1
|
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 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.
Collapse
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
| |
Collapse
|
2
|
Li J, Shu Y, Chen L, Wang B, Chen L, Zhan J, Kuang H, Xia G, Zhou F, Gong H, Zeng X. Disrupted topological organization of functional brain networks in traumatic axonal injury. Brain Imaging Behav 2024; 18:279-291. [PMID: 38044412 PMCID: PMC11156726 DOI: 10.1007/s11682-023-00832-z] [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] [Accepted: 11/20/2023] [Indexed: 12/05/2023]
Abstract
Traumatic axonal injury (TAI) may result in the disruption of brain functional networks and is strongly associated with cognitive impairment. However, the neural mechanisms affecting the neurocognitive function after TAI remain to be elucidated. We collected the resting-state functional magnetic resonance imaging data from 28 patients with TAI and 28 matched healthy controls. An automated anatomical labeling atlas was used to construct a functional brain connectome. We utilized a graph theoretical approach to investigate the alterations in global and regional network topologies, and network-based statistics analysis was utilized to localize the connected networks more precisely. The current study revealed that patients with TAI and healthy controls both showed a typical small-world topology of the functional brain networks. However, patients with TAI exhibited a significantly lower local efficiency compared to healthy controls, whereas no significant difference emerged in other small-world properties (Cp, Lp, γ, λ, and σ) and global efficiency. Moreover, patients with TAI exhibited aberrant nodal centralities in some regions, including the frontal lobes, parietal lobes, caudate nucleus, and cerebellum bilaterally, and right olfactory cortex. The network-based statistics results showed alterations in the long-distance functional connections in the subnetwork in patients with TAI, involving these brain regions with significantly altered nodal centralities. These alterations suggest that brain networks of individuals with TAI present aberrant topological attributes that are associated with cognitive impairment, which could be potential biomarkers for predicting cognitive dysfunction and help understanding the neuropathological mechanisms in patients with TAI.
Collapse
Affiliation(s)
- Jian Li
- Department of Radiology, The First Affiliated Hospital, Nanchang University, 17 Yongwai Zheng Street, Donghu District, Nanchang City, 330006, Jiangxi, China
- Neuroimaging Lab, Jiangxi Province Medical Imaging Research Institute, Nanchang, China
| | - Yongqiang Shu
- Department of Radiology, The First Affiliated Hospital, Nanchang University, 17 Yongwai Zheng Street, Donghu District, Nanchang City, 330006, Jiangxi, China
- Neuroimaging Lab, Jiangxi Province Medical Imaging Research Institute, Nanchang, China
| | - Liting Chen
- Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou, China
| | - Bo Wang
- Department of Radiology, The First Affiliated Hospital, Nanchang University, 17 Yongwai Zheng Street, Donghu District, Nanchang City, 330006, Jiangxi, China
- Neuroimaging Lab, Jiangxi Province Medical Imaging Research Institute, Nanchang, China
| | - Linglong Chen
- Department of Radiology, The First Affiliated Hospital, Nanchang University, 17 Yongwai Zheng Street, Donghu District, Nanchang City, 330006, Jiangxi, China
- Neuroimaging Lab, Jiangxi Province Medical Imaging Research Institute, Nanchang, China
| | - Jie Zhan
- Department of Radiology, The First Affiliated Hospital, Nanchang University, 17 Yongwai Zheng Street, Donghu District, Nanchang City, 330006, Jiangxi, China
- Neuroimaging Lab, Jiangxi Province Medical Imaging Research Institute, Nanchang, China
| | - Hongmei Kuang
- Department of Radiology, The First Affiliated Hospital, Nanchang University, 17 Yongwai Zheng Street, Donghu District, Nanchang City, 330006, Jiangxi, China
- Neuroimaging Lab, Jiangxi Province Medical Imaging Research Institute, Nanchang, China
| | - Guojin Xia
- Department of Radiology, The First Affiliated Hospital, Nanchang University, 17 Yongwai Zheng Street, Donghu District, Nanchang City, 330006, Jiangxi, China
- Neuroimaging Lab, Jiangxi Province Medical Imaging Research Institute, Nanchang, China
| | - Fuqing Zhou
- Department of Radiology, The First Affiliated Hospital, Nanchang University, 17 Yongwai Zheng Street, Donghu District, Nanchang City, 330006, Jiangxi, China
- Neuroimaging Lab, Jiangxi Province Medical Imaging Research Institute, Nanchang, China
| | - Honghan Gong
- Department of Radiology, The First Affiliated Hospital, Nanchang University, 17 Yongwai Zheng Street, Donghu District, Nanchang City, 330006, Jiangxi, China
- Neuroimaging Lab, Jiangxi Province Medical Imaging Research Institute, Nanchang, China
| | - Xianjun Zeng
- Department of Radiology, The First Affiliated Hospital, Nanchang University, 17 Yongwai Zheng Street, Donghu District, Nanchang City, 330006, Jiangxi, China.
- Neuroimaging Lab, Jiangxi Province Medical Imaging Research Institute, Nanchang, China.
| |
Collapse
|