Dataset Information

Amplitude of low-frequency fluctuation-based regional radiomics similarity network: Biomarker for Parkinson's disease.

ABSTRACT: Parkinson's disease (PD) is a highly heterogeneous disorder that is difficult to diagnose. Therefore, reliable biomarkers are needed. We implemented a method constructing a regional radiomics similarity network (R2SN) based on the amplitude of low-frequency fluctuation (ALFF). We classified patients with PD and healthy individuals by using a machine learning approach in accordance with the R2SN connectome. The ALFF-based R2SN exhibited great reproducibility with different brain atlases and datasets. Great classification performances were achieved both in primary (AUC = 0.85 ± 0.02 and accuracy = 0.81 ± 0.03) and independent external validation (AUC = 0.77 and accuracy = 0.70) datasets. The discriminative R2SN edges correlated with the clinical evaluations of patients with PD. The nodes of discriminative R2SN edges were primarily located in the default mode, sensorimotor, executive control, visual and frontoparietal network, cerebellum and striatum. These findings demonstrate that ALFF-based R2SN is a robust potential neuroimaging biomarker for PD and could provide new insights into connectome reorganization in PD.

SUBMITTER: Shi D

PROVIDER: S-EPMC10025115 | biostudies-literature | 2023 Mar

REPOSITORIES: biostudies-literature

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Amplitude of low-frequency fluctuation-based regional radiomics similarity network: Biomarker for Parkinson's disease.

Shi Dafa D Ren Zhendong Z Zhang Haoran H Wang Guangsong G Guo Qiu Q Wang Siyuan S Ding Jie J Yao Xiang X Li Yanfei Y Ren Ke K

Heliyon 20230306 3

Parkinson's disease (PD) is a highly heterogeneous disorder that is difficult to diagnose. Therefore, reliable biomarkers are needed. We implemented a method constructing a regional radiomics similarity network (R2SN) based on the amplitude of low-frequency fluctuation (ALFF). We classified patients with PD and healthy individuals by using a machine learning approach in accordance with the R2SN connectome. The ALFF-based R2SN exhibited great reproducibility with different brain atlases and datas ...[more]

PMID: 36950566

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Project description:BackgroundGeneralized anxiety disorder (GAD) is a common affective disorder characterized by comprehensive anxiety with dysregulation of brain activity which can be reflected by functional magnetic resonance imaging (f-MRI). We aimed to examine abnormal aberrant amplitude low-frequency fluctuation (ALFF) and regional homogeneity (ReHo) in GAD and evaluate their ability to predict treatment remission.MethodsUsing resting-state fMRI (Rs-fMRI), we examined ALFF and ReHo in 30 GAD patients and 30 healthy control (HC) participants. Using on DEPASF4.3 Advanced Edition, voxel-based two-sample t-test analysis was performed on the ALFF and ReHo maps to compare GAD to HC groups, and to compare remitters (n=9) and non-remitters (n=21). Pearson's correlation analysis was used to explore the relationship between baseline Hamilton Anxiety Rating Scale (HAM-A) scores/illness duration and mean ALFF/ReHo values. The severity of GAD symptoms was rated with HAM-A. Remission was defined as HAM-A ≤7 by week 8.ResultsCompared to the HC group, GAD patients showed lower ALFF in the right postcentral and right precentral gyrus; lower ReHo in the right precentral, right postcentral, and left precentral gyrus; and higher ReHo in the left posterior cingulate cortex. ALFF values for left postcentral gyrus was negatively correlated with baseline HAM-A, while that of the middle frontal gyrus was positively correlated with baseline HAM-A scores. ReHo value of the left postcentral gyrus was negatively correlated with baseline HAM-A, while that of the right middle frontal gyrus was positively correlated with baseline HAM-A scores. ALFF of the right frontal_superior_orbital and right frontal-medial-orbital cortex was positively correlated with illness duration. ReHo of the left supplementary motor area cortex was negatively correlated with illness duration. Remitters showed higher ALFF in the left hippocampus and higher ReHo value in the right postcentral cortex compared to nonremitters.ConclusionsThese results suggest that altered regional brain activity and local synchronization may be related to the pathophysiology of GAD and have certain value in predicting remission in treatment.

Project description:Background and purposePrevious studies have focused on the changes of dynamic and static functional connections in cerebral small vessel disease (CSVD). However, the dynamic characteristics of local brain activity are poorly understood. The purpose of this study was to investigate the dynamic cerebral activity changes in patients with CSVD using the dynamic amplitude of low-frequency fluctuation (d-ALFF).MethodsA total of 104 CSVD patients with cognitive impairment (CSVD-CI, n = 52) or normal cognition (CSVD-NC, n = 52) and 63 matched healthy controls (HCs) were included in this study. Every participant underwent magnetic resonance imaging scans and a battery of neuropsychological examinations. The dynamics of spontaneous brain activity were assessed using dynamic changes in the amplitude of low-frequency fluctuation (ALFF) with the sliding-window method. We used voxel-wise one-way analysis of variance (ANOVA) to compare dynamic ALFF variability among the three groups. Post-hoc t-tests were used to evaluate differences between each group pair. Finally, the brain regions with d-ALFF values with differences between CSVD subgroups were taken as regions of interest (ROI), and the d-ALFF values corresponding to the ROI were extracted for partial correlation analysis with memory.Results(1) There was no significant difference in age (p = 0.120), sex (p = 0.673) and education (p = 0.067) among CSVD-CI, CSVD-NC and HC groups, but there were significant differences Prevalence of hypertension and diabetes mellitus among the three groups (p < 10-3). There were significant differences in scores of several neuropsychological scales among the three groups (p < 10-3). (2) ANOVA and post-hoc t-test showed that there were dynamic abnormalities of spontaneous activity in several brain regions in three groups, mainly located in bilateral parahippocampal gyrus and bilateral hippocampus, bilateral insular and frontal lobes, and the static activity abnormalities in bilateral parahippocampal gyrus and bilateral hippocampal regions were observed at the same time, suggesting that bilateral parahippocampal gyrus and bilateral hippocampus may be the key brain regions for cognitive impairment caused by CSVD. (3) The correlation showed that d-ALFF in the bilateral insular was slightly correlated with the Mini-Mental State Examination (MMSE) score and disease progression rate. The d-ALFF value of the left postcentral gyrus was negatively correlated with the Clock Drawing Test (CDT) score (r = -0.416, p = 0.004), and the d-ALFF value of the right postcentral gyrus was negatively correlated with the Rey's Auditory Verbal Learning Test (RAVLT) word recognition (r = -0.320, p = 0.028).ConclusionThere is a wide range of dynamic abnormalities of spontaneous brain activity in patients with CSVD, in which the abnormalities of this activity in specific brain regions are related to memory and execution or emotion.

Dataset Information

Amplitude of low-frequency fluctuation-based regional radiomics similarity network: Biomarker for Parkinson's disease.

Publications

Amplitude of low-frequency fluctuation-based regional radiomics similarity network: Biomarker for Parkinson's disease.

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