ArticleNeuropsychiatric disease and treatment2018
Structural and functional brain abnormalities in drug-naive, first-episode, and chronic patients with schizophrenia: a multimodal MRI study.
Article in Neuropsychiatric disease and treatment, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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17 citing papers in PubMed.
- The gut microbiome is associated with brain structure and function in schizophrenia.Scientific reports · 2021Trial
- Investigating structural-functional brain covariation in bipolar disorder using a multimodal fusion approach.Brain imaging and behavior · 2025Article
- Association of dopamine-based genetic risk score with dynamic low-frequency fluctuations in first-episode drug-naïve schizophrenia.Brain imaging and behavior · 2023Article
- Investigating brain aging trajectory deviations in different brain regions of individuals with schizophrenia using multimodal magnetic resonance imaging and brain-age prediction: a multicenter study.Translational psychiatry · 2023Article
- Discriminative analysis of schizophrenia patients using graph convolutional networks: A combined multimodal MRI and connectomics analysis.Frontiers in neuroscience · 2023Article
- Rich-club reorganization of white matter structural network in schizophrenia patients with auditory verbal hallucinations following 1 Hz rTMS treatment.NeuroImage. Clinical · 2023Article
- Neuroimaging biomarkers for detecting schizophrenia: A resting-state functional MRI-based radiomics analysis.Heliyon · 2022Article
- Multimodal Magnetic Resonance Imaging Reveals Aberrant Brain Age Trajectory During Youth in Schizophrenia Patients.Frontiers in aging neuroscience · 2022Article
- An integrated machine learning framework for a discriminative analysis of schizophrenia using multi-biological data.Scientific reports · 2021Article
- Strategies to solve the reverse inference fallacy in future MRI studies of schizophrenia: a review.Brain imaging and behavior · 2021Review
- Conceptual disorganization and redistribution of resting-state cortical hubs in untreated first-episode psychosis: A 7T study.NPJ schizophrenia · 2021Article
- Effects of Brain Atlases and Machine Learning Methods on the Discrimination of Schizophrenia Patients: A Multimodal MRI Study.Frontiers in neuroscience · 2021Article
- NEURO-LEARN: a Solution for Collaborative Pattern Analysis of Neuroimaging Data.Neuroinformatics · 2021Article
- Discriminative Analysis of Schizophrenia Patients Using Topological Properties of Structural and Functional Brain Networks: A Multimodal Magnetic Resonance Imaging Study.Frontiers in neuroscience · 2021Article
- Article
- Brain function, structure and genomic data are linked but show different sensitivity to duration of illness and disease stage in schizophrenia.NeuroImage. Clinical · 2019Article
- Multimodal Integration of Brain Images for MRI-Based Diagnosis in Schizophrenia.Frontiers in neuroscience · 2019Article
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11 authors.
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Abstract
backgroundStructural and functional brain abnormalities in schizophrenia (SZ) have been widely reported. However, a few studies have investigated both structural and functional characteristics in SZ patients at different stages to understand the neuropathology of SZ.
methodsIn this study, we recruited 44 first-episode drug-naive SZ (FESZ) patients, 44 medicated chronic SZ (CSZ) patients, and 56 normal controls (NCs) and acquired their structural and resting-state functional magnetic resonance imaging (MRI). We then made group comparisons on structural and functional characteristics, including regional gray matter volume (GMV), regional homogeneity, amplitude of low-frequency fluctuation, and degree centrality. A linear support vector machine (SVM) combined with a recursive feature elimination (RFE) algorithm was implemented to discriminate three groups.
resultsOur results indicated that the regional GMV was significantly decreased in patients compared with that in NCs; CSZ patients have more diffused GMV decreases primarily involved in the frontal and temporal lobes when compared with FESZ patients. Both FESZ and CSZ patients showed significant functional alterations compared with NCs; when compared with FESZ patients, CSZ patients showed significant reductions in functional characteristics in several brain regions associated with auditory, visual processing, and sensorimotor functions. Moreover, a linear SVM combined with a RFE algorithm was implemented to discriminate three groups. The accuracies of the three classifiers were 79.80%, 83.16%, and 81.71%, respectively. The performance of classifiers in this study with multimodal MRI was better than that of previous discriminative analyses of SZ patients with single-modal MRI.
conclusionOur findings bring new insights into the understanding of the neuropathology of SZ and contribute to stage-specific biomarkers in diagnosis and interventions of SZ.
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