Tissue Constrained Spherical Deconvolution were used to investigate brain tissue microstructural and free-water composition. The tissue microstructural and free-water composition metrics were analysed using a bespoke voxel-based analysis and cortical region-of-interest analysis approach. Very preterm 13-year-olds exhibited reduced white matter microstructural density and increased free-water content across widespread regions of the white matter compared with controls. Additionally, very preterm 13-year-olds exhibited reduced microstructural density and increased free-water content in specific temporal, sensorimotor, occipital and cingulate cortical regions. These brain tissue composition alterations were strongly associated with cerebral white matter abnormalities identified in the neonatal period, and concurrent adverse cognitive and motor outcomes in very preterm children. The findings demonstrate brain microstructural and free-water alterations up to thirteen years from neonatal brain abnormalities in very preterm children that relate to adverse neurodevelopmental outcomes.
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Affiliation(s)
- Claire Kelly
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Melbourne, Australia; Victorian Infant Brain Studies (VIBeS), Clinical Sciences, Murdoch Children's Research Institute, Melbourne, Australia; Developmental Imaging, Clinical Sciences, Murdoch Children's Research Institute, Melbourne, Australia.
| | - Thijs Dhollander
- Developmental Imaging, Clinical Sciences, Murdoch Children's Research Institute, Melbourne, Australia
| | - Ian H Harding
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, Australia; Monash Biomedical Imaging, Monash University, Melbourne, Australia
| | - Wasim Khan
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, Australia
| | - Richard Beare
- Developmental Imaging, Clinical Sciences, Murdoch Children's Research Institute, Melbourne, Australia
| | - Jeanie Ly Cheong
- Victorian Infant Brain Studies (VIBeS), Clinical Sciences, Murdoch Children's Research Institute, Melbourne, Australia; The Royal Women's Hospital, Melbourne, Australia; Department of Obstetrics and Gynaecology, The University of Melbourne, Melbourne, Australia
| | - Lex W Doyle
- Victorian Infant Brain Studies (VIBeS), Clinical Sciences, Murdoch Children's Research Institute, Melbourne, Australia; The Royal Women's Hospital, Melbourne, Australia; Department of Obstetrics and Gynaecology, The University of Melbourne, Melbourne, Australia; Department of Paediatrics, The University of Melbourne, Melbourne, Australia
| | - Marc Seal
- Developmental Imaging, Clinical Sciences, Murdoch Children's Research Institute, Melbourne, Australia; Department of Paediatrics, The University of Melbourne, Melbourne, Australia
| | - Deanne K Thompson
- Victorian Infant Brain Studies (VIBeS), Clinical Sciences, Murdoch Children's Research Institute, Melbourne, Australia; Developmental Imaging, Clinical Sciences, Murdoch Children's Research Institute, Melbourne, Australia; Department of Paediatrics, The University of Melbourne, Melbourne, Australia
| | - Terrie E Inder
- Department of Pediatric Newborn Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Peter J Anderson
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Melbourne, Australia; Victorian Infant Brain Studies (VIBeS), Clinical Sciences, Murdoch Children's Research Institute, Melbourne, Australia
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10
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Chary K, Narvaez O, Salo RA, San Martín Molina I, Tohka J, Aggarwal M, Gröhn O, Sierra A. Microstructural Tissue Changes in a Rat Model of Mild Traumatic Brain Injury. Front Neurosci 2021; 15:746214. [PMID: 34899158 PMCID: PMC8662623 DOI: 10.3389/fnins.2021.746214] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2021] [Accepted: 10/27/2021] [Indexed: 12/31/2022] Open
Abstract
Our study investigates the potential of diffusion MRI (dMRI), including diffusion tensor imaging (DTI), fixel-based analysis (FBA) and neurite orientation dispersion and density imaging (NODDI), to detect microstructural tissue abnormalities in rats after mild traumatic brain injury (mTBI). The brains of sham-operated and mTBI rats 35 days after lateral fluid percussion injury were imaged ex vivo in a 11.7-T scanner. Voxel-based analyses of DTI-, fixel- and NODDI-based metrics detected extensive tissue changes in directly affected brain areas close to the primary injury, and more importantly, also in distal areas connected to primary injury and indirectly affected by the secondary injury mechanisms. Histology revealed ongoing axonal abnormalities and inflammation, 35 days after the injury, in the brain areas highlighted in the group analyses. Fractional anisotropy (FA), fiber density (FD) and fiber density and fiber bundle cross-section (FDC) showed similar pattern of significant areas throughout the brain; however, FA showed more significant voxels in gray matter areas, while FD and FDC in white matter areas, and orientation dispersion index (ODI) in areas most damage based on histology. Region-of-interest (ROI)-based analyses on dMRI maps and histology in selected brain regions revealed that the changes in MRI parameters could be attributed to both alterations in myelinated fiber bundles and increased cellularity. This study demonstrates that the combination of dMRI methods can provide a more complete insight into the microstructural alterations in white and gray matter after mTBI, which may aid diagnosis and prognosis following a mild brain injury.
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Affiliation(s)
- Karthik Chary
- A. I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
| | - Omar Narvaez
- A. I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
| | - Raimo A. Salo
- A. I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
| | | | - Jussi Tohka
- A. I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
| | - Manisha Aggarwal
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Olli Gröhn
- A. I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
| | - Alejandra Sierra
- A. I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
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11
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Influence of MRI on Diagnostic Efficacy and Satisfaction of Patients with Alzheimer's Disease. COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE 2021; 2021:9038784. [PMID: 34790255 PMCID: PMC8592746 DOI: 10.1155/2021/9038784] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/27/2021] [Revised: 10/06/2021] [Accepted: 11/01/2021] [Indexed: 01/07/2023]
Abstract
OBJECTIVE To inquire into the influence of magnetic resonance imaging (MRI) on the diagnostic efficacy and satisfaction of patients with Alzheimer's disease (AD). METHODS This study included 42 healthy people (control group) and 66 patients with AD (AD group). The hippocampus volume, temporal sulcus spacing, left-right brain diameter, brain lobe volume, hippocampal height, temporal horn width, lateral fissure width, and degree of leukoaraiosis were all measured using an MRI scan. After diagnosis, the satisfaction of patients in both arms was investigated and the satisfaction degree was recorded. RESULTS Compared with the control group, the left and right hippocampal volumes and hippocampal height of AD patients were smaller, while the temporal sulcus spacing, temporal horn width, lateral fissure width, and left-right brain diameter were remarkably higher. A statistical difference was present in the degree of leukoaraiosis between the two arms. The frontal and temporal lobe volumes of AD patients were notably lower while the volumes of parietal and occipital lobes were similar, versus the control group. The total satisfaction was 83.33% in the control group and 86.36% in the AD group, with no statistical difference between the two arms. CONCLUSIONS MRI can effectively mine the brain information of AD patients with a high patient satisfaction, which has potential value in clinical application.
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12
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Palmer JR, Duffy SL, Meares S, Pye J, Calamante F, Cespedes M, Hickie IB, Naismith SL. Rest-activity functioning is related to white matter microarchitecture and modifiable risk factors in older adults at-risk for dementia. Sleep 2021; 44:6082819. [PMID: 33428761 DOI: 10.1093/sleep/zsab007] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2020] [Revised: 12/15/2020] [Indexed: 12/13/2022] Open
Abstract
STUDY OBJECTIVES Growing evidence demonstrates pronounced alterations in rest-activity functioning in older adults at-risk for dementia. White matter degeneration, poor cardiometabolic functioning, and depression have also been linked to a greater risk of decline; however, limited studies have examined the white matter in relation to rest-activity functioning in at-risk older adults. METHODS We investigated associations between nonparametric actigraphy measures and white matter microarchitecture using whole-brain fixel-based analysis of diffusion-weighted imaging in older adults (aged 50 years or older) at-risk for cognitive decline and dementia. The fixel-based metrics assessed were fiber density, fiber cross-section, and combined fiber-density, and cross-section. Interactions between rest-activity functioning and known clinical risk factors, specifically body mass index (BMI), vascular risk factors, depressive symptoms and self-reported exercise, and their association with white matter properties were then investigated. RESULTS Sixty-seven older adults were included (mean = 65.78 years, SD = 7.89). Lower relative amplitude, poorer 24-h synchronization and earlier onset of the least active 5-h period were associated with reductions in markers of white matter atrophy in widespread regions, including cortico-subcortical and cortical association pathways. Preliminary evidence was also found indicating more pronounced white matter alterations in those with lower amplitude and higher BMI (β = 0.25, 95% CI [0.05, 0.46]), poorer 24-h synchronization and more vascular risk factors (β = 0.17, 95% CI [-0.02, 0.36]) and earlier onset of inactivity and greater depressive symptoms (β = 0.17, 95% CI [0.03, 0.30]). CONCLUSIONS These findings highlight the complex interplay between rest-activity rhythms, white matter, and clinical risk factors in individuals at-risk for dementia that should be considered in future studies.
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Affiliation(s)
- Jake R Palmer
- Department of Psychology, Faculty of Medicine, Health and Human Sciences, Macquarie University, Sydney, NSW, Australia.,School of Psychology, Faculty of Science, University of Sydney, Sydney, NSW, Australia.,Brain and Mind Centre and Charles Perkins Centre, University of Sydney, Sydney, NSW, Australia
| | - Shantel L Duffy
- Brain and Mind Centre and Charles Perkins Centre, University of Sydney, Sydney, NSW, Australia.,School of Health Sciences, Faculty of Medicine and Health, University of Sydney, Sydney, NSW, Australia.,NHMRC Centre of Research Excellence to Optimise Sleep in Brain Ageing and Neurodegeneration, Sydney, NSW, Australia
| | - Susanne Meares
- Department of Psychology, Faculty of Medicine, Health and Human Sciences, Macquarie University, Sydney, NSW, Australia
| | - Jonathon Pye
- School of Psychology, Faculty of Science, University of Sydney, Sydney, NSW, Australia.,Brain and Mind Centre and Charles Perkins Centre, University of Sydney, Sydney, NSW, Australia.,Susan Wakil School of Nursing and Midwifery, Faculty of Medicine and Health, University of Sydney, Sydney, NSW, Australia
| | - Fernando Calamante
- Sydney Imaging and School of Biomedical Engineering, Faculty of Engineering, University of Sydney, Sydney, NSW, Australia
| | - Marcela Cespedes
- Australian e-Health Research Centre, CSIRO Health and Biosecurity, Herston, QLD, Australia
| | - Ian B Hickie
- Brain and Mind Centre and Charles Perkins Centre, University of Sydney, Sydney, NSW, Australia
| | - Sharon L Naismith
- School of Psychology, Faculty of Science, University of Sydney, Sydney, NSW, Australia.,Brain and Mind Centre and Charles Perkins Centre, University of Sydney, Sydney, NSW, Australia.,NHMRC Centre of Research Excellence to Optimise Sleep in Brain Ageing and Neurodegeneration, Sydney, NSW, Australia
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13
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Fixel-based Analysis of Diffusion MRI: Methods, Applications, Challenges and Opportunities. Neuroimage 2021; 241:118417. [PMID: 34298083 DOI: 10.1016/j.neuroimage.2021.118417] [Citation(s) in RCA: 87] [Impact Index Per Article: 29.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2020] [Revised: 07/11/2021] [Accepted: 07/20/2021] [Indexed: 12/13/2022] Open
Abstract
Diffusion MRI has provided the neuroimaging community with a powerful tool to acquire in-vivo data sensitive to microstructural features of white matter, up to 3 orders of magnitude smaller than typical voxel sizes. The key to extracting such valuable information lies in complex modelling techniques, which form the link between the rich diffusion MRI data and various metrics related to the microstructural organization. Over time, increasingly advanced techniques have been developed, up to the point where some diffusion MRI models can now provide access to properties specific to individual fibre populations in each voxel in the presence of multiple "crossing" fibre pathways. While highly valuable, such fibre-specific information poses unique challenges for typical image processing pipelines and statistical analysis. In this work, we review the "Fixel-Based Analysis" (FBA) framework, which implements bespoke solutions to this end. It has recently seen a stark increase in adoption for studies of both typical (healthy) populations as well as a wide range of clinical populations. We describe the main concepts related to Fixel-Based Analyses, as well as the methods and specific steps involved in a state-of-the-art FBA pipeline, with a focus on providing researchers with practical advice on how to interpret results. We also include an overview of the scope of all current FBA studies, categorized across a broad range of neuro-scientific domains, listing key design choices and summarizing their main results and conclusions. Finally, we critically discuss several aspects and challenges involved with the FBA framework, and outline some directions and future opportunities.
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14
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Yu X, Yin X, Hong H, Wang S, Jiaerken Y, Zhang F, Pasternak O, Zhang R, Yang L, Lou M, Zhang M, Huang P. Increased extracellular fluid is associated with white matter fiber degeneration in CADASIL: in vivo evidence from diffusion magnetic resonance imaging. Fluids Barriers CNS 2021; 18:29. [PMID: 34193191 PMCID: PMC8247253 DOI: 10.1186/s12987-021-00264-1] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2021] [Accepted: 06/19/2021] [Indexed: 11/18/2022] Open
Abstract
Background White matter hyperintensities (WMHs) are one of the hallmarks of cerebral small vessel disease (CSVD), but the pathological mechanisms underlying WMHs remain unclear. Recent studies suggest that extracellular fluid (ECF) is increased in brain regions with WMHs. It has been hypothesized that ECF accumulation may have detrimental effects on white matter microstructure. To test this hypothesis, we used cerebral autosomal-dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL) as a unique CSVD model to investigate the relationships between ECF and fiber microstructural changes in WMHs. Methods Thirty-eight CADASIL patients underwent 3.0 T MRI with multi-model sequences. Parameters of free water (FW) and apparent fiber density (AFD) obtained from diffusion-weighted imaging (b = 0 and 1000 s/mm2) were respectively used to quantify the ECF and fiber density. WMHs were split into four subregions with four levels of FW using quartiles (FWq1 to FWq4) for each participant. We analyzed the relationships between FW and AFD in each subregion of WMHs. Additionally, we tested whether FW of WMHs were associated with other accompanied CSVD imaging markers including lacunes and microbleeds. Results We found an inverse correlation between FW and AFD in WMHs. Subregions of WMHs with high-level of FW (FWq3 and FWq4) were accompanied with decreased AFD and with changes in FW-corrected diffusion tensor imaging parameters. Furthermore, FW was also independently associated with lacunes and microbleeds. Conclusions Our study demonstrated that increased ECF was associated with WM degeneration and the occurrence of lacunes and microbleeds, providing important new insights into the role of ECF in CADASIL pathology. Improving ECF drainage might become a therapeutic strategy in future. Supplementary Information The online version contains supplementary material available at 10.1186/s12987-021-00264-1.
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Affiliation(s)
- Xinfeng Yu
- Department of Radiology, The 2nd Affiliated Hospital, Zhejiang University School of Medicine, No.88 Jiefang Road, Shangcheng District, Hangzhou, 310009, China
| | - Xinzhen Yin
- Department of Neurology, The 2nd Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Hui Hong
- Department of Radiology, The 2nd Affiliated Hospital, Zhejiang University School of Medicine, No.88 Jiefang Road, Shangcheng District, Hangzhou, 310009, China
| | - Shuyue Wang
- Department of Radiology, The 2nd Affiliated Hospital, Zhejiang University School of Medicine, No.88 Jiefang Road, Shangcheng District, Hangzhou, 310009, China
| | - Yeerfan Jiaerken
- Department of Radiology, The 2nd Affiliated Hospital, Zhejiang University School of Medicine, No.88 Jiefang Road, Shangcheng District, Hangzhou, 310009, China
| | - Fan Zhang
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Ofer Pasternak
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.,Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Ruiting Zhang
- Department of Radiology, The 2nd Affiliated Hospital, Zhejiang University School of Medicine, No.88 Jiefang Road, Shangcheng District, Hangzhou, 310009, China
| | - Linglin Yang
- Department of Psychiatry, The 2nd Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Min Lou
- Department of Neurology, The 2nd Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Minming Zhang
- Department of Radiology, The 2nd Affiliated Hospital, Zhejiang University School of Medicine, No.88 Jiefang Road, Shangcheng District, Hangzhou, 310009, China.
| | - Peiyu Huang
- Department of Radiology, The 2nd Affiliated Hospital, Zhejiang University School of Medicine, No.88 Jiefang Road, Shangcheng District, Hangzhou, 310009, China.
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15
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Qu Y, Wang P, Liu B, Song C, Wang D, Yang H, Zhang Z, Chen P, Kang X, Du K, Yao H, Zhou B, Han T, Zuo N, Han Y, Lu J, Yu C, Zhang X, Jiang T, Zhou Y, Liu Y. AI4AD: Artificial intelligence analysis for Alzheimer's disease classification based on a multisite DTI database. BRAIN DISORDERS 2021. [DOI: 10.1016/j.dscb.2021.100005] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
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