BACKGROUND: Neuroimaging studies show increased diffusivity and decreased anisotropy in Alzheimer's disease (AD) patients by diffusion tensor imaging (DTI). Previous reports have analyzed a correlation with cognitive function and DTI parameters, but their results are inconsistent. A reason for this might be a region of interest (ROI) method, used to calculate parameters for DTI, because this method has various usages of how to place a ROI and includes summations of values for various neuronal fiber tracts, resulting in contamination of unintended fibers. To improve the instability with ROI placement, a tractography-based method might be useful. Our coworker reported decreased fractional anisotropy (FA) and increased apparent diffusion coefficient (ADC) of uncinate fasciculus (UF) in patients with AD by tractography. To confirm whether DTI parameter values are related to severity of cognitive function in patients with AD, we measured mean diffusion anisotropy and diffusivity of coregistered voxels along the tracking lines (i.e. tract of interest) of UF. METHODS: The subjects were 30 patients with probable AD (NINCDS-ADRDA criteria). Assessment of cognitive function was carried out according to the Mini-Mental State Examination (MMSE) and the Alzheimer's Disease Assessment Scale-cognitive component-Japanese version (ADAS-Jcog). A 1.5-T clinical magnetic resonance unit was used to obtain diffusion tensor images. Diffusion tensors were computed and fiber-tract maps were created using 'dTV II' DTI software developed by Masutani et al. We measured mean FA and ADC values along the bilateral UF. RESULTS: FA values were positively correlated with MMSE score (r= 0.67) and were negatively correlated with ADAS-Jcog score (r=-0.62), while ADC values were negatively correlated with MMSE score (r=-0.58) and were positively correlated with ADAS-Jcog score (r= 0.59). CONCLUSION: FA and ADC values might reflect the severity of cognitive dysfunction. The tract-of-interest method might be a useful tool for objectively evaluating DTI parameters in AD.
BACKGROUND: Neuroimaging studies show increased diffusivity and decreased anisotropy in Alzheimer's disease (AD) patients by diffusion tensor imaging (DTI). Previous reports have analyzed a correlation with cognitive function and DTI parameters, but their results are inconsistent. A reason for this might be a region of interest (ROI) method, used to calculate parameters for DTI, because this method has various usages of how to place a ROI and includes summations of values for various neuronal fiber tracts, resulting in contamination of unintended fibers. To improve the instability with ROI placement, a tractography-based method might be useful. Our coworker reported decreased fractional anisotropy (FA) and increased apparent diffusion coefficient (ADC) of uncinate fasciculus (UF) in patients with AD by tractography. To confirm whether DTI parameter values are related to severity of cognitive function in patients with AD, we measured mean diffusion anisotropy and diffusivity of coregistered voxels along the tracking lines (i.e. tract of interest) of UF. METHODS: The subjects were 30 patients with probable AD (NINCDS-ADRDA criteria). Assessment of cognitive function was carried out according to the Mini-Mental State Examination (MMSE) and the Alzheimer's Disease Assessment Scale-cognitive component-Japanese version (ADAS-Jcog). A 1.5-T clinical magnetic resonance unit was used to obtain diffusion tensor images. Diffusion tensors were computed and fiber-tract maps were created using 'dTV II' DTI software developed by Masutani et al. We measured mean FA and ADC values along the bilateral UF. RESULTS: FA values were positively correlated with MMSE score (r= 0.67) and were negatively correlated with ADAS-Jcog score (r=-0.62), while ADC values were negatively correlated with MMSE score (r=-0.58) and were positively correlated with ADAS-Jcog score (r= 0.59). CONCLUSION: FA and ADC values might reflect the severity of cognitive dysfunction. The tract-of-interest method might be a useful tool for objectively evaluating DTI parameters in AD.
Authors: Laura E Korthauer; Nicole T Nowak; Scott D Moffat; Yang An; Laura M Rowland; Peter B Barker; Susan M Resnick; Ira Driscoll Journal: Neurobiol Aging Date: 2015-12-17 Impact factor: 4.673
Authors: Maria Giulia Preti; Francesca Baglio; Maria Marcella Laganà; Ludovica Griffanti; Raffaello Nemni; Mario Clerici; Marco Bozzali; Giuseppe Baselli Journal: PLoS One Date: 2012-04-24 Impact factor: 3.240
Authors: William Reginold; Angela C Luedke; Angela Tam; Justine Itorralba; Juan Fernandez-Ruiz; Jennifer Reginold; Omar Islam; Angeles Garcia Journal: Dement Geriatr Cogn Dis Extra Date: 2015-10-21
Authors: D Felsky; P Szeszko; L Yu; W G Honer; P L De Jager; J A Schneider; A K Malhotra; T Lencz; T Ikuta; J Pipitone; M M Chakravarty; N J Lobaugh; B H Mulsant; B G Pollock; J L Kennedy; D A Bennett; A N Voineskos Journal: Mol Psychiatry Date: 2013-10-29 Impact factor: 15.992