Resting-state functional magnetic resonance study of primary open-angle glaucoma based on voxelwise brain network degree centrality

Shu, Yongqiang; Li, Xiongfeng; Xiong, Chan; Li, Ping; Pang, Yulian; Ye, Wei; Yang, Lu; Zeng, Xianjun; Zhang, Xu

doi:10.1016/j.neulet.2019.134500

Cited by 15 publications

(14 citation statements)

References 28 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…We calculated the following fMRI measurements: amplitude of low-frequency fluctuations (ALFF) [ 34 , 35 ], regional homogeneity (ReHo) [ 35 , 36 ], degree centrality (DC) [ 37 , 38 ], and voxel-mirrored homotopic connectivity (VMHC) [ 19 , 39 ]. We used the DPARSF software default settings to calculate these indices.…”

Section: Methodsmentioning

confidence: 99%

Machine Learning of Schizophrenia Detection with Structural and Functional Neuroimaging

Shi

Zhang

et al. 2021

Disease Markers

View full text Add to dashboard Cite

Schizophrenia (SZ) is a severe psychiatric illness, and it affects around 1% of the general population; however, its reliable diagnosis is challenging. Functional MRI (fMRI) and structural MRI (sMRI) are useful techniques for investigating the functional and structural abnormalities of the human brain, and a growing number of studies have reported that multimodal brain data can improve diagnostic accuracy. Machine learning (ML) is widely used in the diagnosis of neuroscience and neuropsychiatry diseases, and it can obtain high accuracy. However, the conventional ML which concatenated the features into a longer feature vector could not be sufficiently effective to combine different features from different modalities. There are considerable controversies over the use of global signal regression (GSR), and few studies have explored the role of GSR in ML in diagnosing neurological diseases. The current study utilized fMRI and sMRI data to implement a new method named multimodal imaging and multilevel characterization with multiclassifier (M3) to classify SZs and healthy controls (HCs) and investigate the influence of GSR in SZ classification. We found that when we used Brainnetome 246 atlas and without performed GSR, our method obtained a classification accuracy of 83.49%, with a sensitivity of 68.69%, a specificity of 93.75%, and an AUC of 0.8491, respectively. We also got great classification performances with different processing methods (with/without GSR and different brain parcellation schemes). We found that the accuracy and specificity of the models without GSR were higher than that of the models with GSR. Our findings indicate that the M3 method is an effective tool to distinguish SZs from HCs, and it can identify discriminative regions to detect SZ to explore the neural mechanisms underlying SZ. The global signal may contain important neuronal information; it can improve the accuracy and specificity of SZ detection.

show abstract

Section: Methodsmentioning

confidence: 99%

Machine Learning of Schizophrenia Detection with Structural and Functional Neuroimaging

Shi

Zhang

et al. 2021

Disease Markers

View full text Add to dashboard Cite

show abstract

“…Widespread damage to gray matter, anatomic connectivity and functional connectivity can go beyond the visual system in patients with POAG, including into the visual, working memory, attention and executive networks. [4][5][6][20][21][22][23] In addition, altered cerebral vascular autoregulation and vasoreactivity have been discovered in POAG patients. [24][25][26][27][28][29] To date, studies on cerebral blood perfusion in POAG have been mainly limited to the visual cortex, but the relationships between abnormal neurovascular activity and corresponding cerebral blood perfusion changes have not been elucidated.…”

Section: Introductionmentioning

confidence: 99%

Altered coupling of cerebral blood flow and functional connectivity strength in visual and higher order cognitive cortices in primary open angle glaucoma

Wang

Chen

et al. 2020

J Cereb Blood Flow Metab

View full text Add to dashboard Cite

Primary open-angle glaucoma (POAG) has been suggested to be a neurodegenerative disease associated with altered cerebral vascular hemodynamics and widespread disruption of neuronal activity within the visual, working memory, attention and executive networks. We hypothesized that disturbed neurovascular coupling in visual and higher order cognitive cortices exists in POAG patients and correlates with glaucoma stage and visual field defects. Through multimodal magnetic resonance imaging, we evaluated the cerebral blood flow (CBF)-functional connectivity strength (FCS) correlations of the whole gray matter and CBF/FCS ratio per voxel for all subjects. Compared with normal controls, POAG patients showed reduced global CBF-FCS coupling and altered CBF/FCS ratios, predominantly in regions in the visual cortex, salience network, default mode network, and dorsal attentional network. The CBF/FCS ratio was negatively correlated with glaucoma stage, and positively correlated with visual field defects in the lingual gyrus in POAG patients. Moreover, early brain changes were detected in early POAG. These findings indicate neurovascular coupling dysfunction might exist in the visual and higher order cognitive cortices in POAG patients and its clinical relevance. The results may contribute to the monitoring of POAG progression and provide insight into the pathophysiology of the neurodegenerative process in POAG.

show abstract

“…In addition, Zhang et al. (2019) found that FCD values of the left MFG1 in patients with PAAG were significantly lower than those in the HC group. These results were not consistent with our results, which may be related to differences in pathogenesis and pathology between POAG and Stage III of NVG.…”

Section: Discussionmentioning

confidence: 98%

“…ALFF has been widely used to study primary open-angle glaucoma (Liu et al, 2014 andZhang et al, 2019). Here, we used ALFF to study Stage III angle-closure NVG.…”

Section: Discussionmentioning

confidence: 99%

Altered spontaneous brain activity patterns in patients with neovascular glaucoma using amplitude of low‐frequency fluctuations: A functional magnetic resonance imaging study

Peng

Liu

et al. 2021

Brain and Behavior

View full text Add to dashboard Cite

show abstract

Resting-state functional magnetic resonance study of primary open-angle glaucoma based on voxelwise brain network degree centrality

Cited by 15 publications

References 28 publications

Machine Learning of Schizophrenia Detection with Structural and Functional Neuroimaging

Machine Learning of Schizophrenia Detection with Structural and Functional Neuroimaging

Altered coupling of cerebral blood flow and functional connectivity strength in visual and higher order cognitive cortices in primary open angle glaucoma

Altered spontaneous brain activity patterns in patients with neovascular glaucoma using amplitude of low‐frequency fluctuations: A functional magnetic resonance imaging study

Contact Info

Product

Resources

About