Your browser doesn't support javascript.
loading
Comparison of cortical and subcortical structural segmentation methods in Alzheimer's disease: A statistical approach.
Zamani, Jafar; Sadr, Ali; Javadi, Amir-Homayoun.
Afiliação
  • Zamani J; School of Electrical Engineering, Iran University of Science and Technology, Tehran, Iran.
  • Sadr A; School of Electrical Engineering, Iran University of Science and Technology, Tehran, Iran. Electronic address: sadr@iust.ac.ir.
  • Javadi AH; School of Psychology, University of Kent, Canterbury, UK; School of Rehabilitation, Tehran University of Medical Sciences, Tehran, Iran. Electronic address: a.h.javadi@gmail.com.
J Clin Neurosci ; 99: 99-108, 2022 May.
Article em En | MEDLINE | ID: mdl-35278936
BACKGROUND: Automated segmentation methods are developed to help with the segmentation of different brain areas. However, their reliability has yet to be fully investigated. To have a more comprehensive understanding of the distribution of changes in Alzheimer's disease (AD), as well as investigating the reliability of different segmentation methods, in this study we compared volumes of cortical and subcortical brain segments, using HIPS, volBrain, CAT and BrainSuite automated segmentation methods between AD, mild cognitive impairment (MCI) and healthy controls (HC). METHODS: A total of 182 MRI images were taken from the minimal interval resonance imaging in Alzheimer's disease (MIRIAD; 22 AD and 22 HC) and the Alzheimer's disease neuroimaging initiative database (ADNI; 43 AD, 50 MCI and 45 HC) datasets. Statistical methods were used to compare different groups as well as the correlation between different methods. RESULTS: The two methods of volBrain and CAT showed a strong correlation (p's < 0.035 Bonferroni corrected for multiple comparisons). The two methods, however, showed no significant correlation with BrainSuite (p's > 0.820 Bonferroni corrected). Furthermore, BrainSuite did not follow the same trend as the other three methods and only HIPS, volBrain and CAT showed strong conformity with the past literature with strong correlation with mini mental state examination (MMSE) scores. CONCLUSION: Our results showed that automated segmentation methods HIPS, volBrain and CAT can be used in the classification of HC, AD and MCI. This is an indication that such methods can be used to inform researchers and clinicians of underlying mechanisms and progression of AD.
Assuntos
Palavras-chave

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Doença de Alzheimer / Disfunção Cognitiva Limite: Humans Idioma: En Revista: J Clin Neurosci Assunto da revista: NEUROLOGIA Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Irã

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Doença de Alzheimer / Disfunção Cognitiva Limite: Humans Idioma: En Revista: J Clin Neurosci Assunto da revista: NEUROLOGIA Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Irã