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Xu Y, Li X, Yan Q, Zhang Y, Shang S, Xing C, Wu Y, Guan B, Chen YC. Topological disruption of low- and high-order functional networks in presbycusis. Brain Commun 2024; 6:fcae119. [PMID: 38638149 PMCID: PMC11025675 DOI: 10.1093/braincomms/fcae119] [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: 08/18/2023] [Revised: 03/08/2024] [Accepted: 04/05/2024] [Indexed: 04/20/2024] Open
Abstract
Prior efforts have manifested that functional connectivity (FC) network disruptions are concerned with cognitive disorder in presbycusis. The present research was designed to investigate the topological reorganization and classification performance of low-order functional connectivity (LOFC) and high-order functional connectivity (HOFC) networks in patients with presbycusis. Resting-state functional magnetic resonance imaging (Rs-fMRI) data were obtained in 60 patients with presbycusis and 50 matched healthy control subjects (HCs). LOFC and HOFC networks were then constructed, and the topological metrics obtained from the constructed networks were compared to evaluate topological differences in global, nodal network metrics, modularity and rich-club organization between patients with presbycusis and HCs. The use of HOFC profiles boosted presbycusis classification accuracy, sensitivity and specificity compared to that using LOFC profiles. The brain networks in both patients with presbycusis and HCs exhibited small-world properties within the given threshold range, and striking differences between groups in topological metrics were discovered in the constructed networks (LOFC and HOFC). NBS analysis identified a subnetwork involving 26 nodes and 23 signally altered internodal connections in patients with presbycusis in comparison to HCs in HOFC networks. This study highlighted the topological differences between LOFC and HOFC networks in patients with presbycusis, suggesting that HOFC profiles may help to further identify brain network abnormalities in presbycusis.
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Affiliation(s)
- Yixi Xu
- Department of Otolaryngology, Head and Neck Surgery, The Affiliated Lianyungang Hospital of Xuzhou Medical University, Lianyungang 222000, China
| | - Xiangxiang Li
- Department of Nephrology, Nanjing Yuhua Hospital, Yuhua Branch of Nanjing First Hospital, Nanjing 210006, China
| | - Qi Yan
- Department of Otolaryngology, Head and Neck Surgery, Clinical Medical College, Yangzhou University, Yangzhou 225001, China
| | - Yao Zhang
- Department of Otolaryngology, Head and Neck Surgery, Clinical Medical College, Yangzhou University, Yangzhou 225001, China
| | - Song’an Shang
- Department of Radiology, Clinical Medical College, Yangzhou University, Yangzhou 225001, China
| | - Chunhua Xing
- Department of Radiology, Nanjing First Hospital, Nanjing Medical University, Nanjing 210006, China
| | - Yuanqing Wu
- Department of Otolaryngology, Nanjing First Hospital, Nanjing Medical University, Nanjing 210006, China
| | - Bing Guan
- Department of Otolaryngology, Head and Neck Surgery, Clinical Medical College, Yangzhou University, Yangzhou 225001, China
| | - Yu-Chen Chen
- Department of Radiology, Nanjing First Hospital, Nanjing Medical University, Nanjing 210006, China
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Abstract
Cerebral small vessel disease (cSVD) is a major cause of stroke and dementia. This review summarizes recent developments in advanced neuroimaging of cSVD with a focus on clinical and research applications. In the first section, we highlight how advanced structural imaging techniques, including diffusion magnetic resonance imaging (MRI), enable improved detection of tissue damage, including characterization of tissue appearing normal on conventional MRI. These techniques enable progression to be monitored and may be useful as surrogate endpoint in clinical trials. Quantitative MRI, including iron and myelin imaging, provides insights into tissue composition on the molecular level. In the second section, we cover how advanced MRI techniques can demonstrate functional or dynamic abnormalities of the blood vessels, which could be targeted in mechanistic research and early-stage intervention trials. Such techniques include the use of dynamic contrast enhanced MRI to measure blood-brain barrier permeability, and MRI methods to assess cerebrovascular reactivity. In the third section, we discuss how the increased spatial resolution provided by ultrahigh field MRI at 7 T allows imaging of perforating arteries, and flow velocity and pulsatility within them. The advanced MRI techniques we describe are providing novel pathophysiological insights in cSVD and allow improved quantification of disease burden and progression. They have application in clinical trials, both in assessing novel therapeutic mechanisms, and as a sensitive endpoint to assess efficacy of interventions on parenchymal tissue damage. We also discuss challenges of these advanced techniques and suggest future directions for research.
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Affiliation(s)
- Hilde van den Brink
- Department of Neurology and
Neurosurgery, University Medical Center Utrecht Brain Center, Utrecht University,
Utrecht, The Netherlands
| | - Fergus N Doubal
- Centre for Clinical Brain Sciences, UK
Dementia Research Institute, University of Edinburgh, Edinburgh, UK
| | - Marco Duering
- Medical Image Analysis Center (MIAC AG)
and qbig, Department of Biomedical Engineering, University of Basel, Basel,
Switzerland,Marco Duering, Medical Image Analysis
Center (MIAC AG) and qbig, Department of Biomedical Engineering, University of
Basel, Marktgasse 8, Basel, CH-4051, Switzerland.
; @MarcoDuering
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Wang S, Zhang F, Huang P, Hong H, Jiaerken Y, Yu X, Zhang R, Zeng Q, Zhang Y, Kikinis R, Rathi Y, Makris N, Lou M, Pasternak O, Zhang M, O'Donnell LJ. Superficial white matter microstructure affects processing speed in cerebral small vessel disease. Hum Brain Mapp 2022; 43:5310-5325. [PMID: 35822593 PMCID: PMC9812245 DOI: 10.1002/hbm.26004] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2022] [Revised: 06/10/2022] [Accepted: 06/15/2022] [Indexed: 01/15/2023] Open
Abstract
White matter hyperintensities (WMH) are a typical feature of cerebral small vessel disease (CSVD), which contributes to about 50% of dementias worldwide. Microstructural alterations in deep white matter (DWM) have been widely examined in CSVD. However, little is known about abnormalities in superficial white matter (SWM) and their relevance for processing speed, the main cognitive deficit in CSVD. In 141 CSVD patients, processing speed was assessed using Trail Making Test Part A. White matter abnormalities were assessed by WMH burden (volume on T2-FLAIR) and diffusion MRI measures. SWM imaging measures had a large contribution to processing speed, despite a relatively low SWM WMH burden. Across all imaging measures, SWM free water (FW) had the strongest association with processing speed, followed by SWM mean diffusivity (MD). SWM FW was the only marker to significantly increase between two subgroups with the lowest WMH burdens. When comparing two subgroups with the highest WMH burdens, the involvement of WMH in the SWM was accompanied by significant differences in processing speed and white matter microstructure. Mediation analysis revealed that SWM FW fully mediated the association between WMH volume and processing speed, while no mediation effect of MD or DWM FW was observed. Overall, results suggest that the SWM has an important contribution to processing speed, while SWM FW is a sensitive imaging marker associated with cognition in CSVD. This study extends the current understanding of CSVD-related dysfunction and suggests that the SWM, as an understudied region, can be a potential target for monitoring pathophysiological processes.
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Affiliation(s)
- Shuyue Wang
- Department of Radiologythe Second Affiliated Hospital of Zhejiang University School of MedicineChina
- Brigham and Women's Hospital, Harvard Medical SchoolBostonMassachusettsUSA
| | - Fan Zhang
- Brigham and Women's Hospital, Harvard Medical SchoolBostonMassachusettsUSA
| | - Peiyu Huang
- Department of Radiologythe Second Affiliated Hospital of Zhejiang University School of MedicineChina
| | - Hui Hong
- Department of Radiologythe Second Affiliated Hospital of Zhejiang University School of MedicineChina
| | - Yeerfan Jiaerken
- Department of Radiologythe Second Affiliated Hospital of Zhejiang University School of MedicineChina
| | - Xinfeng Yu
- Department of Radiologythe Second Affiliated Hospital of Zhejiang University School of MedicineChina
| | - Ruiting Zhang
- Department of Radiologythe Second Affiliated Hospital of Zhejiang University School of MedicineChina
| | - Qingze Zeng
- Department of Radiologythe Second Affiliated Hospital of Zhejiang University School of MedicineChina
| | - Yao Zhang
- Department of Radiologythe Second Affiliated Hospital of Zhejiang University School of MedicineChina
| | - Ron Kikinis
- Brigham and Women's Hospital, Harvard Medical SchoolBostonMassachusettsUSA
| | - Yogesh Rathi
- Brigham and Women's Hospital, Harvard Medical SchoolBostonMassachusettsUSA
| | - Nikos Makris
- Brigham and Women's Hospital, Harvard Medical SchoolBostonMassachusettsUSA
- Center for Morphometric AnalysisMassachusetts General Hospital, Harvard Medical SchoolBostonMassachusettsUSA
| | - Min Lou
- Department of Neurologythe Second Affiliated Hospital of Zhejiang University School of MedicineChina
| | - Ofer Pasternak
- Brigham and Women's Hospital, Harvard Medical SchoolBostonMassachusettsUSA
| | - Minming Zhang
- Department of Radiologythe Second Affiliated Hospital of Zhejiang University School of MedicineChina
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Song H, Ruan Z, Gao L, Lv D, Sun D, Li Z, Zhang R, Zhou X, Xu H, Zhang J. Structural network efficiency mediates the association between glymphatic function and cognition in mild VCI: a DTI-ALPS study. Front Aging Neurosci 2022; 14:974114. [PMID: 36466598 PMCID: PMC9708722 DOI: 10.3389/fnagi.2022.974114] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2022] [Accepted: 10/27/2022] [Indexed: 09/03/2023] Open
Abstract
Background and objective: Vascular cognitive impairment (VCI) can be caused by multiple types of cerebrovascular pathology and is considered a network disconnection disorder. The heterogeneity hinders research progress in VCI. Glymphatic failure has been considered as a key common pathway to dementia recently. The emergence of a new method, Diffusion Tensor Image Analysis Along the Perivascular Space (DTI-ALPS), makes it possible to investigate the changes of the glymphatic function in humans non-invasively. We aimed to investigate alterations of glymphatic function in VCI and its potential impact on network connectivity. Methods: We recruited 79 patients with mild VCI, including 40 with cerebral small vessel disease cognitive impairment (SVCI) and 39 with post-stroke cognitive impairment (PSCI); and, 77 normal cognitive (NC) subjects were recruited. All subjects received neuropsychological assessments and multimodal magnetic resonance imaging scans. ALPS-index was calculated and structural networks were constructed by deterministic tractography, and then, the topological metrics of these structural connectivity were evaluated. Results: The ALPS-index of VCI patients was significantly lower than that of NC subjects (P < 0.001). Multiple linear regression analysis showed that ALPS-index affects cognitive function independently (β = 0.411, P < 0.001). The results of correlation analysis showed that the ALPS-index was correlated with overall vascular risk factor burden (r = -0.263, P = 0.001) and multiple cerebrovascular pathologies (P < 0.05). In addition, global efficiency (Eg) of network was correlated with ALPS-index in both SVCI (r = 0.348, P = 0.028) and PSCI (r = 0.732, P < 0.001) patients. Finally, the results of mediation analysis showed that Eg partially mediated in the impact of glymphatic dysfunction on cognitive impairment (indirect effect = 7.46, 95% CI 4.08-11.48). Conclusion: In both major subtypes of VCI, the ALPS-index was decreased, indicating impaired glymphatic function in VCI. Glymphatic dysfunction may affect cognitive function in VCI by disrupting network connectivity, and, may be a potential common pathological mechanism of VCI. ALPS-index is expected to become an emerging imaging marker for VCI.
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Affiliation(s)
- Hao Song
- Department of Neurology, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Zhao Ruan
- Department of Radiology, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Lei Gao
- Department of Radiology, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Dongwei Lv
- Department of Neurology, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Dong Sun
- Department of Neurology, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Zeng Li
- Department of Neurology, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Ran Zhang
- Department of Neurology, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Xiaoli Zhou
- Department of Radiology, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Haibo Xu
- Department of Radiology, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Junjian Zhang
- Department of Neurology, Zhongnan Hospital of Wuhan University, Wuhan, China
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Targeting disrupted rich-club network organization with neuroplasticity-based computerized cognitive remediation in major depressive disorder patients. Psychiatry Res 2022; 316:114742. [PMID: 35917652 DOI: 10.1016/j.psychres.2022.114742] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/26/2022] [Revised: 07/17/2022] [Accepted: 07/21/2022] [Indexed: 11/24/2022]
Abstract
Disrupted rich-club organization has been extensively studied in major depressive disorder (MDD) patients. Although data indicate that neuroplasticity-based computerized cognitive remediation (nCCR) can accelerate clinical responses in MDD patients, the mechanisms underlying its antidepressant efficacy are unknown. In this study, all MDD patients underwent two (baseline and week 4) neuropsychological assessments and DTI imaging. Additionally, 17 MDD patients did nCCR for 30 hours spread across 4 weeks. Rich-club organization was calculated with a graph-theoretical approach, and SC-FC coupling was explored. After 4 weeks of treatment, the number of rich-club connections, global efficiency, and SC-FC coupling strength increased significantly and were negatively associated with TMT-B scores. The effects of nCCR on disrupted rich-club organization may partly underlie its efficacy in improving the executive function of patients with MDD. Effects of nCCR on disrupted rich-club organization may partly underlie its efficacy in improving the executive function of patients with MDD.
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da Silva PHR, Paschoal AM, Secchinatto KF, Zotin MCZ, Dos Santos AC, Viswanathan A, Pontes-Neto OM, Leoni RF. Contrast agent-free state-of-the-art magnetic resonance imaging on cerebral small vessel disease - Part 2: Diffusion tensor imaging and functional magnetic resonance imaging. NMR IN BIOMEDICINE 2022; 35:e4743. [PMID: 35429070 DOI: 10.1002/nbm.4743] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/17/2022] [Accepted: 04/04/2022] [Indexed: 06/14/2023]
Abstract
Cerebral small vessel disease (cSVD) has been widely studied using conventional magnetic resonance imaging (MRI) methods, although the association between MRI findings and clinical features of cSVD is not always concordant. We assessed the additional contribution of contrast agent-free, state-of-the-art MRI techniques, particularly diffusion tensor imaging (DTI) and functional magnetic resonance imaging (fMRI), to understand brain damage and structural and functional connectivity impairment related to cSVD. We performed a review following the PICOS worksheet and Search Strategy, including 152 original papers in English, published from 2000 to 2022. For each MRI method, we extracted information about their contributions regarding the origins, pathology, markers, and clinical outcomes in cSVD. In general, DTI studies have shown that changes in mean, radial, and axial diffusivity measures are related to the presence of cSVD. In addition to the classical deficit in executive functions and processing speed, fMRI studies indicate connectivity dysfunctions in other domains, such as sensorimotor, memory, and attention. Neuroimaging metrics have been correlated with the diagnosis, prognosis, and rehabilitation of patients with cSVD. In short, the application of contrast agent-free, state-of-the-art MRI techniques has provided a complete picture of cSVD markers and tools to explore questions that have not yet been clarified about this clinical condition. Longitudinal studies are desirable to look for causal relationships between image biomarkers and clinical outcomes.
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Affiliation(s)
| | - André Monteiro Paschoal
- Department of Physics, FFCLRP, University of São Paulo, Ribeirão Preto, São Paulo, Brazil
- Department of Medical Imaging, Hematology and Clinical Oncology, Ribeirão Preto Medical School, University of São Paulo, Ribeirão Preto, Brazil
| | | | - Maria Clara Zanon Zotin
- Department of Medical Imaging, Hematology and Clinical Oncology, Ribeirão Preto Medical School, University of São Paulo, Ribeirão Preto, Brazil
- J Philip Kistler Stroke Research Center, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Antônio Carlos Dos Santos
- Department of Medical Imaging, Hematology and Clinical Oncology, Ribeirão Preto Medical School, University of São Paulo, Ribeirão Preto, Brazil
| | - Anand Viswanathan
- J Philip Kistler Stroke Research Center, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Octavio M Pontes-Neto
- Department of Neurosciences and Behavioral Science, Ribeirão Preto Medical School, University of Sao Paulo, Ribeirão Preto, São Paulo, Brazil
| | - Renata Ferranti Leoni
- Department of Physics, FFCLRP, University of São Paulo, Ribeirão Preto, São Paulo, Brazil
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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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Guan B, Xu Y, Chen YC, Xing C, Xu L, Shang S, Xu JJ, Wu Y, Yan Q. Reorganized Brain Functional Network Topology in Presbycusis. Front Aging Neurosci 2022; 14:905487. [PMID: 35693344 PMCID: PMC9177949 DOI: 10.3389/fnagi.2022.905487] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2022] [Accepted: 04/27/2022] [Indexed: 11/13/2022] Open
Abstract
Purpose Presbycusis is characterized by bilateral sensorineural hearing loss at high frequencies and is often accompanied by cognitive decline. This study aimed to identify the topological reorganization of brain functional network in presbycusis with/without cognitive decline by using graph theory analysis approaches based on resting-state functional magnetic resonance imaging (rs-fMRI). Methods Resting-state fMRI scans were obtained from 30 presbycusis patients with cognitive decline, 30 presbycusis patients without cognitive decline, and 50 age-, sex-, and education-matched healthy controls. Graph theory was applied to analyze the topological properties of brain functional networks including global and nodal metrics, modularity, and rich-club organization. Results At the global level, the brain functional networks of all participants were found to possess small-world properties. Also, significant group differences in global network metrics were observed among the three groups such as clustering coefficient, characteristic path length, normalized characteristic path length, and small-worldness. At the nodal level, several nodes with abnormal betweenness centrality, degree centrality, nodal efficiency, and nodal local efficiency were detected in presbycusis patients with/without cognitive decline. Changes in intra-modular connections in frontal lobe module and inter-modular connections in prefrontal subcortical lobe module were found in presbycusis patients exposed to modularity analysis. Rich-club nodes were reorganized in presbycusis patients, while the connections among them had no significant group differences. Conclusion Presbycusis patients exhibited topological reorganization of the whole-brain functional network, and presbycusis patients with cognitive decline showed more obvious changes in these topological properties than those without cognitive decline. Abnormal changes of these properties in presbycusis patients may compensate for cognitive impairment by mobilizing additional neural resources.
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Affiliation(s)
- Bing Guan
- Department of Otolaryngology, Head and Neck Surgery, Clinical Medical College, Yangzhou University, Yangzhou, China
| | - Yixi Xu
- Department of Otolaryngology, Head and Neck Surgery, Clinical Medical College, Yangzhou University, Yangzhou, China
| | - Yu-Chen Chen
- Department of Radiology, Nanjing First Hospital, Nanjing Medical University, Nanjing, China
| | - Chunhua Xing
- Department of Radiology, Nanjing First Hospital, Nanjing Medical University, Nanjing, China
| | - Li Xu
- Department of Otolaryngology, Head and Neck Surgery, Clinical Medical College, Yangzhou University, Yangzhou, China
| | - Song'an Shang
- Department of Radiology, Nanjing First Hospital, Nanjing Medical University, Nanjing, China
| | - Jin-Jing Xu
- Department of Otolaryngology, Nanjing First Hospital, Nanjing Medical University, Nanjing, China
| | - Yuanqing Wu
- Department of Otolaryngology, Nanjing First Hospital, Nanjing Medical University, Nanjing, China
- *Correspondence: Yuanqing Wu
| | - Qi Yan
- Department of Otolaryngology, Head and Neck Surgery, Clinical Medical College, Yangzhou University, Yangzhou, China
- Qi Yan
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Lan L, Chen YC, Shang S, Lu L, Xu JJ, Yin X, Wu Y, Cai Y. Topological features of limbic dysfunction in chronicity of tinnitus with intact hearing: New hypothesis for 'noise-cancellation' mechanism. Prog Neuropsychopharmacol Biol Psychiatry 2022; 113:110459. [PMID: 34666066 DOI: 10.1016/j.pnpbp.2021.110459] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/12/2021] [Revised: 10/11/2021] [Accepted: 10/12/2021] [Indexed: 12/17/2022]
Abstract
PURPOSE The reorganization of the limbic regions extend to general cognitive network is believed to exist in the chronicity of tinnitus with particular 'hubs' contributing to a 'noise-cancellation' mechanism. To test this hypothesis, we investigated the topological brain network of tinnitus in different periods. METHODS Resting-state functional magnetic resonance imaging were obtained from 32 patients with acute tinnitus, 41 patients with chronic tinnitus and 60 age- and gender- matched healthy controls (HC). The topological features of their brain networks were explored using graph theory analysis. RESULTS Common small-world attributes were compared between the three groups, all showed a significantly increased values in Cp, Lp, λ (all p < 0.05). Significantly increased nodal centralities in the left superior frontal gyrus and the right precuneus, significantly decreased nodal centralities in the right inferior temporal gyrus were observed for acute tinnitus patients compared to HC. While for chronic tinnitus patients, there were significant increased nodal centralities in the left hippocampus, amygdala, and temporal pole, but decreased nodal centralities in the right inferior temporal gyrus. Additionally, significant higher nodal centralities were found in bilateral medial superior frontal gyrus for acute tinnitus patients compared to chronic tinnitus patients. Besides, alterations in rich-club organization were found in acute tinnitus patients and chronic tinnitus patients compared with HC, with increased functional connections among rich-club nodes and peripheral nodes in patients with tinnitus. CONCLUSIONS Brain network topological properties altered across prefrontal-limbic-subcortical regions in tinnitus. The existed hubs in tinnitus might indicate an emotional and cognitive burden in 'noise-cancellation' mechanism.
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Affiliation(s)
- Liping Lan
- Department of Otolaryngology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou City, Guangdong Province, China
| | - Yu-Chen Chen
- 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
| | - Liyan Lu
- Department of Radiology, Nanjing First Hospital, Nanjing Medical University, Nanjing, China
| | - Jin-Jing Xu
- Department of Otolaryngology, Nanjing First Hospital, Nanjing Medical University, Nanjing, China
| | - Xindao Yin
- Department of Radiology, Nanjing First Hospital, Nanjing Medical University, Nanjing, China
| | - Yuanqing Wu
- Department of Otolaryngology, Nanjing First Hospital, Nanjing Medical University, Nanjing, China.
| | - Yuexin Cai
- Department of Otolaryngology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou City, Guangdong Province, China.
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Miao G, Rao B, Wang S, Fang P, Chen Z, Chen L, Zhang X, Zheng J, Xu H, Liao W. Decreased Functional Connectivities of Low-Degree Level Rich Club Organization and Caudate in Post-stroke Cognitive Impairment Based on Resting-State fMRI and Radiomics Features. Front Neurosci 2022; 15:796530. [PMID: 35250435 PMCID: PMC8890030 DOI: 10.3389/fnins.2021.796530] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2021] [Accepted: 12/31/2021] [Indexed: 11/13/2022] Open
Abstract
BackgroundStroke is an important cause of cognitive impairment. Rich club organization, a highly interconnected network brain core region, is closely related to cognition. We hypothesized that the disturbance of rich club organization exists in patients with post-stroke cognitive impairment (PSCI).MethodsWe collected data on resting-state functional magnetic resonance imaging (rs-fMRI) with 21 healthy controls (HC), 16 hemorrhagic stroke (hPSCI), and 21 infarct stroke (iPSCI). 3D shape features and first-order statistics of stroke lesions were extracted using 3D slicer software. Additionally, we assessed cognitive function using the Montreal Cognitive Assessment (MoCA) and Mini-Mental State Examination (MMSE).ResultsNormalized rich club coefficients were higher in hPSCI and iPSCI than HC at low-degree k-levels (k = 1–8 in iPSCI, k = 2–8 in hPSCI). Feeder and local connections were significantly decreased in PSCI patients versus HC, mainly distributed in salience network (SN), default-mode network (DMN), cerebellum network (CN), and orbitofrontal cortex (ORB), especially involving the right and left caudate with changed nodal efficiency. The feeder and local connections of significantly between-group difference were positively related to MMSE and MoCA scores, primarily distributed in the sensorimotor network (SMN) and visual network (VN) in hPSCI, SN, and DMN in iPSCI. Additionally, decreased local connections and low-degree ϕnorm(k) were correlated to 3D shape features and first-order statistics of stroke lesions.ConclusionThis study reveals the disrupted low-degree level rich club organization and relatively preserved functional core network in PSCI patients. Decreased feeder and local connections in cognition-related networks (DMN, SN, CN, and ORB), particularly involving the caudate nucleus, may offer insight into pathological mechanism of PSCI patients. The shape and signal features of stroke lesions may provide an essential clue for the damage of functional connectivity and the whole brain networks.
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Affiliation(s)
- Guofu Miao
- Department of Rehabilitation Medicine, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Bo Rao
- Department of Radiology, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Sirui Wang
- Department of Rehabilitation Medicine, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Pinyan Fang
- Department of Radiology, Zhongnan Hospital of Wuhan University, Wuhan, China
- Department of Radiology, TEDA International Cardiovascular Hospital, Tianjin, China
| | - Zhuo Chen
- Department of Rehabilitation Medicine, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Linglong Chen
- Department of Radiology, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Xin Zhang
- Department of Rehabilitation Medicine, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Jun Zheng
- Department of Rehabilitation Medicine, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Haibo Xu
- Department of Radiology, Zhongnan Hospital of Wuhan University, Wuhan, China
- *Correspondence: Haibo Xu,
| | - Weijing Liao
- Department of Rehabilitation Medicine, Zhongnan Hospital of Wuhan University, Wuhan, China
- Weijing Liao,
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11
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Egle M, Hilal S, Tuladhar AM, Pirpamer L, Bell S, Hofer E, Duering M, Wason J, Morris RG, Dichgans M, Schmidt R, Tozer DJ, Barrick TR, Chen C, de Leeuw FE, Markus HS. Determining the OPTIMAL DTI analysis method for application in cerebral small vessel disease. NEUROIMAGE: CLINICAL 2022; 35:103114. [PMID: 35908307 PMCID: PMC9421487 DOI: 10.1016/j.nicl.2022.103114] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2022] [Revised: 05/24/2022] [Accepted: 07/10/2022] [Indexed: 11/23/2022] Open
Abstract
We were not able to identify a single optimal diffusion-weighted imaging analysis strategy across all 6 cohorts. Diffusion tensor imaging measures at baseline predicted dementia conversion in cerebral small vessel disease and mild cognitive impairment. Diffusion tensor imaging measures at baseline may be sensitive to differentiate between later vascular dementia vs Alzheimer’s disease dementia. Diffusion tensor imaging measures significantly changed over time in cohorts with cerebral small vessel disease and cohorts with mild cognitive impairment. Change in diffusion tensor imaging measures were only consistently associated with dementia conversion in severe SVD. The diffusion tensor imaging measures PSMD and DSEG required the lowest minimum sample sizes for a hypothetical clinical trial in patients with sporadic cerebral small vessel disease and mild cognitive impairment.
Background DTI is sensitive to white matter (WM) microstructural damage and has been suggested as a surrogate marker for phase 2 clinical trials in cerebral small vessel disease (SVD). The study’s objective is to establish the best way to analyse the diffusion-weighted imaging data in SVD for this purpose. The ideal method would be sensitive to change and predict dementia conversion, but also straightforward to implement and ideally automated. As part of the OPTIMAL collaboration, we evaluated five different DTI analysis strategies across six different cohorts with differing SVD severity. Methods Those 5 strategies were: (1) conventional mean diffusivity WM histogram measure (MD median), (2) a principal component-derived measure based on conventional WM histogram measures (PC1), (3) peak width skeletonized mean diffusivity (PSMD), (4) diffusion tensor image segmentation θ (DSEG θ) and (5) a WM measure of global network efficiency (Geff). The association between each measure and cognitive function was tested using a linear regression model adjusted by clinical markers. Changes in the imaging measures over time were determined. In three cohort studies, repeated imaging data together with data on incident dementia were available. The association between the baseline measure, change measure and incident dementia conversion was examined using Cox proportional-hazard regression or logistic regression models. Sample size estimates for a hypothetical clinical trial were furthermore computed for each DTI analysis strategy. Results There was a consistent cross-sectional association between the imaging measures and impaired cognitive function across all cohorts. All baseline measures predicted dementia conversion in severe SVD. In mild SVD, PC1, PSMD and Geff predicted dementia conversion. In MCI, all markers except Geff predicted dementia conversion. Baseline DTI was significantly different in patients converting to vascular dementia than to Alzheimer’ s disease. Significant change in all measures was associated with dementia conversion in severe but not in mild SVD. The automatic and semi-automatic measures PSMD and DSEG θ required the lowest minimum sample sizes for a hypothetical clinical trial in single-centre sporadic SVD cohorts. Conclusion DTI parameters obtained from all analysis methods predicted dementia, and there was no clear winner amongst the different analysis strategies. The fully automated analysis provided by PSMD offers advantages particularly for large datasets.
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Affiliation(s)
- Marco Egle
- Stroke Research Group, Department of Clinical Neurosciences, University of Cambridge, Cambridge, United Kingdom.
| | - Saima Hilal
- Department of Pharmacology, National University of Singapore, Singapore; Memory Ageing and Cognition Center, National University Health System, Singapore
| | - Anil M Tuladhar
- Department of Neurology, Donders Center for Medical Neuroscience, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Lukas Pirpamer
- Department of Neurology, Medical University of Graz, Graz, Austria
| | - Steven Bell
- Stroke Research Group, Department of Clinical Neurosciences, University of Cambridge, Cambridge, United Kingdom
| | - Edith Hofer
- Department of Neurology, Medical University of Graz, Graz, Austria; Institute for Medical Informatics, Statistics and Documentation, Medical University of Graz, Graz, Austria
| | - Marco Duering
- Institute for Stroke and Dementia Research, University Hospital, LMU Munich, Munich, Germany; Medical Image Analysis Center (MIAC) and Department of Biomedical Engineering, University of Basel, Basel, Switzerland
| | - James Wason
- Population Health Sciences Institute, Newcastle University, Baddiley-Clark Building, Newcastle Upon Tyne, United Kingdom
| | - Robin G Morris
- Department of Psychology (R.G.M.), King's College, Institute of Psychiatry, Psychology and Neuroscience, London, United Kingdom
| | - Martin Dichgans
- Institute for Stroke and Dementia Research, University Hospital, LMU Munich, Munich, Germany; Munich Cluster for Systems Neurology (SyNergy), Munich, Germany; German Center for Neurodegenerative Diseases (DZNE), Munich, Germany
| | - Reinhold Schmidt
- Department of Neurology, Medical University of Graz, Graz, Austria
| | - Daniel J Tozer
- Stroke Research Group, Department of Clinical Neurosciences, University of Cambridge, Cambridge, United Kingdom
| | - Thomas R Barrick
- Neurosciences Research Centre, Institute for Molecular and Clinical Sciences, St George's, University of London, United Kingdom
| | - Christopher Chen
- Department of Pharmacology, National University of Singapore, Singapore; Memory Ageing and Cognition Center, National University Health System, Singapore
| | - Frank-Erik de Leeuw
- Department of Neurology, Donders Center for Medical Neuroscience, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Hugh S Markus
- Stroke Research Group, Department of Clinical Neurosciences, University of Cambridge, Cambridge, United Kingdom
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12
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de Brito Robalo BM, Biessels GJ, Chen C, Dewenter A, Duering M, Hilal S, Koek HL, Kopczak A, Yin Ka Lam B, Leemans A, Mok V, Onkenhout LP, van den Brink H, de Luca A. Diffusion MRI harmonization enables joint-analysis of multicentre data of patients with cerebral small vessel disease. Neuroimage Clin 2021; 32:102886. [PMID: 34911192 PMCID: PMC8609094 DOI: 10.1016/j.nicl.2021.102886] [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: 10/21/2021] [Accepted: 11/16/2021] [Indexed: 01/10/2023]
Abstract
OBJECTIVES Acquisition-related differences in diffusion magnetic resonance imaging (dMRI) hamper pooling of multicentre data to achieve large sample sizes. A promising solution is to harmonize the raw diffusion signal using rotation invariant spherical harmonic (RISH) features, but this has not been tested in elderly subjects. Here we aimed to establish if RISH harmonization effectively removes acquisition-related differences in multicentre dMRI of elderly subjects with cerebral small vessel disease (SVD), while preserving sensitivity to disease effects. METHODS Five cohorts of patients with SVD (N = 397) and elderly controls (N = 175) with 3 Tesla MRI on different systems were included. First, to establish effectiveness of harmonization, the RISH method was trained with data of 13 to 15 age and sex-matched controls from each site. Fractional anisotropy (FA) and mean diffusivity (MD) were compared in matched controls between sites using tract-based spatial statistics (TBSS) and voxel-wise analysis, before and after harmonization. Second, to assess sensitivity to disease effects, we examined whether the contrast (effect sizes of FA, MD and peak width of skeletonized MD - PSMD) between patients and controls within each site remained unaffected by harmonization. Finally, we evaluated the association between white matter hyperintensity (WMH) burden, FA, MD and PSMD using linear regression analyses both within individual cohorts as well as with pooled scans from multiple sites, before and after harmonization. RESULTS Before harmonization, significant differences in FA and MD were observed between matched controls of different sites (p < 0.05). After harmonization these site-differences were removed. Within each site, RISH harmonization did not alter the effect sizes of FA, MD and PSMD between patients and controls (relative change in Cohen's d = 4 %) nor the strength of association with WMH volume (relative change in R2 = 2.8 %). After harmonization, patient data of all sites could be aggregated in a single analysis to infer the association between WMH volume and FA (R2 = 0.62), MD (R2 = 0.64), and PSMD (R2 = 0.60). CONCLUSIONS We showed that RISH harmonization effectively removes acquisition-related differences in dMRI of elderly subjects while preserving sensitivity to SVD-related effects. This study provides proof of concept for future multicentre SVD studies with pooled datasets.
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Affiliation(s)
- Bruno M de Brito Robalo
- Department of Neurology and Neurosurgery, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht, The Netherlands; Image Sciences Institute, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands.
| | - Geert Jan Biessels
- Department of Neurology and Neurosurgery, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht, The Netherlands.
| | - Christopher Chen
- Memory, Aging and Cognition Center, Department of Pharmacology, National University of Singapore, Singapore.
| | - Anna Dewenter
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Germany.
| | - Marco Duering
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Germany; Medical Image Analysis Center (MIAC AG) and qbig, Department of Biomedical Engineering, University of Basel, Basel, Switzerland.
| | - Saima Hilal
- Memory, Aging and Cognition Center, Department of Pharmacology, National University of Singapore, Singapore.
| | - Huiberdina L Koek
- Department of Geriatric Medicine, University Medical Center Utrecht, Utrecht, The Netherlands.
| | - Anna Kopczak
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Germany.
| | - Bonnie Yin Ka Lam
- Division of Neurology, Department of Medicine and Therapeutics, Gerald Choa Neuroscience Centre, Faculty of Medicine, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region.
| | - Alexander Leemans
- Image Sciences Institute, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands.
| | - Vincent Mok
- Division of Neurology, Department of Medicine and Therapeutics, Gerald Choa Neuroscience Centre, Faculty of Medicine, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region.
| | - Laurien P Onkenhout
- Department of Neurology and Neurosurgery, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht, The Netherlands.
| | - Hilde van den Brink
- Department of Neurology and Neurosurgery, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht, The Netherlands.
| | - Alberto de Luca
- Department of Neurology and Neurosurgery, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht, The Netherlands; Image Sciences Institute, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands.
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13
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Lu Y, Li Y, Feng Q, Shen R, Zhu H, Zhou H, Zhao Z. Rich-Club Analysis of the Structural Brain Network in Cases with Cerebral Small Vessel Disease and Depression Symptoms. Cerebrovasc Dis 2021; 51:92-101. [PMID: 34537766 DOI: 10.1159/000517243] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2021] [Accepted: 05/13/2021] [Indexed: 11/19/2022] Open
Abstract
BACKGROUND Altered white matter brain networks have been extensively studied in cerebral small vessel disease (SVD). However, there exists currently a deficiency of comprehending the performance of changes within the structural networks of the brain in cases with cerebral SVD and depression symptoms. The main aim of the present research is to study the network topology behaviors and features of rich-club organization in SVD patients using graph theory and diffusion tensor imaging (DTI) to characterize changes in the microstructure of the brain. METHODS DTI datasets were acquired from 26 SVD patients with symptoms of depression (SVD + D) and 26 SVD patients without symptoms of depression (SVD - D), and a series of neuropsychological assessments were completed. A structural network was created using a deterministic fiber tracking method. The analysis of rich-club was performed in company with analysis of the global network features of the network to characterize the topological properties of all subjects. RESULTS DTI data were obtained from SVD patients who manifested symptoms of depression (SVD + D) and from control SVD patients (SVD - D). In comparison with SVD - D patients, SVD + D cases demonstrated a diminished coefficient of clustering along with lower global efficiencies and longer path length characteristics. Rich-club analysis showed SVD + D patients had decreased feeder connectivity and local connectivity strengths compared to SVD - D patients. Our data also showed that the feeder connections in the brain correlated significantly with the severity of depression in SVD + D patients. CONCLUSIONS Our study revealed that SVD patients with depressive symptoms have disrupted white matter networks that characteristically have reduced network efficiency compared to the networks in other SVD patients. Disrupted information interactions among the regions of nonrich-club and rich-club in SVD cases are related to the severity of depression. Our data suggest that DTI may be utilized as an appropriate biomarker for the diagnosis of depression in comorbid SVD patients.
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Affiliation(s)
- Yanjing Lu
- Department of Neurology, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou, China
| | - Yifan Li
- Department of Neurology, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou, China
| | - Qian Feng
- Department of Neurology, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou, China
| | - Rong Shen
- Department of Neurology, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou, China
| | - Hao Zhu
- Department of Neurology, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou, China
| | - Hua Zhou
- Department of Neurology, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou, China
| | - Zhong Zhao
- Department of Neurology, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou, China
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14
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Qiao Y, He X, Zhang J, Liang Y, Shao W, Zhang Z, Zhang S, Peng D. The Associations Between White Matter Disruptions and Cognitive Decline at the Early Stage of Subcortical Vascular Cognitive Impairment: A Case-Control Study. Front Aging Neurosci 2021; 13:681208. [PMID: 34408641 PMCID: PMC8364958 DOI: 10.3389/fnagi.2021.681208] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2021] [Accepted: 06/04/2021] [Indexed: 11/13/2022] Open
Abstract
Objective Emerging evidence suggests that white matter (WM) disruption is associated with the incidence of subcortical vascular cognitive impairment (SVCI). However, our knowledge regarding this relationship in the early stage of SVCI is limited. We aimed to investigate the associations between WM disruptions and cognitive declines at the early stage of SVCI. Method We performed a case–control study, involving 22 cases and 19 controls. The cases were patients at the early stage of SVCI, which was defined as subcortical ischemic vascular disease with normal global cognitive measures (pre-SVCI). The controls were healthy people matched by age, sex, and education years. We assessed the differences in a battery of neuropsychological tests between the two groups, investigated the diffusion changes in 40 WM tracts among the participants via an atlas-based segmentation strategy, and compared the differences between the cases and controls by multiple linear regression analysis. We then evaluated the relationships between diffusion indices and cognitive assessment scores by Pearson’s correlation. Results The pre-SVCI group exhibited significant differences in the Montreal cognitive assessment (MoCA), Rey–Osterrieth Complex Figure (R-O)-copy, and Trail Making Test (TMT)-B test compared with the controls. Compared with the controls, some long associative and projective bundles, such as the right anterior corona radiata (ACR), the right inferior fronto-occipital fasciculus (IFOF), and the left external capsule (EC), were extensively damaged in cases after Bonferroni correction (p < 0.05/40). Damages to specific fibers, such as the right ACR, IFOF, and posterior thalamic radiation (PTR), exhibited significant correlations with declines in MoCA, R-O delay, and the Mini-Mental State Examination (MMSE), respectively, after Bonferroni correction (p < 0.05/14). Conclusion Long WM tracts, especially those in the right hemisphere, were extensively damaged in the pre-SVCI patients and correlated with declines in executive functions and spatial processing. Patients of pre-SVCI are likely at an ultra-early stage of SVCI, and there is a very high risk of this condition becoming SVCI.
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Affiliation(s)
- Yanan Qiao
- Department of Neurology, China-Japan Friendship Hospital, Beijing, China
| | - Xuwen He
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Junying Zhang
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Ying Liang
- School of Biomedical Engineering, Capital Medical University, Beijing, China
| | - Wen Shao
- Department of Neurology, China-Japan Friendship Hospital, Beijing, China
| | - Zhanjun Zhang
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Sihang Zhang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
| | - Dantao Peng
- Department of Neurology, China-Japan Friendship Hospital, Beijing, China
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15
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Liu X, Cheng R, Chen L, Gong J, Luo T, Lv F. Altered Neurovascular Coupling in Subcortical Ischemic Vascular Disease. Front Aging Neurosci 2021; 13:598365. [PMID: 34054499 PMCID: PMC8149589 DOI: 10.3389/fnagi.2021.598365] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2020] [Accepted: 03/18/2021] [Indexed: 11/18/2022] Open
Abstract
Patients with subcortical ischemic vascular disease (SIVD) exhibit a high risk of cognitive impairment that might be caused by neurologic deficits and vascular injuries. However, the mechanism remains unknown. In current study, 24 normal controls (NC) and 54 SIVD patients, including 26 SIVD patients with no cognitive impairment (SIVD-NCI) and 28 SIVD patients with mild cognitive impairment (SIVD-MCI) underwent the resting-state functional MRI (rs-fMRI) and neuropsychological assessments. We combined regional homogeneity (ReHo) and cerebral blood flow (CBF) by using the global ReHo-CBF correlations coefficient and the ReHo/CBF ratio to detect the inner link between neuronal activity and vascular responses. Correlations between the ReHo/CBF ratio and neuropsychological assessments were explored in patients with SIVD. As a result, we identified significantly decreased global ReHo-CBF coupling in the SIVD-NCI group and SIVD- MCI group with respect to the NC. The SIVD-MCI group showed more serious decoupling of the global ReHo-CBF correlation. We also found a significantly abnormal ReHo/CBF ratio predominantly located in cognitive-related brain regions, including the left insula, right middle temporal gyrus, right precuneus, left precentral gyrus, and left inferior parietal lobule but not the supramarginal and angular gyri. The SIVD-MCI group showed more severe disorders of neurovascular coupling than the other two groups. Moreover, the ReHo/CBF ratio in the left precentral gyrus of the SIVD-NCI group exhibited a positive correlation with the MMSE scores. These findings suggested that patients with SIVD show abnormal neurovascular coupling at the early stage of the disease and during disease development. It might be associated with disease severity and cognitive impairment. Neurovascular decoupling in brain may be a possible neuropathological mechanism of SIVD.
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Affiliation(s)
- Xiaoshuang Liu
- Department of Radiology, First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Runtian Cheng
- Department of Radiology, First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Li Chen
- Department of Radiology, Affiliated Hospital of North Sichuan Medical College, Sichuan, China
| | - Junwei Gong
- Department of Radiology, First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Tianyou Luo
- Department of Radiology, First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Fajin Lv
- Department of Radiology, First Affiliated Hospital of Chongqing Medical University, Chongqing, China
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16
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Kim DJ, Min BK. Rich-club in the brain's macrostructure: Insights from graph theoretical analysis. Comput Struct Biotechnol J 2020; 18:1761-1773. [PMID: 32695269 PMCID: PMC7355726 DOI: 10.1016/j.csbj.2020.06.039] [Citation(s) in RCA: 36] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2020] [Revised: 06/19/2020] [Accepted: 06/22/2020] [Indexed: 02/07/2023] Open
Abstract
The brain is a complex network. Growing evidence supports the critical roles of a set of brain regions within the brain network, known as the brain’s cores or hubs. These regions require high energy cost but possess highly efficient neural information transfer in the brain’s network and are termed the rich-club. The rich-club of the brain network is essential as it directly regulates functional integration across multiple segregated regions and helps to optimize cognitive processes. Here, we review the recent advances in rich-club organization to address the fundamental roles of the rich-club in the brain and discuss how these core brain regions affect brain development and disorders. We describe the concepts of the rich-club behind network construction in the brain using graph theoretical analysis. We also highlight novel insights based on animal studies related to the rich-club and illustrate how human studies using neuroimaging techniques for brain development and psychiatric/neurological disorders may be relevant to the rich-club phenomenon in the brain network.
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Key Words
- AD, Alzheimer’s disease
- ADHD, attention deficit hyperactivity disorder
- ASD, autism spectrum disorder
- BD, bipolar disorder
- Brain connectivity
- Brain network
- DTI, diffusion tensor imaging
- EEG, electroencephalography
- Graph theory
- MDD, major depressive disorder
- MEG, magnetoencephalography
- MRI, magnetic resonance imaging
- Neuroimaging
- Rich-club
- TBI, traumatic brain injury
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Affiliation(s)
- Dae-Jin Kim
- Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN 47405, USA
| | - Byoung-Kyong Min
- Department of Brain and Cognitive Engineering, Korea University, Seoul 02841, Republic of Korea
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