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1.
Journal of Southern Medical University ; (12): 1023-1029, 2019.
Article in Chinese | WPRIM | ID: wpr-773495

ABSTRACT

OBJECTIVE@#To compare the effectiveness and sensitivity of entropy and regional homogeneity (ReHo) for identifying irritable bowel syndrome (IBS) based on functional magnetic resonance imaging (fMRI).@*METHODS@#Voxel-based approximate entropy (ApEn) was calculated based on findings of resting fMRI of 54 patients with IBS and 54 healthy control subjects. Feature selection was performed using independent sample -test, and support vector machine was then used to classify and identify different groups. The classification performance obtained from ApEn was compared with that from ReHo.@*RESULTS@#Significant differences between the two groups were found in the left triangle part of inferior prefrontal gyrus, right angular gyrus of the inferior parietal lobule, left inferior temporal gyrus, left middle temporal gyrus, left lingual gyrus, bilateral middle occipital gyrus and bilateral superior occipital gyrus for ReHo ( < 0.05), and in the bilateral postcentral gyrus, right precentral gyrus, right inferior temporal gyrus, bilateral middle temporal gyrus and left superior occipital gyrus for ApEn ( < 0.05). ApEn consistently showed better performance than ReHo regardless of the variations in the number of features. The classification accuracy, specificity and sensitivity of ApEn were 93.5185%, 90.7407% and 96.2963%, respectively, as compared with 86.1111%, 85.1852% and 87.037% of ReHo.@*CONCLUSIONS@#Entropy analysis based on fMRI can be more sensitive and effective than ReHo for identification of IBS.


Subject(s)
Humans , Brain , Diagnostic Imaging , Brain Mapping , Case-Control Studies , Entropy , Irritable Bowel Syndrome , Diagnostic Imaging , Magnetic Resonance Imaging
2.
Journal of Neurogastroenterology and Motility ; : 107-118, 2018.
Article in English | WPRIM | ID: wpr-740727

ABSTRACT

BACKGROUND/AIMS: The Rome III criteria separated chronic constipation into functional constipation (FC) and constipation-predominant irritable bowel syndrome (IBS-C), but some researchers questioned the partitioning and treated both as distinct parts of a continuum. The study aims to explore the similarity and diversity of brain white matter between FC and IBS-C. METHODS: The voxel-wise analysis of the diffusion parameters was used to quantify the white matter changes of female brains in 18 FC patients and 20 IBS-C patients compared with a comparison group with 19 healthy controls by tract-based spatial statistics. The correlations between diffusive parameters and clinical symptoms were evaluated using a Pearson’s correlation. RESULTS: In comparison to healthy controls, FC patients showed a decrease of fractional anisotropy (FA) and an increase of radial diffusivity (RD) in multiple major fibers encompassing the corpus callosum (CC, P = 0.001 at peak), external capsule (P = 0.002 at peak), corona radiata (CR, P = 0.001 at peak), and superior longitudinal fasciculus (SLF, P = 0.002 at peak). In contrast, IBS-C patients showed FA and RD aberrations in the CC (P = 0.048 at peak). Moreover, the direct comparison between FC and IBS-C showed only RD differences in the CR and SLF. In addition, FA and RD in the CC were significantly associated with abdominal pain for all patients, whereas FA in CR (P = 0.016) and SLF (P = 0.040) were significantly associated with the length of time per attempt and incomplete evacuation separately for FC patients. CONCLUSION: These results may improve our understanding of the pathophysiological mechanisms underlying different types of constipation.


Subject(s)
Female , Humans , Abdominal Pain , Anisotropy , Brain , Constipation , Corpus Callosum , Diffusion , Diffusion Tensor Imaging , External Capsule , Irritable Bowel Syndrome , White Matter
3.
Journal of Neurogastroenterology and Motility ; : 118-128, 2016.
Article in English | WPRIM | ID: wpr-162045

ABSTRACT

BACKGROUND/AIMS: Previous studies reported that integrated information in the brain ultimately determines the subjective experience of patients with chronic pain, but how the information is integrated in the brain connectome of functional dyspepsia (FD) patients remains largely unclear. The study aimed to quantify the topological changes of the brain network in FD patients. METHODS: Small-world properties, network efficiency and nodal centrality were utilized to measure the changes in topological architecture in 25 FD patients and 25 healthy controls based on functional magnetic resonance imaging. Pearson's correlation assessed the relationship of each topological property with clinical symptoms. RESULTS: FD patients showed an increase of clustering coefficients and local efficiency relative to controls from the perspective of a whole network as well as elevated nodal centrality in the right orbital part of the inferior frontal gyrus, left anterior cingulate gyrus and left hippocampus, and decreased nodal centrality in the right posterior cingulate gyrus, left cuneus, right putamen, left middle occipital gyrus and right inferior occipital gyrus. Moreover, the centrality in the anterior cingulate gyrus was significantly associated with symptom severity and duration in FD patients. Nevertheless, the inclusion of anxiety and depression scores as covariates erased the group differences in nodal centralities in the orbital part of the inferior frontal gyrus and hippocampus. CONCLUSIONS: The results suggest topological disruption of the functional brain networks in FD patients, presumably in response to disturbances of sensory information integrated with emotion, memory, pain modulation, and selective attention in patients.


Subject(s)
Humans , Anxiety , Brain , Chronic Pain , Connectome , Depression , Dyspepsia , Gyrus Cinguli , Hippocampus , Magnetic Resonance Imaging , Memory , Orbit , Putamen
4.
Journal of Neurogastroenterology and Motility ; : 103-110, 2015.
Article in English | WPRIM | ID: wpr-14530

ABSTRACT

BACKGROUND/AIMS: Increasing evidence shows involvement of psychological disorders in functional dyspepsia (FD), but how psychological factors exert their influences upon FD remains largely unclear. The purpose of the present study was to explore the brain-based correlations of psychological factors and FD. METHODS: Based on Fluorine-18-deoxyglucose positron emission tomography-computed tomography, the altered cerebral glycometabolism was investigated in 40 FD patients compared with 20 healthy controls during resting state using statistical parametric mapping software. RESULTS: FD patients exhibited increased glucose metabolism in multiple regions relative to controls (P < 0.001, family-wise error corrected). After controlling for the dyspeptic symptoms, increased aberrations persisted within the insula, anterior cingulate cortex (ACC), middle cingulate cortex (MCC) and middle frontal cortex (midFC), which was related to anxiety and depression score. Interestingly, FD patients without anxiety/depression symptoms also showed increased glycometabolism within the insula, ACC, MCC and midFC. Moreover, FD patients with anxiety/depression symptoms exhibited more significant hypermetabolism within the above 4 sites compared with patients without anxiety/depression symptoms. CONCLUSIONS: Our results suggested that the altered cerebral glycometabolism may be in a vicious cycle of psychological vulnerabilities and increased gastrointestinal symptoms.


Subject(s)
Humans , Anxiety , Cerebral Cortex , Depression , Dyspepsia , Electrons , Glucose , Gyrus Cinguli , Metabolism , Psychology
5.
Journal of Biomedical Engineering ; (6): 653-657, 2011.
Article in Chinese | WPRIM | ID: wpr-359205

ABSTRACT

Based on the fact that the signals of electroencephalogram (EEG) possess non-linear and non-stationary properties, Hilbert-Huang Transform (HHT) was proposed for the EEG analysis of driving fatigue. Firstly, C4-lead EEG was selected, and the data of normal driving state and fatigue driving state was analyzed by HHT to explore the differences. Then O2-lead EEG was chosen for contrastive analysis of differences between the different leads. It was found through the analysis that the EEG signals had different Hilbert marginal spectrums for different states, and there were also some differences at the same state for the two leads. It can be certain that HHT can well distinguish different states of drivers as a novel approach for driving fatigue detection, and the selected lead may affect detectable results to some extent.


Subject(s)
Humans , Automobile Driving , Psychology , Electroencephalography , Methods , Mental Fatigue , Psychology , Signal Processing, Computer-Assisted
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