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Kang X, Yoon BC, Grossner E, Adamson MM. Characteristics of the Structural Connectivity in Patients with Brain Injury and Chronic Health Symptoms: A Pilot Study. Neuroinformatics 2024:10.1007/s12021-024-09681-7. [PMID: 38990502 DOI: 10.1007/s12021-024-09681-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/03/2024] [Indexed: 07/12/2024]
Abstract
Diffusion properties from diffusion tensor imaging (DTI) are exquisitely sensitive to white matter abnormalities incurred during traumatic brain injury (TBI), especially for those patients with chronic post-TBI symptoms such as headaches, dizziness, fatigue, etc. The evaluation of structural and functional connectivity using DTI has become a promising method for identifying subtle alterations in brain connectivity associated with TBI that are otherwise not visible with conventional imaging. This study assessed whether TBI patients with (n = 17) or without (n = 16) chronic symptoms (TBIcs/TBIncs) exhibit any changes in structural connectivity (SC) and mean fractional anisotropy (mFA) of intra- and inter-hemispheric connections when compared to a control group (CG) (n = 13). Reductions in SC and mFA were observed for TBIcs compared to CG, but not for TBIncs. More connections were found to have mFA reductions than SC reductions. On the whole, SC is dominated by ipsilateral connections for all the groups after the comparison of contralateral and ipsilateral connections. More contra-ipsi reductions of mFA were found for TBIcs than TBIncs compared to CG. These findings suggest that TBI patients with chronic symptoms not only demonstrate decreased global and regional mFA but also reduced structural network connectivity.
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Affiliation(s)
- Xiaojian Kang
- WRIISC-Women, VA Palo Alto Health Care System, 3801 Miranda Avenue, Palo Alto, CA, 94304, USA.
- Rehabilitation Service, VA Palo Alto Health Care System, 3801 Miranda Avenue, Palo Alto, CA, 94304, USA.
| | - Byung C Yoon
- Department of Radiology, Stanford University School of Medicine, VA Palo Alto Heath Care System, Palo Alto, CA, 94304, USA
| | - Emily Grossner
- Department of Psychology, VA Palo Alto Health Care System, 3801 Miranda Avenue, Palo Alto, CA, 94304, USA
| | - Maheen M Adamson
- WRIISC-Women, VA Palo Alto Health Care System, 3801 Miranda Avenue, Palo Alto, CA, 94304, USA
- Rehabilitation Service, VA Palo Alto Health Care System, 3801 Miranda Avenue, Palo Alto, CA, 94304, USA
- Department of Neurosurgery, Stanford University School of Medicine, 300 Pasteur Dr, Stanford, CA, 94305, USA
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Imms P, Chowdhury NF, Chaudhari NN, Amgalan A, Poudel G, Caeyenberghs K, Irimia A. Prediction of cognitive outcome after mild traumatic brain injury from acute measures of communication within brain networks. Cortex 2024; 171:397-412. [PMID: 38103453 PMCID: PMC10922490 DOI: 10.1016/j.cortex.2023.10.022] [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: 11/07/2022] [Revised: 09/04/2023] [Accepted: 10/20/2023] [Indexed: 12/19/2023]
Abstract
A considerable but ill-defined proportion of patients with mild traumatic brain injury (mTBI) experience persistent cognitive sequelae; the ability to identify such individuals early can help their neurorehabilitation. Here we tested the hypothesis that acute measures of efficient communication within brain networks are associated with patients' risk for unfavorable cognitive outcome six months after mTBI. Diffusion and T1-weighted magnetic resonance imaging, alongside cognitive measures, were obtained to map connectomes both one week and six months post injury in 113 adult patients with mTBI (71 males). For task-related brain networks, communication measures (characteristic path length, global efficiency, navigation efficiency) were moderately correlated with changes in cognition. Taking into account the covariance of age and sex, more unfavorable communication within networks were associated with worse outcomes within cognitive domains frequently impacted by mTBI (episodic and working memory, verbal fluency, inductive reasoning, and processing speed). Individuals with more unfavorable outcomes had significantly longer and less efficient pathways within networks supporting verbal fluency (all t > 2.786, p < .006), highlighting the vulnerability of language to mTBI. Participants in whom a task-related network was relatively inefficient one week post injury were up to eight times more likely to have unfavorable cognitive outcome pertaining to that task. Our findings suggest that communication measures within task-related networks identify mTBI patients who are unlikely to develop persistent cognitive deficits after mTBI. Our approach and findings can help to stratify mTBI patients according to their expected need for follow-up and/or neurorehabilitation.
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Affiliation(s)
- Phoebe Imms
- Leonard Davis School of Gerontology, University of Southern California, Los Angeles, CA USA.
| | - Nahian F Chowdhury
- Leonard Davis School of Gerontology, University of Southern California, Los Angeles, CA USA.
| | - Nikhil N Chaudhari
- Leonard Davis School of Gerontology, University of Southern California, Los Angeles, CA USA; Corwin D. Denney Research Center, Department of Biomedical Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, CA USA.
| | - Anar Amgalan
- Leonard Davis School of Gerontology, University of Southern California, Los Angeles, CA USA.
| | - Govinda Poudel
- Mary Mackillop Institute for Health Research, Australian Catholic University, Melbourne, Australia.
| | - Karen Caeyenberghs
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Melbourne Burwood Campus, Burwood, VIC, Australia.
| | - Andrei Irimia
- Leonard Davis School of Gerontology, University of Southern California, Los Angeles, CA USA; Corwin D. Denney Research Center, Department of Biomedical Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, CA USA; Department of Quantitative & Computational Biology, Dana and David Dornsife College of Arts & Sciences, University of Southern California, Los Angeles, CA USA.
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Danielli E, Simard N, DeMatteo CA, Kumbhare D, Ulmer S, Noseworthy MD. A review of brain regions and associated post-concussion symptoms. Front Neurol 2023; 14:1136367. [PMID: 37602240 PMCID: PMC10435092 DOI: 10.3389/fneur.2023.1136367] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2023] [Accepted: 07/12/2023] [Indexed: 08/22/2023] Open
Abstract
The human brain is an exceptionally complex organ that is comprised of billions of neurons. Therefore, when a traumatic event such as a concussion occurs, somatic, cognitive, behavioral, and sleep impairments are the common outcome. Each concussion is unique in the sense that the magnitude of biomechanical forces and the direction, rotation, and source of those forces are different for each concussive event. This helps to explain the unpredictable nature of post-concussion symptoms that can arise and resolve. The purpose of this narrative review is to connect the anatomical location, healthy function, and associated post-concussion symptoms of some major cerebral gray and white matter brain regions and the cerebellum. As a non-exhaustive description of post-concussion symptoms nor comprehensive inclusion of all brain regions, we have aimed to amalgamate the research performed for specific brain regions into a single article to clarify and enhance clinical and research concussion assessment. The current status of concussion diagnosis is highly subjective and primarily based on self-report of symptoms, so this review may be able to provide a connection between brain anatomy and the clinical presentation of concussions to enhance medical imaging assessments. By explaining anatomical relevance in terms of clinical concussion symptom presentation, an increased understanding of concussions may also be achieved to improve concussion recognition and diagnosis.
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Affiliation(s)
- Ethan Danielli
- School of Biomedical Engineering, McMaster University, Hamilton, ON, Canada
- Imaging Research Centre, St. Joseph's Healthcare Hamilton, Hamilton, ON, Canada
- KITE Research Institute, Toronto Rehabilitation Institute, University Health Network, Toronto, ON, Canada
| | - Nicholas Simard
- Imaging Research Centre, St. Joseph's Healthcare Hamilton, Hamilton, ON, Canada
- Department of Electrical and Computer Engineering, McMaster University, Hamilton, ON, Canada
| | - Carol A. DeMatteo
- ARiEAL Research Centre, McMaster University, Hamilton, ON, Canada
- Department of Rehabilitation Sciences, McMaster University, Hamilton, ON, Canada
| | - Dinesh Kumbhare
- School of Biomedical Engineering, McMaster University, Hamilton, ON, Canada
- Imaging Research Centre, St. Joseph's Healthcare Hamilton, Hamilton, ON, Canada
- KITE Research Institute, Toronto Rehabilitation Institute, University Health Network, Toronto, ON, Canada
- Division of Physical Medicine and Rehabilitation, Department of Medicine, University of Toronto, Toronto, ON, Canada
| | - Stephan Ulmer
- Neurorad.ch, Zurich, Switzerland
- Department of Radiology and Neuroradiology, University Hospital of Schleswig-Holstein, Kiel, Germany
| | - Michael D. Noseworthy
- School of Biomedical Engineering, McMaster University, Hamilton, ON, Canada
- Imaging Research Centre, St. Joseph's Healthcare Hamilton, Hamilton, ON, Canada
- Department of Electrical and Computer Engineering, McMaster University, Hamilton, ON, Canada
- ARiEAL Research Centre, McMaster University, Hamilton, ON, Canada
- Department of Radiology, McMaster University, Hamilton, ON, Canada
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4
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Fixel-based analysis of the diffusion properties of the patients with brain injury and chronic health symptoms. Neurosci Res 2023:S0168-0102(23)00009-3. [PMID: 36682692 DOI: 10.1016/j.neures.2023.01.009] [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: 10/19/2022] [Revised: 12/28/2022] [Accepted: 01/17/2023] [Indexed: 01/21/2023]
Abstract
The diffusion properties from diffusion tensor imaging (DTI) are sensitive to white matter (WM) abnormalities and could serve as indicators of diffuse axonal damages incurred during a traumatic brain injury (TBI). Analyses of diffusion metrics in the regions of interest (ROIs) were used to compare the differences in the 18 major fiber tracts in 46 participants, between TBI participants with (n = 17) or without (n = 16) chronic symptoms (CS) and a control group (CG, n = 13). In addition to the widely used diffusion metrics, such as fractional anisotropy (FA), mean (MD), axial (AD) and radial (RD) diffusivities, apparent fiber density (AFD), complexity (CX) and fixel number (FN) derived from Mrtrix3 software package were used to characterize WM tracts and compare between participant groups in the ROIs defined by the fixel numbers. Significant differences were found in FA, AFD, MD, RD and CX in ROIs with different FNs in the corpus callosum forceps minor, left and right inferior longitudinal fasciculus, and left and right uncinate fasciculus for both TBI groups compared to controls. Diffusion properties in ROIs with different FNs can serve as detailed biomarkers of WM abnormalities, especially for individuals with chronic TBI related symptoms.
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Rauchman SH, Albert J, Pinkhasov A, Reiss AB. Mild-to-Moderate Traumatic Brain Injury: A Review with Focus on the Visual System. Neurol Int 2022; 14:453-470. [PMID: 35736619 PMCID: PMC9227114 DOI: 10.3390/neurolint14020038] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2022] [Revised: 05/23/2022] [Accepted: 05/25/2022] [Indexed: 02/01/2023] Open
Abstract
Traumatic Brain Injury (TBI) is a major global public health problem. Neurological damage from TBI may be mild, moderate, or severe and occurs both immediately at the time of impact (primary injury) and continues to evolve afterwards (secondary injury). In mild (m)TBI, common symptoms are headaches, dizziness and fatigue. Visual impairment is especially prevalent. Insomnia, attentional deficits and memory problems often occur. Neuroimaging methods for the management of TBI include computed tomography and magnetic resonance imaging. The location and the extent of injuries determine the motor and/or sensory deficits that result. Parietal lobe damage can lead to deficits in sensorimotor function, memory, and attention span. The processing of visual information may be disrupted, with consequences such as poor hand-eye coordination and balance. TBI may cause lesions in the occipital or parietal lobe that leave the TBI patient with incomplete homonymous hemianopia. Overall, TBI can interfere with everyday life by compromising the ability to work, sleep, drive, read, communicate and perform numerous activities previously taken for granted. Treatment and rehabilitation options available to TBI sufferers are inadequate and there is a pressing need for new ways to help these patients to optimize their functioning and maintain productivity and participation in life activities, family and community.
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Affiliation(s)
- Steven H. Rauchman
- The Fresno Institute of Neuroscience, Fresno, CA 93730, USA
- Correspondence:
| | - Jacqueline Albert
- Department of Medicine, Biomedical Research Institute, NYU Long Island School of Medicine, Mineola, NY 11501, USA; (J.A.); (A.B.R.)
| | - Aaron Pinkhasov
- Department of Psychiatry, NYU Long Island School of Medicine, Mineola, NY 11501, USA;
| | - Allison B. Reiss
- Department of Medicine, Biomedical Research Institute, NYU Long Island School of Medicine, Mineola, NY 11501, USA; (J.A.); (A.B.R.)
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Abdul Rahman MR, Abd Hamid AI, Noh NA, Omar H, Chai WJ, Idris Z, Ahmad AH, Fitzrol DN, Ab. Ghani ARIG, Wan Mohamad WNA, Mohamed Mustafar MF, Hanafi MH, Reza MF, Umar H, Mohd Zulkifly MF, Ang SY, Zakaria Z, Musa KI, Othman A, Embong Z, Sapiai NA, Kandasamy R, Ibrahim H, Abdullah MZ, Amaruchkul K, Valdes-Sosa P, Luisa-Bringas M, Biswal B, Songsiri J, Yaacob HS, Sumari P, Jamir Singh PS, Azman A, Abdullah JM. Alteration in the Functional Organization of the Default Mode Network Following Closed Non-severe Traumatic Brain Injury. Front Neurosci 2022; 16:833320. [PMID: 35418832 PMCID: PMC8995774 DOI: 10.3389/fnins.2022.833320] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2021] [Accepted: 02/04/2022] [Indexed: 02/05/2023] Open
Abstract
The debilitating effect of traumatic brain injury (TBI) extends years after the initial injury and hampers the recovery process and quality of life. In this study, we explore the functional reorganization of the default mode network (DMN) of those affected with non-severe TBI. Traumatic brain injury (TBI) is a wide-spectrum disease that has heterogeneous effects on its victims and impacts everyday functioning. The functional disruption of the default mode network (DMN) after TBI has been established, but its link to causal effective connectivity remains to be explored. This study investigated the differences in the DMN between healthy participants and mild and moderate TBI, in terms of functional and effective connectivity using resting-state functional magnetic resonance imaging (fMRI). Nineteen non-severe TBI (mean age 30.84 ± 14.56) and twenty-two healthy (HC; mean age 27.23 ± 6.32) participants were recruited for this study. Resting-state fMRI data were obtained at the subacute phase (mean days 40.63 ± 10.14) and analyzed for functional activation and connectivity, independent component analysis, and effective connectivity within and between the DMN. Neuropsychological tests were also performed to assess the cognitive and memory domains. Compared to the HC, the TBI group exhibited lower activation in the thalamus, as well as significant functional hypoconnectivity between DMN and LN. Within the DMN nodes, decreased activations were detected in the left inferior parietal lobule, precuneus, and right superior frontal gyrus. Altered effective connectivities were also observed in the TBI group and were linked to the diminished activation in the left parietal region and precuneus. With regard to intra-DMN connectivity within the TBI group, positive correlations were found in verbal and visual memory with the language network, while a negative correlation was found in the cognitive domain with the visual network. Our results suggested that aberrant activities and functional connectivities within the DMN and with other RSNs were accompanied by the altered effective connectivities in the TBI group. These alterations were associated with impaired cognitive and memory domains in the TBI group, in particular within the language domain. These findings may provide insight for future TBI observational and interventional research.
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Affiliation(s)
- Muhammad Riddha Abdul Rahman
- Department of Neurosciences, School of Medical Sciences, Universiti Sains Malaysia, Kota Bharu, Malaysia
- School of Medical Imaging, Faculty of Health Sciences, Universiti Sultan Zainal Abidin, Kuala Nerus, Malaysia
- Brain and Behavior Cluster, School of Medical Sciences, Universiti Sains Malaysia, Kota Bharu, Malaysia
| | - Aini Ismafairus Abd Hamid
- Department of Neurosciences, School of Medical Sciences, Universiti Sains Malaysia, Kota Bharu, Malaysia
- Brain and Behavior Cluster, School of Medical Sciences, Universiti Sains Malaysia, Kota Bharu, Malaysia
- Hospital Universiti Sains Malaysia, Universiti Sains Malaysia, Kota Bharu, Malaysia
- *Correspondence: Aini Ismafairus Abd Hamid,
| | - Nor Azila Noh
- Faculty of Medicine and Health Sciences, Universiti Sains Islam Malaysia, Nilai, Malaysia
| | - Hazim Omar
- Department of Neurosciences, School of Medical Sciences, Universiti Sains Malaysia, Kota Bharu, Malaysia
- Brain and Behavior Cluster, School of Medical Sciences, Universiti Sains Malaysia, Kota Bharu, Malaysia
- Hospital Universiti Sains Malaysia, Universiti Sains Malaysia, Kota Bharu, Malaysia
| | - Wen Jia Chai
- Department of Neurosciences, School of Medical Sciences, Universiti Sains Malaysia, Kota Bharu, Malaysia
- Brain and Behavior Cluster, School of Medical Sciences, Universiti Sains Malaysia, Kota Bharu, Malaysia
| | - Zamzuri Idris
- Department of Neurosciences, School of Medical Sciences, Universiti Sains Malaysia, Kota Bharu, Malaysia
- Brain and Behavior Cluster, School of Medical Sciences, Universiti Sains Malaysia, Kota Bharu, Malaysia
- Hospital Universiti Sains Malaysia, Universiti Sains Malaysia, Kota Bharu, Malaysia
| | - Asma Hayati Ahmad
- Department of Physiology, School of Medical Sciences, Universiti Sains Malaysia, Kota Bharu, Malaysia
| | - Diana Noma Fitzrol
- Department of Neurosciences, School of Medical Sciences, Universiti Sains Malaysia, Kota Bharu, Malaysia
- Brain and Behavior Cluster, School of Medical Sciences, Universiti Sains Malaysia, Kota Bharu, Malaysia
- Hospital Universiti Sains Malaysia, Universiti Sains Malaysia, Kota Bharu, Malaysia
| | - Ab. Rahman Izaini Ghani Ab. Ghani
- Department of Neurosciences, School of Medical Sciences, Universiti Sains Malaysia, Kota Bharu, Malaysia
- Brain and Behavior Cluster, School of Medical Sciences, Universiti Sains Malaysia, Kota Bharu, Malaysia
- Hospital Universiti Sains Malaysia, Universiti Sains Malaysia, Kota Bharu, Malaysia
| | - Wan Nor Azlen Wan Mohamad
- Department of Neurosciences, School of Medical Sciences, Universiti Sains Malaysia, Kota Bharu, Malaysia
- Brain and Behavior Cluster, School of Medical Sciences, Universiti Sains Malaysia, Kota Bharu, Malaysia
- Hospital Universiti Sains Malaysia, Universiti Sains Malaysia, Kota Bharu, Malaysia
| | - Mohamed Faiz Mohamed Mustafar
- Department of Neurosciences, School of Medical Sciences, Universiti Sains Malaysia, Kota Bharu, Malaysia
- Brain and Behavior Cluster, School of Medical Sciences, Universiti Sains Malaysia, Kota Bharu, Malaysia
- Hospital Universiti Sains Malaysia, Universiti Sains Malaysia, Kota Bharu, Malaysia
| | - Muhammad Hafiz Hanafi
- Department of Neurosciences, School of Medical Sciences, Universiti Sains Malaysia, Kota Bharu, Malaysia
- Brain and Behavior Cluster, School of Medical Sciences, Universiti Sains Malaysia, Kota Bharu, Malaysia
- Hospital Universiti Sains Malaysia, Universiti Sains Malaysia, Kota Bharu, Malaysia
| | - Mohamed Faruque Reza
- Department of Neurosciences, School of Medical Sciences, Universiti Sains Malaysia, Kota Bharu, Malaysia
- Brain and Behavior Cluster, School of Medical Sciences, Universiti Sains Malaysia, Kota Bharu, Malaysia
- Hospital Universiti Sains Malaysia, Universiti Sains Malaysia, Kota Bharu, Malaysia
| | - Hafidah Umar
- Department of Neurosciences, School of Medical Sciences, Universiti Sains Malaysia, Kota Bharu, Malaysia
- Brain and Behavior Cluster, School of Medical Sciences, Universiti Sains Malaysia, Kota Bharu, Malaysia
- Hospital Universiti Sains Malaysia, Universiti Sains Malaysia, Kota Bharu, Malaysia
| | - Mohd Faizal Mohd Zulkifly
- Department of Neurosciences, School of Medical Sciences, Universiti Sains Malaysia, Kota Bharu, Malaysia
- Brain and Behavior Cluster, School of Medical Sciences, Universiti Sains Malaysia, Kota Bharu, Malaysia
- Hospital Universiti Sains Malaysia, Universiti Sains Malaysia, Kota Bharu, Malaysia
| | - Song Yee Ang
- Department of Neurosciences, School of Medical Sciences, Universiti Sains Malaysia, Kota Bharu, Malaysia
- Brain and Behavior Cluster, School of Medical Sciences, Universiti Sains Malaysia, Kota Bharu, Malaysia
- Hospital Universiti Sains Malaysia, Universiti Sains Malaysia, Kota Bharu, Malaysia
| | - Zaitun Zakaria
- Department of Neurosciences, School of Medical Sciences, Universiti Sains Malaysia, Kota Bharu, Malaysia
- Brain and Behavior Cluster, School of Medical Sciences, Universiti Sains Malaysia, Kota Bharu, Malaysia
- Hospital Universiti Sains Malaysia, Universiti Sains Malaysia, Kota Bharu, Malaysia
| | - Kamarul Imran Musa
- Department of Community Medicine, School of Medical Sciences, Universiti Sains Malaysia, Kota Bharu, Malaysia
| | - Azizah Othman
- Department of Paediatrics, School of Medical Sciences, Universiti Sains Malaysia, Kota Bharu, Malaysia
| | - Zunaina Embong
- Department of Ophthalmology, School of Medical Sciences, Universiti Sains Malaysia, Kota Bharu, Malaysia
| | - Nur Asma Sapiai
- Department of Radiology, School of Medical Sciences, Universiti Sains Malaysia, Kota Bharu, Malaysia
| | | | - Haidi Ibrahim
- School of Electrical and Electronic Engineering, Universiti Sains Malaysia, Nibong Tebal, Malaysia
| | - Mohd Zaid Abdullah
- School of Electrical and Electronic Engineering, Universiti Sains Malaysia, Nibong Tebal, Malaysia
| | - Kannapha Amaruchkul
- Graduate School of Applied Statistics, National Institute of Development Administration (NIDA), Bangkok, Thailand
| | - Pedro Valdes-Sosa
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China
- The Cuban Neurosciences Center, Havana, Cuba
| | - Maria Luisa-Bringas
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China
- The Cuban Neurosciences Center, Havana, Cuba
| | - Bharat Biswal
- Department of Biomedical Engineering, New Jersey Institute of Technology, Newark, NJ, United States
| | - Jitkomut Songsiri
- EE410 Control Systems Laboratory, Department of Electrical Engineering, Faculty of Engineering, Chulalongkorn University, Bangkok, Thailand
| | - Hamwira Sakti Yaacob
- Department of Computer Science, Kulliyah of Information and Communication Technology, International Islamic University Malaysia, Kuala Lumpur, Malaysia
| | - Putra Sumari
- School of Computer Sciences, Universiti Sains Malaysia, Gelugor, Malaysia
| | | | - Azlinda Azman
- School of Social Sciences, Universiti Sains Malaysia, Gelugor, Malaysia
| | - Jafri Malin Abdullah
- Department of Neurosciences, School of Medical Sciences, Universiti Sains Malaysia, Kota Bharu, Malaysia
- Brain and Behavior Cluster, School of Medical Sciences, Universiti Sains Malaysia, Kota Bharu, Malaysia
- Hospital Universiti Sains Malaysia, Universiti Sains Malaysia, Kota Bharu, Malaysia
- Jafri Malin Abdullah,
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Lower cortical volume is associated with poor sleep quality after traumatic brain injury. Brain Imaging Behav 2022; 16:1362-1371. [PMID: 35018551 DOI: 10.1007/s11682-021-00615-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/02/2021] [Indexed: 11/02/2022]
Abstract
Traumatic brain injury (TBI) is known to be associated with poor sleep. In this report, we aimed to identify associations between differences in cortical volume and sleep quality post-TBI. MRI anatomical scans from 88 cases with TBI were analyzed in this report. Subjective sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI). Voxel Based Morphometry (VBM), was used to obtain statistical maps of the association between PSQI and cortical volume in gray matter and white matter voxels. Higher PSQI total scores (poor sleep quality) were strongly associated with smaller gray matter volume in the cerebellum. White matter volume was not associated with total PSQI. The sleep disturbance subcomponent showed a significant association with gray and white matter volumes in the cerebellum. Although not significant, cortical areas such as the cingulate and medial frontal regions were associated with sleep quality. The cerebellum with higher contribution to motor and autonomic systems was associated strongly with poor sleep quality. Additionally, regions that play critical roles in inhibitory brain function and suppress mind wandering (i.e., default mode network including medial frontal and cingulate regions) were associated (although to a lesser extent) with sleep. Our findings suggest that poor sleep quality following TBI is significantly associated with lower cerebellar volume, with trending relationships in regions associated with inhibitory function.
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Abstract
This article discusses new diffusion-weighted imaging (DWI) sequences, diffusion tensor imaging (DTI), and fiber tractography (FT), as well as more advanced diffusion imaging in pediatric brain and spine. Underlying disorder and pathophysiology causing diffusion abnormalities are discussed. Multishot echo planar imaging (EPI) DWI and non-EPI DWI provide higher spatial resolution with less susceptibility artifact and distortion, which are replacing conventional single-shot EPI DWI. DTI and FT have established clinical significance in pediatric brain and spine. This article discusses advanced diffusion imaging, including diffusion kurtosis imaging, neurite orientation dispersion and density imaging, diffusion spectrum imaging, intravoxel incoherent motion, and oscillating-gradient spin-echo.
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Affiliation(s)
- Toshio Moritani
- Division of Neuroradiology, Department of Radiology, University of Michigan, 1500 East Medical Center Drive, UH B2 A209K, Ann Arbor, MI 48109, USA.
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9
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Zakharova NE, Potapov AA, Pronin IN, Danilov GV, Aleksandrova EV, Fadeeva LM, Pogosbekyan EL, Batalov AI, Goryaynov SA. [Diffusion kurtosis imaging in diffuse axonal injury]. ZHURNAL VOPROSY NEĬROKHIRURGII IMENI N. N. BURDENKO 2019; 83:5-16. [PMID: 31339493 DOI: 10.17116/neiro2019830315] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Diffuse axonal injury (DAI) is one of the most severe traumatic brain injuries. The availability of neuroimaging biomarkers for monitoring expansion of traumatic brain injury in vivo is a topical issue. PURPOSE To evaluate novel neuroimaging biomarkers for monitoring brain injury using diffusion kurtosis imaging (DKI) in patients with severe diffuse axonal injury. MATERIAL AND METHODS DKI data of 12 patients with severe DAI (11 patients with a Glasgow Coma Scale (GCS) score of ≤ 8 and 1 patient with a GCS score of 9) and 8 healthy volunteers (control group) were compared. MRI examination was performed 5 to 19 days after injury; 7 of the 12 patients underwent repeated MRI examinations. We assessed the following parameters: mean, axial, and radial kurtosis (MK, AK, RK, respectively) and kurtosis anisotropy (KA) of the white and gray matter; fractional anisotropy (FA), axonal water fraction (AWF), axial and radial extra-axonal diffusion (AxEAD and RadEAD, respectively), and tortuosity (TORT) of the extra-axonal space) of the white matter. Regions of interest (ROIs) were set bilaterally in the centrum semiovale, genu and splenium of the corpus callosum, anterior and posterior limbs of the internal capsule, putamen, thalamus, midbrain, and pons. RESULTS A significant reduction in KA (p<0.05) in most of ROIs set on the white matter was revealed. AK was increased (p<0.05) not only in the white matter but also in the putamen and thalamus. A significant reduction in MK with time was observed when the first and second DKI data were compared. AWF was reduced in the centrum semiovale and peduncles. The TORT parameter was decreased (p<0.05) in the majority of ROIs in the white matter, with the most pronounced changes occurring in the genu and splenium of the corpus callosum. CONCLUSION DKI provides novel data about microstructural injury in DAI and improves our knowledge of brain trauma pathophysiology. DKI parameters should be considered as potential biomarkers of brain injury and potential predictors of the outcome.
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Affiliation(s)
| | - A A Potapov
- Burdenko Neurosurgical Center, Moscow, Russia
| | - I N Pronin
- Burdenko Neurosurgical Center, Moscow, Russia
| | - G V Danilov
- Burdenko Neurosurgical Center, Moscow, Russia
| | | | - L M Fadeeva
- Burdenko Neurosurgical Center, Moscow, Russia
| | | | - A I Batalov
- Burdenko Neurosurgical Center, Moscow, Russia
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10
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Kremneva EI, Legostaeva LA, Morozova SN, Sergeev DV, Sinitsyn DO, Iazeva EG, Suslin AS, Suponeva NA, Krotenkova MV, Piradov MA, Maximov II. Feasibility of Non-Gaussian Diffusion Metrics in Chronic Disorders of Consciousness. Brain Sci 2019; 9:brainsci9050123. [PMID: 31137909 PMCID: PMC6562474 DOI: 10.3390/brainsci9050123] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2019] [Revised: 05/23/2019] [Accepted: 05/23/2019] [Indexed: 01/06/2023] Open
Abstract
Diagnostic accuracy of different chronic disorders of consciousness (DOC) can be affected by the false negative errors in up to 40% cases. In the present study, we aimed to investigate the feasibility of a non-Gaussian diffusion approach in chronic DOC and to estimate a sensitivity of diffusion kurtosis imaging (DKI) metrics for the differentiation of vegetative state/unresponsive wakefulness syndrome (VS/UWS) and minimally conscious state (MCS) from a healthy brain state. We acquired diffusion MRI data from 18 patients in chronic DOC (11 VS/UWS, 7 MCS) and 14 healthy controls. A quantitative comparison of the diffusion metrics for grey (GM) and white (WM) matter between the controls and patient group showed a significant (p < 0.05) difference in supratentorial WM and GM for all evaluated diffusion metrics, as well as for brainstem, corpus callosum, and thalamus. An intra-subject VS/UWS and MCS group comparison showed only kurtosis metrics and fractional anisotropy differences using tract-based spatial statistics, owing mainly to macrostructural differences on most severely lesioned hemispheres. As a result, we demonstrated an ability of DKI metrics to localise and detect changes in both WM and GM and showed their capability in order to distinguish patients with a different level of consciousness.
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Affiliation(s)
- Elena I Kremneva
- Research Center of Neurology, 80 Volokolamskoe shosse, 125367 Moscow, Russia.
| | | | - Sofya N Morozova
- Research Center of Neurology, 80 Volokolamskoe shosse, 125367 Moscow, Russia.
| | - Dmitry V Sergeev
- Research Center of Neurology, 80 Volokolamskoe shosse, 125367 Moscow, Russia.
| | - Dmitry O Sinitsyn
- Research Center of Neurology, 80 Volokolamskoe shosse, 125367 Moscow, Russia.
| | - Elizaveta G Iazeva
- Research Center of Neurology, 80 Volokolamskoe shosse, 125367 Moscow, Russia.
| | - Aleksandr S Suslin
- Research Center of Neurology, 80 Volokolamskoe shosse, 125367 Moscow, Russia.
| | - Natalia A Suponeva
- Research Center of Neurology, 80 Volokolamskoe shosse, 125367 Moscow, Russia.
| | - Marina V Krotenkova
- Research Center of Neurology, 80 Volokolamskoe shosse, 125367 Moscow, Russia.
| | - Michael A Piradov
- Research Center of Neurology, 80 Volokolamskoe shosse, 125367 Moscow, Russia.
| | - Ivan I Maximov
- Department of Psychology, University of Oslo, Forskningsveien 3A, 0373 Oslo, Norway.
- Norwegian Centre for Mental Disorders Research (NORMENT), Norway and Institute of Clinical Medicine, University of Oslo, Oslo Universitetssykehus Bygg 48 Ullevål, 0317 Oslo, Norway.
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