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- Title
- Pre-implant Brain Activation Modeling to Drive Placement of Depth Leads in White Matter for Direct Neurostimulation Therapy in Epilepsy
- Creator
- Cendejas Zaragoza, Leopoldo
- Date
- 2019
- Description
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A critical step towards applying direct brain stimulation therapy in focal onset epilepsy is to effectively interface with epileptogenic...
Show moreA critical step towards applying direct brain stimulation therapy in focal onset epilepsy is to effectively interface with epileptogenic neural circuits using a limited set of active contacts. This takes special relevance when interacting with networks that exhibit two or more foci. A strategy to influence the maximum extent of the epileptogenic circuit is to stimulate white matter pathways to enhance propagation to distant epileptic tissue.A significant number of elements must be considered in the clinical response to stimulation delivered directly to neuronal populations. These variables include: stimulation parameter settings, number and interdependence of anatomical targets, electrode number, electrode location and orientation, geometry or shape of the electrode contacts, contact polarity, biophysical properties of stimulated medium, andtrajectory of axonal bundles adjacent to the stimulation site.This document addresses the development of a computational model which takes into consideration all the mentioned variables to predict activation of distant sites via white matter pathways. A method to calculate the extracellular potential field, induced by the application of time-dependent stimulation waveforms, is discussed. Such a method considers both the anisotropic conductivity nature of neural tissue and the electrochemical phenomena of the electrode-tissue interface. The response of white matter fibers is then evaluated by solving a compartmental cable model based in the Hodgkin and Huxley membrane description.The model was integrated into a pre-surgical workflow and was used prospectively to guide stereotactic implantation of depth leads to apply direct neurostimulation therapy in four patients with refractory focal onset epilepsy.
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- Title
- DEVELOPMENT OF BIOMARKERS OF SMALL VESSEL DISEASE IN AGING
- Creator
- Makkinejad, Nazanin
- Date
- 2021
- Description
-
Age-related neuropathologies including cerebrovascular and neurodegenerative diseases play a critical role in cognitive dysfunction, and...
Show moreAge-related neuropathologies including cerebrovascular and neurodegenerative diseases play a critical role in cognitive dysfunction, and development of dementia. Designing methodologies for early prediction of these diseases are much needed. Since multiple pathologies commonly coexist in brains of older adults, clinical diagnosis lacks the specificity to isolate the pathology of interest, and gold standard is determined only at autopsy. Magnetic resonance imaging (MRI) provides a non-invasive tool to study abnormalities in brain characteristics that is unique to each pathology. Utilizing ex-vivo MRI for brain imaging proves to be useful as it eliminates two important biases of in-vivo MRI. First, no additional pathology would develop between imaging and pathologic examination, and second, frail older adults would not be excluded from MRI.Hence, the aims of this dissertation were two-fold: to study brain correlates of age- related neuropathologies, and to develop and validate classifiers of small vessel diseases by combining ex-vivo MRI and pathology in a large community cohort of older adults. The structure of the project is as follows.First, the association of amygdala volume and shape with transactive response DNA-binding protein 43 (TDP-43) pathology was investigated. Using a regularized regression technique, higher TDP-43 was associated with lower amygdala volume. Also, shape analysis of amygdala showed unique patterns of spatial atrophy associated with TDP-43 independent of other pathologies. Lastly, using linear mixed effect models, amygdala volume was shown to explain an additional portion of variance in cognitive decline above and beyond what was explained by the neuropathologies and demographics.Second, the previous study was extended to analyze other subcortical regions including the hippocampus, thalamus, nucleus accumbens, caudate, and putamen, and was also conducted in a larger dataset. The results showed unique contribution of TDP-43, neurofibrillary tangles (hallmark characteristic of Alzheimer’s disease pathology), and atherosclerosis (a cerebrovascular pathology) to atrophy on the surface of subcortical structures. Understanding the independent effects of each pathology on volume and shape of different brain regions can form a basis for the development of classifiers of age-related neuropathologies.Third, an in-vivo classifier of arteriolosclerosis was developed and validated. Arteriolosclerosis is one of the main pathologies of small vessel disease, is associated with cognitive decline and dementia, and currently has no standard biomarker available. In this work, the classifier was developed ex-vivo using machine learning (ML) techniques and was then translated to in-vivo. The in-vivo classifier was packaged as a software called ARTS, which outputs a score that is the likelihood of arteriolosclerosis when the required input is given to the software. It was tested and validated in various cohorts and showed to have high performance in predicting the pathology. It was also shown that higher ARTS score was associated with greater cognitive decline in domains that are specific to small vessel disease.Fourth, motivated by current trends and superiority of deep learning (DL) techniques in classification tasks in computer vision and medical imaging, a preliminary study was designed to use DL for training an ex-vivo classifier of arteriolosclerosis. Specifically, convolutional neural networks (CNNs) were applied on 3 Tesla ex-vivo MR images directly without providing prior information of brain correlates of arteriolosclerosis. One interesting aspect of the results was that the network learnt that white matter hyperintense lesions contributed the most to classification of arteriolosclerosis. These results were encouraging, and more future work will exploit the capability of DL techniques alongside the traditional ML approaches for more automation and possibly better performance.Finally, a preliminary classifier of arteriolosclerosis and small vessel atherosclerosis was developed since the existence of both pathologies in brain have devastating effects on cognition. The methodology was similar to the one used for development of arteriolosclerosis classifier with minor differences. The classifier showed a good performance in-vivo, although the testing needs to be assessed in more cohorts.The comprehensive study of age-related neuropathologies and their contribution to abnormalities of subcortical brain structures offers a great potential to develop a biomarker of each pathology. Also, the finding that the MR-based classifier of arteriolosclerosis showed high performance in-vivo demonstrate the potential of ex-vivo studies for development of biomarkers that are precise (because they are based on autopsy, which is the gold standard) and are expected to work well in-vivo. The implications of this study include development of biomarkers that could potentially be used in refined participant selection and enhanced monitoring of the treatment response in clinical drug and prevention trials.
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- Title
- Comparing the effects of an adjunct brief action planning intervention to standard treatment in a heterogeneous sample of chronic pain patients
- Creator
- Mikrut, Cassandra Leona
- Date
- 2022
- Description
-
Objectives: Behavioral treatments for chronic pain have been associated with positive outcomes, but they are often time consuming in nature....
Show moreObjectives: Behavioral treatments for chronic pain have been associated with positive outcomes, but they are often time consuming in nature. The aim of the present study was to investigate the effectiveness of a brief behavioral treatment for chronic pain and compare Brief Action Planning used in conjunction with treatment as usual (BAP + TAU) to TAU, on changes in pain severity, pain interference, pain self-efficacy, quality of life, and anxiety and depression in a heterogeneous sample of chronic pain patients. Methods: A total of 172 participants were recruited from an urban pain clinic. Eighty-five participants were quasi-randomly assigned to the BAP + TAU group and 87 participants were quasi-randomly assigned to the TAU control group. After completing T1 measures, two iterations of the BAP protocol were delivered to the intervention group by a trained clinician over the phone, with two weeks in between iterations. The TAU group received check-in calls, collecting brief mood and pain scores, to control for clinician contact. All participants completed T2 measures following the last phone call. Validated measures were used at T1 and T2 to examine participant outcomes. Results: Two-way repeated measures analysis of variance (ANOVA) tests were used to test the primary hypotheses that there would be a Group x Time interaction, on pain severity, pain interference, pain self-efficacy, quality of life (QOL), and anxiety and depression, such that participants assigned to the BAP + TAU group would endorse improved scores from T1 to T2, while TAU participants would not. Results showed a significant Group x Time interaction on pain severity and anxiety and depression. However, there was not a significant Group x Time interaction on pain interference, pain self-efficacy, or QOL. Discussion: These findings provide preliminary support for the effectiveness of BAP, as an adjunctive treatment to TAU, when provided by a trained clinician, as a treatment for reducing pain severity and anxiety and depression, in a heterogeneous chronic pain population. These results advance the current BAP literature, providing preliminary support for using BAP with individuals with a wide variety of chronic pain diagnoses.
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