Magnetic resonance imaging (MRI) has increasingly become the preferred imaging modality in modern day research to study disease. MRI presents an imaging technique that is practically non-invasive and without any ionizing radiation. This dissertation presents the use of contrast agents in MRI studies to differentiate compartments, to study dose dependence of relaxation times, and to characterize tumors using signal amplifying enzymes in the brain. Differentiating compartments in the brain can be useful in diffusion studies to detect stroke at an early stage. Diffusion-weighted NMR techniques have established that the apparent diffusion coefficient (ADC) of cerebral tissue water decreases during ischemia. However, it is unclear whether the ADC change occurs due to changes in the intracellular (IC) space, extracellular (EC) space, or both. To better understand the mechanism of water ADC changes in response to ischemic injury, making IC and EC compartment specific measurements of water diffusion is essential. The first study was done where manganese (Mn2+) was used as an IC contrast agent. Mn2+ uptake by cells causes shortening of the T1 relaxation time of IC water. The relative difference in T1 relaxation times between the IC and EC compartments can be used to discriminate between the MR signals arising from water in the respective compartments. Mn2+ is also widely used in manganese-enhanced MRI (MEMRI) studies to visualize functional neural tracts and anatomy in the brain in vivo. In animal studies, the goal is to use a dose of Mn2+ that will maximize the contrast while minimizing its toxic effects. The goal of dose study was to investigate the MRI dose response of Mn2+ in rat brain following SC administration of Mn2+. The dose dependence and temporal dynamics of Mn2+ after SC injection can prove useful for longitudinal in vivo studies that require brain enhancement to persist for a long period of time to visualize neuroarchitecture like in neurodegenerative disease studies. Contrast agents, in addition to their use in compartmental differentiation and dose studies, can be used for imaging tumors. The last study in this dissertation focuses on imaging EGF receptors in brain tumors. We tested a novel pretargeting imaging approach that includes the administration of humanized monoclonal antibody (anti-EGFR mAb, EMD72000) linked to enzymes with complementing activities that use a low-molecular weight paramagnetic molecule (diTyr-GdDTPA) as a reducing substrate administered following the mAb conjugates. We analyzed the differential MR tumor signal decay in vivo using orthotopic models of human glioma. The patterns of MR signal change following substrate administration revealed differences in elimination patterns that allowed distinguishing between non-specific and specific modes of MR signal decay.

A consensus model combines statistical methods with signal processing to create a better picture of the family of related signals. In this thesis, we will consider 32 signals produced by a single electroencephalogram (EEG) recording session. The consensus model will be produced by using the S-Transform of the individual signals and then normalized to unit energy. A bootstrapping process is used to produce a consensus spectrum. This leads to the consensus model via the inverse S-Transform of the consensus spectrum. The method will be applied to both a control and experimental EEG to show how the results can be used in clinical settings to analyze experimental outcomes.

Despite the amount of research that has been conducted on self-injury there is a lack of empirically validated instruments with which to measure self-injurious behavior. The present study developed a measure to examine self-injury and the associated features. Undergraduate students (n = 184) were administered a set of surveys to assess demographics, self-injurious behavior, suicidal ideation, Axis I and Axis II disorders, and impulsivity. Results indicated that a reliable measure, able to assess the extent of self-injury as well as associated features, was developed. Such a measure will enable clinicians to better assess self-injury and enable researchers to more fully examine self-injury and its relationship to other disorders.

The vestibular system senses head motion and facilitates gaze stabilization, allowing for clear vision during movement. The vestibulo-ocular reflex (VOR) causes the eyes to move opposite head motion, thus maintaining focus on a target. Consequently, uncompensated loss of vestibular function leads to reduced VOR function resulting in dizziness, nausea, and visual disturbance. Different testing methods have been developed to measure VOR loss. These tests generally require bulky, expensive equipment, and must be performed by a trained examiner. A newly developed digital form of the dynamic visual acuity (DVA) test requires less equipment, is cost-effective, and may be performed at home making it more accessible. The purpose of this study was to determine the validity and test-retest reliability of the digital DVA test and provide normative data for healthy adults. Fifteen adults – 10 female and 5 male (mean age = 22.0 ± 3.1, range: 19-31 years) – completed the study. Exclusion criteria included age older than 49 years, history of vestibular or neurological disorders, and history of significant head injury. Subjects were screened for normal vestibular function using video head impulse testing. The study consisted of two visits, 3-15 days apart. Participants underwent DVA testing with both the validated NeuroCom (InVision software) system and newly developed digital DVA during the initial visit and the digital DVA during the second visit. The digital DVA system consists of a laptop computer paired with a head/eye tracker (Tobii Eye Tracker 5) and Health in Motion software (Blue Marble Health Company). Outcome measures of interest were the difference between static and dynamic visual acuity measured in LogMAR (DVA loss) for rightward and leftward head movement. Pearson Product-Moment bivariate correlations were used to determine validity of the digital DVA outcomes compared to NeuroCom outcomes. Intraclass correlation coefficients (ICCs) were calculated to determine test-retest reliability of the digital DVA. Pearson correlation coefficients for validity were r = 0.025 and r = -0.015 for left and right DVA loss, respectively. ICCs for test-retest reliability were r = 0.366 and r = 0.313 for left and right DVA loss, respectively. Mean values across both sessions for left and right DVA loss measured by digital DVA were 0.26 ± 0.13 and 0.26 ± 0.11, respectively. Correlations between the digital DVA and standard computerized DVA were poor indicating the need for further development of the current digital system/software. Test-retest reliability for the digital DVA system in its current state was also poor. Tobii sensor used in the software is limited by a 200 ms delay in reporting head motion to the software. Future development of a digital DVA may need to consider other sensors. The current digital DVA will not replace the computerized system; however, it may provide important information for clinicians who do not have access to computerized DVA.

Statistical data suggests that increased use of evidence-based medical therapies has largely contributed to the decrease in American death rate caused by heart disease. And my studies are about two applications of magnetic resonance imaging (MRI) as a non-invasive approach in evidence-based health care research. In my first study, the achievement of a pulmonary valve replacement surgery was assessed on a patient with tetralogy of Fallot (TOF). In order to evaluate the remodeling of right ventricle, two biventricular finite element models were built up for pre-surgical images and post-surgical images. In my second study, 3D Lagrangian strains and torsion in the left ventricle of ten rats were investigated using Displacement ENcoding with Stimulated Echoes (DENSE) cardiac magnetic resonance (CMR) images. Tools written in MATLAB were developed for 2D contouring, 3D modeling, strain and torsion computations, and statistical comparison across subjects.

Many cerebral diseases are associated with abnormal cerebral hemodynamics and impaired cerebral autoregulation (CA). CA is a mechanism to maintain cerebral blood flow (CBF) stable when mean arterial pressure (MAP) fluctuates. Evaluating these abnormalities requires direct measurements of cerebral hemodynamics and MAP. Several near-infrared diffuse optical instruments have been developed in our laboratory for hemodynamic measurements including near-infrared spectroscopy (NIRS), diffuse correlation spectroscopy (DCS), hybrid NIRS/DCS, and dual-wavelength DCS flow-oximeter. We utilized these noninvasive technologies to quantify CBF and cerebral oxygenation in different populations under different physiological conditions/manipulations. A commercial finger plethysmograph was used to continuously monitor MAP. For investigating the impact of obstructive sleep apnea (OSA) on cerebral hemodynamics and CA, a portable DCS device was used to monitor relative changes of CBF (rCBF) during bilateral thigh cuff occlusion. Compared to healthy controls, smaller reductions in rCBF and MAP following cuff deflation were observed in patients with OSA, which might result from the impaired vasodilation. However, dynamic CAs quantified in time-domain (defined by rCBF drop/MAP drop) were not significantly different between the two groups. We also evaluated dynamic CA in frequency-domain, i.e., to quantify the phase shifts of low frequency oscillations (LFOs) at 0.1 Hz between cerebral hemodynamics and MAP under 3 different physiological conditions (i.e., supine resting, head-up tilt (HUT), paced breathing). To capture dynamic LFOs, a hybrid NIRS/DCS device was upgraded to achieve faster sampling rate and better signal-to-noise. We determined the best hemodynamic parameters (i.e., CBF, oxygenated and total hemoglobin concentrations) among the measured variables and optimal physiological condition (HUT) for detecting LFOs in healthy subjects. Finally, a novel dual-wavelength DCS flow-oximeter was developed to monitor cerebral hemodynamics during HUT-induced vasovagal presyncope (VVS) in healthy subjects. rCBF was found to have the best sensitivity for the assessment of VVS among the measured variables and was likely the final trigger of VVS. A threshold of ~50% rCBF decline was observed which can completely separate subjects with or without presyncope, suggesting its potential role for predicting VVS. With further development and applications, NIRS/DCS techniques are expected to have significant impacts on the evaluation of cerebral hemodynamics and autoregulation.

BACKGROUND: Several studies have demonstrated the association between the time to hypertension event and multiple baseline measurements for adults, yet other survival cardiovascular disease (CVD) outcomes such as high cholesterol and heart attack have been somewhat less considered. The Fels Longitudinal Study (FLS) provides us an opportunity to connect adult blood pressure (BP) at certain ages to the time to first CVD outcomes. The availability of long-term serial BP measurements from FLS also potentially allows us to evaluate if the trend of the measured BP biomarkers over time predicts survival outcomes in adulthood through statistical modeling. METHODS: When the reference standard is right-censored time-to-event (survival) outcome, the C index or concordance C, is commonly used as a summary measure of discrimination between a survival outcome that is possibly right censored and a predictive-score variable, say, a measured biomarker or a composite-score output from a statistical model that combines multiple biomarkers. When we have subjects longitudinally followed up, it is of primary interest to assess if some baseline measurements predict the time-to-event outcome. Specifically, in this study, systolic blood pressure, diastolic blood pressure, as well as their variation over time, are considered predictive biomarkers, and we assess their predictive ability for certain time-to-event outcomes in terms of the C index. RESULTS: There are a few summary C index differences that are statistically significant in predicting and discriminating certain CVD metric at certain age stage, though some of these differences are altered in the presence of medicine treatment and lifestyle characteristics. The variation of systolic BP measures over time has a significantly different predicting ability comparing with systolic BP measures at certain given time point, for predicting certain survival outcome such as high cholesterol level. CONCLUSIONS: Adult systolic and diastolic BP measurements may have significantly different ability in predicting time to first CVD events. The fluctuation of BP measurements over time may have better association than BP measurement at a single baseline time point, with the time to first CVD events.

Parkinson’s disease and Essential tremor are the two most prevalent movement disorders in the world, but due to overlapping clinical symptoms, accurate differential diagnosis is difficult. As a result, approximately 60% of patients with movement disorders symptoms will have their diagnosis changed at least once before death. By their subjective nature, clinical exams are inherently imprecise, leading to the desire to create an objective, quantifiable test for movement disorders; a test that currently is elusive. Eye movements have been studied for a century, and are widely appreciated to be quantifiably affected in those with neurological disease. Through a collaborative effort between the VA hospital and VCU, over 1,000 movement disorder subjects had their eye movements recorded, utilizing an SR Research Eyelink 2. Patients with Parkinson’s disease exhibited an ocular gaze tremor during fixation, normal reflexive saccades, and reduced blink rate. Subjects with Essential tremor exhibited slowed saccadic dynamics, with increased latencies, in addition to a larger number of square wave jerk interruptions of otherwise stable fixation. After diagnostic features of each disorder were identified, prospective data collection could occur in a blinded fashion, and oculomotor features used to predict clinical diagnoses. It was determined that measures of fixation stability were capable of almost perfectly differentiating subjects with PD, and a novel, combined parameter was capable of similar results in ET. As a group, it appears as if these symptoms do not progress as the disease does, but subanalyses show that individual patients on constant pharmaceutical doses tracked over time do slightly change and progress. The near perfect separation of disease states suggest the ability of oculomotor recording to be a powerful biomarker to be used for the differential diagnosis of movement disorders. This tool could potentially impact and improve the lives of millions of people the world over.

Four dimensional imaging has become part of the standard of care for diagnosing and treating non-small cell lung cancer. In radiotherapy applications 4D fan-beam computed tomography (4D-CT) and 4D cone-beam computed tomography (4D-CBCT) are two advanced imaging modalities that afford clinical practitioners knowledge of the underlying kinematics and structural dynamics of diseased tissues and provide insight into the effects of regular organ motion and the nature of tissue deformation over time. While these imaging techniques can facilitate the use of more targeted radiotherapies, issues surrounding image quality and accuracy currently limit the utility of these images clinically. The purpose of this project is to develop methods that retrospectively compensate for anatomical motion in 4D-CBCT and correct motion artifacts present in 4D-CT to improve the image quality of reconstructed volume and assist in localizing respiration-influenced, diseased tissue and mobile structures of interest. In the first half of the project, a series of motion compensation (MoCo) workflow methods incorporating groupwise deformable image registration and projection-warped reconstruction were developed for use with 4D-CBCT imaging. In the latter half of the project, novel motion artifact observation and artifact- weighted groupwise registration-based image correction algorithms were designed and tested. Both deliverable components of this project were evaluated for their ability to enhance image quality when applied to clinical patient datasets and demonstrated qualitative and quantitative improvements over current state-of-the-art.

In humans and other organisms, monoaminergic systems are crucial in neuronal function and behavior. The monoamine transporters (MATs), which can be found on the presynaptic plasma membrane of neurons in the central nervous system (CNS), are crucial in the regulation of neurotransmitter concentration in the synaptic cleft. As the duration and concentration of neurotransmitters in the cleft affect further downstream signaling responses, these proteins are important targets for both understanding neuronal physiology and compounds of interest. Multiple theories exist proponing the contribution of MATs to a variety of mental and neurological disorders, including depression. This theory establishes that depression is caused by imbalances in monoamine neurotransmitters. Compounds such as Fluoxetine (FLX) are classified as selective serotonin reuptake inhibitors (SSRIs), these drugs selectively block the reuptake of neurotransmitters at the serotonin transporter (SERT). Since differences in MAT selectivity of inhibitory compounds are influential to selecting efficacious antidepressant treatments, we utilized a unique fluorescent analysis technique to explore three therapeutic compounds of interest (in-vitro) which contain structural similarity to FLX. Our results confirm the selectivity of FLX at SERT, and classify the novel compounds studied into different potential categories of reuptake inhibitors. We hope these compounds will be studied further to elucidate their potentially therapeutic roles and mitigation of undesired side effects seen in other medications.