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Mills EP, Bosma RL, Rogachov A, Cheng JC, Osborne NR, Kim JA, Besik A, El‐Sayed R, Bhatia A, Davis KD. Sex-Specific White Matter Abnormalities Across the Dynamic Pain Connectome in Neuropathic Pain: A Fixel-Based Analysis Study. Hum Brain Mapp 2025; 46:e70135. [PMID: 39803943 PMCID: PMC11726370 DOI: 10.1002/hbm.70135] [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: 06/25/2024] [Revised: 12/13/2024] [Accepted: 12/29/2024] [Indexed: 01/16/2025] Open
Abstract
A fundamental issue in neuroscience is a lack of understanding regarding the relationship between brain function and the white matter architecture that supports it. Individuals with chronic neuropathic pain (NP) exhibit functional abnormalities throughout brain networks collectively termed the "dynamic pain connectome" (DPC), including the default mode network (DMN), salience network, and ascending nociceptive and descending pain modulation systems. These functional abnormalities are often observed in a sex-dependent fashion. However, the enigmatic white matter structural features underpinning these functional networks and the relationship between structure and function/dysfunction in NP remain poorly understood. Here we used fixel-based analysis of diffusion weighted imaging data in 80 individuals (40 with NP [21 female, 19 male] and 40 sex- and age-matched healthy controls [HCs]) to evaluate white matter microstructure (fiber density [FD]), macrostructure (fiber bundle cross section) and combined microstructure and macrostructure (fiber density and cross section) within anatomical connections that support the DPC. We additionally examined whether there are sex-specific abnormalities in NP white matter structure. We performed fixel-wise and connection-specific mean analyses and found three main ways in which individuals with NP differed from HCs: (1) people with NP exhibited abnormally low FD and FDC within the corona radiata consistent with the ascending nociceptive pathway between the sensory thalamus and primary somatosensory cortex (S1). Furthermore, the entire sensory thalamus-S1 pathway exhibited abnormally low FD and FDC in people with NP, and this effect was driven by the females with NP; (2) females, but not males, with NP had abnormally low FD within the cingulum consistent with the right medial prefrontal cortex-posterior cingulate cortex DMN pathway; and (3) individuals with NP had higher connection-specific mean FDC than HCs in the anterior insula-temporoparietal junction and sensory thalamus-posterior insula pathways. However, sex-specific analyses did not corroborate these connection-specific findings in either females or males with NP. Our findings suggest that females with NP exhibit microstructural and macrostructural white matter abnormalities within the DPC networks including the ascending nociceptive system and DMN. We propose that aberrant white matter structure contributes to or is driven by functional abnormalities associated with NP. Our sex-specific findings highlight the utility and importance of using sex-disaggregated analyses to identify white matter abnormalities in clinical conditions such as chronic pain.
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Affiliation(s)
- Emily P. Mills
- Division of Brain, Imaging, and Behaviour, Krembil Brain InstituteUniversity Health NetworkTorontoOntarioCanada
| | - Rachael L. Bosma
- Division of Brain, Imaging, and Behaviour, Krembil Brain InstituteUniversity Health NetworkTorontoOntarioCanada
| | - Anton Rogachov
- Division of Brain, Imaging, and Behaviour, Krembil Brain InstituteUniversity Health NetworkTorontoOntarioCanada
- Institute of Medical ScienceUniversity of TorontoTorontoOntarioCanada
| | - Joshua C. Cheng
- Division of Brain, Imaging, and Behaviour, Krembil Brain InstituteUniversity Health NetworkTorontoOntarioCanada
- Institute of Medical ScienceUniversity of TorontoTorontoOntarioCanada
| | - Natalie R. Osborne
- Division of Brain, Imaging, and Behaviour, Krembil Brain InstituteUniversity Health NetworkTorontoOntarioCanada
- Institute of Medical ScienceUniversity of TorontoTorontoOntarioCanada
| | - Junseok A. Kim
- Division of Brain, Imaging, and Behaviour, Krembil Brain InstituteUniversity Health NetworkTorontoOntarioCanada
- Institute of Medical ScienceUniversity of TorontoTorontoOntarioCanada
| | - Ariana Besik
- Division of Brain, Imaging, and Behaviour, Krembil Brain InstituteUniversity Health NetworkTorontoOntarioCanada
| | - Rima El‐Sayed
- Division of Brain, Imaging, and Behaviour, Krembil Brain InstituteUniversity Health NetworkTorontoOntarioCanada
- Institute of Medical ScienceUniversity of TorontoTorontoOntarioCanada
| | - Anuj Bhatia
- Department of Anesthesia and Pain ManagementUniversity Health NetworkTorontoOntarioCanada
- Department of AnesthesiaUniversity of TorontoTorontoOntarioCanada
| | - Karen D. Davis
- Division of Brain, Imaging, and Behaviour, Krembil Brain InstituteUniversity Health NetworkTorontoOntarioCanada
- Institute of Medical ScienceUniversity of TorontoTorontoOntarioCanada
- Department of SurgeryUniversity of TorontoTorontoOntarioCanada
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Tinney EM, Warren AEL, Ai M, Morris TP, O'Brien A, Odom H, Sutton BP, Jain S, Kang C, Huang H, Wan L, Oberlin L, Burns JM, Vidoni ED, McAuley E, Kramer AF, Erickson KI, Hillman CH. Understanding Cognitive Aging Through White Matter: A Fixel-Based Analysis. Hum Brain Mapp 2024; 45:e70121. [PMID: 39720841 PMCID: PMC11669003 DOI: 10.1002/hbm.70121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2024] [Revised: 11/27/2024] [Accepted: 12/13/2024] [Indexed: 12/26/2024] Open
Abstract
Diffusion-weighted imaging (DWI) has been frequently used to examine age-related deterioration of white matter microstructure and its relationship to cognitive decline. However, typical tensor-based analytical approaches are often difficult to interpret due to the challenge of decomposing and (mis)interpreting the impact of crossing fibers within a voxel. We hypothesized that a novel analytical approach capable of resolving fiber-specific changes within each voxel (i.e., fixel-based analysis [FBA])-would show greater sensitivity relative to the traditional tensor-based approach for assessing relationships between white matter microstructure, age, and cognitive performance. To test our hypothesis, we studied 636 cognitively normal adults aged 65-80 years (mean age = 69.8 years; 71% female) using diffusion-weighted MRI. We analyzed fixels (i.e., fiber-bundle elements) to test our hypotheses. A fixel provides insight into the structural integrity of individual fiber populations in each voxel in the presence of multiple crossing fiber pathways, allowing for potentially increased specificity over other diffusion measures. Linear regression was used to investigate associations between each of three fixel metrics (fiber density, cross-section, and density × cross-section) with age and cognitive performance. We then compared and contrasted the FBA results to a traditional tensor-based approach examining voxel-wise fractional anisotropy. In a whole-brain analysis, significant associations were found between fixel-based metrics and age after adjustments for sex, education, total brain volume, site, and race. We found that increasing age was associated with decreased fiber density and cross-section, namely in the fornix, striatal, and thalamic pathways. Further analysis revealed that lower fiber density and cross-section were associated with poorer performance in measuring processing speed and attentional control. In contrast, the tensor-based analysis failed to detect any white matter tracts significantly associated with age or cognition. Taken together, these results suggest that FBAs of DWI data may be more sensitive for detecting age-related white matter changes in an older adult population and can uncover potentially clinically important associations with cognitive performance.
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Affiliation(s)
- Emma M. Tinney
- Department of PsychologyNortheastern UniversityBostonMassachusettsUSA
- Center for Cognitive & Brain HealthNortheastern UniversityBostonMassachusettsUSA
| | - Aaron E. L. Warren
- Department of Neurosurgery, Brigham and Women's HospitalHarvard Medical SchoolBostonMassachusettsUSA
| | - Meishan Ai
- Department of PsychologyNortheastern UniversityBostonMassachusettsUSA
- Center for Cognitive & Brain HealthNortheastern UniversityBostonMassachusettsUSA
| | - Timothy P. Morris
- Center for Cognitive & Brain HealthNortheastern UniversityBostonMassachusettsUSA
- Department of Physical Therapy, Movement, & Rehabilitation SciencesNortheastern UniversityBostonMassachusettsUSA
- Department of Applied PsychologyNortheastern UniversityBostonMassachusettsUSA
| | - Amanda O'Brien
- Department of PsychologyNortheastern UniversityBostonMassachusettsUSA
- Center for Cognitive & Brain HealthNortheastern UniversityBostonMassachusettsUSA
| | - Hannah Odom
- Department of PsychologyNortheastern UniversityBostonMassachusettsUSA
- Center for Cognitive & Brain HealthNortheastern UniversityBostonMassachusettsUSA
| | - Bradley P. Sutton
- Beckman InstituteUniversity of IllinoisUrbanaIllinoisUSA
- Department of BioengineeringUniversity of IllinoisUrbanaIllinoisUSA
| | - Shivangi Jain
- AdventHealth Research InstituteNeuroscienceOrlandoFloridaUSA
| | - Chaeryon Kang
- Department of BiostatisticsUniversity of PittsburghPittsburghPennsylvaniaUSA
| | - Haiqing Huang
- AdventHealth Research InstituteNeuroscienceOrlandoFloridaUSA
| | - Lu Wan
- AdventHealth Research InstituteNeuroscienceOrlandoFloridaUSA
| | - Lauren Oberlin
- AdventHealth Research InstituteNeuroscienceOrlandoFloridaUSA
- Weill Cornell Institute of Geriatric PsychiatryWeill Cornell MedicineWhite PlainsNew YorkUSA
| | | | | | - Edward McAuley
- Beckman InstituteUniversity of IllinoisUrbanaIllinoisUSA
- Department of Health and KinesiologyUniversity of IllinoisUrbanaIllinoisUSA
| | - Arthur F. Kramer
- Department of PsychologyNortheastern UniversityBostonMassachusettsUSA
- Center for Cognitive & Brain HealthNortheastern UniversityBostonMassachusettsUSA
- Beckman InstituteUniversity of IllinoisUrbanaIllinoisUSA
| | | | - Charles H. Hillman
- Department of PsychologyNortheastern UniversityBostonMassachusettsUSA
- Center for Cognitive & Brain HealthNortheastern UniversityBostonMassachusettsUSA
- Department of Physical Therapy, Movement, & Rehabilitation SciencesNortheastern UniversityBostonMassachusettsUSA
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3
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de la Cruz F, Schumann A, Rieger K, Güllmar D, Reichenbach JR, Bär KJ. White matter differences between younger and older adults revealed by fixel-based analysis. AGING BRAIN 2024; 6:100132. [PMID: 39650611 PMCID: PMC11625364 DOI: 10.1016/j.nbas.2024.100132] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2024] [Revised: 11/11/2024] [Accepted: 11/12/2024] [Indexed: 12/11/2024] Open
Abstract
The process of healthy aging involves complex alterations in neural structures, with white matter (WM) changes significantly impacting cognitive and motor functions. Conventional methods such as diffusion tensor imaging provide valuable insights, but their limitations in capturing complex WM geometry advocate for more advanced approaches. In this study involving 120 healthy volunteers, we investigated whole-brain WM differences between young and old individuals using a novel technique called fixel-based analysis (FBA). This approach revealed that older adults exhibited reduced FBA-derived metrics in several WM tracts, with frontal areas particularly affected. Surprisingly, age-related differences in FBA-derived measures showed no significant correlation with risk factors such as alcohol consumption, exercise frequency, or pulse pressure but predicted cognitive performance. These findings emphasize FBA's potential in characterizing complex WM changes and the link between cognitive abilities and WM alterations in healthy aging. Overall, this study advances our understanding of age-related neurodegeneration, highlighting the importance of comprehensive assessments that integrate advanced neuroimaging techniques, cognitive evaluation, and demographic factors to gain insights into healthy aging.
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Affiliation(s)
- Feliberto de la Cruz
- Lab for Autonomic Neuroscience, Imaging and Cognition (LANIC), Department of Psychosomatic Medicine and Psychotherapy, Jena University Hospital, Jena, Germany
| | - Andy Schumann
- Lab for Autonomic Neuroscience, Imaging and Cognition (LANIC), Department of Psychosomatic Medicine and Psychotherapy, Jena University Hospital, Jena, Germany
| | - Katrin Rieger
- Lab for Autonomic Neuroscience, Imaging and Cognition (LANIC), Department of Psychosomatic Medicine and Psychotherapy, Jena University Hospital, Jena, Germany
| | - Daniel Güllmar
- Medical Physics Group, Institute of Diagnostic and Interventional Radiology, Jena University Hospital, Jena, Germany
| | - Jürgen R. Reichenbach
- Medical Physics Group, Institute of Diagnostic and Interventional Radiology, Jena University Hospital, Jena, Germany
| | - Karl-Jürgen Bär
- Lab for Autonomic Neuroscience, Imaging and Cognition (LANIC), Department of Psychosomatic Medicine and Psychotherapy, Jena University Hospital, Jena, Germany
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Koschutnig K, Weber B, Fink A. Tidying up white matter: Neuroplastic transformations in sensorimotor tracts following slackline skill acquisition. Hum Brain Mapp 2024; 45:e26791. [PMID: 39524014 PMCID: PMC11551625 DOI: 10.1002/hbm.26791] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2023] [Revised: 06/20/2024] [Accepted: 07/05/2024] [Indexed: 11/16/2024] Open
Abstract
This study investigated changes in white matter (WM) morphology following complex motor learning, that is, the learning to walk a slackline. A sample of young adults from the general population underwent brain imaging before the slackline intervention, after successful learning, and after a subsequent follow-up period by applying state-of-the-art measures for the assessment of micro- and macrostructural characteristics of WM fiber tracts (voxel-based and fixel-based). A randomly assigned control group (CG) was scanned at the same time points of assessment but received no intervention over the study period. Learning to walk a slackline resulted in manifold changes in WM morphology: (1) Whole brain fixel-based analyses revealed robust increases in the fiber cross-section in bundles closely associated with sensorimotor functions (e.g., superior longitudinal fasciculi, corticospinal tract); (2) The neurite orientation dispersion and density imaging (NODDI) parameters showed widespread decreases in overlapping fiber bundles. In the CG, no time-related WM changes were apparent at all. This well-controlled longitudinal intervention study provides substantial new evidence that learning a complex motor skill modulates fiber organization and fiber density in sensorimotor tracts.
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Affiliation(s)
- Karl Koschutnig
- Department of Psychology, MRI‐Lab GrazUniversity of GrazGrazAustria
- Present address:
MRI‐Lab Graz, University of Graz, Kopernikusgasse 24GrazAustria
| | | | - Andreas Fink
- Department of PsychologyUniversity of GrazGrazAustria
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Nasrallah HA. Is self-disturbance in schizophrenia due to inter- and intra-hemispheric white matter dysconnectivity? Schizophr Res 2024; 270:129-131. [PMID: 38901209 DOI: 10.1016/j.schres.2024.06.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/28/2024] [Revised: 06/02/2024] [Accepted: 06/03/2024] [Indexed: 06/22/2024]
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Simon C, Bolton DAE, Meaney JF, Kenny RA, Simon VA, De Looze C, Knight S, Ruddy KL. White matter fibre density in the brain's inhibitory control network is associated with falling in low activity older adults. Eur J Neurosci 2024; 59:3184-3202. [PMID: 38638001 DOI: 10.1111/ejn.16327] [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: 11/30/2023] [Revised: 02/20/2024] [Accepted: 03/09/2024] [Indexed: 04/20/2024]
Abstract
Recent research has indicated that the relationship between age-related cognitive decline and falling may be mediated by the individual's capacity to quickly cancel or inhibit a motor response. This longitudinal investigation demonstrates that higher white matter fibre density in the motor inhibition network paired with low physical activity was associated with falling in elderly participants. We measured the density of white matter fibre tracts connecting key nodes in the inhibitory control network in a large sample (n = 414) of older adults. We modelled their self-reported frequency of falling over a 4-year period with white matter fibre density in pathways corresponding to the direct and hyperdirect cortical-subcortical loops implicated in the inhibitory control network. Only connectivity between right inferior frontal gyrus and right subthalamic nucleus was associated with falling as measured cross-sectionally. The connectivity was not, however, predictive of future falling when measured 2 and 4 years later. Higher white matter fibre density was associated with falling, but only in combination with low levels of physical activity. No such relationship existed for selected control brain regions that are not implicated in the inhibitory control network. Albeit statistically robust, the direction of this effect was counterintuitive (more dense connectivity associated with falling) and warrants further longitudinal investigation into whether white matter fibre density changes over time in a manner correlated with falling, and mediated by physical activity.
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Affiliation(s)
- Colin Simon
- Trinity College Institute of Neuroscience and School of Psychology, Trinity College Dublin, Dublin, Ireland
| | - David A E Bolton
- Department of Kinesiology and Health Science, Utah State University, Logan, Utah, USA
| | - James F Meaney
- Centre for Advanced Medical Imaging (CAMI), St James's Hospital, Dublin, Ireland
| | - Rose Anne Kenny
- The Irish Longitudinal Study on Ageing (TILDA), Trinity College Dublin, Dublin, Ireland
- Discipline of Medical Gerontology, School of Medicine, Trinity College Dublin, Dublin, Ireland
- Mercer's Institute for Successful Ageing (MISA), St James's Hospital, Dublin, Ireland
| | - Vivienne A Simon
- Trinity College Institute of Neuroscience and School of Psychology, Trinity College Dublin, Dublin, Ireland
| | - Céline De Looze
- The Irish Longitudinal Study on Ageing (TILDA), Trinity College Dublin, Dublin, Ireland
- Discipline of Medical Gerontology, School of Medicine, Trinity College Dublin, Dublin, Ireland
| | - Silvin Knight
- Discipline of Medical Gerontology, School of Medicine, Trinity College Dublin, Dublin, Ireland
- Global Brain Health Institute (GBHI), Trinity College Dublin, Dublin, Ireland
| | - Kathy L Ruddy
- Trinity College Institute of Neuroscience and School of Psychology, Trinity College Dublin, Dublin, Ireland
- School of Psychology, Queen's University Belfast, Belfast, UK
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7
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Svobodová V, Profant O, Škoch A, Tintěra J, Tóthová D, Chovanec M, Čapková D, Syka J. The effect of aging, hearing loss, and tinnitus on white matter in the human auditory system revealed with fixel-based analysis. Front Aging Neurosci 2024; 15:1283660. [PMID: 38264549 PMCID: PMC10803717 DOI: 10.3389/fnagi.2023.1283660] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2023] [Accepted: 12/12/2023] [Indexed: 01/25/2024] Open
Abstract
Introduction Aging negatively influences the structure of the human brain including the white matter. The objective of our study was to identify, using fixel-based morphometry, the age induced changes in the pathways connecting several regions of the central auditory system (inferior colliculus, Heschl's gyrus, planum temporale) and the pathways connecting these structures with parts of the limbic system (anterior insula, hippocampus and amygdala). In addition, we were interested in the extent to which the integrity of these pathways is influenced by hearing loss and tinnitus. Methods Tractographic data were acquired using a 3 T MRI in 79 volunteers. The participants were categorized into multiple groups in accordance with their age, auditory thresholds and tinnitus status. Fixel-based analysis was utilized to identify alterations in the subsequent three parameters: logarithm of fiber cross-section, fiber density, fiber density and cross-section. Two modes of analysis were used: whole brain analysis and targeted analysis using fixel mask, corresponding to the pathways connecting the aforementioned structures. Results A significantly negative effect of aging was present for all fixel-based metrics, namely the logarithm of the fiber cross-section, (7 % fixels in whole-brain, 14% fixels in fixel mask), fiber density (5 % fixels in whole-brain, 15% fixels in fixel mask), fiber density and cross section (7 % fixels in whole-brain, 19% fixels in fixel mask). Expressed age-related losses, exceeding 30% fixels, were particularly present in pathways connecting the auditory structures with limbic structures. The effect of hearing loss and/or tinnitus did not reach significance. Conclusions Our results show that although an age-related reduction of fibers is present in pathways connecting several auditory regions, the connections of these structures with limbic structures are even more reduced. To what extent this fact influences the symptoms of presbycusis, such as decreased speech comprehension, especially in noise conditions, remains to be elucidated.
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Affiliation(s)
- Veronika Svobodová
- Department of Auditory Neuroscience, Institute of Experimental Medicine of the Czech Academy of Sciences, Prague, Czechia
- Department of Otorhinolaryngology and Head and Neck Surgery, 1st Faculty of Medicine, Charles University in Prague, University Hospital Motol, Prague, Czechia
| | - Oliver Profant
- Department of Auditory Neuroscience, Institute of Experimental Medicine of the Czech Academy of Sciences, Prague, Czechia
- Department of Otorhinolaryngology, 3rd Faculty of Medicine, Charles University in Prague, University Hospital Královské Vinohrady, Prague, Czechia
| | - Antonín Škoch
- Department of Radiodiagnostic and Interventional Radiology, Institute of Clinical and Experimental Medicine, Prague, Czechia
| | - Jaroslav Tintěra
- Department of Radiodiagnostic and Interventional Radiology, Institute of Clinical and Experimental Medicine, Prague, Czechia
| | - Diana Tóthová
- Department of Auditory Neuroscience, Institute of Experimental Medicine of the Czech Academy of Sciences, Prague, Czechia
- Department of Otorhinolaryngology and Head and Neck Surgery, 1st Faculty of Medicine, Charles University in Prague, University Hospital Motol, Prague, Czechia
| | - Martin Chovanec
- Department of Otorhinolaryngology, 3rd Faculty of Medicine, Charles University in Prague, University Hospital Královské Vinohrady, Prague, Czechia
| | - Dora Čapková
- Department of Auditory Neuroscience, Institute of Experimental Medicine of the Czech Academy of Sciences, Prague, Czechia
- Department of Otorhinolaryngology, 3rd Faculty of Medicine, Charles University in Prague, University Hospital Královské Vinohrady, Prague, Czechia
| | - Josef Syka
- Department of Auditory Neuroscience, Institute of Experimental Medicine of the Czech Academy of Sciences, Prague, Czechia
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Han A, Dhollander T, Sun YL, Chad JA, Chen JJ. Fiber-specific age-related differences in the white matter of healthy adults uncovered by fixel-based analysis. Neurobiol Aging 2023; 130:22-29. [PMID: 37423114 DOI: 10.1016/j.neurobiolaging.2023.06.007] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2022] [Revised: 05/31/2023] [Accepted: 06/08/2023] [Indexed: 07/11/2023]
Abstract
Diffusion magnetic resonance imaging studies often investigate white matter (WM) microstructural degeneration in aging by probing WM regions that exhibit negative age associations of fractional anisotropy (FA). However, WM regions in which FA is unassociated with age are not necessarily "spared" in aging. Besides the confound of inter-participant heterogeneity, FA conflates all intravoxel fiber populations and does not allow the detection of individual fiber-specific age associations. In this study of 541 healthy adults aged 36-100 years, we use fixel-based analysis to investigate age associations among each "fixel" within a voxel, representing individual fiber populations. We find age associations of fixel-based measures that indicate age-related differences in individual fiber populations amid complex fiber architectures. Different crossing fiber populations exhibit different slopes of age associations. Our findings may provide evidence of selective degeneration of intravoxel WM fibers in aging, which does not necessarily manifest as a change in FA and therefore escapes notice if conventional voxel-based analyses are relied upon alone.
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Affiliation(s)
- Ana Han
- Rotman Research Institute, Baycrest Health Sciences, Toronto, Ontario, Canada
| | - Thijs Dhollander
- Developmental Imaging, Murdoch Children's Research Institute, Melbourne, Australia
| | - Yutong L Sun
- Rotman Research Institute, Baycrest Health Sciences, Toronto, Ontario, Canada; Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
| | - Jordan A Chad
- Rotman Research Institute, Baycrest Health Sciences, Toronto, Ontario, Canada; Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada.
| | - J Jean Chen
- Rotman Research Institute, Baycrest Health Sciences, Toronto, Ontario, Canada; Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada; Department of Biomedical Engineering, University of Toronto, Toronto, Ontario, Canada
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9
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Li X, Salami A, Persson J. Hub architecture of the human structural connectome: Links to aging and processing speed. Neuroimage 2023; 278:120270. [PMID: 37423273 DOI: 10.1016/j.neuroimage.2023.120270] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2023] [Revised: 06/30/2023] [Accepted: 07/06/2023] [Indexed: 07/11/2023] Open
Abstract
The human structural brain network, or connectome, has a rich-club organization with a small number of brain regions showing high network connectivity, called hubs. Hubs are centrally located in the network, energy costly, and critical for human cognition. Aging has been associated with changes in brain structure, function, and cognitive decline, such as processing speed. At a molecular level, the aging process is a progressive accumulation of oxidative damage, which leads to subsequent energy depletion in the neuron and causes cell death. However, it is still unclear how age affects hub connections in the human connectome. The current study aims to address this research gap by constructing structural connectome using fiber bundle capacity (FBC). FBC is derived from Constrained Spherical Deconvolution (CSD) modeling of white-matter fiber bundles, which represents the capacity of a fiber bundle to transfer information. Compared to the raw number of streamlines, FBC is less bias for quantifying connection strength within biological pathways. We found that hubs exhibit longer-distance connections and higher metabolic rates compared to peripheral brain regions, suggesting that hubs are biologically costly. Although the landscape of structural hubs was relatively age-invariant, there were wide-spread age effects on FBC in the connectome. Critically, these age effects were larger in connections within hub compared to peripheral brain connections. These findings were supported by both a cross-sectional sample with wide age-range (N = 137) and a longitudinal sample across 5 years (N = 83). Moreover, our results demonstrated that associations between FBC and processing speed were more concentrated in hub connections than chance level, and FBC in hub connections mediated the age-effects on processing speed. Overall, our findings indicate that structural connections of hubs, which demonstrate greater energy demands, are particular vulnerable to aging. The vulnerability may contribute to age-related impairments in processing speed among older adults.
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Affiliation(s)
- Xin Li
- Aging Research Center, Karolinska Institute and Stockholm University, Stockholm 171 65, Sweden.
| | - Alireza Salami
- Aging Research Center, Karolinska Institute and Stockholm University, Stockholm 171 65, Sweden; Umeå Center for Functional Brain Imaging (UFBI), Umeå University, Umeå 901 87, Sweden; Wallenberg Centre for Molecular Medicine, Umeå University, Umeå 901 87, Sweden; Department of Integrative Medical Biology, Umeå University, Umeå 901 87, Sweden
| | - Jonas Persson
- Aging Research Center, Karolinska Institute and Stockholm University, Stockholm 171 65, Sweden; Center for Lifespan Developmental Research (LEADER), School of Behavioral, Social and Legal Sciences, Örebro University, Örebro 701 82, Sweden
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10
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Rasooli A, Adab HZ, Van Ruitenbeek P, Weerasekera A, Chalavi S, Cuypers K, Levin O, Dhollander T, Peeters R, Sunaert S, Mantini D, Swinnen SP. White matter and neurochemical mechanisms underlying age-related differences in motor processing speed. iScience 2023; 26:106794. [PMID: 37255665 PMCID: PMC10225899 DOI: 10.1016/j.isci.2023.106794] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2022] [Revised: 01/11/2023] [Accepted: 04/27/2023] [Indexed: 06/01/2023] Open
Abstract
Aging is associated with changes in the central nervous system and leads to reduced life quality. Here, we investigated the age-related differences in the CNS underlying motor performance deficits using magnetic resonance spectroscopy and diffusion MRI. MRS measured N-acetyl aspartate (NAA), choline (Cho), and creatine (Cr) concentrations in the sensorimotor and occipital cortex, whereas dMRI quantified apparent fiber density (FD) in the same voxels to evaluate white matter microstructural organization. We found that aging was associated with increased reaction time and reduced FD and NAA concentration in the sensorimotor voxel. Both FD and NAA mediated the association between age and reaction time. The NAA concentration was found to mediate the association between age and FD in the sensorimotor voxel. We propose that the age-related decrease in NAA concentration may result in reduced axonal fiber density in the sensorimotor cortex which may ultimately account for the response slowness of older participants.
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Affiliation(s)
- Amirhossein Rasooli
- Movement Control & Neuroplasticity Research Group, Group Biomedical Sciences, KU Leuven, Leuven, Belgium
- KU Leuven Brain Institute, KU Leuven, Leuven, Belgium
| | - Hamed Zivari Adab
- Movement Control & Neuroplasticity Research Group, Group Biomedical Sciences, KU Leuven, Leuven, Belgium
- KU Leuven Brain Institute, KU Leuven, Leuven, Belgium
| | - Peter Van Ruitenbeek
- Movement Control & Neuroplasticity Research Group, Group Biomedical Sciences, KU Leuven, Leuven, Belgium
- Department of Neuropsychology and Psychopharmacology, Faculty of Psychology and Neuroscience, Maastricht University, 6200 MD Maastricht, the Netherlands
| | - Akila Weerasekera
- Movement Control & Neuroplasticity Research Group, Group Biomedical Sciences, KU Leuven, Leuven, Belgium
- KU Leuven Brain Institute, KU Leuven, Leuven, Belgium
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Sima Chalavi
- Movement Control & Neuroplasticity Research Group, Group Biomedical Sciences, KU Leuven, Leuven, Belgium
- KU Leuven Brain Institute, KU Leuven, Leuven, Belgium
| | - Koen Cuypers
- Movement Control & Neuroplasticity Research Group, Group Biomedical Sciences, KU Leuven, Leuven, Belgium
- KU Leuven Brain Institute, KU Leuven, Leuven, Belgium
- REVAL Rehabilitation Research Center, Hasselt University, Diepenbeek, Belgium
| | - Oron Levin
- Movement Control & Neuroplasticity Research Group, Group Biomedical Sciences, KU Leuven, Leuven, Belgium
- KU Leuven Brain Institute, KU Leuven, Leuven, Belgium
| | - Thijs Dhollander
- Murdoch Children’s Research Institute, Melbourne, VIC, Australia
| | - Ronald Peeters
- KU Leuven, Department of Imaging and Pathology, Group Biomedical Sciences, KU Leuven, Leuven, Belgium
| | - Stefan Sunaert
- KU Leuven, Department of Imaging and Pathology, Group Biomedical Sciences, KU Leuven, Leuven, Belgium
| | - Dante Mantini
- Movement Control & Neuroplasticity Research Group, Group Biomedical Sciences, KU Leuven, Leuven, Belgium
- KU Leuven Brain Institute, KU Leuven, Leuven, Belgium
| | - Stephan P. Swinnen
- Movement Control & Neuroplasticity Research Group, Group Biomedical Sciences, KU Leuven, Leuven, Belgium
- KU Leuven Brain Institute, KU Leuven, Leuven, Belgium
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11
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Polk SE, Kleemeyer MM, Bodammer NC, Misgeld C, Porst J, Wolfarth B, Kühn S, Lindenberger U, Düzel S, Wenger E. Aerobic exercise is associated with region-specific changes in volumetric, tensor-based, and fixel-based measures of white matter integrity in healthy older adults. NEUROIMAGE: REPORTS 2023. [DOI: 10.1016/j.ynirp.2022.100155] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
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12
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Radhakrishnan V, Gallea C, Valabregue R, Krishnan S, Kesavadas C, Thomas B, James P, Menon R, Kishore A. Cerebellar and basal ganglia structural connections in humans: Effect of aging and relation with memory and learning. Front Aging Neurosci 2023; 15:1019239. [PMID: 36776439 PMCID: PMC9908607 DOI: 10.3389/fnagi.2023.1019239] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2022] [Accepted: 01/06/2023] [Indexed: 01/27/2023] Open
Abstract
Introduction The cerebellum and basal ganglia were initially considered anatomically distinct regions, each connected via thalamic relays which project to the same cerebral cortical targets, such as the motor cortex. In the last two decades, transneuronal viral transport studies in non-human primates showed bidirectional connections between the cerebellum and basal ganglia at the subcortical level, without involving the cerebral cortical motor areas. These findings have significant implications for our understanding of neurodevelopmental and neurodegenerative diseases. While these subcortical connections were established in smaller studies on humans, their evolution with natural aging is less understood. Methods In this study, we validated and expanded the previous findings of the structural connectivity within the cerebellum-basal ganglia subcortical network, in a larger dataset of 64 subjects, across different age ranges. Tractography and fixel-based analysis were performed on the 3 T diffusion-weighted dataset using Mrtrix3 software, considering fiber density and cross-section as indicators of axonal integrity. Tractography of the well-established cerebello-thalamo-cortical tract was conducted as a control. We tested the relationship between the structural white matter integrity of these connections with aging and with the performance in different domains of Addenbrooke's Cognitive Examination. Results Tractography analysis isolated connections from the dentate nucleus to the contralateral putamen via the thalamus, and reciprocal tracts from the subthalamic nucleus to the contralateral cerebellar cortex via the pontine nuclei. Control tracts of cerebello-thalamo-cortical tracts were also isolated, including associative cerebello-prefrontal tracts. A negative linear relationship was found between the fiber density of both the ascending and descending cerebellum-basal ganglia tracts and age. Considering the cognitive assessments, the fiber density values of cerebello-thalamo-putaminal tracts correlated with the registration/learning domain scores. In addition, the fiber density values of cerebello-frontal and subthalamo-cerebellar (Crus II) tracts correlated with the cognitive assessment scores from the memory domain. Conclusion We validated the structural connectivity within the cerebellum-basal ganglia reciprocal network, in a larger dataset of human subjects, across wider age range. The structural features of the subcortical cerebello-basal ganglia tracts in human subjects display age-related neurodegeneration. Individual morphological variability of cerebellar tracts to the striatum and prefrontal cortex was associated with different cognitive functions, suggesting a functional contribution of cerebellar tracts to cognitive decline with aging. This study offers new perspectives to consider the functional role of these pathways in motor learning and the pathophysiology of movement disorders involving the cerebellum and striatum.
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Affiliation(s)
- Vineeth Radhakrishnan
- Comprehensive Care Centre for Movement Disorders, Department of Neurology, Sree Chitra Tirunal Institute of Medical Sciences and Technology, Thiruvananthapuram, India
| | - Cecile Gallea
- INSERM, CNRS, Paris Brain Institute, Sorbonne Université, Paris, France
| | - Romain Valabregue
- INSERM, CNRS, Paris Brain Institute, Sorbonne Université, Paris, France
| | - Syam Krishnan
- Comprehensive Care Centre for Movement Disorders, Department of Neurology, Sree Chitra Tirunal Institute of Medical Sciences and Technology, Thiruvananthapuram, India
| | - Chandrasekharan Kesavadas
- Department of Imaging Sciences and Interventional Radiology, Sree Chitra Tirunal Institute of Medical Sciences and Technology, Thiruvananthapuram, India
| | - Bejoy Thomas
- Department of Imaging Sciences and Interventional Radiology, Sree Chitra Tirunal Institute of Medical Sciences and Technology, Thiruvananthapuram, India
| | - Praveen James
- Comprehensive Care Centre for Movement Disorders, Department of Neurology, Sree Chitra Tirunal Institute of Medical Sciences and Technology, Thiruvananthapuram, India
| | - Ramshekhar Menon
- Department of Neurology, Sree Chitra Tirunal Institute for Medical Sciences and Technology, Thiruvananthapuram, India
| | - Asha Kishore
- Comprehensive Care Centre for Movement Disorders, Department of Neurology, Sree Chitra Tirunal Institute of Medical Sciences and Technology, Thiruvananthapuram, India,Parkinson and Movement Disorder Centre, Department of Neurology, Aster Medcity, Kochi, India,*Correspondence: Asha Kishore, ✉
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13
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Robertson JW, Aristi G, Hashmi JA. White matter microstructure predicts measures of clinical symptoms in chronic back pain patients. Neuroimage Clin 2023; 37:103309. [PMID: 36621020 PMCID: PMC9850203 DOI: 10.1016/j.nicl.2022.103309] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2022] [Revised: 11/30/2022] [Accepted: 12/26/2022] [Indexed: 12/28/2022]
Abstract
Chronic back pain (CBP) has extensive clinical and social implications for its sufferers and is a major source of disability. Chronic pain has previously been shown to have central neural factors underpinning it, including the loss of white matter (WM), however traditional methods of analyzing WM microstructure have produced mixed and unclear results. To better understand these factors, we assessed the WM microstructure of 50 patients and 40 healthy controls (HC) using diffusion-weighted imaging. The data were analyzed using fixel-based analysis (FBA), a higher-order diffusion modelling technique applied to CBP for the first time here. Subjects also answered questionnaires relating to pain, disability, catastrophizing, and mood disorders, to establish the relationship between fixelwise metrics and clinical symptoms. FBA determined that, compared to HC, CBP patients had: 1) lower fibre density (FD) in several tracts, specifically the right anterior and bilateral superior thalamic radiations, right spinothalamic tract, right middle cerebellar peduncle, and the body and splenium of corpus callosum; 2) higher FD in the genu of corpus callosum; and 3) lower FDC - a combined fibre density and cross-section measure - in the bilateral spinothalamic tracts and right anterior thalamic radiation. Exploratory correlations showed strong negative relationships between fixelwise metrics and clinical questionnaire scores, especially pain catastrophizing. These results have important implications for the intake and processing of sensory data in CBP that warrant further investigation.
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Affiliation(s)
- Jason W Robertson
- Department of Anesthesia, Pain Management and Perioperative Medicine, Dalhousie University, 1276 South Park St., Halifax, Nova Scotia B3H 2Y9, Canada; Nova Scotia Health Authority, 1276 South Park St., Halifax, Nova Scotia B3H 2Y9, Canada.
| | - Guillermo Aristi
- Department of Anesthesia, Pain Management and Perioperative Medicine, Dalhousie University, 1276 South Park St., Halifax, Nova Scotia B3H 2Y9, Canada; Nova Scotia Health Authority, 1276 South Park St., Halifax, Nova Scotia B3H 2Y9, Canada
| | - Javeria A Hashmi
- Department of Anesthesia, Pain Management and Perioperative Medicine, Dalhousie University, 1276 South Park St., Halifax, Nova Scotia B3H 2Y9, Canada; Nova Scotia Health Authority, 1276 South Park St., Halifax, Nova Scotia B3H 2Y9, Canada.
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14
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Singh M, Skippen P, He J, Thomson P, Fuelscher I, Caeyenberghs K, Anderson V, Nicholson JM, Hyde C, Silk TJ. Longitudinal developmental trajectories of inhibition and white-matter maturation of the fronto-basal-ganglia circuits. Dev Cogn Neurosci 2022; 58:101171. [PMID: 36372005 PMCID: PMC9660590 DOI: 10.1016/j.dcn.2022.101171] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2022] [Revised: 10/06/2022] [Accepted: 10/29/2022] [Indexed: 01/13/2023] Open
Abstract
Response inhibition refers to the cancelling of planned (or restraining of ongoing) actions and is required in much of our everyday life. Response inhibition appears to improve dramatically in early development and plateau in adolescence. The fronto-basal-ganglia network has long been shown to predict individual differences in the ability to enact response inhibition. In the current study, we examined whether developmental trajectories of fiber-specific white matter properties of the fronto-basal-ganglia network was predictive of parallel developmental trajectories of response inhibition. 138 children aged 9-14 completed the stop-signal task (SST). A subsample of 73 children underwent high-angular resolution diffusion MRI data for up to three time points. Performance on the SST was assessed using a parametric race modelling approach. White matter organization of the fronto-basal-ganglia circuit was estimated using fixel-based analysis. Contrary to predictions, we did not find any significant associations between maturational trajectories of fronto-basal-ganglia white matter and developmental improvements in SST performance. Findings suggest that the development of white matter organization of the fronto-basal-ganglia and development of stopping performance follow distinct maturational trajectories.
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Affiliation(s)
- Mervyn Singh
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Geelong, Victoria, Australia; Centre for Social and Early Emotional Development, Deakin University, Geelong, Victoria, Australia.
| | - Patrick Skippen
- Neuroscience Research Australia, Randwick, NSW 2031, Australia
| | - Jason He
- Department of Forensic and Neurodevelopmental Sciences, Sackler Institute for Translational Neurodevelopment, Institute of Psychiatry, Psychology, and Neuroscience, King's College London, London, UK
| | - Phoebe Thomson
- Developmental Imaging, Murdoch Children's Research Institute, Melbourne, Victoria, Australia; Department of Paediatrics, University of Melbourne, Melbourne, Victoria, Australia
| | - Ian Fuelscher
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Geelong, Victoria, Australia; Centre for Social and Early Emotional Development, Deakin University, Geelong, Victoria, Australia
| | - Karen Caeyenberghs
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Geelong, Victoria, Australia; Centre for Social and Early Emotional Development, Deakin University, Geelong, Victoria, Australia
| | - Vicki Anderson
- Developmental Imaging, Murdoch Children's Research Institute, Melbourne, Victoria, Australia; Department of Paediatrics, University of Melbourne, Melbourne, Victoria, Australia; The Royal Children's Hospital, Melbourne, Australia
| | - Jan M Nicholson
- Judith Lumley Centre, La Trobe University, Melbourne, Australia
| | - Christian Hyde
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Geelong, Victoria, Australia; Centre for Social and Early Emotional Development, Deakin University, Geelong, Victoria, Australia
| | - Timothy J Silk
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Geelong, Victoria, Australia; Centre for Social and Early Emotional Development, Deakin University, Geelong, Victoria, Australia; Developmental Imaging, Murdoch Children's Research Institute, Melbourne, Victoria, Australia
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15
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Taskin HO, Qiao Y, Sydnor VJ, Cieslak M, Haggerty EB, Satterthwaite TD, Morgan JI, Shi Y, Aguirre GK. Retinal ganglion cell endowment is correlated with optic tract fiber cross section, not density. Neuroimage 2022; 260:119495. [PMID: 35868617 PMCID: PMC10362491 DOI: 10.1016/j.neuroimage.2022.119495] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2022] [Revised: 06/27/2022] [Accepted: 07/19/2022] [Indexed: 11/30/2022] Open
Abstract
There is substantial variation between healthy individuals in the number of retinal ganglion cells (RGC) in the eye, with commensurate variation in the number of axons in the optic tracts. Fixel-based analysis of diffusion MR produces estimates of fiber density (FD) and cross section (FC). Using these fixel measurements along with retinal imaging, we asked if individual differences in RGC tissue volume are correlated with individual differences in FD and FC measurements obtained from the optic tracts, and subsequent structures along the cortical visual pathway. We find that RGC endowment is correlated with optic tract FC, but not with FD. RGC volume had a decreasing relationship with measurements from subsequent regions of the visual system (LGN volume, optic radiation FC/FD, and V1 surface area). However, we also found that the variations in each visual area were correlated with the variations in its immediately adjacent visual structure. We only observed these serial correlations when FC is used as the measure of interest for the optic tract and radiations, but no significant relationship was found when FD represented these white matter structures. From these results, we conclude that the variations in RGC endowment, LGN volume, and V1 surface area are better predicted by the overall cross section of the optic tract and optic radiations as compared to the intra-axonal restricted signal component of these white matter pathways. Additionally, the presence of significant correlations between adjacent, but not distant, anatomical structures suggests that there are multiple, local sources of anatomical variation along the visual pathway.
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Affiliation(s)
- Huseyin O Taskin
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104
| | - Yuchuan Qiao
- Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033
| | - Valerie J Sydnor
- Biomedical Graduate Studies, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104
| | - Matthew Cieslak
- Department of Neuropsychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104
| | - Edda B Haggerty
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104
| | - Theodore D Satterthwaite
- Department of Psychiatry, Penn Lifespan Informatics and Neuroimaging Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104
| | - Jessica Iw Morgan
- Department of Ophthalmology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104
| | - Yonggang Shi
- Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033
| | - Geoffrey K Aguirre
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104.
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16
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Wang J, Wen C, Li J, Chen J, Feng Y. Automated quantification of brain connectivity in Alzheimer's disease using ClusterMetric. Neurosci Lett 2022; 785:136724. [PMID: 35697157 DOI: 10.1016/j.neulet.2022.136724] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2022] [Revised: 04/26/2022] [Accepted: 06/08/2022] [Indexed: 11/18/2022]
Abstract
Diffusion magnetic resonance imaging tractography allows investigating brain structural connections in a noninvasive way and has been widely used for understanding neurological disease. Quantification of brain connectivity along with its length by dividing a fiber bundle into multiple segments (node) is a powerful approach to assess biological properties, which is termed as tractometry. However, current tractometry methods face challenges in node identification along with the length of complex bundles whose morphology is difficult to summarize. In addition, the anatomic measure reflecting the macroscopic fiber cross-section has not been followed in previous tractometry. In this paper, we propose an automated fiber bundle quantification, which we refer to as ClusterMetric. The ClusterMetric uses a data-driven approach to identify fiber clusters corresponding to subdivisions of the white matter anatomy and identify consistent space nodes along the length of clusters across individuals. The proposed method is demonstrated by applicating to our collected dataset including 23 Alzheimer's disease (AD) patients and 22 healthy controls (HCs) and a public dataset of ADNI including 53 AD patients and 85 HCs. The altered white matter tracts in AD group are observed using both datasets, which involve several major fiber tracts including the corpus callosum, corona-radiata-frontal, arcuate fasciculus, inferior occipito-frontal fasciculus, uncinate fasciculus, thalamo-frontal, superior longitudinal fasciculus, inferior cerebellar peduncle, cingulum bundle, and extreme capsule. These fiber clusters represent the white matter connections that could be most affected in AD, suggesting the ability of our method in identifying potential abnormalities specific to local regions within a fiber cluster.
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Affiliation(s)
- Jingqiang Wang
- Institution of Information Processing and Automation, College of Information Engineering, Zhejiang University of Technology, Hangzhou, China
| | - Caiyun Wen
- The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Jinwen Li
- Institution of Information Processing and Automation, College of Information Engineering, Zhejiang University of Technology, Hangzhou, China
| | | | - Yuanjing Feng
- Institution of Information Processing and Automation, College of Information Engineering, Zhejiang University of Technology, Hangzhou, China.
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17
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Andica C, Kamagata K, Uchida W, Takabayashi K, Shimoji K, Kaga H, Someya Y, Tamura Y, Kawamori R, Watada H, Hori M, Aoki S. White matter fiber-specific degeneration in older adults with metabolic syndrome. Mol Metab 2022; 62:101527. [PMID: 35691528 PMCID: PMC9234232 DOI: 10.1016/j.molmet.2022.101527] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/28/2022] [Revised: 06/05/2022] [Accepted: 06/06/2022] [Indexed: 11/16/2022] Open
Abstract
OBJECTIVE Metabolic syndrome (MetS) is defined as a complex of interrelated risk factors for type 2 diabetes and cardiovascular disease, including glucose intolerance, abdominal obesity, hypertension, and dyslipidemia. Studies using diffusion tensor imaging (DTI) have reported white matter (WM) microstructural abnormalities in MetS. However, interpretation of DTI metrics is limited primarily due to the challenges of modeling complex WM structures. The present study used fixel-based analysis (FBA) to assess the effect of MetS on the fiber tract-specific WM microstructure in older adults and its relationship with MetS-related measurements and cognitive and locomotor functions to better understand the pathophysiology of MetS. METHODS Fixel-based metrics, including microstructural fiber density (FD), macrostructural fiber-bundle cross-section (FC), and a combination of FD and FC (FDC), were evaluated in 16 healthy controls (no components of MetS; four men; mean age, 71.31 ± 5.06 years), 57 individuals with premetabolic syndrome (preMetS; one or two components of MetS; 29 men; mean age, 72.44 ± 5.82 years), and 46 individuals with MetS (three to five components of MetS; 27 men; mean age, 72.15 ± 4.97 years) using whole-brain exploratory FBA. Tract of interest (TOI) analysis was then performed using TractSeg across 14 selected WM tracts previously associated with MetS. The associations between fixel-based metrics and MetS-related measurements, neuropsychological, and locomotor function tests were also analyzed in individuals with preMetS and MetS combined. In addition, tensor-based metrics (i.e., fractional anisotropy [FA] and mean diffusivity [MD]) were compared among the groups using tract-based spatial statistics (TBSS) analysis. RESULTS In whole-brain FBA, individuals with MetS showed significantly lower FD, FC, and FDC compared with healthy controls in WM areas, such as the splenium of the corpus callosum (CC), corticospinal tract (CST), middle cerebellar peduncle (MCP), and superior cerebellar peduncle (SCP). Meanwhile, in fixel-based TOI, significantly reduced FD was observed in individuals with preMetS and MetS in the anterior thalamic radiation, CST, SCP, and splenium of the CC compared with healthy controls, with relatively greater effect sizes observed in individuals with MetS. Compared with healthy controls, significantly reduced FC and FDC were only demonstrated in individuals with MetS, including regions with loss of FD, inferior cerebellar peduncle, inferior fronto-occipital fasciculus, MCP, and superior longitudinal fasciculus part I. Furthermore, negative correlations were observed between FD and Brinkman index of cigarette consumption cumulative amount and between FC or FDC and the Trail Making Test (parts B-A), which is a measure of executive function, waist circumference, or low-density lipoprotein cholesterol. Finally, TBSS analysis revealed that FA and MD were not significantly different among all groups. CONCLUSIONS The FBA results demonstrate that substantial axonal loss and atrophy in individuals with MetS and early axonal loss without fiber-bundle morphological changes in those with preMetS within the WM tracts are crucial to cognitive and motor function. FBA also clarified the association between executive dysfunction, abdominal obesity, hyper-low-density lipoprotein cholesterolemia, smoking habit, and compromised WM neural tissue microstructure in MetS.
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Affiliation(s)
- Christina Andica
- Faculty of Health Data Science, Juntendo University, Urayasu, Chiba, 279-0013, Japan; Department of Radiology, Juntendo University Graduate School of Medicine, Bunkyo, Tokyo, 113-8421, Japan.
| | - Koji Kamagata
- Department of Radiology, Juntendo University Graduate School of Medicine, Bunkyo, Tokyo, 113-8421, Japan
| | - Wataru Uchida
- Department of Radiology, Juntendo University Graduate School of Medicine, Bunkyo, Tokyo, 113-8421, Japan
| | - Kaito Takabayashi
- Department of Radiology, Juntendo University Graduate School of Medicine, Bunkyo, Tokyo, 113-8421, Japan
| | - Keigo Shimoji
- Department of Radiology, Juntendo University Graduate School of Medicine, Bunkyo, Tokyo, 113-8421, Japan
| | - Hideyoshi Kaga
- Sportology Center, Juntendo University Graduate School of Medicine, Bunkyo, Tokyo, 113-0034, Japan; Department of Metabolism & Endocrinology, Juntendo University Graduate School of Medicine, Bunkyo, Tokyo, 113-8421, Japan
| | - Yuki Someya
- Sportology Center, Juntendo University Graduate School of Medicine, Bunkyo, Tokyo, 113-0034, Japan
| | - Yoshifumi Tamura
- Sportology Center, Juntendo University Graduate School of Medicine, Bunkyo, Tokyo, 113-0034, Japan; Department of Metabolism & Endocrinology, Juntendo University Graduate School of Medicine, Bunkyo, Tokyo, 113-8421, Japan
| | - Ryuzo Kawamori
- Sportology Center, Juntendo University Graduate School of Medicine, Bunkyo, Tokyo, 113-0034, Japan; Department of Metabolism & Endocrinology, Juntendo University Graduate School of Medicine, Bunkyo, Tokyo, 113-8421, Japan
| | - Hirotaka Watada
- Sportology Center, Juntendo University Graduate School of Medicine, Bunkyo, Tokyo, 113-0034, Japan; Department of Metabolism & Endocrinology, Juntendo University Graduate School of Medicine, Bunkyo, Tokyo, 113-8421, Japan
| | - Masaaki Hori
- Department of Radiology, Juntendo University Graduate School of Medicine, Bunkyo, Tokyo, 113-8421, Japan; Department of Radiology, Toho University Omori Medical Center, Ota, Tokyo, 143-8541, Japan
| | - Shigeki Aoki
- Department of Radiology, Juntendo University Graduate School of Medicine, Bunkyo, Tokyo, 113-8421, Japan
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18
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Jünemann K, Marie D, Worschech F, Scholz DS, Grouiller F, Kliegel M, Van De Ville D, James CE, Krüger THC, Altenmüller E, Sinke C. Six Months of Piano Training in Healthy Elderly Stabilizes White Matter Microstructure in the Fornix, Compared to an Active Control Group. Front Aging Neurosci 2022; 14:817889. [PMID: 35242025 PMCID: PMC8886041 DOI: 10.3389/fnagi.2022.817889] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2021] [Accepted: 01/06/2022] [Indexed: 12/31/2022] Open
Abstract
While aging is characterized by neurodegeneration, musical training is associated with experience-driven brain plasticity and protection against age-related cognitive decline. However, evidence for the positive effects of musical training mostly comes from cross-sectional studies while randomized controlled trials with larger sample sizes are rare. The current study compares the influence of six months of piano training with music listening/musical culture lessons in 121 musically naïve healthy elderly individuals with regard to white matter properties using fixel-based analysis. Analyses revealed a significant fiber density decline in the music listening/musical culture group (but not in the piano group), after six months, in the fornix, which is a white matter tract that naturally declines with age. In addition, these changes in fiber density positively correlated to episodic memory task performances and the amount of weekly piano training. These findings not only provide further evidence for the involvement of the fornix in episodic memory encoding but also more importantly show that learning to play the piano at an advanced age may stabilize white matter microstructure of the fornix.
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Affiliation(s)
- Kristin Jünemann
- Division of Clinical Psychology & Sexual Medicine, Department of Psychiatry, Social Psychiatry and Psychotherapy, Hanover Medical School, Hanover, Germany.,Center for Systems Neuroscience, Hanover, Germany
| | - Damien Marie
- Geneva Musical Minds Lab, Geneva School of Health Sciences, University of Applied Sciences and Arts Western Switzerland, Geneva, Switzerland.,Faculty of Psychology and Educational Sciences, University of Geneva, Geneva, Switzerland
| | - Florian Worschech
- Center for Systems Neuroscience, Hanover, Germany.,Institute of Music Physiology and Musicians' Medicine, Hanover University of Music, Drama and Media, Hanover, Germany
| | - Daniel S Scholz
- Center for Systems Neuroscience, Hanover, Germany.,Institute of Music Physiology and Musicians' Medicine, Hanover University of Music, Drama and Media, Hanover, Germany
| | - Frédéric Grouiller
- Swiss Center for Affective Sciences, University of Geneva, Geneva, Switzerland
| | - Matthias Kliegel
- Faculty of Psychology and Educational Sciences, University of Geneva, Geneva, Switzerland.,Center for the Interdisciplinary Study of Gerontology and Vulnerability, University of Geneva, Geneva, Switzerland
| | - Dimitri Van De Ville
- Ecole Polytechnique Fédérale de Lausanne, Campus Biotech, Geneva, Switzerland.,Faculty of Medicine, University of Geneva, Campus Biotech, Geneva, Switzerland
| | - Clara E James
- Geneva Musical Minds Lab, Geneva School of Health Sciences, University of Applied Sciences and Arts Western Switzerland, Geneva, Switzerland.,Faculty of Psychology and Educational Sciences, University of Geneva, Geneva, Switzerland
| | - Tillmann H C Krüger
- Division of Clinical Psychology & Sexual Medicine, Department of Psychiatry, Social Psychiatry and Psychotherapy, Hanover Medical School, Hanover, Germany.,Center for Systems Neuroscience, Hanover, Germany
| | - Eckart Altenmüller
- Center for Systems Neuroscience, Hanover, Germany.,Institute of Music Physiology and Musicians' Medicine, Hanover University of Music, Drama and Media, Hanover, Germany
| | - Christopher Sinke
- Division of Clinical Psychology & Sexual Medicine, Department of Psychiatry, Social Psychiatry and Psychotherapy, Hanover Medical School, Hanover, Germany
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Guo Y, Yang X, Yuan Z, Qiu J, Lu W. A comparison between diffusion tensor imaging and generalized q-sampling imaging in the age prediction of healthy adults via machine learning approaches. J Neural Eng 2022; 19. [PMID: 35038689 DOI: 10.1088/1741-2552/ac4bfe] [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: 08/10/2021] [Accepted: 01/17/2022] [Indexed: 11/12/2022]
Abstract
OBJECTIVE Brain age, which is predicted using neuroimaging data, has become an important biomarker in aging research. This study applied diffusion tensor imaging (DTI) and generalized q-sampling imaging (GQI) model to predict age respectively, with the purpose of evaluating which diffusion model is more accurate in estimating age and revealing age-related changes in the brain. APPROACH Diffusion MRI data of 125 subjects from two sites were collected. Fractional anisotropy (FA) and quantitative anisotropy (QA) from the two diffusion models were calculated and were used as features of machine learning models. Sequential backward elimination algorithm was used for feature selection. Six machine learning approaches including linear regression, ridge regression, support vector regression (SVR) with linear kernel, quadratic kernel and radial basis function (RBF) kernel and feedforward neural network were used to predict age using FA and QA features respectively. MAIN RESULTS Age predictions using FA features were more accurate than predictions using QA features for all the 6 machine learning algorithms. Post-hoc analysis revealed that FA was more sensitive to age-related white matter alterations in the brain. In addition, SVR with RBF kernel based on FA features achieved better performances than the competing algorithms with MAE ranging from 7.74 to 10.54, MSE ranging from 87.79 to 150.86, and nMSE ranging from 0.05 to 0.14 Significance: FA from DTI model was more suitable than QA from GQI model in age prediction. FA metric was more sensitive to age-related white matter changes in the brain and FA of several brain regions could be used as white matter biomarkers in aging.
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Affiliation(s)
- Yingying Guo
- Department of Radiology, Shandong First Medical University, No.619 Changcheng Road, Jinan, Shandong, 250000, CHINA
| | - Xi Yang
- Pennsylvania State University, Department of Mathematics, The Pennsylvania State University, University Park, PA, 16801, USA, State College, Pennsylvania, 16801, UNITED STATES
| | - Zilong Yuan
- Hubei Cancer Hospital, No. 116 South Zhuodaoquan Road, Wuhan, Hubei, 430079, CHINA
| | - Jianfeng Qiu
- Shandong Medical University, No. 6699 Qingdao Road, Jinan, 250100, CHINA
| | - Weizhao Lu
- Department of Radiology, Taishan Medical University, No.619 Changcheng Road, Taian, Shandong, 271016, CHINA
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20
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Finkelstein A, Faiyaz A, Weber MT, Qiu X, Uddin MN, Zhong J, Schifitto G. Fixel-Based Analysis and Free Water Corrected DTI Evaluation of HIV-Associated Neurocognitive Disorders. Front Neurol 2021; 12:725059. [PMID: 34803875 PMCID: PMC8600320 DOI: 10.3389/fneur.2021.725059] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2021] [Accepted: 10/04/2021] [Indexed: 12/12/2022] Open
Abstract
Background: White matter (WM) damage is a consistent finding in HIV-infected (HIV+) individuals. Previous studies have evaluated WM fiber tract-specific brain regions in HIV-associated neurocognitive disorders (HAND) using diffusion tensor imaging (DTI). However, DTI might lack an accurate biological interpretation, and the technique suffers from several limitations. Fixel-based analysis (FBA) and free water corrected DTI (fwcDTI) have recently emerged as useful techniques to quantify abnormalities in WM. Here, we sought to evaluate FBA and fwcDTI metrics between HIV+ and healthy controls (HIV−) individuals. Using machine learning classifiers, we compared the specificity of both FBA and fwcDTI metrics in their ability to distinguish between individuals with and without cognitive impairment in HIV+ individuals. Methods: Forty-two HIV+ and 52 HIV– participants underwent MRI exam, clinical, and neuropsychological assessments. FBA metrics included fiber density (FD), fiber bundle cross section (FC), and fiber density and cross section (FDC). We also obtained fwcDTI metrics such as fractional anisotropy (FAT) and mean diffusivity (MDT). Tract-based spatial statistics (TBSS) was performed on FAT and MDT. We evaluated the correlations between MRI metrics with cognitive performance and blood markers, such as neurofilament light chain (NfL), and Tau protein. Four different binary classifiers were used to show the specificity of the MRI metrics for classifying cognitive impairment in HIV+ individuals. Results: Whole-brain FBA showed significant reductions (up to 15%) in various fiber bundles, specifically the cerebral peduncle, posterior limb of internal capsule, middle cerebellar peduncle, and superior corona radiata. TBSS of fwcDTI metrics revealed decreased FAT in HIV+ individuals compared to HIV– individuals in areas consistent with those observed in FBA, but these were not significant. Machine learning classifiers were consistently better able to distinguish between cognitively normal patients and those with cognitive impairment when using fixel-based metrics as input features as compared to fwcDTI metrics. Conclusion: Our findings lend support that FBA may serve as a potential in vivo biomarker for evaluating and monitoring axonal degeneration in HIV+ patients at risk for neurocognitive impairment.
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Affiliation(s)
- Alan Finkelstein
- Department of Biomedical Engineering, University of Rochester, Rochester, NY, United States
| | - Abrar Faiyaz
- Department of Electrical and Computer Engineering, University of Rochester, Rochester, NY, United States
| | - Miriam T Weber
- Department of Neurology, University of Rochester, Rochester, NY, United States
| | - Xing Qiu
- Department of Biostatistics and Computational Biology, University of Rochester, Rochester, NY, United States
| | - Md Nasir Uddin
- Department of Neurology, University of Rochester, Rochester, NY, United States
| | - Jianhui Zhong
- Department of Biomedical Engineering, University of Rochester, Rochester, NY, United States.,Department of Physics and Astronomy, University of Rochester, Rochester, NY, United States.,Department of Imaging Sciences, University of Rochester, Rochester, NY, United States
| | - Giovanni Schifitto
- Department of Electrical and Computer Engineering, University of Rochester, Rochester, NY, United States.,Department of Neurology, University of Rochester, Rochester, NY, United States.,Department of Imaging Sciences, University of Rochester, Rochester, NY, United States
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21
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Watanabe H, Bagarinao E, Maesawa S, Hara K, Kawabata K, Ogura A, Ohdake R, Shima S, Mizutani Y, Ueda A, Ito M, Katsuno M, Sobue G. Characteristics of Neural Network Changes in Normal Aging and Early Dementia. Front Aging Neurosci 2021; 13:747359. [PMID: 34880745 PMCID: PMC8646086 DOI: 10.3389/fnagi.2021.747359] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2021] [Accepted: 10/18/2021] [Indexed: 12/03/2022] Open
Abstract
To understand the mechanisms underlying preserved and impaired cognitive function in healthy aging and dementia, respectively, the spatial relationships of brain networks and mechanisms of their resilience should be understood. The hub regions of the brain, such as the multisensory integration and default mode networks, are critical for within- and between-network communication, remain well-preserved during aging, and play an essential role in compensatory processes. On the other hand, these brain hubs are the preferred sites for lesions in neurodegenerative dementias, such as Alzheimer's disease. Disrupted primary information processing networks, such as the auditory, visual, and sensorimotor networks, may lead to overactivity of the multisensory integration networks and accumulation of pathological proteins that cause dementia. At the cellular level, the brain hub regions contain many synapses and require a large amount of energy. These regions are rich in ATP-related gene expression and had high glucose metabolism as demonstrated on positron emission tomography (PET). Importantly, the number and function of mitochondria, which are the center of ATP production, decline by about 8% every 10 years. Dementia patients often have dysfunction of the ubiquitin-proteasome and autophagy-lysosome systems, which require large amounts of ATP. If there is low energy supply but the demand is high, the risk of disease can be high. Imbalance between energy supply and demand may cause accumulation of pathological proteins and play an important role in the development of dementia. This energy imbalance may explain why brain hub regions are vulnerable to damage in different dementias. Here, we review (1) the characteristics of gray matter network, white matter network, and resting state functional network changes related to resilience in healthy aging, (2) the mode of resting state functional network disruption in neurodegenerative dementia, and (3) the cellular mechanisms associated with the disruption.
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Affiliation(s)
- Hirohisa Watanabe
- Department of Neurology, Fujita Health University, Toyoake, Japan
- Brain and Mind Research Center, Nagoya University, Nagoya, Japan
| | - Epifanio Bagarinao
- Brain and Mind Research Center, Nagoya University, Nagoya, Japan
- Department of Integrated Health Sciences, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Satoshi Maesawa
- Brain and Mind Research Center, Nagoya University, Nagoya, Japan
- Department of Neurosurgery, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Kazuhiro Hara
- Department of Neurology, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Kazuya Kawabata
- Department of Neurology, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Aya Ogura
- Department of Neurology, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Reiko Ohdake
- Department of Neurology, Fujita Health University, Toyoake, Japan
- Brain and Mind Research Center, Nagoya University, Nagoya, Japan
| | - Sayuri Shima
- Department of Neurology, Fujita Health University, Toyoake, Japan
| | - Yasuaki Mizutani
- Department of Neurology, Fujita Health University, Toyoake, Japan
| | - Akihiro Ueda
- Department of Neurology, Fujita Health University, Toyoake, Japan
| | - Mizuki Ito
- Department of Neurology, Fujita Health University, Toyoake, Japan
| | - Masahisa Katsuno
- Department of Neurology, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Gen Sobue
- Brain and Mind Research Center, Nagoya University, Nagoya, Japan
- Aichi Medical University, Nagakute, Japan
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22
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Ogura A, Kawabata K, Watanabe H, Choy SW, Bagarinao E, Kato T, Imai K, Masuda M, Ohdake R, Hara K, Nakamura R, Atsuta N, Nakamura T, Katsuno M, Sobue G. Fiber-specific white matter analysis reflects upper motor neuron impairment in amyotrophic lateral sclerosis. Eur J Neurol 2021; 29:432-440. [PMID: 34632672 DOI: 10.1111/ene.15136] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2021] [Accepted: 09/30/2021] [Indexed: 11/28/2022]
Abstract
BACKGROUND AND PURPOSE To clarify the relationship between fiber-specific white matter changes in amyotrophic lateral sclerosis (ALS) and clinical signs of upper motor neuron (UMN) involvement, we performed a fixel-based analysis (FBA), a novel framework for diffusion-weighted imaging analysis. METHODS We enrolled 96 participants, including 48 nonfamilial ALS patients and 48 age- and sex-matched healthy controls (HCs), in this study and conducted whole-brain FBA and voxel-based morphometry analysis. We compared the fiber density (FD), fiber morphology (fiber cross-section [FC]), and a combined index of FD and FC (FDC) between the ALS and HC groups. We performed a tract-of-interest analysis to extract FD values across the significant regions in the whole-brain analysis. Then, we evaluated the associations between FD values and clinical variables. RESULTS The bilateral corticospinal tracts (CSTs) and the corpus callosum (CC) showed reduced FD and FDC in ALS patients compared with HCs (p < 0.05, familywise error-corrected), and the comparison of FCs revealed no region that was significantly different from another. Voxel-based morphometry showed cortical volume reduction in the regions, including the primary motor area. Clinical scores showed correlations with FD values in the CSTs (UMN score: rho = -0.530, p < 0.001; central motor conduction time [CMCT] in the upper limb: rho = -0.474, p = 0.008; disease duration: rho = -0.383, p = 0.007; ALS Functional Rating Scale-Revised: rho = 0.340, p = 0.018). In addition, patients whose CMCT was not calculated due to unevoked waves also showed FD reduction in the CSTs. CONCLUSIONS Our findings suggest that FD values in the CST estimated via FBA can be potentially used in evaluating UMN impairments.
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Affiliation(s)
- Aya Ogura
- Department of Neurology, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Kazuya Kawabata
- Department of Neurology, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Hirohisa Watanabe
- Brain and Mind Research Center, Nagoya University, Nagoya, Japan.,Department of Neurology, School of Medicine, Fujita Health University, Toyoake, Japan
| | - Shao Wei Choy
- Center for Intelligent Signal and Imaging Research, Universiti Teknologi PETRONAS, Seri Iskandar, Malaysia
| | - Epifanio Bagarinao
- Brain and Mind Research Center, Nagoya University, Nagoya, Japan.,Department of Integrated Health Sciences, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Toshiyasu Kato
- Department of Neurology, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Kazunori Imai
- Department of Neurology, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Michihito Masuda
- Department of Neurology, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Reiko Ohdake
- Brain and Mind Research Center, Nagoya University, Nagoya, Japan
| | - Kazuhiro Hara
- Department of Neurology, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Ryoichi Nakamura
- Department of Neurology, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Naoki Atsuta
- Department of Neurology, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Tomohiko Nakamura
- Department of Neurology, Nagoya University Graduate School of Medicine, Nagoya, Japan.,Department of Laboratory Medicine, Nagoya University Hospital, Nagoya, Japan
| | - Masahisa Katsuno
- Department of Neurology, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Gen Sobue
- Brain and Mind Research Center, Nagoya University, Nagoya, Japan.,Research Division of Dementia and Neurodegenerative Disease, Nagoya University Graduate School of Medicine, Nagoya, Japan.,Aichi Medical University, Nagakute, Japan
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23
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van Aalst J, Devrome M, Van Weehaeghe D, Rezaei A, Radwan A, Schramm G, Ceccarini J, Sunaert S, Koole M, Van Laere K. Regional glucose metabolic decreases with ageing are associated with microstructural white matter changes: a simultaneous PET/MR study. Eur J Nucl Med Mol Imaging 2021; 49:664-680. [PMID: 34398271 DOI: 10.1007/s00259-021-05518-6] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2021] [Accepted: 08/02/2021] [Indexed: 12/22/2022]
Abstract
PURPOSE Human ageing is associated with a regional reduction in cerebral neuronal activity as assessed by numerous studies on brain glucose metabolism and perfusion, grey matter (GM) density and white matter (WM) integrity. As glucose metabolism may impact energetics to maintain myelin integrity, but changes in functional connectivity may also alter regional metabolism, we conducted a cross-sectional simultaneous FDG PET/MR study in a large cohort of healthy volunteers with a wide age range, to directly assess the underlying associations between reduced glucose metabolism, GM atrophy and decreased WM integrity in a single ageing cohort. METHODS In 94 healthy subjects between 19.9 and 82.5 years (mean 50.1 ± 17.1; 47 M/47F, MMSE ≥ 28), simultaneous FDG-PET, structural MR and diffusion tensor imaging (DTI) were performed. Voxel-wise associations between age and grey matter (GM) density, RBV partial-volume corrected (PVC) glucose metabolism, white matter (WM) fractional anisotropy (FA) and mean diffusivity (MD), and age were assessed. Clusters representing changes in glucose metabolism correlating significantly with ageing were used as seed regions for tractography. Both linear and quadratic ageing models were investigated. RESULTS An expected age-related reduction in GM density was observed bilaterally in the frontal, lateral and medial temporal cortex, striatum and cerebellum. After PVC, relative FDG uptake was negatively correlated with age in the inferior and midfrontal, cingulate and parietal cortex and subcortical regions, bilaterally. FA decreased with age throughout the entire brain WM. Four white matter tracts were identified connecting brain regions with declining glucose metabolism with age. Within these, relative FDG uptake in both origin and target clusters correlated positively with FA (0.32 ≤ r ≤ 0.71) and negatively with MD (- 0.75 ≤ r ≤ - 0.41). CONCLUSION After appropriate PVC, we demonstrated that regional cerebral glucose metabolic declines with age and that these changes are related to microstructural changes in the interconnecting WM tracts. The temporal course and potential causality between ageing effects on glucose metabolism and WM integrity should be further investigated in longitudinal cohort PET/MR studies.
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Affiliation(s)
- June van Aalst
- Nuclear Medicine and Molecular Imaging, Department of Imaging and Pathology, KU Leuven, Leuven, Belgium
| | - Martijn Devrome
- Nuclear Medicine and Molecular Imaging, Department of Imaging and Pathology, KU Leuven, Leuven, Belgium
| | - Donatienne Van Weehaeghe
- Nuclear Medicine and Molecular Imaging, Department of Imaging and Pathology, KU Leuven, Leuven, Belgium
- Division of Nuclear Medicine, University Hospitals Leuven, Leuven, Belgium
| | - Ahmadreza Rezaei
- Nuclear Medicine and Molecular Imaging, Department of Imaging and Pathology, KU Leuven, Leuven, Belgium
| | - Ahmed Radwan
- Translational MRI, Department of Imaging and Pathology, KU Leuven, Leuven, Belgium
| | - Georg Schramm
- Nuclear Medicine and Molecular Imaging, Department of Imaging and Pathology, KU Leuven, Leuven, Belgium
| | - Jenny Ceccarini
- Nuclear Medicine and Molecular Imaging, Department of Imaging and Pathology, KU Leuven, Leuven, Belgium
| | - Stefan Sunaert
- Translational MRI, Department of Imaging and Pathology, KU Leuven, Leuven, Belgium
- Radiology, University Hospitals Leuven, Leuven, Belgium
| | - Michel Koole
- Nuclear Medicine and Molecular Imaging, Department of Imaging and Pathology, KU Leuven, Leuven, Belgium
| | - Koen Van Laere
- Nuclear Medicine and Molecular Imaging, Department of Imaging and Pathology, KU Leuven, Leuven, Belgium.
- Division of Nuclear Medicine, University Hospitals Leuven, Leuven, Belgium.
- UZ Leuven, Campus Gasthuisberg, Nucleaire Geneeskunde, E901, Herestraat 49, BE-3000 , Leuven, Belgium.
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24
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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: 127] [Impact Index Per Article: 31.8] [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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25
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Xiao Y, Peters TM, Khan AR. Characterizing white matter alterations subject to clinical laterality in drug-naïve de novo Parkinson's disease. Hum Brain Mapp 2021; 42:4465-4477. [PMID: 34106502 PMCID: PMC8410564 DOI: 10.1002/hbm.25558] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2021] [Revised: 05/18/2021] [Accepted: 06/01/2021] [Indexed: 01/18/2023] Open
Abstract
Parkinson's disease (PD) is a progressive neurodegenerative disorder that is characterized by a range of motor and nonmotor symptoms, often with the motor dysfunction initiated unilaterally. Knowledge regarding disease‐related alterations in white matter pathways can effectively help improve the understanding of the disease and propose targeted treatment strategies. Microstructural imaging techniques, including diffusion tensor imaging (DTI), allows inspection of white matter integrity to study the pathogenesis of various neurological conditions. Previous voxel‐based analyses with DTI measures, such as fractional anisotropy and mean diffusivity have uncovered changes in brain regions that are associated with PD, but the conclusions were inconsistent, partially due to small patient cohorts and the lack of consideration for clinical laterality onset, particularly in early PD. Fixel‐based analysis (FBA) is a recent framework that offers tract‐specific insights regarding white matter health, but very few FBA studies on PD exist. We present a study that reveals strengthened and weakened white matter integrity that is subject to symptom laterality in a large drug‐naïve de novo PD cohort using complementary DTI and FBA measures. The findings suggest that the disease gives rise to tissue degeneration and potential re‐organization in the early stage.
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Affiliation(s)
- Yiming Xiao
- Department of Computer Science and Software Engineering, Concordia University, Montreal, Canada.,PERFORM Centre, Concordia University, Montreal, Canada
| | - Terry M Peters
- Imaging Research Laboratories, Robarts Research Institute, Western University, London, Canada.,Department of Medical Biophysics, Schulich School of Medicine and Dentistry, Western University, London, Canada.,School of Biomedical Engineering, Western University, London, Canada
| | - Ali R Khan
- Imaging Research Laboratories, Robarts Research Institute, Western University, London, Canada.,Department of Medical Biophysics, Schulich School of Medicine and Dentistry, Western University, London, Canada.,School of Biomedical Engineering, Western University, London, Canada.,The Brain and Mind Institute, Western University, London, Canada
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26
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Hédouin R, Metere R, Chan KS, Licht C, Mollink J, van Walsum AMC, Marques JP. Decoding the microstructural properties of white matter using realistic models. Neuroimage 2021; 237:118138. [PMID: 33964461 DOI: 10.1016/j.neuroimage.2021.118138] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2020] [Revised: 04/14/2021] [Accepted: 04/19/2021] [Indexed: 11/24/2022] Open
Abstract
Multi-echo gradient echo (ME-GRE) magnetic resonance signal evolution in white matter has a strong dependence on the orientation of myelinated axons with respect to the main static field. Although analytical solutions have been able to predict some of the white matter (WM) signal behaviour of the hollow cylinder model, it has been shown that realistic models of WM offer a better description of the signal behaviour observed. In this work, we present a pipeline to (i) generate realistic 2D WM models with their microstructure based on real axon morphology with adjustable fiber volume fraction (FVF) and g-ratio. We (ii) simulate their interaction with the static magnetic field to be able to simulate their MR signal. For the first time, we (iii) demonstrate that realistic 2D WM models can be used to simulate a MR signal that provides a good approximation of the signal obtained from a real 3D WM model derived from electron microscopy. We then (iv) demonstrate in silico that 2D WM models can be used to predict microstructural parameters in a robust way if ME-GRE multi-orientation data is available and the main fiber orientation in each pixel is known using DTI. A deep learning network was trained and characterized in its ability to recover the desired microstructural parameters such as FVF, g-ratio, free and bound water transverse relaxation and magnetic susceptibility. Finally, the network was trained to recover these micro-structural parameters from an ex vivo dataset acquired in 9 orientations with respect to the magnetic field and 12 echo times. We demonstrate that this is an overdetermined problem and that as few as 3 orientations can already provide comparable results for some of the decoded metrics.
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Affiliation(s)
- Renaud Hédouin
- Radboud University, Donders Institute for Brain, Cognition and Behaviour, Nijmegen, Netherlands; Empenn, INRIA, INSERM, CNRS, Université de Rennes 1, Rennes, France.
| | - Riccardo Metere
- Radboud University, Donders Institute for Brain, Cognition and Behaviour, Nijmegen, Netherlands
| | - Kwok-Shing Chan
- Radboud University, Donders Institute for Brain, Cognition and Behaviour, Nijmegen, Netherlands
| | - Christian Licht
- Computer Assisted Clinical Medicine, Medical Faculty Mannheim, Heidelberg University, Germany
| | - Jeroen Mollink
- Radboud University Medical Centre, Medical Imaging and Anatomy, Nijmegen, Netherlands
| | | | - José P Marques
- Radboud University, Donders Institute for Brain, Cognition and Behaviour, Nijmegen, Netherlands
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27
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Luo X, Wang S, Jiaerken Y, Li K, Zeng Q, Zhang R, Wang C, Xu X, Wu D, Huang P, Zhang M. Distinct fiber-specific white matter reductions pattern in early- and late-onset Alzheimer's disease. Aging (Albany NY) 2021; 13:12410-12430. [PMID: 33930871 PMCID: PMC8148465 DOI: 10.18632/aging.202702] [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: 10/07/2020] [Accepted: 02/08/2021] [Indexed: 01/31/2023]
Abstract
Background: The underlying white matter impairment in patients with early and late-onset Alzheimer’s disease (EOAD and LOAD) is still unclear, and this might due to the complex AD pathology. Methods: We included 31 EOAD, 45 LOAD, and 64 younger, 46 elder controls in our study to undergo MRI examinations. Fiber density (FD) and fiber bundle cross-section (FC) were measured using fixel-based analysis based on diffusion weighted images. On whole brain and tract-based level, we compared these parameters among different groups (p<0.05, FWE corrected). Moreover, we verified our results in another independent dataset using the same analyses. Results: Compared to young healthy controls, EOAD had significantly lower FD in the splenium of corpus callosum, limbic tracts, cingulum bundles, and posterior thalamic radiation, and higher FC in the splenium of corpus callosum, dorsal cingulum and posterior thalamic radiation. On the other hand, LOAD had lower FD and FC as well. Importantly, a similar pattern was found in the independent validation dataset. Among all groups, both the FD and FC were associated with cognitive function. Furthermore, FD of fornix column and body, and FC of ventral cingulum were associated with composite amyloid and tau level (r=-0.34 and -0.53, p<0.001) respectively. Conclusions: EOAD and LOAD were characterized by distinct white matter impairment patterns, which may be attributable to their different neuropathologies.
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Affiliation(s)
- Xiao Luo
- Department of Radiology, The 2nd Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Shuyue Wang
- Department of Radiology, The 2nd Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Yeerfan Jiaerken
- Department of Radiology, The 2nd Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Kaicheng Li
- Department of Radiology, The 2nd Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Qingze Zeng
- Department of Radiology, The 2nd Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Ruiting Zhang
- Department of Radiology, The 2nd Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Chao Wang
- Department of Radiology, The 2nd Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Xiaopei Xu
- Department of Radiology, The 2nd Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Dan Wu
- Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China
| | - Peiyu Huang
- Department of Radiology, The 2nd Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Minming Zhang
- Department of Radiology, The 2nd Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
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28
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Verhelst H, Dhollander T, Gerrits R, Vingerhoets G. Fibre-specific laterality of white matter in left and right language dominant people. Neuroimage 2021; 230:117812. [PMID: 33524578 DOI: 10.1016/j.neuroimage.2021.117812] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2020] [Revised: 12/23/2020] [Accepted: 01/20/2021] [Indexed: 12/13/2022] Open
Abstract
Language is the most commonly described lateralised cognitive function, relying more on the left hemisphere compared to the right hemisphere in over 90% of the population. Most research examining the structure-function relationship of language lateralisation only included people showing a left language hemisphere dominance. In this work, we applied a state-of-the-art "fixel-based" analysis approach, allowing statistical analysis of white matter micro- and macrostructure on a fibre-specific level in a sample of participants with left and right language dominance (LLD and RLD). Both groups showed a similar extensive pattern of white matter lateralisation including a comparable leftwards lateralisation of the arcuate fasciculus, regardless of their functional language lateralisation. These results suggest that lateralisation of language functioning and the arcuate fasciculus are driven by independent biases. Finally, a significant group difference of lateralisation was detected in the forceps minor, with a leftwards lateralisation in LLD and rightwards lateralisation for the RLD group.
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Affiliation(s)
- Helena Verhelst
- Department of Experimental Psychology, Ghent University, Belgium.
| | - Thijs Dhollander
- Developmental Imaging, Murdoch Children's Research Institute, Melbourne, Australia
| | - Robin Gerrits
- Department of Experimental Psychology, Ghent University, Belgium
| | - Guy Vingerhoets
- Department of Experimental Psychology, Ghent University, Belgium
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29
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Chavoshnejad P, Li X, Zhang S, Dai W, Vasung L, Liu T, Zhang T, Wang X, Razavi MJ. Role of axonal fibers in the cortical folding patterns: A tale of variability and regularity. BRAIN MULTIPHYSICS 2021. [DOI: 10.1016/j.brain.2021.100029] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022] Open
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30
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Yang FPG, Bal SS, Lee JF, Chen CC. White Matter Differences in Networks in Elders with Mild Cognitive Impairment and Alzheimer's Disease. Brain Connect 2020; 11:180-188. [PMID: 32731749 DOI: 10.1089/brain.2020.0767] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
Background: Alzheimer's disease (AD) is associated with impairment of large-scale brain networks, disruption in structural connections, and functional disconnection between distant brain regions. Although decreased functional connectivity has been thoroughly investigated and reported by existing functional neuroimaging literature, this study investigated network-based differences due to the structural changes in white matter pathways in AD patients. We hypothesize that diffusion metrics of disrupted tracts that go through cognitive networks related with intrinsic awareness, motor movement, and executive control can be utilized as biomarkers to distinguish prodromal stage from AD stage. Methods: Diffusion MRI data of a total 154 subjects, including patients with clinical AD (n = 47) and patients with mild cognitive impairment (MCI) (n = 107) was used. To study structural changes associated with white matter fiber pathways voxel-averaged diffusion metrics and fiber density metrics were calculated. Results: Study revealed that AD patients exhibit disruptions in intrahemispheric tracts and projection fiber tracts as suggested by diffusion indices. Our whole brain analysis revealed that network differences within default mode network (DMN), sensory motor network, and frontoparietal networks are associated with disruption in inferior fronto-occipital fasciculus (IFOF), corticospinal tract, and superior longitudinal fasciculus. Global function revealed by Mini Mental State Examination correlate with those fiber pathways that form reciprocal connections within networks associated with motor movement and executive control. Conclusion: Diffusion metrics appear to be more sensitive than fiber density metrics in differentiating the structural changes in the white matter. Decreased fractional anisotropy along with increased mean diffusivity and radial diffusivity in forceps minor, corticospinal tract, and IFOF as an imaging biomarker would be ideal to distinguish AD patients from MCI patients. Difference of DMN, sensory motor network, and frontal parietal network in our study reveals that AD patients may suffer from poor motor movement and degraded executive control.
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Affiliation(s)
- Fan Pei Gloria Yang
- Center for Cognition and Mind Sciences, National Tsing Hua University, Hsinchu, Taiwan
| | - Sukhdeep Singh Bal
- Department of Mathematical Sciences Liverpool, University of Liverpool, Merseyside, United Kingdom.,International Intercollegiate PhD Programme, National Tsing Hua University, Hsinchu, Taiwan
| | - Jia-Fu Lee
- Department of Psychiatry, Taipei Tzu Chi Hospital, Taipei, Taiwan
| | - Chia-Chi Chen
- Department of Early Childhood Care and Education, Kang Ning Junior College of Nursing, Taipei, Taiwan
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Choy SW, Bagarinao E, Watanabe H, Ho ETW, Maesawa S, Mori D, Hara K, Kawabata K, Yoneyama N, Ohdake R, Imai K, Masuda M, Yokoi T, Ogura A, Taoka T, Koyama S, Tanabe HC, Katsuno M, Wakabayashi T, Kuzuya M, Hoshiyama M, Isoda H, Naganawa S, Ozaki N, Sobue G. Changes in white matter fiber density and morphology across the adult lifespan: A cross-sectional fixel-based analysis. Hum Brain Mapp 2020; 41:3198-3211. [PMID: 32304267 PMCID: PMC7375080 DOI: 10.1002/hbm.25008] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2019] [Revised: 03/27/2020] [Accepted: 04/01/2020] [Indexed: 12/13/2022] Open
Abstract
White matter (WM) fiber bundles change dynamically with age. These changes could be driven by alterations in axonal diameter, axonal density, and myelin content. In this study, we applied a novel fixel‐based analysis (FBA) framework to examine these changes throughout the adult lifespan. Using diffusion‐weighted images from a cohort of 293 healthy volunteers (89 males/204 females) from ages 21 to 86 years old, we performed FBA to analyze age‐related changes in microscopic fiber density (FD) and macroscopic fiber morphology (fiber cross section [FC]). Our results showed significant and widespread age‐related alterations in FD and FC across the whole brain. Interestingly, some fiber bundles such as the anterior thalamic radiation, corpus callosum, and superior longitudinal fasciculus only showed significant negative relationship with age in FD values, but not in FC. On the other hand, some segments of the cerebello‐thalamo‐cortical pathway only showed significant negative relationship with age in FC, but not in FD. Analysis at the tract‐level also showed that major fiber tract groups predominantly distributed in the frontal lobe (cingulum, forceps minor) exhibited greater vulnerability to the aging process than the others. Differences in FC and the combined measure of FD and cross section values observed between sexes were mostly driven by differences in brain sizes although male participants tended to exhibit steeper negative linear relationship with age in FD as compared to female participants. Overall, these findings provide further insights into the structural changes the brain's WM undergoes due to the aging process.
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Affiliation(s)
- Shao Wei Choy
- Center for Intelligent Signal and Imaging Research, Universiti Teknologi Petronas, Seri Iskandar, Perak, Malaysia
| | | | - Hirohisa Watanabe
- Brain and Mind Research Center, Nagoya University, Nagoya, Aichi, Japan.,Department of Neurology, Fujita Health University School of Medicine, Toyoake, Aichi, Japan.,Department of Neurology, Nagoya University Graduate School of Medicine, Nagoya, Aichi, Japan
| | - Eric Tatt Wei Ho
- Center for Intelligent Signal and Imaging Research, Universiti Teknologi Petronas, Seri Iskandar, Perak, Malaysia
| | - Satoshi Maesawa
- Brain and Mind Research Center, Nagoya University, Nagoya, Aichi, Japan.,Department of Neurosurgery, Nagoya University Graduate School of Medicine, Nagoya, Aichi, Japan
| | - Daisuke Mori
- Brain and Mind Research Center, Nagoya University, Nagoya, Aichi, Japan
| | - Kazuhiro Hara
- Department of Neurology, Nagoya University Graduate School of Medicine, Nagoya, Aichi, Japan
| | - Kazuya Kawabata
- Department of Neurology, Nagoya University Graduate School of Medicine, Nagoya, Aichi, Japan
| | - Noritaka Yoneyama
- Department of Neurology, Nagoya University Graduate School of Medicine, Nagoya, Aichi, Japan
| | - Reiko Ohdake
- Department of Neurology, Nagoya University Graduate School of Medicine, Nagoya, Aichi, Japan
| | - Kazunori Imai
- Department of Neurology, Nagoya University Graduate School of Medicine, Nagoya, Aichi, Japan
| | - Michihito Masuda
- Department of Neurology, Nagoya University Graduate School of Medicine, Nagoya, Aichi, Japan
| | - Takamasa Yokoi
- Department of Neurology, Nagoya University Graduate School of Medicine, Nagoya, Aichi, Japan
| | - Aya Ogura
- Department of Neurology, Nagoya University Graduate School of Medicine, Nagoya, Aichi, Japan
| | - Toshiaki Taoka
- Department of Radiology, Nagoya University Graduate School of Medicine, Nagoya, Aichi, Japan
| | - Shuji Koyama
- Brain and Mind Research Center, Nagoya University, Nagoya, Aichi, Japan
| | - Hiroki C Tanabe
- Department of Cognitive and Psychological Sciences, Graduate School of Informatics, Nagoya University, Nagoya, Aichi, Japan
| | - Masahisa Katsuno
- Department of Neurology, Nagoya University Graduate School of Medicine, Nagoya, Aichi, Japan
| | - Toshihiko Wakabayashi
- Department of Neurosurgery, Nagoya University Graduate School of Medicine, Nagoya, Aichi, Japan
| | - Masafumi Kuzuya
- Department of Community Healthcare and Geriatrics, Nagoya University Graduate School of Medicine and Institute of Innovation for Future Society, Nagoya University, Nagoya, Aichi, Japan
| | - Minoru Hoshiyama
- Brain and Mind Research Center, Nagoya University, Nagoya, Aichi, Japan
| | - Haruo Isoda
- Brain and Mind Research Center, Nagoya University, Nagoya, Aichi, Japan
| | - Shinji Naganawa
- Department of Radiology, Nagoya University Graduate School of Medicine, Nagoya, Aichi, Japan
| | - Norio Ozaki
- Brain and Mind Research Center, Nagoya University, Nagoya, Aichi, Japan.,Department of Psychiatry, Nagoya University Graduate School of Medicine, Nagoya, Aichi, Japan
| | - Gen Sobue
- Brain and Mind Research Center, Nagoya University, Nagoya, Aichi, Japan
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