Extent and Distribution of Extent and Distribution of White Matter White Matter Hyperintensities in Normal Hyperintensities in Normal Aging, Mild Cognitive Aging, Mild Cognitive Impairment and Alzheimer’s Impairment and Alzheimer’s Disease Disease Mitsuhiro Yoshita, Evan Fletcher, Oliver Martinez, Mario Ortega, Oliver Martinez, Mario Ortega, Bruce Reed, Da n Mungas and Charles DeCarli Department of Neurology and Center for Neuroscience University of California at Davis
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Extent and Distribution of White Matter Hyperintensities in Normal Aging, Mild Cognitive Impairment and Alzheimer’s Disease Mitsuhiro Yoshita, Evan Fletcher,
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Extent and Distribution ofExtent and Distribution ofWhite Matter Hyperintensities in White Matter Hyperintensities in
Normal Aging, Mild Cognitive Normal Aging, Mild Cognitive Impairment and Alzheimer’s Disease Impairment and Alzheimer’s Disease
Mitsuhiro Yoshita, Evan Fletcher, Oliver Martinez, Mario Ortega,Oliver Martinez, Mario Ortega, Bruce Reed, Da
n Mungas and Charles DeCarli
Department of Neurology and Center for Neuroscience
Schema for WMH segmentation and nonlinear transformation for mapping
DeCarli C, et al. Stroke 2005.
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Composite image
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ROI on 3-D WMH mapsROI on 3-D WMH maps
Cg: genu of corpus callosum, Cs: splenium of corpus callosum, Pa: anterior periventricular region, Pb: body of periventricular region, Pp: posterior periventricular region, Po: occipital periventricular region.
We computed the number of voxel of WMH in each ROI, andcalculated percentage of voxel which have WMH in each ROIof each subject.
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Cg
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Po
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PpPa
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Cs
Statistical AnalysisStatistical Analysis
1. Groups were compared using analysis of variance (ANOVA) or Kruskal-Wallis test as appropriate according to the distribution of the data, with post hoc analysis.
2. Correlations were evaluated by Spearman’s ranks correlation test.
3. Results are expressed as mean values ± standard deviation.
4. A p value less than 0.05 was considered significant.
5. Data were analyzed using the Statistical Package for Social Sciences (SPSS for Windows, version 12.0; SPSS Inc, Chicago, IL).
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X= 2(A-2)
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Z= 28(B-1)
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Z= 22(B-2)
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Y= -4(C-1)
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Y= -26(C-2)
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WMH frequency maps in all subjectsWMH frequency maps in all subjects
3-D WMH frequency maps3-D WMH frequency maps in each group in each group
(A) (B) (C)
Three-dimensional reconstruction of the WMH (orange) and ventricular (grey) maps. Orange color indicate the frequency of voxels containing the WMH more than 10%.
(A): group of NA(B): group of MCI(C): group of AD
Group difference of WMH Group difference of WMH severity in each ROIseverity in each ROI
Error bars indicate standard deviation of the mean.
(B): Corpus callosum region
: AD
: MCI
: NA
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Genu Splenium
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* p < 0.05, ** p < 0.01.
(A): Periventricular region
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Anterior Body Posterior Occipital
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Correlations between age, MMSE Correlations between age, MMSE and WMH severity in each ROIand WMH severity in each ROI
Pa: anterior periventricular region Pb: body of periventricular region Pp: posterior periventricular region Po: occipital periventricular regionCg: genu of corpus callosum Cs: splenium of corpus callosum
We believe the methods developed here conclusively show the difference of WMH distribution of each cognitive stage.
These observations also support the notion of both a common ischemic etiology and Wallerian degeneration as a mechanism of WMH in each cognitive stage.
Our study shows that measurements of the e
xtent and distribution of WMH in both corpus callosum and periventricular area are suitable for assessment for NA, MCI and AD.
ConclusionConclusion
ThanksThanks
Student:Student: Ryan Berthold,Ryan Berthold, Chris Davies, Chris Davies, Alex Early, Alex Early, Marty Greenia, Marty Greenia, Evan LloydEvan Lloyd
Staff:Staff: Lauren Cibattari,Lauren Cibattari, Krista Garcia,Krista Garcia, Oliver Martinez,Oliver Martinez, Mario Ortega,Mario Ortega, Baljeet Singh,Baljeet Singh, Laura Whiteside,Laura Whiteside, Sky RaptentsetsangSky Raptentsetsang