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- All Subjects: MRI
- Creators: Kostelich, Eric
- Creators: Braden, B. Blair
Description
Cognitive deficits often accompany language impairments post-stroke. Past research has focused on working memory in aphasia, but attention is largely underexplored. Therefore, this dissertation will first quantify attention deficits post-stroke before investigating whether preserved cognitive abilities, including attention, can improve auditory sentence comprehension post-stroke. In Experiment 1a, three components of attention (alerting, orienting, executive control) were measured in persons with aphasia and matched-controls using visual and auditory versions of the well-studied Attention Network Test. Experiment 1b then explored the neural resources supporting each component of attention in the visual and auditory modalities in chronic stroke participants. The results from Experiment 1a indicate that alerting, orienting, and executive control are uniquely affected by presentation modality. The lesion-symptom mapping results from Experiment 1b associated the left angular gyrus with visual executive control, the left supramarginal gyrus with auditory alerting, and Broca’s area (pars opercularis) with auditory orienting attention post-stroke. Overall, these findings indicate that perceptual modality may impact the lateralization of some aspects of attention, thus auditory attention may be more susceptible to impairment after a left hemisphere stroke.
Prosody, rhythm and pitch changes associated with spoken language may improve spoken language comprehension in persons with aphasia by recruiting intact cognitive abilities (e.g., attention and working memory) and their associated non-lesioned brain regions post-stroke. Therefore, Experiment 2 explored the relationship between cognition, two unique prosody manipulations, lesion location, and auditory sentence comprehension in persons with chronic stroke and matched-controls. The combined results from Experiment 2a and 2b indicate that stroke participants with better auditory orienting attention and a specific left fronto-parietal network intact had greater comprehension of sentences spoken with sentence prosody. For list prosody, participants with deficits in auditory executive control and/or short-term memory and the left angular gyrus and globus pallidus relatively intact, demonstrated better comprehension of sentences spoken with list prosody. Overall, the results from Experiment 2 indicate that following a left hemisphere stroke, individuals need good auditory attention and an intact left fronto-parietal network to benefit from typical sentence prosody, yet when cognitive deficits are present and this fronto-parietal network is damaged, list prosody may be more beneficial.
Prosody, rhythm and pitch changes associated with spoken language may improve spoken language comprehension in persons with aphasia by recruiting intact cognitive abilities (e.g., attention and working memory) and their associated non-lesioned brain regions post-stroke. Therefore, Experiment 2 explored the relationship between cognition, two unique prosody manipulations, lesion location, and auditory sentence comprehension in persons with chronic stroke and matched-controls. The combined results from Experiment 2a and 2b indicate that stroke participants with better auditory orienting attention and a specific left fronto-parietal network intact had greater comprehension of sentences spoken with sentence prosody. For list prosody, participants with deficits in auditory executive control and/or short-term memory and the left angular gyrus and globus pallidus relatively intact, demonstrated better comprehension of sentences spoken with list prosody. Overall, the results from Experiment 2 indicate that following a left hemisphere stroke, individuals need good auditory attention and an intact left fronto-parietal network to benefit from typical sentence prosody, yet when cognitive deficits are present and this fronto-parietal network is damaged, list prosody may be more beneficial.
ContributorsLaCroix, Arianna (Author) / Rogalsky, Corianne (Thesis advisor) / Azuma, Tamiko (Committee member) / Braden, B. Blair (Committee member) / Liss, Julie (Committee member) / Arizona State University (Publisher)
Created2019
Description
Glioblastoma multiforme (GBM) is a malignant, aggressive and infiltrative cancer of the central nervous system with a median survival of 14.6 months with standard care. Diagnosis of GBM is made using medical imaging such as magnetic resonance imaging (MRI) or computed tomography (CT). Treatment is informed by medical images and includes chemotherapy, radiation therapy, and surgical removal if the tumor is surgically accessible. Treatment seldom results in a significant increase in longevity, partly due to the lack of precise information regarding tumor size and location. This lack of information arises from the physical limitations of MR and CT imaging coupled with the diffusive nature of glioblastoma tumors. GBM tumor cells can migrate far beyond the visible boundaries of the tumor and will result in a recurring tumor if not killed or removed. Since medical images are the only readily available information about the tumor, we aim to improve mathematical models of tumor growth to better estimate the missing information. Particularly, we investigate the effect of random variation in tumor cell behavior (anisotropy) using stochastic parameterizations of an established proliferation-diffusion model of tumor growth. To evaluate the performance of our mathematical model, we use MR images from an animal model consisting of Murine GL261 tumors implanted in immunocompetent mice, which provides consistency in tumor initiation and location, immune response, genetic variation, and treatment. Compared to non-stochastic simulations, stochastic simulations showed improved volume accuracy when proliferation variability was high, but diffusion variability was found to only marginally affect tumor volume estimates. Neither proliferation nor diffusion variability significantly affected the spatial distribution accuracy of the simulations. While certain cases of stochastic parameterizations improved volume accuracy, they failed to significantly improve simulation accuracy overall. Both the non-stochastic and stochastic simulations failed to achieve over 75% spatial distribution accuracy, suggesting that the underlying structure of the model fails to capture one or more biological processes that affect tumor growth. Two biological features that are candidates for further investigation are angiogenesis and anisotropy resulting from differences between white and gray matter. Time-dependent proliferation and diffusion terms could be introduced to model angiogenesis, and diffusion weighed imaging (DTI) could be used to differentiate between white and gray matter, which might allow for improved estimates brain anisotropy.
ContributorsAnderies, Barrett James (Author) / Kostelich, Eric (Thesis director) / Kuang, Yang (Committee member) / Stepien, Tracy (Committee member) / Harrington Bioengineering Program (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
Glioblastoma Multiforme (GBM) is an aggressive and deadly form of brain cancer with a median survival time of about a year with treatment. Due to the aggressive nature of these tumors and the tendency of gliomas to follow white matter tracks in the brain, each tumor mass has a unique growth pattern. Consequently it is difficult for neurosurgeons to anticipate where the tumor will spread in the brain, making treatment planning difficult. Archival patient data including MRI scans depicting the progress of tumors have been helpful in developing a model to predict Glioblastoma proliferation, but limited scans per patient make the tumor growth rate difficult to determine. Furthermore, patient treatment between scan points can significantly compound the challenge of accurately predicting the tumor growth. A partnership with Barrow Neurological Institute has allowed murine studies to be conducted in order to closely observe tumor growth and potentially improve the current model to more closely resemble intermittent stages of GBM growth without treatment effects.
ContributorsSnyder, Lena Haley (Author) / Kostelich, Eric (Thesis director) / Frakes, David (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Harrington Bioengineering Program (Contributor)
Created2014-05
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
Description
This dissertation develops a second order accurate approximation to the magnetic resonance (MR) signal model used in the PARSE (Parameter Assessment by Retrieval from Single Encoding) method to recover information about the reciprocal of the spin-spin relaxation time function (R2*) and frequency offset function (w) in addition to the typical steady-state transverse magnetization (M) from single-shot magnetic resonance imaging (MRI) scans. Sparse regularization on an approximation to the edge map is used to solve the associated inverse problem. Several studies are carried out for both one- and two-dimensional test problems, including comparisons to the first order approximation method, as well as the first order approximation method with joint sparsity across multiple time windows enforced. The second order accurate model provides increased accuracy while reducing the amount of data required to reconstruct an image when compared to piecewise constant in time models. A key component of the proposed technique is the use of fast transforms for the forward evaluation. It is determined that the second order model is capable of providing accurate single-shot MRI reconstructions, but requires an adequate coverage of k-space to do so. Alternative data sampling schemes are investigated in an attempt to improve reconstruction with single-shot data, as current trajectories do not provide ideal k-space coverage for the proposed method.
ContributorsJesse, Aaron Mitchel (Author) / Platte, Rodrigo (Thesis advisor) / Gelb, Anne (Committee member) / Kostelich, Eric (Committee member) / Mittelmann, Hans (Committee member) / Moustaoui, Mohamed (Committee member) / Arizona State University (Publisher)
Created2019