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Abnormal regional homogeneity in right caudate as a potential neuroimaging biomarker for mild cognitive impairment: A
Yujun Gao1, Xinfu Zhao2, JiChao Huang3
1Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan, China.
Objective:
Mild cognitive impairment (MCI) is a heterogeneous syndrome characterized by cognitive impairment on neurocognitive tests but accompanied by relatively intact daily activities. Due to high variation and no objective methods for diagnosing and treating MCI, guidance on neuroimaging is needed. The study has explored the neuroimaging biomarkers using the support vector machine (SVM) method to predict MCI.
Methods:
In total, 53 patients with MCI and 68 healthy controls were involved in scanning resting-state functional magnetic resonance imaging (rs-fMRI). Neurocognitive testing and Structured Clinical Interview, such as Alzheimer's Disease Assessment Scale-Cognitive Subscale (ADAS-Cog) test, Activity of Daily Living (ADL) Scale, Hachinski Ischemic Score (HIS), Clinical Dementia Rating (CDR), Montreal Cognitive Assessment (MoCA), and Hamilton Rating Scale for Depression (HRSD), were utilized to assess participants' cognitive state. Neuroimaging data were analyzed with the regional homogeneity (ReHo) and SVM methods.
Results:
Compared with healthy comparisons (HCs), ReHo of patients with MCI was decreased in the right caudate. In addition, the SVM classification achieved an overall accuracy of 68.6%, sensitivity of 62.26%, and specificity of 58.82%.
Conclusion:
The results suggest that abnormal neural activity in the right cerebrum may play a vital role in the pathophysiological process of MCI. Moreover, the ReHo in the right caudate may serve as a neuroimaging biomarker for MCI, which can provide objective guidance on diagnosing and managing MCI in the future.
Insights
Neuroimaging using resting-state functional MRI reveals decreased activity in the right caudate region for individuals with mild cognitive impairment (MCI). This finding may help develop objective biomarkers for diagnosing and managing MCI.
Area of Science:
- Neuroimaging
- Neurology
- Biomarkers
Background:
- Mild cognitive impairment (MCI) presents heterogeneous symptoms, lacking objective diagnostic and treatment methods.
- Neuroimaging guidance is crucial for understanding and managing MCI.
- The study investigates neuroimaging biomarkers for MCI prediction.
Purpose of the Study:
- To explore neuroimaging biomarkers for predicting Mild Cognitive Impairment (MCI).
- To utilize the Support Vector Machine (SVM) method for MCI prediction.
- To identify potential objective markers for MCI diagnosis and management.
Main Methods:
- Resting-state functional magnetic resonance imaging (rs-fMRI) was performed on 53 MCI patients and 68 healthy controls (HCs).
- Neurocognitive tests and clinical interviews (e.g., ADAS-Cog, ADL, MoCA) assessed cognitive status.
- Regional homogeneity (ReHo) and SVM analyses were applied to neuroimaging data.
Main Results:
- Patients with MCI showed decreased ReHo in the right caudate compared to HCs.
- The SVM model achieved 68.6% accuracy, 62.26% sensitivity, and 58.82% specificity in classifying MCI.
- Abnormal neural activity in the right cerebrum is implicated in MCI pathophysiology.
Conclusions:
- Decreased ReHo in the right caudate may serve as a neuroimaging biomarker for MCI.
- These findings offer potential for objective guidance in diagnosing and managing MCI.
- Abnormal neural activity in the right cerebrum is vital in MCI's pathophysiological process.
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