Functional Magnetic Resonance Imaging (fMRI) was used to examine brain activity in women with early stage Breast Cancer (BC) and to compare their neural profiles to a matched control group. This was accomplished as participants performed two working memory tasks, before and at two time points following the chemotherapy intervention of the BC group. Nineteen BC patients between the ages of 18 and 65 years were recruited from the Ottawa Hospital Regional Cancer Centre. The nineteen control participants were matched on sex, language, age and education. The results, from whole brain analyses, show significant differences in neural activity between BC patients and matched control participants during both verbal and visuospatial working memory tasks, before and right after chemotherapy. However, these differences were no longer observed one year post chemotherapy for verbal WM processing. Performance results were not significantly different between groups until the third imaging sessions when patients made significantly more errors of omission than controls for both tasks. Importantly, mood, anxiety and fatigue all played significant roles in the observed findings demonstrating the multifaceted nature of the impact of both cancer and chemotherapy on neural function during working memory. This is one of the first fMRI studies to measure neural activations during cognitive performance both before and after chemotherapy in BC patients and a control group while controlling for many potentially confounding variables. While BC patients should be made aware of the potential cognitive challenges they might face before, during and shortly after treatment, they can also feel reassured that these impairments may not be long lasting.

Functional Magnetic Resonance Imaging (fMRI) was used to examine brain activity in women with early stage Breast Cancer (BC) and to compare their neural profiles to a matched control group. This was accomplished as participants performed two working memory tasks, before and at two time points following the chemotherapy intervention of the BC group. Nineteen BC patients between the ages of 18 and 65 years were recruited from the Ottawa Hospital Regional Cancer Centre. The nineteen control participants were matched on sex, language, age and education. The results, from whole brain analyses, show significant differences in neural activity between BC patients and matched control participants during both verbal and visuospatial working memory tasks, before and right after chemotherapy. However, these differences were no longer observed one year post chemotherapy for verbal WM processing. Performance results were not significantly different between groups until the third imaging sessions when patients made significantly more errors of omission than controls for both tasks. Importantly, mood, anxiety and fatigue all played significant roles in the observed findings demonstrating the multifaceted nature of the impact of both cancer and chemotherapy on neural function during working memory. This is one of the first fMRI studies to measure neural activations during cognitive performance both before and after chemotherapy in BC patients and a control group while controlling for many potentially confounding variables. While BC patients should be made aware of the potential cognitive challenges they might face before, during and shortly after treatment, they can also feel reassured that these impairments may not be long lasting.

Chemotherapy related neurotoxicity is the decrease in cognitive function observed in patients receiving chemotherapy for breast cancer. For cancers with higher survival rates such as breast cancer, quality of life for patients after treatment cessation is a major concern. In studies performed in our laboratory, we reported cognitive deficiencies in male Swiss-Webster mice on administering 75 mg/kg 5-FU with 3.2 mg/kg MTX and these deficits were significantly greater than groups receiving either drug alone or in another higher dose combination. The probable mechanisms for the reported drug-drug interaction (DDI) between 5-FU and MTX could be either pharmacokinetic (PK) or pharmacological. Since the reported study consists of a combination of two drugs, it is imperative to determine if the PK of either drug was altered. On performing the PK based study we established the nature of the DDI to be PK based. We observed statistically significant changes for PK parameters clearance and apparent volume of distribution. Since, 5-FU and MTX are high clearance drugs, uptake transporters responsible for presenting the drugs to the clearing organs are the limiting factors for their clearance. Therefore, for any PK based interactions observed between 5-FU and MTX in the different dose groups a highly probable mechanism would be interactions at the site of uptake transporters. Based on the physicochemical properties of 5-FU and MTX and the results observed form the PK study, we hypothesized transporter-based interactions to be a probable mechanism for the observed DDI. From the transporter based studies we hypothesized 5-FU probably inhibited the uptake of MTX's transport across the blood brain barrier (BBB). To date the transport of MTX and other similar folates has not been characterized extensively. However, MTX is a very close analogue for reduced folates and therefore shares the transporter reduced folate carrier-1 (Rfc-1) expressed abundantly at the BBB, with endogenous reduced folates. Hence we hypothesized the decreased exposure of MTX in the presence of 5-FU would most probably be as a result of inhibition of uptake transporters such as Rfc-1. Finally, we developed a mathematical PK model for MTX to predict appropriately drug concentrations in the plasma and the brain tissue. The utility of the model was to support the hypothesized interactions responsible for the observed PK data. This models utility is to provide the PK component for the future PK-pharmacodynamic models, which would narrow the gap between the reported cognitive deficits and the PK results reported in this dissertation. / Pharmaceutical Sciences

Assessment of diffuse brain disorders, where the brain may appear normal, has proven difficult to translate into personalized treatments. Previous methods based on brain magnetic resonance imaging (MRI) resting state blood oxygen level dependent (rs-BOLD) signal routinely rely on group analysis where large data sets are assessed using region-of interest (ROI) or probabilistic independent component analysis (PICA) to identify temporal synchrony or desynchrony among regions of the brain. Brain connectivity occurs in a complex, multilevel and multi-temporal manner, driving the fluctuations observed in local oxygen demand. These fluctuations have previously been characterized as fractal, as they auto-correlate at different time scales. In this study we propose a model-free complexity analysis based on the fractal dimension of the rs-BOLD signal, acquired with MRI. The fractal dimension can be interpreted as a measure of signal complexity and connectivity. Previous studies have suggested that reduction in signal complexity can be associated with disease. Therefore, we hypothesized that a detectable differences in rs-BOLD signal complexity could be observed between patients with diffuse or heterogeneous brain disorders and healthy controls. In this study, we obtained anatomical and functional data from patients with brain disorders where traditional methods have been insufficient to fully assess the condition. More specifically, we tested our method on mild traumatic brain injury, autism spectrum disorder, chemotherapy-induced cognitive impairment and chronic fatigue syndrome patients. Three major databases from the Neuroimaging Informatics Tools and Resources Clearinghouse (NITRC) project were used to acquire large numbers of age matched healthy controls. Healthy control data was downloaded from the the Autism Brain Imaging Data Exchange (ABIDE), the Alzheimer's Disease Neuroimaging Initiative (ADNI) and the Human Connectome Project specifically matching our experimental design. In all of our studies, the voxel-wise rs-BOLD signal fractal dimension was calculated following a procedure described by Eke and Herman et al. 2000. This method was previously used to assess brain rs-BOLD signal in small mammals and humans. The method consists of estimating the Hurst exponent in the frequency domain using a power spectral density approach and refining the estimation in the time domain with de-trended fluctuation analysis and signal summation conversion methods. Voxel-wise fractal dimension (FD) was then calculated for every subject in the control and patient groups to create ROI-based Z-scores for each individual patient. Voxel-wise validation of FD normality across controls was studied and non-Gaussian voxels, determined using kurtosis and skewness calculations, were eliminated from subsequent analysis. To maintain a 95 % confidence level, only regions where Z-score values were at least 2 standard deviations away from the mean were included in the analysis. In the case of chronic fatigue patients and chemotherapy induced cognitive impairment, DTI analysis was added to also determine whether white matter abnormalities were also relevent. Similar Z-score analysis on DTI metrics was also performed. Brain microscopic networks, modeled as complex systems, become affected in diffuse brain disorders. Z-scoring of the fractal rs-BOLD frequency domain delineated patient-specific regional brain anomalies which correlated with patient-specific symptoms. This technique can be used alone, or in combination with DTI Z-scoring, to characterize a single patient without any need for group analysis, making it ideal for personalized diagnostics. / Thesis / Doctor of Philosophy (PhD)