Dataset Information

An automatic framework for quantitative validation of voxel based morphometry measures of anatomical brain asymmetry.

ABSTRACT: The study of anatomical brain asymmetries has been a topic of great interest in the neuroimaging community in the past decades. However, the accuracy of brain asymmetry measurements has been rarely investigated. In this study, we propose a fully automatic methodology for the quantitative validation of brain tissue asymmetries as measured by Voxel Based Morphometry (VBM) from structural magnetic resonance (MR) images. Starting from a real MR image, the methodology generates simulated 3D MR images with a known and realistic pattern of inter-hemispheric asymmetry that models the left-occipital right-frontal petalia of a normal brain and the related rightward bending of the inter-hemispheric fissure. As an example, we generated a dataset of 64 simulated MR images and applied this dataset for the quantitative validation of optimized VBM measures of asymmetries in brain tissue composition. Our results suggested that VBM analysis strongly depended on the spatial normalization of the individual brain images, the selected template space, and the amount of spatial smoothing applied. The most accurate asymmetry detections were achieved by 9-degrees of freedom registration to the symmetrical template space with 4 to 8mm spatial smoothing.

SUBMITTER: Pepe A

PROVIDER: S-EPMC4457344 | biostudies-literature | 2014 Oct

REPOSITORIES: biostudies-literature

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An automatic framework for quantitative validation of voxel based morphometry measures of anatomical brain asymmetry.

Pepe Antonietta A Dinov Ivo I Tohka Jussi J

NeuroImage 20140618

The study of anatomical brain asymmetries has been a topic of great interest in the neuroimaging community in the past decades. However, the accuracy of brain asymmetry measurements has been rarely investigated. In this study, we propose a fully automatic methodology for the quantitative validation of brain tissue asymmetries as measured by Voxel Based Morphometry (VBM) from structural magnetic resonance (MR) images. Starting from a real MR image, the methodology generates simulated 3D MR images ...[more]

PMID: 24952229

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Project description:BackgroundAging is the most significant risk factor for dementia. Alzheimer's disease (AD) accounts for approximately 60-80% of all dementia cases in older adults. This study aimed to examine the relationship between finger movements and brain volume in AD patients using a voxel-based reginal analysis system for Alzheimer's disease (VSRAD) software.MethodsPatients diagnosed with AD at the Center for Comprehensive Care and Research on Memory Disorders were included. The diagnostic criteria were based on the National Institute on Aging-Alzheimer's Association. A finger-tapping device was used for all measurements. Participants performed the tasks in the following order: with their non-dominant hand, dominant hand, both hands simultaneously, and alternate hands. Movements were measured for 15 s each. The relationship between distance and output was measured. Magnetic resonance imaging measurements were performed, and VSRAD was conducted using sagittal section 3D T1-weighted images. The Z-score was used to calculate the severity of medial temporal lobe atrophy. Pearson's product-moment correlation coefficient analyzed the relationship between the severity of medial temporal lobe atrophy and mean values of the parameters in the finger-tapping movements. The statistical significance level was set at <5%. The calculated p-values were corrected using the Bonferroni method.ResultsSixty-two patients were included in the study. Comparison between VSRAD and MoCA-J scores corrected for p-values showed a significant negative correlation with the extent of gray matter atrophy (r = -0. 52; p< 0.001). A positive correlation was observed between the severity of medial temporal lobe atrophy and standard deviation (SD) of the distance rate of velocity peak in extending movements in the non-dominant hand (r = 0. 51; p< 0.001).ConclusionsThe SD of distance rate of velocity peak in extending movements extracted from finger taps may be a useful parameter for the early detection of AD and diagnosis of its severity.

Dataset Information

An automatic framework for quantitative validation of voxel based morphometry measures of anatomical brain asymmetry.

Publications

An automatic framework for quantitative validation of voxel based morphometry measures of anatomical brain asymmetry.

Similar Datasets

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