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- All Subjects: MRI
- Creators: Baxter, Leslie
Description
Background: Noninvasive MRI methods that can accurately detect subtle brain changes are highly desirable when studying disease-modifying interventions. Texture analysis is a novel imaging technique which utilizes the extraction of a large number of image features with high specificity and predictive power. In this investigation, we use texture analysis to assess and classify age-related changes in the right and left hippocampal regions, the areas known to show some of the earliest change in Alzheimer's disease (AD). Apolipoprotein E (APOE)'s e4 allele confers an increased risk for AD, so studying differences in APOE e4 carriers may help to ascertain subtle brain changes before there has been an obvious change in behavior. We examined texture analysis measures that predict age-related changes, which reflect atrophy in a group of cognitively normal individuals. We hypothesized that the APOE e4 carriers would exhibit significant age-related differences in texture features compared to non-carriers, so that the predictive texture features hold promise for early assessment of AD. Methods: 120 normal adults between the ages of 32 and 90 were recruited for this neuroimaging study from a larger parent study at Mayo Clinic Arizona studying longitudinal cognitive functioning (Caselli et al., 2009). As part of the parent study, the participants were genotyped for APOE genetic polymorphisms and received comprehensive cognitive testing every two years, on average. Neuroimaging was done at Barrow Neurological Institute and a 3D T1-weighted magnetic resonance image was obtained during scanning that allowed for subsequent texture analysis processing. Voxel-based features of the appearance, structure, and arrangement of these regions of interest were extracted utilizing the Mayo Clinic Python Texture Analysis Pipeline (pyTAP). Algorithms applied in feature extraction included Grey-Level Co-Occurrence Matrix (GLCM), Gabor Filter Banks (GFB), Local Binary Patterns (LBP), Discrete Orthogonal Stockwell Transform (DOST), and Laplacian-of-Gaussian Histograms (LoGH). Principal component (PC) analysis was used to reduce the dimensionality of the algorithmically selected features to 13 PCs. A stepwise forward regression model was used to determine the effect of APOE status (APOE e4 carriers vs. noncarriers), and the texture feature principal components on age (as a continuous variable). After identification of 5 significant predictors of age in the model, the individual feature coefficients of those principal components were examined to determine which features contributed most significantly to the prediction of an aging brain. Results: 70 texture features were extracted for the two regions of interest in each participant's scan. The texture features were coded as 70 initial components andwere rotated to generate 13 principal components (PC) that contributed 75% of the variance in the dataset by scree plot analysis. The forward stepwise regression model used in this exploratory study significantly predicted age, accounting for approximately 40% of the variance in the data. The regression model revealed 5 significant regressors (2 right PC's, APOE status, and 2 left PC by APOE interactions). Finally, the specific texture features that contributed to each significant PCs were identified. Conclusion: Analysis of image texture features resulted in a statistical model that was able to detect subtle changes in brain integrity associated with age in a group of participants who are cognitively normal, but have an increased risk of developing AD based on the presence of the APOE e4 phenotype. This is an important finding, given that detecting subtle changes in regions vulnerable to the effects of AD in patients could allow certain texture features to serve as noninvasive, sensitive biomarkers predictive of AD. Even with only a small number of patients, the ability for us to determine sensitive imaging biomarkers could facilitate great improvement in speed of detection and effectiveness of AD interventions..
ContributorsSilva, Annelise Michelle (Author) / Baxter, Leslie (Thesis director) / McBeath, Michael (Committee member) / Presson, Clark (Committee member) / School of Life Sciences (Contributor) / Department of Psychology (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
The objective of the research presented here was to validate the use of kinetic models for the analysis of the dynamic behavior of a contrast agent in tumor tissue and evaluate the utility of such models in determining kinetic properties - in particular perfusion and molecular binding uptake associated with tissue hypoxia - of the imaged tissue, from concentration data acquired with dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) procedure. Data from two separate DCE-MRI experiments, performed in the past, using a standard contrast agent and a hypoxia-binding agent respectively, were analyzed. The results of the analysis demonstrated that the models used may provide novel characterization of the tumor tissue properties. Future research will work to further characterize the physical significance of the estimated parameters, particularly to provide quantitative oxygenation data for the imaged tissue.
ContributorsMartin, Jonathan Michael (Author) / Kodibagkar, Vikram (Thesis director) / Rege, Kaushal (Committee member) / Barrett, The Honors College (Contributor) / Chemical Engineering Program (Contributor) / School of Mathematical and Statistical Sciences (Contributor)
Created2013-12
Description
Background: Gait disturbance, clumsiness, and other mild movement problems are often observed in children with autism spectrum disorder (ASD) (Maurer and Damasio 1982). As the brain ages, these symptoms may persist or worsen in late adulthood in those diagnosed with ASD. This study focused on older adults with ASD to study motor behavior and underlying brain integrity. Using a finger tapping task, motor performance was measured in a cross-sectional study comparing older adults with ASD and age-matched typically developing (TD) controls. We hypothesized that older adults with ASD would show poorer motor performance (slower finger tapping speed). We also hypothesized that underlying brain differences, measured using MRI, in regions associated with motor function including the primary motor cortex, basal ganglia, and cerebellum, as well as the white matter connecting tracts would exist between groups and be associated with the proposed disparity in motor performance.
Method: A finger oscillation (Finger Tapping) test was administered to both ASD (n=21) and TD (n=20) participants aged 40-70 year old participants as a test of fine motor speed. Magnetic resonance (MR) images were collected using a Philips 3 Tesla scanner. 3D T1-weighted and diffusion tensor images (DTI) were obtained to measure gray and white matter volume and white matter integrity, respectively. FreeSurfer, an automated volumetric measurement software, was used to determine group volumetric differences. Mean, radial, and axial diffusivity, fractional anisotropy, and local diffusion homogeneity were measured from DTI images using PANDA software in order to evaluate white matter integrity.
Results: All participants were right-handed and there were no significant differences in demographic variables (ASD/TD, means) including age (51.9/49.1 years), IQ (107/112) and years education (15/16). Total brain volume was not significantly different between groups. No statistically significant group differences were observed in finger tapping speed. ASD participants compared to TDs showed a trend of slower finger tapping (taps/10 seconds) speed on the dominant hand (47.00 (±11.2) vs. (50.5 (±6.6)) and nondominant hand (44.6 (±7.6) vs. (47.2 (±6.6)). However, a large degree of variability was observed in the ASD group, and the Levene’s test for homogeneity of variance approached significance (p=0.053) on the dominant, but not the nondominant, hand. No significant group differences in gray matter regional volume were found for brain regions associated with performing motor tasks. In contrast, group differences were found on several measures of white matter including the corticospinal tract, anterior internal capsule and middle cerebellar peduncle. Brain-behavior correlations showed that dominant finger tapping speed correlated with left hemisphere white matter integrity of the corticospinal tract and right hemisphere cerebellar white matter in the ASD group.
Conclusions: No significant differences were observed between groups in finger tapping speed but the high degree of variability seen in the ASD group. Differences in motor performance appear to be associated with observed brain differences, particularly in the integrity of white matter tracts contributing to motor functioning.
Method: A finger oscillation (Finger Tapping) test was administered to both ASD (n=21) and TD (n=20) participants aged 40-70 year old participants as a test of fine motor speed. Magnetic resonance (MR) images were collected using a Philips 3 Tesla scanner. 3D T1-weighted and diffusion tensor images (DTI) were obtained to measure gray and white matter volume and white matter integrity, respectively. FreeSurfer, an automated volumetric measurement software, was used to determine group volumetric differences. Mean, radial, and axial diffusivity, fractional anisotropy, and local diffusion homogeneity were measured from DTI images using PANDA software in order to evaluate white matter integrity.
Results: All participants were right-handed and there were no significant differences in demographic variables (ASD/TD, means) including age (51.9/49.1 years), IQ (107/112) and years education (15/16). Total brain volume was not significantly different between groups. No statistically significant group differences were observed in finger tapping speed. ASD participants compared to TDs showed a trend of slower finger tapping (taps/10 seconds) speed on the dominant hand (47.00 (±11.2) vs. (50.5 (±6.6)) and nondominant hand (44.6 (±7.6) vs. (47.2 (±6.6)). However, a large degree of variability was observed in the ASD group, and the Levene’s test for homogeneity of variance approached significance (p=0.053) on the dominant, but not the nondominant, hand. No significant group differences in gray matter regional volume were found for brain regions associated with performing motor tasks. In contrast, group differences were found on several measures of white matter including the corticospinal tract, anterior internal capsule and middle cerebellar peduncle. Brain-behavior correlations showed that dominant finger tapping speed correlated with left hemisphere white matter integrity of the corticospinal tract and right hemisphere cerebellar white matter in the ASD group.
Conclusions: No significant differences were observed between groups in finger tapping speed but the high degree of variability seen in the ASD group. Differences in motor performance appear to be associated with observed brain differences, particularly in the integrity of white matter tracts contributing to motor functioning.
ContributorsDeatherage, Brandon R. (Co-author) / Braden, B. Blair (Co-author, Committee member) / Smith, Christopher J. (Co-author) / McBeath, Michael (Co-author, Thesis director) / Thompson, Aimee M. (Co-author) / Wood, Emily G. (Co-author) / McGee, Samuel C. (Co-author) / Sinha, Krishna (Co-author) / Baxter, Leslie (Co-author, Committee member) / Barrett, The Honors College (Contributor) / School of Nutrition and Health Promotion (Contributor) / Department of Information Systems (Contributor)
Created2017-05