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Garcia-Cordero I, Vasilevskaya A, Taghdiri F, Khodadadi M, Mikulis D, Tarazi A, Mushtaque A, Anssari N, Colella B, Green R, Rogaeva E, Sato C, Grinberg M, Moreno D, Hussain MW, Blennow K, Zetterberg H, Davis KD, Wennberg R, Tator C, Tartaglia MC. Functional connectivity changes in neurodegenerative biomarker-positive athletes with repeated concussions. J Neurol 2024; 271:4180-4190. [PMID: 38589629 DOI: 10.1007/s00415-024-12340-1] [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: 12/05/2023] [Revised: 02/27/2024] [Accepted: 03/19/2024] [Indexed: 04/10/2024]
Abstract
Multimodal biomarkers may identify former contact sports athletes with repeated concussions and at risk for dementia. Our study aims to investigate whether biomarker evidence of neurodegeneration in former professional athletes with repetitive concussions (ExPro) is associated with worse cognition and mood/behavior, brain atrophy, and altered functional connectivity. Forty-one contact sports athletes with repeated concussions were divided into neurodegenerative biomarker-positive (n = 16) and biomarker-negative (n = 25) groups based on positivity of serum neurofilament light-chain. Six healthy controls (negative for biomarkers) with no history of concussions were also analyzed. We calculated cognitive and mood/behavior composite scores from neuropsychological assessments. Gray matter volume maps and functional connectivity of the default mode, salience, and frontoparietal networks were compared between groups using ANCOVAs, controlling for age, and total intracranial volume. The association between the connectivity networks and sports characteristics was analyzed by multiple regression analysis in all ExPro. Participants presented normal-range mean performance in executive function, memory, and mood/behavior tests. The ExPro groups did not differ in professional years played, age at first participation in contact sports, and number of concussions. There were no differences in gray matter volume between groups. The neurodegenerative biomarker-positive group had lower connectivity in the default mode network (DMN) compared to the healthy controls and the neurodegenerative biomarker-negative group. DMN disconnection was associated with increased number of concussions in all ExPro. Biomarkers of neurodegeneration may be useful to detect athletes that are still cognitively normal, but with functional connectivity alterations after concussions and at risk of dementia.
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Affiliation(s)
- Indira Garcia-Cordero
- Tanz Centre for Research in Neurodegenerative Diseases, University of Toronto, Toronto, Canada
- Canadian Concussion Centre, Toronto Western Hospital, University Health Network, Toronto, Canada
| | - Anna Vasilevskaya
- Tanz Centre for Research in Neurodegenerative Diseases, University of Toronto, Toronto, Canada
| | - Foad Taghdiri
- Tanz Centre for Research in Neurodegenerative Diseases, University of Toronto, Toronto, Canada
| | - Mozhgan Khodadadi
- Canadian Concussion Centre, Toronto Western Hospital, University Health Network, Toronto, Canada
| | - David Mikulis
- Canadian Concussion Centre, Toronto Western Hospital, University Health Network, Toronto, Canada
| | - Apameh Tarazi
- Canadian Concussion Centre, Toronto Western Hospital, University Health Network, Toronto, Canada
| | - Asma Mushtaque
- Canadian Concussion Centre, Toronto Western Hospital, University Health Network, Toronto, Canada
| | - Neda Anssari
- Canadian Concussion Centre, Toronto Western Hospital, University Health Network, Toronto, Canada
- Brain Vision and Concussion Clinic, Winnipeg, Canada
| | - Brenda Colella
- Canadian Concussion Centre, Toronto Western Hospital, University Health Network, Toronto, Canada
| | - Robin Green
- Canadian Concussion Centre, Toronto Western Hospital, University Health Network, Toronto, Canada
| | - Ekaterina Rogaeva
- Tanz Centre for Research in Neurodegenerative Diseases, University of Toronto, Toronto, Canada
| | - Christine Sato
- Tanz Centre for Research in Neurodegenerative Diseases, University of Toronto, Toronto, Canada
| | - Mark Grinberg
- Tanz Centre for Research in Neurodegenerative Diseases, University of Toronto, Toronto, Canada
| | - Danielle Moreno
- Tanz Centre for Research in Neurodegenerative Diseases, University of Toronto, Toronto, Canada
| | - Mohammed W Hussain
- Tanz Centre for Research in Neurodegenerative Diseases, University of Toronto, Toronto, Canada
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, UK
- UK Dementia Research Institute at UCL, London, UK
- Hong Kong Center for Neurodegenerative Diseases, Clear Water Bay, Hong Kong, China
| | - Karen D Davis
- Canadian Concussion Centre, Toronto Western Hospital, University Health Network, Toronto, Canada
- Krembil Brain Institute, University Health Network, Toronto, Canada
- Department of Surgery, University of Toronto, Toronto, Canada
- Institute of Medical Science, University of Toronto, Toronto, Canada
| | - Richard Wennberg
- Canadian Concussion Centre, Toronto Western Hospital, University Health Network, Toronto, Canada
| | - Charles Tator
- Canadian Concussion Centre, Toronto Western Hospital, University Health Network, Toronto, Canada
| | - Maria C Tartaglia
- Tanz Centre for Research in Neurodegenerative Diseases, University of Toronto, Toronto, Canada.
- Canadian Concussion Centre, Toronto Western Hospital, University Health Network, Toronto, Canada.
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Dogra S, Arabshahi S, Wei J, Saidenberg L, Kang SK, Chung S, Laine A, Lui YW. Functional Connectivity Changes on Resting-State fMRI after Mild Traumatic Brain Injury: A Systematic Review. AJNR Am J Neuroradiol 2024; 45:795-801. [PMID: 38637022 PMCID: PMC11288594 DOI: 10.3174/ajnr.a8204] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2023] [Accepted: 01/22/2024] [Indexed: 04/20/2024]
Abstract
BACKGROUND Mild traumatic brain injury is theorized to cause widespread functional changes to the brain. Resting-state fMRI may be able to measure functional connectivity changes after traumatic brain injury, but resting-state fMRI studies are heterogeneous, using numerous techniques to study ROIs across various resting-state networks. PURPOSE We systematically reviewed the literature to ascertain whether adult patients who have experienced mild traumatic brain injury show consistent functional connectivity changes on resting-state -fMRI, compared with healthy patients. DATA SOURCES We used 5 databases (PubMed, EMBASE, Cochrane Central, Scopus, Web of Science). STUDY SELECTION Five databases (PubMed, EMBASE, Cochrane Central, Scopus, and Web of Science) were searched for research published since 2010. Search strategies used keywords of "functional MR imaging" and "mild traumatic brain injury" as well as related terms. All results were screened at the abstract and title levels by 4 reviewers according to predefined inclusion and exclusion criteria. For full-text inclusion, each study was evaluated independently by 2 reviewers, with discordant screening settled by consensus. DATA ANALYSIS Data regarding article characteristics, cohort demographics, fMRI scan parameters, data analysis processing software, atlas used, data characteristics, and statistical analysis information were extracted. DATA SYNTHESIS Across 66 studies, 80 areas were analyzed 239 times for at least 1 time point, most commonly using independent component analysis. The most analyzed areas and networks were the whole brain, the default mode network, and the salience network. Reported functional connectivity changes varied, though there may be a slight trend toward decreased whole-brain functional connectivity within 1 month of traumatic brain injury and there may be differences based on the time since injury. LIMITATIONS Studies of military, sports-related traumatic brain injury, and pediatric patients were excluded. Due to the high number of relevant studies and data heterogeneity, we could not be as granular in the analysis as we would have liked. CONCLUSIONS Reported functional connectivity changes varied, even within the same region and network, at least partially reflecting differences in technical parameters, preprocessing software, and analysis methods as well as probable differences in individual injury. There is a need for novel rs-fMRI techniques that better capture subject-specific functional connectivity changes.
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Affiliation(s)
- Siddhant Dogra
- From the Department of Radiology (S.D., J.W., S.K.K., S.C., Y.L.), New York University Grossman School of Medicine, New York, New York
| | - Soroush Arabshahi
- Department of Biomedical Engineering (S.A., A.L.), Department of Radiology, Columbia University, New York, New York
| | - Jason Wei
- From the Department of Radiology (S.D., J.W., S.K.K., S.C., Y.L.), New York University Grossman School of Medicine, New York, New York
| | - Lucia Saidenberg
- Department of Neurology (L.S.), Department of Radiology. New York University Grossman School of Medicine, New York, New York
| | - Stella K Kang
- From the Department of Radiology (S.D., J.W., S.K.K., S.C., Y.L.), New York University Grossman School of Medicine, New York, New York
| | - Sohae Chung
- From the Department of Radiology (S.D., J.W., S.K.K., S.C., Y.L.), New York University Grossman School of Medicine, New York, New York
| | - Andrew Laine
- Department of Biomedical Engineering (S.A., A.L.), Department of Radiology, Columbia University, New York, New York
| | - Yvonne W Lui
- From the Department of Radiology (S.D., J.W., S.K.K., S.C., Y.L.), New York University Grossman School of Medicine, New York, New York
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Arabshahi S, Chung S, Alivar A, Amorapanth PX, Flanagan SR, Foo FYA, Laine AF, Lui YW. A Comprehensive and Broad Approach to Resting-State Functional Connectivity in Adult Patients with Mild Traumatic Brain Injury. AJNR Am J Neuroradiol 2024; 45:637-646. [PMID: 38604737 PMCID: PMC11288538 DOI: 10.3174/ajnr.a8193] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2023] [Accepted: 01/12/2024] [Indexed: 04/13/2024]
Abstract
BACKGROUND AND PURPOSE Several recent works using resting-state fMRI suggest possible alterations of resting-state functional connectivity after mild traumatic brain injury. However, the literature is plagued by various analysis approaches and small study cohorts, resulting in an inconsistent array of reported findings. In this study, we aimed to investigate differences in whole-brain resting-state functional connectivity between adult patients with mild traumatic brain injury within 1 month of injury and healthy control subjects using several comprehensive resting-state functional connectivity measurement methods and analyses. MATERIALS AND METHODS A total of 123 subjects (72 patients with mild traumatic brain injury and 51 healthy controls) were included. A standard fMRI preprocessing pipeline was used. ROI/seed-based analyses were conducted using 4 standard brain parcellation methods, and the independent component analysis method was applied to measure resting-state functional connectivity. The fractional amplitude of low-frequency fluctuations was also measured. Group comparisons were performed on all measurements with appropriate whole-brain multilevel statistical analysis and correction. RESULTS There were no significant differences in age, sex, education, and hand preference between groups as well as no significant correlation between all measurements and these potential confounders. We found that each resting-state functional connectivity measurement revealed various regions or connections that were different between groups. However, after we corrected for multiple comparisons, the results showed no statistically significant differences between groups in terms of resting-state functional connectivity across methods and analyses. CONCLUSIONS Although previous studies point to multiple regions and networks as possible mild traumatic brain injury biomarkers, this study shows that the effect of mild injury on brain resting-state functional connectivity has not survived after rigorous statistical correction. A further study using subject-level connectivity analyses may be necessary due to both subtle and variable effects of mild traumatic brain injury on brain functional connectivity across individuals.
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Affiliation(s)
- Soroush Arabshahi
- From Biomedical Engineering Department (S.A., A.F.L.), Columbia University, New York, New York
| | - Sohae Chung
- Departments of Radiology (S.C., A.A., Y.W.L.), NYU Grossman School of Medicine, New York, New York
| | - Alaleh Alivar
- Departments of Radiology (S.C., A.A., Y.W.L.), NYU Grossman School of Medicine, New York, New York
| | - Prin X Amorapanth
- Rehabilitation Medicine (P.X.A., S.R.F.), NYU Grossman School of Medicine, New York, New York
| | - Steven R Flanagan
- Rehabilitation Medicine (P.X.A., S.R.F.), NYU Grossman School of Medicine, New York, New York
| | - Farng-Yang A Foo
- Department of Neurology (F.-Y.A.F.), NYU Grossman School of Medicine, New York, New York
| | - Andrew F Laine
- From Biomedical Engineering Department (S.A., A.F.L.), Columbia University, New York, New York
| | - Yvonne W Lui
- Departments of Radiology (S.C., A.A., Y.W.L.), NYU Grossman School of Medicine, New York, New York
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Yorita A, Kawayama T, Inoue M, Kinoshita T, Oda H, Tokunaga Y, Tateishi T, Shoji Y, Uchimura N, Abe T, Hoshino T, Taniwaki T. Altered Functional Connectivity during Mild Transient Respiratory Impairment Induced by a Resistive Load. J Clin Med 2024; 13:2556. [PMID: 38731091 PMCID: PMC11084533 DOI: 10.3390/jcm13092556] [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: 03/19/2024] [Revised: 04/17/2024] [Accepted: 04/23/2024] [Indexed: 05/13/2024] Open
Abstract
Background: Previous neuroimaging studies have identified brain regions related to respiratory motor control and perception. However, little is known about the resting-state functional connectivity (FC) associated with respiratory impairment. We aimed to determine the FC involved in mild respiratory impairment without altering transcutaneous oxygen saturation. Methods: We obtained resting-state functional magnetic resonance imaging data from 36 healthy volunteers during normal respiration and mild respiratory impairment induced by resistive load (effort breathing). ROI-to-ROI and seed-to-voxel analyses were performed using Statistical Parametric Mapping 12 and the CONN toolbox. Results: Compared to normal respiration, effort breathing activated FCs within and between the sensory perceptual area (postcentral gyrus, anterior insular cortex (AInsula), and anterior cingulate cortex) and visual cortex (the visual occipital, occipital pole (OP), and occipital fusiform gyrus). Graph theoretical analysis showed strong centrality in the visual cortex. A significant positive correlation was observed between the dyspnoea score (modified Borg scale) and FC between the left AInsula and right OP. Conclusions: These results suggested that the FCs within the respiratory sensory area via the network hub may be neural mechanisms underlying effort breathing and modified Borg scale scores. These findings may provide new insights into the visual networks that contribute to mild respiratory impairments.
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Affiliation(s)
- Akiko Yorita
- Division of Respirology, Neurology, and Rheumatology, Department of Medicine, Kurume University School of Medicine, Kurume 830-0011, Japan; (A.Y.); (T.K.); (T.K.); (H.O.); (Y.T.); (T.T.); (T.H.)
| | - Tomotaka Kawayama
- Division of Respirology, Neurology, and Rheumatology, Department of Medicine, Kurume University School of Medicine, Kurume 830-0011, Japan; (A.Y.); (T.K.); (T.K.); (H.O.); (Y.T.); (T.T.); (T.H.)
| | - Masayuki Inoue
- Cognitive and Molecular Research Institute of Brain Disease, Kurume University, Kurume 830-0011, Japan; (M.I.); (Y.S.); (N.U.)
| | - Takashi Kinoshita
- Division of Respirology, Neurology, and Rheumatology, Department of Medicine, Kurume University School of Medicine, Kurume 830-0011, Japan; (A.Y.); (T.K.); (T.K.); (H.O.); (Y.T.); (T.T.); (T.H.)
| | - Hanako Oda
- Division of Respirology, Neurology, and Rheumatology, Department of Medicine, Kurume University School of Medicine, Kurume 830-0011, Japan; (A.Y.); (T.K.); (T.K.); (H.O.); (Y.T.); (T.T.); (T.H.)
| | - Yoshihisa Tokunaga
- Division of Respirology, Neurology, and Rheumatology, Department of Medicine, Kurume University School of Medicine, Kurume 830-0011, Japan; (A.Y.); (T.K.); (T.K.); (H.O.); (Y.T.); (T.T.); (T.H.)
| | - Takahisa Tateishi
- Division of Respirology, Neurology, and Rheumatology, Department of Medicine, Kurume University School of Medicine, Kurume 830-0011, Japan; (A.Y.); (T.K.); (T.K.); (H.O.); (Y.T.); (T.T.); (T.H.)
| | - Yoshihisa Shoji
- Cognitive and Molecular Research Institute of Brain Disease, Kurume University, Kurume 830-0011, Japan; (M.I.); (Y.S.); (N.U.)
| | - Naohisa Uchimura
- Cognitive and Molecular Research Institute of Brain Disease, Kurume University, Kurume 830-0011, Japan; (M.I.); (Y.S.); (N.U.)
| | - Toshi Abe
- Department of Radiology, Kurume University School of Medicine, Kurume 830-0011, Japan;
| | - Tomoaki Hoshino
- Division of Respirology, Neurology, and Rheumatology, Department of Medicine, Kurume University School of Medicine, Kurume 830-0011, Japan; (A.Y.); (T.K.); (T.K.); (H.O.); (Y.T.); (T.T.); (T.H.)
| | - Takayuki Taniwaki
- Division of Respirology, Neurology, and Rheumatology, Department of Medicine, Kurume University School of Medicine, Kurume 830-0011, Japan; (A.Y.); (T.K.); (T.K.); (H.O.); (Y.T.); (T.T.); (T.H.)
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Vedaei F, Mashhadi N, Alizadeh M, Zabrecky G, Monti D, Wintering N, Navarreto E, Hriso C, Newberg AB, Mohamed FB. Deep learning-based multimodality classification of chronic mild traumatic brain injury using resting-state functional MRI and PET imaging. Front Neurosci 2024; 17:1333725. [PMID: 38312737 PMCID: PMC10837852 DOI: 10.3389/fnins.2023.1333725] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2023] [Accepted: 12/28/2023] [Indexed: 02/06/2024] Open
Abstract
Mild traumatic brain injury (mTBI) is a public health concern. The present study aimed to develop an automatic classifier to distinguish between patients with chronic mTBI (n = 83) and healthy controls (HCs) (n = 40). Resting-state functional MRI (rs-fMRI) and positron emission tomography (PET) imaging were acquired from the subjects. We proposed a novel deep-learning-based framework, including an autoencoder (AE), to extract high-level latent and rectified linear unit (ReLU) and sigmoid activation functions. Single and multimodality algorithms integrating multiple rs-fMRI metrics and PET data were developed. We hypothesized that combining different imaging modalities provides complementary information and improves classification performance. Additionally, a novel data interpretation approach was utilized to identify top-performing features learned by the AEs. Our method delivered a classification accuracy within the range of 79-91.67% for single neuroimaging modalities. However, the performance of classification improved to 95.83%, thereby employing the multimodality model. The models have identified several brain regions located in the default mode network, sensorimotor network, visual cortex, cerebellum, and limbic system as the most discriminative features. We suggest that this approach could be extended to the objective biomarkers predicting mTBI in clinical settings.
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Affiliation(s)
- Faezeh Vedaei
- Department of Radiology, Jefferson Integrated Magnetic Resonance Imaging Center, Thomas Jefferson University, Philadelphia, PA, United States
| | - Najmeh Mashhadi
- Department of Computer Science and Engineering, University of California, Santa Cruz, Santa Cruz, CA, United States
| | - Mahdi Alizadeh
- Department of Radiology, Jefferson Integrated Magnetic Resonance Imaging Center, Thomas Jefferson University, Philadelphia, PA, United States
| | - George Zabrecky
- Department of Integrative Medicine and Nutritional Sciences, Marcus Institute of Integrative, Health, Thomas Jefferson University, Philadelphia, PA, United States
| | - Daniel Monti
- Department of Integrative Medicine and Nutritional Sciences, Marcus Institute of Integrative, Health, Thomas Jefferson University, Philadelphia, PA, United States
| | - Nancy Wintering
- Department of Integrative Medicine and Nutritional Sciences, Marcus Institute of Integrative, Health, Thomas Jefferson University, Philadelphia, PA, United States
| | - Emily Navarreto
- Department of Integrative Medicine and Nutritional Sciences, Marcus Institute of Integrative, Health, Thomas Jefferson University, Philadelphia, PA, United States
| | - Chloe Hriso
- Department of Integrative Medicine and Nutritional Sciences, Marcus Institute of Integrative, Health, Thomas Jefferson University, Philadelphia, PA, United States
| | - Andrew B. Newberg
- Department of Radiology, Jefferson Integrated Magnetic Resonance Imaging Center, Thomas Jefferson University, Philadelphia, PA, United States
- Department of Integrative Medicine and Nutritional Sciences, Marcus Institute of Integrative, Health, Thomas Jefferson University, Philadelphia, PA, United States
| | - Feroze B. Mohamed
- Department of Radiology, Jefferson Integrated Magnetic Resonance Imaging Center, Thomas Jefferson University, Philadelphia, PA, United States
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Boisgontier J, Beccaria K, Saitovitch A, Blauwblomme T, Guida L, Fillon L, Dufour C, Grill J, Lemaitre H, Puget S, Vinçon-Leite A, Dangouloff-Ros V, Charpy S, Benichi S, Levy R, Roux CJ, Grévent D, Bourgeois M, Saidoun L, Gaillard R, Zilbovicius M, Boddaert N. Case Report: Zolpidem's paradoxical restorative action: A case report of functional brain imaging. Front Neurosci 2023; 17:1127542. [PMID: 37123350 PMCID: PMC10140395 DOI: 10.3389/fnins.2023.1127542] [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: 12/19/2022] [Accepted: 03/09/2023] [Indexed: 05/02/2023] Open
Abstract
Zolpidem is a sedative drug that has been shown to induce a paradoxical effect, restoring brain function in wide range of neurological disorders. The underlying functional mechanism of the effect of zolpidem in the brain in clinical improvement is still poorly understood. Thus, we aimed to investigate rest brain function to study zolpidem-induced symptom improvement in a patient who developed postoperative pediatric cerebellar mutism syndrome, a postoperative complication characterized by delayed onset transient mutism/reduced speech that can occur after medulloblastoma resection. The patient experienced clinical recovery after a single dose of zolpidem. Brain function was investigated using arterial spin labeling MRI and resting-state functional MRI. Imaging was performed at three time-points: preoperative, postoperative during symptoms, and after zolpidem intake when the symptoms regressed. Whole brain rest cerebral blood flow (CBF) and resting state functional connectivity using Pearson coefficient correlations between pairs of regions of interest were investigated two-by-two at the different time points. A comparison between postoperative and preoperative images showed a significant decrease in rest CBF in the left supplementary motor area, Broca's area, and the left striatum and a decrease in functional connectivity within the dentato-thalamo-cortical and cortico-striato-pallido-thalamo-cortical loops. Post-zolpidem images showed increased CBF in the left striatum and increased functional connectivity within the disrupted loops relative to postoperative images. Thus, we observed functional changes within the broader speech network and thalamo-subcortical interactions associated with the paradoxical effect of zolpidem in promoting clinical recovery. This should encourage further functional investigations in the brain to better understand the mechanism of zolpidem in neurological recovery.
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Affiliation(s)
- Jennifer Boisgontier
- Department of Pediatric Radiology, Necker-Enfants Malades Hospital, AP-HP, Université Paris-Cité, Paris, France
- Imagine Institute, INSERM U1163, Université Paris Cité, Paris, France
- *Correspondence: Jennifer Boisgontier,
| | - Kévin Beccaria
- Department of Pediatric Neurosurgery, Necker-Enfants Malades Hospital, AP-HP, Université Paris-Cité, Paris, France
| | - Ana Saitovitch
- Department of Pediatric Radiology, Necker-Enfants Malades Hospital, AP-HP, Université Paris-Cité, Paris, France
- Imagine Institute, INSERM U1163, Université Paris Cité, Paris, France
| | - Thomas Blauwblomme
- Department of Pediatric Neurosurgery, Necker-Enfants Malades Hospital, AP-HP, Université Paris-Cité, Paris, France
| | - Lelio Guida
- Department of Pediatric Neurosurgery, Necker-Enfants Malades Hospital, AP-HP, Université Paris-Cité, Paris, France
| | - Ludovic Fillon
- Department of Pediatric Radiology, Necker-Enfants Malades Hospital, AP-HP, Université Paris-Cité, Paris, France
- Imagine Institute, INSERM U1163, Université Paris Cité, Paris, France
| | - Christelle Dufour
- Department of Pediatric and Adolescent Oncology, Gustave Roussy Institute, Villejuif, France
| | - Jacques Grill
- Department of Pediatric and Adolescent Oncology, Gustave Roussy Institute, Villejuif, France
| | - Hervé Lemaitre
- Neurodegenerative Diseases Institute, Neurofunctional Imaging Group (GIN), Univ. Bordeaux, CNRS, UMR 5293, Bordeaux, France
| | - Stéphanie Puget
- Department of Neurosurgery, Centre Hospitalier Universitaire de Fort de France, University of Antilles, Fort-de-France, Martinique
| | - Alice Vinçon-Leite
- Department of Pediatric Radiology, Necker-Enfants Malades Hospital, AP-HP, Université Paris-Cité, Paris, France
- Imagine Institute, INSERM U1163, Université Paris Cité, Paris, France
| | - Volodia Dangouloff-Ros
- Department of Pediatric Radiology, Necker-Enfants Malades Hospital, AP-HP, Université Paris-Cité, Paris, France
- Imagine Institute, INSERM U1163, Université Paris Cité, Paris, France
| | - Sarah Charpy
- Department of Pediatric Radiology, Necker-Enfants Malades Hospital, AP-HP, Université Paris-Cité, Paris, France
| | - Sandro Benichi
- Department of Pediatric Neurosurgery, Necker-Enfants Malades Hospital, AP-HP, Université Paris-Cité, Paris, France
| | - Raphaël Levy
- Department of Pediatric Radiology, Necker-Enfants Malades Hospital, AP-HP, Université Paris-Cité, Paris, France
- Imagine Institute, INSERM U1163, Université Paris Cité, Paris, France
| | - Charles-Joris Roux
- Department of Pediatric Radiology, Necker-Enfants Malades Hospital, AP-HP, Université Paris-Cité, Paris, France
- Imagine Institute, INSERM U1163, Université Paris Cité, Paris, France
| | - David Grévent
- Department of Pediatric Radiology, Necker-Enfants Malades Hospital, AP-HP, Université Paris-Cité, Paris, France
| | - Marie Bourgeois
- Department of Pediatric Neurosurgery, Necker-Enfants Malades Hospital, AP-HP, Université Paris-Cité, Paris, France
| | - Lila Saidoun
- Department of Pediatric and Adolescent Oncology, Gustave Roussy Institute, Villejuif, France
| | - Raphaël Gaillard
- Department of Psychiatry, Faculty of Medicine, Sainte-Anne Hospital, Université Paris Cité, Paris, France
| | - Monica Zilbovicius
- Ecole Normale Supérieure Paris-Saclay, INSERM U1299, ERL “Developmental Trajectories and Psychiatry”: Université Paris Saclay, Université de Paris, CNRS, Centre Borelli, France
| | - Nathalie Boddaert
- Department of Pediatric Radiology, Necker-Enfants Malades Hospital, AP-HP, Université Paris-Cité, Paris, France
- Imagine Institute, INSERM U1163, Université Paris Cité, Paris, France
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7
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Klimova A, Breukelaar IA, Bryant RA, Korgaonkar MS. A comparison of the functional connectome in mild traumatic brain injury and post-traumatic stress disorder. Hum Brain Mapp 2022; 44:813-824. [PMID: 36206284 PMCID: PMC9842915 DOI: 10.1002/hbm.26101] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2022] [Revised: 08/25/2022] [Accepted: 09/07/2022] [Indexed: 01/25/2023] Open
Abstract
Post-traumatic stress disorder (PTSD) and mild traumatic brain injury (mTBI) often co-occur in the context of threat to one's life. These conditions also have an overlapping symptomatology and include symptoms of anxiety, poor concentration and memory problems. A major challenge has been articulating the underlying neurobiology of these overlapping conditions. The primary aim of this study was to compare intrinsic functional connectivity between mTBI (without PTSD) and PTSD (without mTBI). The study included functional MRI data from 176 participants: 42 participants with mTBI, 67 with PTSD and a comparison group of 66 age and sex-matched healthy controls. We used network-based statistical analyses for connectome-wide comparisons of intrinsic functional connectivity between mTBI relative to PTSD and controls. Our results showed no connectivity differences between mTBI and PTSD groups. However, we did find that mTBI had significantly reduced connectivity relative to healthy controls within an extensive network of regions including default mode, executive control, visual and auditory networks. The mTBI group also displayed hyperconnectivity between dorsal and ventral attention networks and perceptual regions. The PTSD group also demonstrated abnormal connectivity within these networks relative to controls. Connectivity alterations were not associated with severity of PTSD or post-concussive symptoms in either clinical group. Taken together, the similar profiles of intrinsic connectivity alterations in these two conditions provide neural evidence that can explain, in part, the overlapping symptomatology between mTBI and PTSD.
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Affiliation(s)
- Aleksandra Klimova
- Brain Dynamics Centre, Westmead Institute for Medical ResearchThe University of SydneyWestmeadAustralia
| | - Isabella A. Breukelaar
- Brain Dynamics Centre, Westmead Institute for Medical ResearchThe University of SydneyWestmeadAustralia,School of PsychologyUniversity of New South WalesSydneyAustralia
| | - Richard A. Bryant
- Brain Dynamics Centre, Westmead Institute for Medical ResearchThe University of SydneyWestmeadAustralia,School of PsychologyUniversity of New South WalesSydneyAustralia
| | - Mayuresh S. Korgaonkar
- Brain Dynamics Centre, Westmead Institute for Medical ResearchThe University of SydneyWestmeadAustralia,Department of Psychiatry, Faculty of Medicine and HealthUniversity of SydneyWestmeadAustralia
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8
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Li F, Liu Y, Lu L, Shang S, Chen H, Haidari NA, Wang P, Yin X, Chen YC. Rich-club reorganization of functional brain networks in acute mild traumatic brain injury with cognitive impairment. Quant Imaging Med Surg 2022; 12:3932-3946. [PMID: 35782237 PMCID: PMC9246720 DOI: 10.21037/qims-21-915] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2021] [Accepted: 03/30/2022] [Indexed: 06/12/2024]
Abstract
BACKGROUND Mild traumatic brain injury (mTBI) is typically characterized by temporally limited cognitive impairment and regarded as a brain connectome disorder. Recent findings have suggested that a higher level of organization named the "rich-club" may play a central role in enabling the integration of information and efficient communication across different systems of the brain. However, the alterations in rich-club organization and hub topology in mTBI and its relationship with cognitive impairment after mTBI have been scarcely elucidated. METHODS Resting-state functional magnetic resonance imaging (rs-fMRI) data were collected from 88 patients with mTBI and 85 matched healthy controls (HCs). Large-scale functional brain networks were established for each participant. Rich-club organizations and network properties were assessed and analyzed between groups. Finally, we analyzed the correlations between the cognitive performance and changes in rich-club organization and network properties. RESULTS Both mTBI and HCs groups showed significant rich-club organization. Meanwhile, the rich-club organization was aberrant, with enhanced functional connectivity (FC) among rich-club nodes and peripheral regions in acute mTBI. In addition, significant differences in partial global and local network topological property measures were found between mTBI patients and HCs (P<0.01). In patients with mTBI, changes in rich-club organization and network properties were found to be related to early cognitive impairment after mTBI (P<0.05). CONCLUSIONS Our findings suggest that such patterns of disruption and reorganization will provide the basic functional architecture for cognitive function, which may subsequently be used as an earlier biomarker for cognitive impairment after mTBI.
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Affiliation(s)
| | | | - Liyan Lu
- Department of Radiology, Nanjing First Hospital, Nanjing Medical University, Nanjing, China
| | - Song’an Shang
- Department of Radiology, Nanjing First Hospital, Nanjing Medical University, Nanjing, China
| | - Huiyou Chen
- Department of Radiology, Nanjing First Hospital, Nanjing Medical University, Nanjing, China
| | - Nasir Ahmad Haidari
- Department of Radiology, Nanjing First Hospital, Nanjing Medical University, Nanjing, China
| | - Peng Wang
- Department of Radiology, Nanjing First Hospital, Nanjing Medical University, Nanjing, China
| | - Xindao Yin
- Department of Radiology, Nanjing First Hospital, Nanjing Medical University, Nanjing, China
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9
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Liu Y, Lu L, Li F, Chen YC. Neuropathological Mechanisms of Mild Traumatic Brain Injury: A Perspective From Multimodal Magnetic Resonance Imaging. Front Neurosci 2022; 16:923662. [PMID: 35784844 PMCID: PMC9247389 DOI: 10.3389/fnins.2022.923662] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2022] [Accepted: 05/30/2022] [Indexed: 01/20/2023] Open
Abstract
Mild traumatic brain injury (mTBI) accounts for more than 80% of the total number of TBI cases. The mechanism of injury for patients with mTBI has a variety of neuropathological processes. However, the underlying neurophysiological mechanism of the mTBI is unclear, which affects the early diagnosis, treatment decision-making, and prognosis evaluation. More and more multimodal magnetic resonance imaging (MRI) techniques have been applied for the diagnosis of mTBI, such as functional magnetic resonance imaging (fMRI), arterial spin labeling (ASL) perfusion imaging, susceptibility-weighted imaging (SWI), and diffusion MRI (dMRI). Various imaging techniques require to be used in combination with neuroimaging examinations for patients with mTBI. The understanding of the neuropathological mechanism of mTBI has been improved based on different angles. In this review, we have summarized the application of these aforementioned multimodal MRI techniques in mTBI and evaluated its benefits and drawbacks.
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10
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Effects of Mild Traumatic Brain Injury on Resting State Brain Network Connectivity in Older Adults. Brain Imaging Behav 2022; 16:1863-1872. [PMID: 35394617 PMCID: PMC9279274 DOI: 10.1007/s11682-022-00662-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/10/2022] [Indexed: 11/02/2022]
Abstract
Older age is associated with worsened outcome after mild traumatic brain injury (mTBI) and a higher risk of developing persistent post-traumatic complaints. However, the effects of mTBI sequelae on brain connectivity at older age and their association with post-traumatic complaints remain understudied.We analyzed multi-echo resting-state functional magnetic resonance imaging data from 25 older adults with mTBI (mean age: 68 years, SD: 5 years) in the subacute phase (mean injury to scan interval: 38 days, SD: 9 days) and 20 age-matched controls. Severity of complaints (e.g. fatigue, dizziness) was assessed using self-reported questionnaires. Group independent component analysis was used to identify intrinsic connectivity networks (ICNs). The effects of group and severity of complaints on ICNs were assessed using spatial maps intensity (SMI) as a measure of within-network connectivity, and (static) functional network connectivity (FNC) as a measure of between-network connectivity.Patients indicated a higher total severity of complaints than controls. Regarding SMI measures, we observed hyperconnectivity in left-mid temporal gyrus (cognitive-language network) and hypoconnectivity in the right-fusiform gyrus (visual-cerebellar network) that were associated with group. Additionally, we found interaction effects for SMI between severity of complaints and group in the visual(-cerebellar) domain. Regarding FNC measures, no significant effects were found.In older adults, changes in cognitive-language and visual(-cerebellar) networks are related to mTBI. Additionally, group-dependent associations between connectivity within visual(-cerebellar) networks and severity of complaints might indicate post-injury (mal)adaptive mechanisms, which could partly explain post-traumatic complaints (such as dizziness and balance disorders) that are common in older adults during the subacute phase.
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11
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Amir J, Nair JKR, Del Carpio-O'Donovan R, Ptito A, Chen JK, Chankowsky J, Tinawi S, Lunkova E, Saluja RS. Atypical resting state functional connectivity in mild traumatic brain injury. Brain Behav 2021; 11:e2261. [PMID: 34152089 PMCID: PMC8413771 DOI: 10.1002/brb3.2261] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/30/2021] [Revised: 06/08/2021] [Accepted: 06/08/2021] [Indexed: 12/12/2022] Open
Abstract
OBJECTIVES This study aimed to investigate changes in three intrinsic functional connectivity networks (IFCNs; default mode network [DMN], salience network [SN], and task-positive network [TPN]) in individuals who had sustained a mild traumatic brain injury (mTBI). METHODS Resting-state functional magnetic resonance imaging (rs-fMRI) data were acquired from 27 mTBI patients with persistent postconcussive symptoms, along with 26 age- and sex-matched controls. These individuals were recruited from a Level-1 trauma center, at least 3 months after a traumatic episode. IFCNs were established based on seed-to-voxel, region-of-interest (ROI) to ROI, and independent component analyses (ICA). Subsequently, we analyzed the relationship between functional connectivity and postconcussive symptoms. RESULTS Seed-to-voxel analysis of rs-fMRI demonstrated decreased functional connectivity in the right lateral parietal lobe, part of the DMN, and increased functional connectivity in the supramarginal gyrus, part of the SN. Our TPN showed both hypo- and hyperconnectivity dependent on seed location. Within network hypoconnectivity was observed in the visual network also using group comparison. Using an ICA, we identified altered network functional connectivity in regions within four IFCNs (sensorimotor, visual, DMN, and dorsal attentional). A significant negative correlation between dorsal attentional network connectivity and behavioral symptoms score was also found. CONCLUSIONS Our findings indicate that rs-fMRI may be of use clinically in order to assess disrupted functional connectivity among IFCNs in mTBI patients. Improved mTBI diagnostic and prognostic information could be especially relevant for athletes looking to safely return to play, as well for individuals from the general population with persistent postconcussive symptoms months after injury, who hope to resume activity.
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Affiliation(s)
- Joelle Amir
- Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec, Canada
| | | | | | - Alain Ptito
- Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec, Canada.,Research Institute of the McGill University Health Centre, Montreal, Quebec, Canada
| | - Jen-Kai Chen
- Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec, Canada
| | - Jeffrey Chankowsky
- Department of Radiology, McGill University Health Centre, Montreal, Quebec, Canada
| | - Simon Tinawi
- Department of Rehabilitation Medicine, McGill University Health Centre, Montreal, Quebec, Canada
| | - Ekaterina Lunkova
- Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec, Canada
| | - Rajeet Singh Saluja
- Department of Radiology, McGill University Health Centre, Montreal, Quebec, Canada.,Research Institute of the McGill University Health Centre, Montreal, Quebec, Canada
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