1
|
Chen Y, Liang L, Wei Y, Liu Y, Li X, Zhang Z, Li L, Deng D. Disrupted morphological brain network organization in subjective cognitive decline and mild cognitive impairment. Brain Imaging Behav 2024; 18:387-395. [PMID: 38147273 DOI: 10.1007/s11682-023-00839-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/01/2023] [Indexed: 12/27/2023]
Abstract
We aim to investigate the alterations in gray matter for subjective cognitive decline (SCD) and mild cognitive impairment (MCI) from the perspective of the human connectome. High-resolution T1-weighted images were acquired from 54 patients with SCD, 95 patients with MCI, and 65 healthy controls (HC). Morphological brain networks (MBN) were constructed using similarities in the distribution of gray matter volumes between regions. The strength of morphological connections and topographic metrics derived from the graph-theoretical analysis were compared. Furthermore, we assessed the relationship between the observed morphological abnormalities and disease severity. According to the results, we found a significantly decreased morphological connection between the somatomotor network and ventral attention network in SCD compared to HC and MCI compared to SCD. The graph-theoretic analysis illustrated disruptions in the whole network organization, where the normalized shortest path increased and the global efficiency (Eg) decreased in MCI compared to SCD. In addition, Montreal Cognitive Assessment scores of SCD patients had a significantly negative correlation with Eg. The primary limitations of the present study include the cross-sectional design, no enrolled AD patients, no assessment of amyloidosis, and the need for more comprehensive neuropsychological tests. Our findings indicate the abnormalities of morphological networks at early stages in the AD continuum, which could be interpreted as compensatory changes to retain a normal level of cognitive function. The present study could provide new insight into the mechanism of AD.
Collapse
Affiliation(s)
- Yuxin Chen
- Medical College of Guangxi University, Guangxi University, Nanning, Guangxi, China
- Department of Radiology, the People's Hospital of Guangxi Zhuang Autonomous Region, Guangxi Academy of Medical Science, Nanning, Guangxi, China
| | - Lingyan Liang
- Department of Radiology, the People's Hospital of Guangxi Zhuang Autonomous Region, Guangxi Academy of Medical Science, Nanning, Guangxi, China
| | - Yichen Wei
- Department of Radiology, the People's Hospital of Guangxi Zhuang Autonomous Region, Guangxi Academy of Medical Science, Nanning, Guangxi, China
| | - Ying Liu
- Department of Radiology, the People's Hospital of Guangxi Zhuang Autonomous Region, Guangxi Academy of Medical Science, Nanning, Guangxi, China
| | - Xiaocheng Li
- Department of Radiology, the People's Hospital of Guangxi Zhuang Autonomous Region, Guangxi Academy of Medical Science, Nanning, Guangxi, China
| | - Zhiguo Zhang
- School of Computer Science and Technology, Harbin Institute of Technology, Shenzhen, Guangdong, China
- Peng Cheng Laboratory, Shenzhen, Guangdong, China
| | - Linling Li
- School of Biomedical Engineering, Shenzhen University Medical School, Shenzhen University, Shenzhen, Guangdong, China.
- Guangdong Provincial Key Laboratory of Biomedical Measurements and Ultrasound Imaging, Shenzhen, Guangdong, China.
| | - Demao Deng
- Medical College of Guangxi University, Guangxi University, Nanning, Guangxi, China.
- Department of Radiology, the People's Hospital of Guangxi Zhuang Autonomous Region, Guangxi Academy of Medical Science, Nanning, Guangxi, China.
| |
Collapse
|
2
|
Maruoka H, Hattori T, Hase T, Takahashi K, Ohara M, Orimo S, Yokota T. Aberrant morphometric networks in Alzheimer's disease have hemispheric asymmetry and age dependence. Eur J Neurosci 2024; 59:1332-1347. [PMID: 38105486 DOI: 10.1111/ejn.16225] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2023] [Revised: 11/24/2023] [Accepted: 11/27/2023] [Indexed: 12/19/2023]
Abstract
Alzheimer's disease (AD) is associated with abnormal accumulations of hyperphosphorylated tau and amyloid-β proteins, resulting in unique patterns of atrophy in the brain. We aimed to elucidate some characteristics of the AD's morphometric networks constructed by associating different morphometric features among brain areas and evaluating their relationship to Mini-Mental State Examination total score and age. Three-dimensional T1-weighted (3DT1) image data scanned by the same 1.5T magnetic resonance imaging (MRI) were obtained from 62 AD patients and 41 healthy controls (HCs) and were analysed by using FreeSurfer. The associations of the extracted six morphometric features between regions were estimated by correlation coefficients. The global and local graph theoretical measures for this network were evaluated. Associations between graph theoretical measures and age, sex and cognition were evaluated by multiple regression analysis in each group. Global measures of integration: global efficiency and mean information centrality were significantly higher in AD patients. Local measures of integration: node global efficiency and information centrality were significantly higher in the entorhinal cortex, fusiform gyrus and posterior cingulate cortex of AD patients but only in the left hemisphere. All global measures were correlated with age in AD patients but not in HCs. The information centrality was associated with age in AD's broad brain regions. Our results showed that altered morphometric networks due to AD are left-hemisphere dominant, suggesting that AD pathogenesis has a left-right asymmetry. Ageing has a unique impact on the morphometric networks in AD patients. The information centrality is a sensitive graph theoretical measure to detect this association.
Collapse
Affiliation(s)
- Hiroyuki Maruoka
- Department of Neurology and Neurological Science, Graduate School of Medical and Dental Science, Tokyo Medical and Dental University, Tokyo, Japan
- Department of Neurology, Kanto Central Hospital, Tokyo, Japan
| | - Takaaki Hattori
- Department of Neurology and Neurological Science, Graduate School of Medical and Dental Science, Tokyo Medical and Dental University, Tokyo, Japan
| | - Takeshi Hase
- Innovative Human Resource Development Division, Institute of Education, Tokyo Medical and Dental University, Tokyo, Japan
- Faculty of Pharmacy, Keio University, Tokyo, Japan
- Research, The Systems Biology Institute, Tokyo, Japan
- Research, SBX BioSciences, Vancouver, British Columbia, Canada
| | - Kunihiko Takahashi
- Department of Biostatistics, M&D Data Science Center, Tokyo Medical and Dental University, Tokyo, Japan
| | - Masahiro Ohara
- Department of Neurology and Neurological Science, Graduate School of Medical and Dental Science, Tokyo Medical and Dental University, Tokyo, Japan
| | - Satoshi Orimo
- Department of Neurology, Kanto Central Hospital, Tokyo, Japan
| | - Takanori Yokota
- Department of Neurology and Neurological Science, Graduate School of Medical and Dental Science, Tokyo Medical and Dental University, Tokyo, Japan
| |
Collapse
|
3
|
Zhang W, Duan Y, Qi L, Li Z, Ren J, Nangale N, Yang C. Distinguishing Patients with MRI-Negative Temporal Lobe Epilepsy from Normal Controls Based on Individual Morphological Brain Network. Brain Topogr 2023:10.1007/s10548-023-00962-z. [PMID: 37204610 DOI: 10.1007/s10548-023-00962-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2022] [Accepted: 04/15/2023] [Indexed: 05/20/2023]
Abstract
Temporal Lobe Epilepsy (TLE) is the most common subtype of focal epilepsy and the most refractory to drug treatment. Roughly 30% of patients do not have easily identifiable structural abnormalities. In other words, MRI-negative TLE has normal MRI scans on visual inspection. Thus, MRI-negative TLE is a diagnostic and therapeutic challenge. In this study, we investigate the cortical morphological brain network to identify MRI-negative TLE. The 210 cortical ROIs based on the Brainnetome atlas were used to define the network nodes. The least absolute shrinkage and selection operator (LASSO) algorithm and Pearson correlation methods were used to calculate the inter-regional morphometric features vector correlation respectively. As a result, two types of networks were constructed. The topological characteristics of networks were calculated by graph theory. Then after, a two-stage feature selection strategy, including a two-sample t-test and support vector machine-based recursive feature elimination (SVM-RFE), was performed in feature selection. Finally, classification with support vector machine (SVM) and leave-one-out cross-validation (LOOCV) was employed for the training and evaluation of the classifiers. The performance of two constructed brain networks was compared in MRI-negative TLE classification. The results indicated that the LASSO algorithm achieved better performance than the Pearson pairwise correlation method. The LASSO algorithm provides a robust method of individual morphological network construction for distinguishing patients with MRI-negative TLE from normal controls.
Collapse
Affiliation(s)
- Wenxiu Zhang
- Department of Environment and Life Sciences, Beijing University of Technology, Beijing, China
| | - Ying Duan
- Beijing Universal Medical Imaging Diagnostic Center, Beijing, China
| | - Lei Qi
- Beijing Universal Medical Imaging Diagnostic Center, Beijing, China
| | - Zhimei Li
- Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Jiechuan Ren
- Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | | | - Chunlan Yang
- Department of Environment and Life Sciences, Beijing University of Technology, Beijing, China.
| |
Collapse
|
4
|
Identification of Alzheimer’s Disease Progression Stages Using Topological Measures of Resting-State Functional Connectivity Networks: A Comparative Study. Behav Neurol 2022; 2022:9958525. [PMID: 35832401 PMCID: PMC9273422 DOI: 10.1155/2022/9958525] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2021] [Revised: 02/19/2022] [Accepted: 06/17/2022] [Indexed: 11/21/2022] Open
Abstract
Resting-state functional magnetic resonance imaging (rs-fMRI) has been widely employed to examine brain functional connectivity (FC) alterations in various neurological disorders. At present, various computational methods have been proposed to estimate connectivity strength between different brain regions, as the edge weight of FC networks. However, little is known about which model is more sensitive to Alzheimer's disease (AD) progression. This study comparatively characterized topological properties of rs-FC networks constructed with Pearson correlation (PC), dynamic time warping (DTW), and group information guided independent component analysis (GIG-ICA), aimed at investigating the sensitivity and effectivity of these methods in differentiating AD stages. A total of 54 subjects from Alzheimer's Disease Neuroimaging Initiative (ANDI) database, divided into healthy control (HC), mild cognition impairment (MCI), and AD groups, were included in this study. Network-level (global efficiency and characteristic path length) and nodal (clustering coefficient) metrics were used to capture groupwise difference across HC, MCI, and AD groups. The results showed that almost no significant differences were found according to global efficiency and characteristic path length. However, in terms of clustering coefficient, 52 brain parcels sensitive to AD progression were identified in rs-FC networks built with GIG-ICA, much more than PC (6 parcels) and DTW (3 parcels). This indicates that GIG-ICA is more sensitive to AD progression than PC and DTW. The findings also confirmed that the AD-linked FC alterations mostly appeared in temporal, cingulate, and angular areas, which might contribute to clinical diagnosis of AD. Overall, this study provides insights into the topological properties of rs-FC networks over AD progression, suggesting that FC strength estimation of FC networks cannot be neglected in AD-related graph analysis.
Collapse
|
5
|
Fu Z, Zhao M, He Y, Wang X, Li X, Kang G, Han Y, Li S. Aberrant topological organization and age-related differences in the human connectome in subjective cognitive decline by using regional morphology from magnetic resonance imaging. Brain Struct Funct 2022; 227:2015-2033. [PMID: 35579698 DOI: 10.1007/s00429-022-02488-9] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2021] [Accepted: 03/24/2022] [Indexed: 11/25/2022]
Abstract
Subjective cognitive decline (SCD) is characterized by self-experienced deficits in cognitive capacity with normal performance in objective cognitive tests. Previous structural covariance studies showed specific insights into understanding the structural alterations of the brain in neurodegenerative diseases. Moreover, in subjects with neurodegenerative diseases, accelerated brain degeneration with aging was shown. However, the age-related variations in coordinated topological patterns of morphological networks in individuals with SCD remain poorly understood. In this study, 77 individual morphological networks were constructed, including 42 normal controls (NCs) and 35 SCD individuals, from structural magnetic resonance imaging (sMRI). A stepwise linear regression model and partial correlation analysis were constructed to evaluate the differences in age-related alterations of the network properties in individuals with SCD compared with NCs. Compared with NC, the properties of integration and segregation in individuals with SCD were lower, and the aberrant metrics were negatively correlated with age in SCD. The rich-club connections persevered, but the paralimbic system connections were disrupted in individuals with SCD compared with NCs. In addition, age-related differences in nodal global efficiency are distributed mainly in prefrontal cortex regions. In conclusion, the age-related disruption of topological organizations in individuals with SCD may indicate that the degeneration of brain efficiency with aging was accelerated in individuals with SCD.
Collapse
Affiliation(s)
- Zhenrong Fu
- Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science & Medical Engineering, Beihang University, Beijing, China
| | - Mingyan Zhao
- Department of Neurology, Tangshan Gongren Hospital, Tangshan, Hebei, China
- Department of Neurology, XuanWu Hospital of Capital Medical University, Beijing, China
| | - Yirong He
- Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science & Medical Engineering, Beihang University, Beijing, China
| | - Xuetong Wang
- Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science & Medical Engineering, Beihang University, Beijing, China
| | - Xin Li
- School of Electrical Engineering, Yanshan University, Qinhuangdao, China
- Measurement Technology and Instrumentation Key Lab of Hebei Province, Qinhuangdao, China
| | - Guixia Kang
- School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing, China
| | - Ying Han
- Department of Neurology, XuanWu Hospital of Capital Medical University, Beijing, China
- Center of Alzheimer's Disease, Beijing Institute for Brain Disorders, Beijing, China
- Biomedical Engineering Institute, Hainan University, Haikou, China
- National Clinical Research Center for Geriatric Disorders, Beijing, China
| | - Shuyu Li
- Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science & Medical Engineering, Beihang University, Beijing, China.
| |
Collapse
|
6
|
Zhang W, Yang C, Li Z, Ren J. A Comparison of Three Brain Atlases for Temporal Lobe Epilepsy Prediction. J Med Biol Eng 2022. [DOI: 10.1007/s40846-021-00676-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
|
7
|
Singh K, Cauzzo S, García-Gomar MG, Stauder M, Vanello N, Passino C, Bianciardi M. Functional connectome of arousal and motor brainstem nuclei in living humans by 7 Tesla resting-state fMRI. Neuroimage 2022; 249:118865. [PMID: 35031472 DOI: 10.1016/j.neuroimage.2021.118865] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2021] [Revised: 11/30/2021] [Accepted: 12/27/2021] [Indexed: 01/21/2023] Open
Abstract
Brainstem nuclei play a pivotal role in many functions, such as arousal and motor control. Nevertheless, the connectivity of arousal and motor brainstem nuclei is understudied in living humans due to the limited sensitivity and spatial resolution of conventional imaging, and to the lack of atlases of these deep tiny regions of the brain. For a holistic comprehension of sleep, arousal and associated motor processes, we investigated in 20 healthy subjects the resting-state functional connectivity of 18 arousal and motor brainstem nuclei in living humans. To do so, we used high spatial-resolution 7 Tesla resting-state fMRI, as well as a recently developed in-vivo probabilistic atlas of these nuclei in stereotactic space. Further, we verified the translatability of our brainstem connectome approach to conventional (e.g. 3 Tesla) fMRI. Arousal brainstem nuclei displayed high interconnectivity, as well as connectivity to the thalamus, hypothalamus, basal forebrain and frontal cortex, in line with animal studies and as expected for arousal regions. Motor brainstem nuclei showed expected connectivity to the cerebellum, basal ganglia and motor cortex, as well as high interconnectivity. Comparison of 3 Tesla to 7 Tesla connectivity results indicated good translatability of our brainstem connectome approach to conventional fMRI, especially for cortical and subcortical (non-brainstem) targets and to a lesser extent for brainstem targets. The functional connectome of 18 arousal and motor brainstem nuclei with the rest of the brain might provide a better understanding of arousal, sleep and accompanying motor function in living humans in health and disease.
Collapse
Affiliation(s)
- Kavita Singh
- Brainstem Imaging Laboratory, Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States.
| | - Simone Cauzzo
- Brainstem Imaging Laboratory, Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States; Institute of Life Sciences, Sant'Anna School of Advanced Studies, Pisa, Italy
| | - María Guadalupe García-Gomar
- Brainstem Imaging Laboratory, Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
| | - Matthew Stauder
- Brainstem Imaging Laboratory, Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
| | - Nicola Vanello
- Dipartimento di Ingegneria dell'Informazione, University of Pisa, Pisa, Italy
| | - Claudio Passino
- Institute of Life Sciences, Sant'Anna School of Advanced Studies, Pisa, Italy; Fondazione Toscana Gabriele Monasterio, Pisa, Italy
| | - Marta Bianciardi
- Brainstem Imaging Laboratory, Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States; Division of Sleep Medicine, Harvard University, Boston, MA.
| |
Collapse
|
8
|
Sheng X, Chen H, Shao P, Qin R, Zhao H, Xu Y, Bai F. Brain Structural Network Compensation Is Associated With Cognitive Impairment and Alzheimer's Disease Pathology. Front Neurosci 2021; 15:630278. [PMID: 33716654 PMCID: PMC7947929 DOI: 10.3389/fnins.2021.630278] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2020] [Accepted: 01/26/2021] [Indexed: 12/12/2022] Open
Abstract
BACKGROUND Structural network alterations in Alzheimer's disease (AD) are related to worse cognitive impairment. The aim of this study was to quantify the alterations in gray matter associated with impaired cognition and their pathological biomarkers in AD-spectrum patients. METHODS We extracted gray matter networks from 3D-T1 magnetic resonance imaging scans, and a graph theory analysis was used to explore alterations in the network metrics in 34 healthy controls, 70 mild cognitive impairment (MCI) patients, and 40 AD patients. Spearman correlation analysis was computed to investigate the relationships among network properties, neuropsychological performance, and cerebrospinal fluid pathological biomarkers (i.e., Aβ, t-tau, and p-tau) in these subjects. RESULTS AD-spectrum individuals demonstrated higher nodal properties and edge properties associated with impaired memory function, and lower amyloid-β or higher tau levels than the controls. Furthermore, these compensations at the brain regional level in AD-spectrum patients were mainly in the medial temporal lobe; however, the compensation at the whole-brain network level gradually extended from the frontal lobe to become widely distributed throughout the cortex with the progression of AD. CONCLUSION The findings provide insight into the alterations in the gray matter network related to impaired cognition and pathological biomarkers in the progression of AD. The possibility of compensation was detected in the structural networks in AD-spectrum patients; the compensatory patterns at regional and whole-brain levels were different and the clinical significance was highlighted.
Collapse
Affiliation(s)
- Xiaoning Sheng
- Department of Neurology, Affiliated Drum Tower Hospital of Medical School and The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing, China
| | - Haifeng Chen
- Department of Neurology, Affiliated Drum Tower Hospital of Medical School and The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing, China
- Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China
- Nanjing Neuropsychiatry Clinic Medical Center, Nanjing, China
| | - Pengfei Shao
- Department of Neurology, Affiliated Drum Tower Hospital of Medical School and The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing, China
| | - Ruomeng Qin
- Department of Neurology, Affiliated Drum Tower Hospital of Medical School and The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing, China
- Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China
- Nanjing Neuropsychiatry Clinic Medical Center, Nanjing, China
| | - Hui Zhao
- Department of Neurology, Affiliated Drum Tower Hospital of Medical School and The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing, China
- Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China
- Nanjing Neuropsychiatry Clinic Medical Center, Nanjing, China
| | - Yun Xu
- Department of Neurology, Affiliated Drum Tower Hospital of Medical School and The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing, China
- Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China
- Nanjing Neuropsychiatry Clinic Medical Center, Nanjing, China
| | - Feng Bai
- Department of Neurology, Affiliated Drum Tower Hospital of Medical School and The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing, China
- Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China
- Nanjing Neuropsychiatry Clinic Medical Center, Nanjing, China
| | | |
Collapse
|
9
|
Chan YL, Ung WC, Lim LG, Lu CK, Kiguchi M, Tang TB. Automated Thresholding Method for fNIRS-Based Functional Connectivity Analysis: Validation With a Case Study on Alzheimer's Disease. IEEE Trans Neural Syst Rehabil Eng 2020; 28:1691-1701. [PMID: 32746314 DOI: 10.1109/tnsre.2020.3007589] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
While functional integration has been suggested to reflect brain health, non-standardized network thresholding methods complicate network interpretation. We propose a new method to analyze functional near-infrared spectroscopy-based functional connectivity (fNIRS-FC). In this study, we employed wavelet analysis for motion correction and orthogonal minimal spanning trees (OMSTs) to derive the brain connectivity. The proposed method was applied to an Alzheimer's disease (AD) dataset and was compared with a number of well-known thresholding techniques. The results demonstrated that the proposed method outperformed the benchmarks in filtering cost-effective networks and in differentiation between patients with mild AD and healthy controls. The results also supported the proposed method as a feasible technique to analyze fNIRS-FC, especially with cost-efficiency, assortativity and laterality as a set of effective features for the diagnosis of AD.
Collapse
|
10
|
Connectome analysis of brain functional network alterations in breast cancer survivors with and without chemotherapy. PLoS One 2020; 15:e0232548. [PMID: 32365133 PMCID: PMC7197781 DOI: 10.1371/journal.pone.0232548] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2020] [Accepted: 04/16/2020] [Indexed: 01/31/2023] Open
Abstract
Purpose Treatment modalities for breast cancer, the leading cause of cancer-related deaths in women worldwide, include surgery, radiotherapy, adjuvant chemotherapy, targeted therapy, and hormonal therapy. The advancement in medical technology has facilitated substantial reduction in breast cancer mortality. However, patients may experience cognitive impairment after chemotherapy. This phenomenon called chemotherapy-induced cognitive impairment (i.e., “chemobrain”) is common among breast cancer survivors. However, cognitive function deficits may exist before chemotherapy initiation. This study examined the functional network alterations in breast survivors by using resting-state functional magnetic resonance imaging (fMRI). Methods We recruited 172 female participants and separated them into three groups: C+ (57 breast cancer survivors who had finished 3–12-month-long chemotherapy), C- (45 breast cancer survivors who had not undergone chemotherapy), and HC (70 participants with no breast cancer history). We analyzed mean fractional amplitudes of low-frequency fluctuation and graph theoretical topologies from resting-state fMRI and applied network-based analysis to portray functional changes among the three groups. Results Among the three groups, the C- group demonstrated hyperactivity in the prefrontal cortex, bilateral middle temporal gyrus, right inferior temporal gyrus and right angular gyrus. Only the left caudate demonstrated significantly more hypoactivity in the C- group than in the C+ group. Graph theoretical analysis demonstrated that the brains of the C+ group became inclined toward regular networks and the brains of the C- group became inclined toward random networks. Conclusion Subtle alterations were noted in the brain activity and networks of our cancer survivors. Moreover, functional network disruptions occurred regardless of chemotherapeutic agent administration.
Collapse
|
11
|
Song DY, Wang XW, Wang S, Ge SQ, Ding GY, Chen XY, Chen YR, Liu HM, Xie XM, Xing WJ, Li D, Zhou Y. Jidong cognitive impairment cohort study: objectives, design, and baseline screening. Neural Regen Res 2020; 15:1111-1119. [PMID: 31823892 PMCID: PMC7034269 DOI: 10.4103/1673-5374.266070] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Abstract
The risk of dementia increases in patients with cognitive impairment. However, it is not clear what factors contribute to the onset of dementia in those with cognitive impairment. In this prospective cohort study, we will investigate the every-five-year incidence of cognitive impairment and prognostic factors for cognitive impairment. The Jidong cognitive impairment cohort was established from April 2012 to August 2015, during which we recruited 5854 healthy participants (55.1% male) older than 45 years (mean, 57 years). Participants received a health examination in the Staff Hospital, Jidong Oilfield Branch, China National Petroleum Corporation. Baseline data and blood samples were collected. Cognitive impairment was evaluated using the Mini-Mental State Examination, and was defined as a Mini-Mental State Examination score of less than 24. Dementia was assessed using the criteria of Diagnostic and Statistical Manual of Mental Disorders (Fourth edition), the International Working Group criteria, and the Mini-Mental State Examination score. The follow-up will continue until December 2024, during which a prognostic model will be constructed. The primary outcome is the presence/absence of dementia and the secondary outcome is quality of life. Baseline screening results showed the following: (1) Cognitive impairment was apparent in 320 participants (5.5%). These participants will be excluded from the Jidong cohort study, and the remaining participants will be followed up. (2) Of the 320 participants with cognitive impairment, there was a significantly higher prevalence of illiteracy than other education levels (35.9%, P < 0.05). Age, arterial hypertension, alcohol consumption, and passive smoking differed significantly between the cognitive impairment and healthy groups (P < 0.05). Multivariate logistic regression models showed that age (odds ratio [OR] = 1.059, 95% confidence interval [CI]: 1.044–1.074) and arterial hypertension (OR = 1.665, 95% CI: 1.143–2.427) were risk factors for mild cognitive impairment. With the increase of educational level (illiteracy, primary school, junior high school, high school, university, and above), cognitive impairment gradually decreased (OR < 1, P < 0.05). (3) This cohort study has initially screened for several risk factors for cognitive impairment at baseline, and subsequent prospective data will further describe, validate, and evaluate the effects of these risk factors on cognitive impairment and dementia. These results can provide clinical evidence for the early prevention of cognitive impairment and dementia. The study was approved by the Ethics Committee of Kailuan General Hospital of Tangshan City and the Medical Ethics Committee, Staff Hospital, Jidong Oilfield Branch, China National Petroleum Corporation on July 12, 2013 (approval No. 2013 YILUNZI 1).
Collapse
Affiliation(s)
- Dai-Yu Song
- School of public health, Shandong First Medical University & Shandong Academy of Medical Sciences, Taian, Shandong Province, China; School of Ophthalmology and Optometry, Eye Hospital, Wenzhou Medical University, Wenzhou, Zhejiang Province, China
| | - Xian-Wei Wang
- School of Ophthalmology and Optometry, Eye Hospital, Wenzhou Medical University, Wenzhou, Zhejiang Province, China
| | - Sa Wang
- Department of Neurology, The Affiliated Wenling Hospital of Wenzhou Medical University, Wenling, Zhejiang Province, China
| | - Si-Qi Ge
- Department of Neuroepidemiology, Beijing Neurosurgical Institute; Capital Medical University, Beijing, China
| | - Guo-Yong Ding
- School of public health, Shandong First Medical University & Shandong Academy of Medical Sciences, Taian, Shandong Province, China
| | - Xue-Yu Chen
- School of public health, Shandong First Medical University & Shandong Academy of Medical Sciences, Taian, Shandong Province, China
| | - Yan-Ru Chen
- School of public health, Shandong First Medical University & Shandong Academy of Medical Sciences, Taian, Shandong Province, China
| | - Hua-Min Liu
- School of public health, Shandong First Medical University & Shandong Academy of Medical Sciences, Taian, Shandong Province, China
| | - Xiao-Mei Xie
- Staff hospital of jidong oilfield, Caofeidian district, Tangshan, Hebei Province, China
| | - Wei-Jia Xing
- School of public health, Shandong First Medical University & Shandong Academy of Medical Sciences, Taian, Shandong Province, China
| | - Dong Li
- School of public health, Shandong First Medical University & Shandong Academy of Medical Sciences, Taian, Shandong Province, China
| | - Yong Zhou
- School of Ophthalmology and Optometry, Eye Hospital, Wenzhou Medical University, Wenzhou, Zhejiang Province, China
| |
Collapse
|