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논문 기본 정보

자료유형
학술저널
저자정보
저널정보
대한신경정신의학회 PSYCHIATRY INVESTIGATION PSYCHIATRY INVESTIGATION 제12권 제1호
발행연도
2015.1
수록면
92 - 102 (11page)

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초록· 키워드

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ObjectiveaaThis study proposes an automated diagnostic method to classify patients with Alzheimer’s disease (AD) of degenerative etiology using magnetic resonance imaging (MRI) markers. MethodsaaTwenty-seven patients with subjective memory impairment (SMI), 18 patients with mild cognitive impairment (MCI), and 27 patients with AD participated. MRI protocols included three dimensional brain structural imaging and diffusion tensor imaging to assess the cortical thickness, subcortical volume and white matter integrity. Recursive feature elimination based on support vector machine (SVM) was conducted to determine the most relevant features for classifying abnormal regions and imaging parameters, and then a factor analysis for the top-ranked factors was performed. Subjects were classified using nonlinear SVM. ResultsaaMedial temporal regions in AD patients were dominantly detected with cortical thinning and volume atrophy compared with SMI and MCI patients. Damage to white matter integrity was also accredited with decreased fractional anisotropy and increased mean diffusivity (MD) across the three groups. The microscopic damage in the subcortical gray matter was reflected in increased MD. Classification accuracy between pairs of groups (SMI vs. MCI, MCI vs. AD, SMI vs. AD) and among all three groups were 84.4% (±13.8), 86.9% (±10.5), 96.3% (±4.6), and 70.5% (±11.5), respectively. ConclusionaaThis proposed method may be a potential tool to diagnose AD pathology with the current clinical criteria

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