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Automated Classification to Predict the Progression of Alzheimer's Disease Using Whole-Brain Volumetry and DTI.

Jung WB, Lee YM, Kim YH, Mun CW - Psychiatry Investig (2015)

Bottom Line: Medial 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.This proposed method may be a potential tool to diagnose AD pathology with the current clinical criteria.

View Article: PubMed Central - PubMed

Affiliation: Department of Biomedical Engineering/u-HARC, Inje University, Gimhae, Republic of Korea.

ABSTRACT

Objective: This study proposes an automated diagnostic method to classify patients with Alzheimer's disease (AD) of degenerative etiology using magnetic resonance imaging (MRI) markers.

Methods: Twenty-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.

Results: Medial 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.

Conclusion: This proposed method may be a potential tool to diagnose AD pathology with the current clinical criteria.

No MeSH data available.


Related in: MedlinePlus

Examples of two-dimensional feature map using the ninth data set derived from factor extraction. A: Black indicators (i.e., '○' and '×') exhibit the Alzheimer's disease (AD) dataset, green represents subjective memory impairment (SMI), and red is mild cognitive impairment (MCI). B: Black indicators are the MCI dataset, and red is SMI. C: Black indicators are the AD dataset, and red is MCI. D: Black indicators are the AD dataset, and red is SMI. The symbol '×' in the dataset is a support vector to determine the hyperplane between the groups. Colored background visualizes partitions of the classified group regions. The horizontal axis represents the first standard score derived from the PCA feature extraction, and the vertical axis indicates the second score.
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Figure 5: Examples of two-dimensional feature map using the ninth data set derived from factor extraction. A: Black indicators (i.e., '○' and '×') exhibit the Alzheimer's disease (AD) dataset, green represents subjective memory impairment (SMI), and red is mild cognitive impairment (MCI). B: Black indicators are the MCI dataset, and red is SMI. C: Black indicators are the AD dataset, and red is MCI. D: Black indicators are the AD dataset, and red is SMI. The symbol '×' in the dataset is a support vector to determine the hyperplane between the groups. Colored background visualizes partitions of the classified group regions. The horizontal axis represents the first standard score derived from the PCA feature extraction, and the vertical axis indicates the second score.

Mentions: Neurodegenerative WM damages were associated with a FA decrease and an MD increase. A significant (p<0.05) or progressive decrease in FA values was observed in 12 WM ROIs across the three groups (Figure 3). These regions included the bilateral anterior corona radiate (ACR), two cingulums of cingulate gyrus and hippocampal portions, the fornix of cres (Fx), the corpus callosum (CC) of genu, body, and splenium portions and the left uncinate fasciculus (UF). The FA values in patients with AD were significantly decreased in all of these regions compared with those in patients with SMI. Compared to patients with MCI, the FA values in bilateral cingulum of the cingulate gyrus (CGC) were also significantly decreased in AD. The remaining 10 WM regions, except the bilateral ACR, showed significant differences in MD values between AD and SMI patients (Figure 4). In particular, MD values of AD patients were higher in the body of corpus callosum (BCC), the two cingulums and Fx than in MCI patients. MD values of MCI patients were increased only in the left cingulum of hippocampus (CGH) compared with SMI patients. Along with these results, the microscopic damage in the subcortical GM showing volume atrophy were reflected by an increase in MD values, but not in FA values (Figure 5). Patients with AD showed the MD increase in all regions, whereas patients with MCI showed an increase in the left HP alone compared to patients with SMI. All regions except the NA and right AMG showed higher MD values in patients with AD than in those with MCI.


Automated Classification to Predict the Progression of Alzheimer's Disease Using Whole-Brain Volumetry and DTI.

Jung WB, Lee YM, Kim YH, Mun CW - Psychiatry Investig (2015)

Examples of two-dimensional feature map using the ninth data set derived from factor extraction. A: Black indicators (i.e., '○' and '×') exhibit the Alzheimer's disease (AD) dataset, green represents subjective memory impairment (SMI), and red is mild cognitive impairment (MCI). B: Black indicators are the MCI dataset, and red is SMI. C: Black indicators are the AD dataset, and red is MCI. D: Black indicators are the AD dataset, and red is SMI. The symbol '×' in the dataset is a support vector to determine the hyperplane between the groups. Colored background visualizes partitions of the classified group regions. The horizontal axis represents the first standard score derived from the PCA feature extraction, and the vertical axis indicates the second score.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4310927&req=5

Figure 5: Examples of two-dimensional feature map using the ninth data set derived from factor extraction. A: Black indicators (i.e., '○' and '×') exhibit the Alzheimer's disease (AD) dataset, green represents subjective memory impairment (SMI), and red is mild cognitive impairment (MCI). B: Black indicators are the MCI dataset, and red is SMI. C: Black indicators are the AD dataset, and red is MCI. D: Black indicators are the AD dataset, and red is SMI. The symbol '×' in the dataset is a support vector to determine the hyperplane between the groups. Colored background visualizes partitions of the classified group regions. The horizontal axis represents the first standard score derived from the PCA feature extraction, and the vertical axis indicates the second score.
Mentions: Neurodegenerative WM damages were associated with a FA decrease and an MD increase. A significant (p<0.05) or progressive decrease in FA values was observed in 12 WM ROIs across the three groups (Figure 3). These regions included the bilateral anterior corona radiate (ACR), two cingulums of cingulate gyrus and hippocampal portions, the fornix of cres (Fx), the corpus callosum (CC) of genu, body, and splenium portions and the left uncinate fasciculus (UF). The FA values in patients with AD were significantly decreased in all of these regions compared with those in patients with SMI. Compared to patients with MCI, the FA values in bilateral cingulum of the cingulate gyrus (CGC) were also significantly decreased in AD. The remaining 10 WM regions, except the bilateral ACR, showed significant differences in MD values between AD and SMI patients (Figure 4). In particular, MD values of AD patients were higher in the body of corpus callosum (BCC), the two cingulums and Fx than in MCI patients. MD values of MCI patients were increased only in the left cingulum of hippocampus (CGH) compared with SMI patients. Along with these results, the microscopic damage in the subcortical GM showing volume atrophy were reflected by an increase in MD values, but not in FA values (Figure 5). Patients with AD showed the MD increase in all regions, whereas patients with MCI showed an increase in the left HP alone compared to patients with SMI. All regions except the NA and right AMG showed higher MD values in patients with AD than in those with MCI.

Bottom Line: Medial 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.This proposed method may be a potential tool to diagnose AD pathology with the current clinical criteria.

View Article: PubMed Central - PubMed

Affiliation: Department of Biomedical Engineering/u-HARC, Inje University, Gimhae, Republic of Korea.

ABSTRACT

Objective: This study proposes an automated diagnostic method to classify patients with Alzheimer's disease (AD) of degenerative etiology using magnetic resonance imaging (MRI) markers.

Methods: Twenty-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.

Results: Medial 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.

Conclusion: This proposed method may be a potential tool to diagnose AD pathology with the current clinical criteria.

No MeSH data available.


Related in: MedlinePlus