Browsing by Subject "Magnetic resonance imaging"

More than 400,000 anterior cruciate ligament (ACL) injuries occur annually in the United States, 70% of which are non-contact. A severe consequence of ACL injury is the increased risk of early-onset of osteoarthritis (OA). Importantly, the increased risk of OA persists even if the ACL is surgically reconstructed. Thus, due to the long term physical consequences and high financial burden of treatment, injury prevention and improved reconstruction techniques are critical. However, the causes of non-contact ACL injuries remain unclear, which has hindered efforts to develop effective training programs targeted at preventing these injuries. Improved understanding of the knee motions that increase the risk of ACL injury can inform more effective injury prevention strategies. Furthermore, there is presently limited in vivo data to describe the function of ACL under dynamic loading conditions. Understanding how the ACL functions to stabilize the knee joint under physiologic loading conditions can inform design criteria for grafts used in ACL reconstruction. Grafts that more accurately mimic the native function of the ACL may help prevent these severe long term degenerative changes in the knee joint after injury.

To this end, measurements of in vivo ACL function during knee motion are critical to understanding how non-contact ACL injuries occur and the function of the ACL in stabilizing the joint during activities of daily living. Specifically, identifying the knee motions that increase ACL length and strain can elucidate the mechanisms of non-contact ACL injury, as a taut ligament is more likely to fail. Furthermore, measuring ACL elongation patterns during dynamic activity can inform the design criteria for grafts used in reconstructive surgery. To obtain measurements, 3D imaging techniques that can be used to measure dynamic in vivo ACL elongation and strain at high temporal and spatial resolution are needed.

Thus, in this dissertation a method of measuring knee motion and ACL function during dynamic activity in vivo using high-speed biplanar radiography in combination with magnetic resonance (MR) imaging was developed. In this technique, 3D surface models of the knee joint are created from MR images and registered to high-speed biplanar radiographs of knee motion. The use of MR imaging to model the joint allows for visualization of bone and soft tissue anatomy, in particular the attachment site footprints of the ligaments. By registering the bone models to biplanar radiographs using software developed in this dissertation, the relative positions of the bones and associated ligament attachment site footprints at the time of radiographic imaging can be reproduced. Thus, measurements of knee kinematics and ligament function during dynamic activity can be obtained at high spatial and temporal resolution.

We have applied the techniques developed in this dissertation to obtain novel dynamic in vivo measurements of the mechanical function of the knee joint. Specifically, the physiologic elongation and strain behaviors of the ACL during gait and single-legged jumping were measured. Additionally, the dynamic function of the patellar tendon during single legged jumping was measured. The findings of this dissertation have helped to elucidate the knee kinematics that increase ACL injury vulnerability by identifying the dynamic motions that result in elongation and strain in the ACL. Furthermore, the findings of this dissertation have provided critical data to inform design criteria for grafts used in reconstructive surgery such that reconstructive techniques better mimic the physiologic function of the ACL.

The methodologies described in this dissertation can be applied to study the mechanical behavior of other joints such as the spine, and other soft tissues, such as articular cartilage, under various loading conditions. Therefore, these methods may have a significant impact on the field of biomechanics as a whole, and may have applicability to a number of musculoskeletal applications.

There always exists a demand to accelerate the time-consuming MRI acquisition process. Many methods have been proposed to achieve this goal, including deep learning method which appears to be a robust tool compared to conventional methods. While many works have been done to evaluate the performance of neural networks on standard anatomical MR images, few attentions have been paid to accelerating other less conventional MR image acquisitions. This work aims to evaluate the feasibility of neural networks on accelerating Brain DTI and Gynecological Brachytherapy MRI. Three neural networks including U-net, Cascade-net and PD-net were evaluated. Brain DTI data was acquired from public database RIDER NEURO MRI while cervix gynecological MRI data was acquired from Duke University Hospital clinic data. A 25% Cartesian undersampling strategy was applied to all the training and test data. Diffusion weighted images and quantitative functional maps in Brain DTI, T1-spgr and T2 images in GYN studies were reconstructed. The performance of the neural networks was evaluated by quantitatively calculating the similarity between the reconstructed images and the reference images, using the metric Total Relative Error (TRE). Results showed that with the architectures and parameters set in this work, all three neural networks could accelerate Brain DTI and GYN T2 MR imaging. Generally, PD-net slightly outperformed Cascade-net, and they both outperformed U-net with respect to image reconstruction performance. While this was also true for reconstruction of quantitative functional diffusion weighted maps and GYN T1-spgr images, the overall performance of the three neural networks on these two tasks needed further improvement. To be concluded, PD-net is very promising on accelerating T2-weighted-based MR imaging. Future work can focus on adjusting the parameters and architectures of the neural networks to improve the performance on accelerating GYN T1-spgr MR imaging and adopting more robust undersampling strategy such as radial undersampling strategy to further improve the overall acceleration performance.

Alzheimer's disease (AD) accounts for 60%-80% of dementia. AD patients start by having mild memory, language, and thinking difficulties, then gradually lose more critical abilities, such as dressing, bathing, or walking. AD not only degrades patients’ life quality but also burdens caregivers and the health system. Specifically, there are 6.5 million AD cases in the U.S. today, and the annual health costs for 2022 are estimated to be $321 billion. AD diagnosis has been evolving in the past 30 years. The criteria established in 1984 recommended that AD cannot be identified until a post-mortem neuropathological test is performed. Recently, more biomarkers have gradually been discovered, such as brain atrophy, Positron Emission Tomography (PET) measures of glucose hypometabolism, and cerebrospinal fluid (CSF) and PET measures of pathological amyloid-beta and tau. However, these biomarkers lack the specificity to probe the damage in the neuronal microstructure that directly causes the disease, and they only provide late diagnoses when the AD progression is no longer reversible. Since the neuronal damages are believed to begin 20 years or more before symptoms start, biomarkers that can detect abnormalities in the neuronal microstructure would enable the diagnosis of AD at the very early stage of neurodegeneration, years before the onset of symptoms, and they could thus potentially enable better treatment outcomes since neuronal damage at the early stage could be reversible.Diffusion tensor imaging (DTI) is a magnetic resonance imaging technique that can noninvasively probe the microstructure of the human brain in vivo. Some regions in the cortical gray matter and hippocampus are known to experience early neurodegeneration in AD, and changes in DTI metrics in these regions could reflect the early stage of AD. However, the cortex is folded and is made of different cortical layers and cortical regions and the hippocampus is made of different subfields that have distinct neuronal populations with a specific microstructure. Additionally, neurodegeneration does not necessarily occur at the same time across different cortical depths or regions in the cortex or across different subfields in the hippocampus. As such, the development of early diagnostic biomarkers would require the ability to probe the neuronal microstructure at specific cortical depths and in specific cortical regions and hippocampal subfields in vivo. However, doing so with DTI has been challenging because the average cortical thickness is only 2.5 mm and the average hippocampal volume is only 2.84 mL. Therefore, a high-resolution DTI acquisition within a reasonable scan time is needed. In this dissertation, we first aim to develop DTI acquisition and reconstruction methodologies to acquire high-resolution (0.9-mm to 1.0-mm isotropic) whole-brain DTI images. Specifically, we used an efficient multi-band multi-shot echo-planar imaging sequence and a multi-band multiplexed sensitivity-encoding reconstruction. Furthermore, we aim to develop a data analysis pipeline that can quantitatively probe the microstructure and capture characteristic features: 1) in the cortex by performing a column-based cortical depth analysis of the diffusion anisotropy and radiality; and 2) in the hippocampus by investigating intra-hippocampal fiber tracts and connectomes, with the long-term goal of enabling the early diagnosis of AD. In the cortex, a column-based cortical depth analysis that samples the fractional anisotropy (FA) and radiality index (RI) along radially oriented cortical columns was performed to quantitatively analyze the FA and RI dependence on the cortical depth, cortical region, cortical curvature, and cortical thickness across the whole brain. We first studied young healthy subjects to optimize the data acquisition and analysis pipeline and to investigate the consistency of the results. The results showed characteristic FA and RI vs. cortical depth profiles, with an FA local maximum and minimum (or two inflection points) and a single RI maximum at intermediate cortical depths in most cortical regions, except for the postcentral gyrus where no FA peaks and a lower RI were observed. These results were consistent between repeated scans from the same subjects and across different subjects. They were also dependent on the cortical curvature and cortical thickness in that the characteristic FA and RI peaks were more pronounced i) at the banks than at the crown of gyri or at the fundus of sulci and ii) as the cortical thickness increases. We then performed a preliminary clinical study in a small cohort of AD patients and age-matched healthy controls (HC) to further examine if this methodology could be applied to detect differences in the FA and RI vs. cortical depth profiles between the AD and HC groups. The FA and RI at each cortical depth and in different regions of interest (ROIs) were sampled and compared between these two groups to look for any significant differences. Additionally, based on the results from the young healthy subjects, we minimized the dependence of these DTI metrics (FA and RI) on structural metrics such as cortical thickness and cortical curvature. The results showed significant differences (p < 0.05) in the FA and RI profiles between the AD and HC groups for specific cortical depths, curvature subsets, and ROIs. To generate intra-hippocampal fiber tracts and connectomes, the hippocampus of all subjects was registered to a common template and deterministic fiber tracking was performed. The fiber orientations across hippocampal subfields were investigated, and the connectivity among subfields was quantified. The results showed characteristic fiber orientations in different hippocampal subfields that were generally consistent between repeated scans and across all subjects: right/left in the middle of the CA4/dentate gyrus subfield and the inferior part of the subiculum; anterior/posterior in CA2/CA3; superior/inferior in the medial and inferior parts of the molecular layer and subiculum. These in vivo fiber orientations aligned with those obtained from an ex vivo specimen scanned over 21 hours at a 0.2-mm isotropic resolution. However, the ex vivo scan delineated the C-shaped molecular layer, which was not shown in the in vivo scans. The in vivo connectomes were generally consistent between repeated scans and across all subjects. The in vivo and ex vivo connectomes both showed more connectivity within the head than within the body of the hippocampus; however, the in vivo and ex vivo connectivity ranking across pairs of subfields was not exactly the same, which could be explained by altered diffusion properties in the ex vivo sample due to fixation or by the higher resolution in the ex vivo scan. In conclusion, the proposed high-resolution whole-brain DTI acquisition, column-based cortical depth analysis of the diffusion anisotropy and radiality, and intra-hippocampal fiber tracking captured characteristic features of FA and RI vs. cortical depth profiles in the cortex and characteristic fiber orientations and connectivity strengths across different subfields of the hippocampus, which were consistent between repeated scans from the same subjects and across different subjects. In addition, the cortical analysis applied in a preliminary clinical study of AD patients vs. HC showed significant differences in the FA and RI profiles between these two groups, showing the potential of this methodology to generate biomarkers for the early diagnosis of AD.

Understanding the structure of the brain has been a major goal of neuroscience research over the past century, driven in part by the understanding that brain structure closely follows function. Normative brain maps, or atlases, can be used to understand normal brain structure, and to identify structural differences resulting from disease. Recently, diffusion tensor magnetic resonance imaging has emerged as a powerful tool for brain atlasing; however, its utility is hindered by image resolution and signal limitations. These limitations can be overcome by imaging fixed ex-vivo specimens stained with MRI contrast agents, a technique known as diffusion tensor magnetic resonance histology (DT-MRH). DT-MRH represents a unique, quantitative tool for mapping the brain with unprecedented structural detail. This technique has engendered a new generation of 3D, digital brain atlases, capable of representing complex dynamic processes such as neurodevelopment. This dissertation explores the use of DT-MRH for quantitative brain atlasing in an animal model and initial work in the human brain.

Chapter 1 describes the advantages of the DT-MRH technique, and the motivations for generating a quantitative atlas of rat postnatal neurodevelopment. The second chapter covers optimization of the DT-MRH hardware and pulse sequence design for imaging the developing rat brain. Chapter 3 details the acquisition and curation of rat neurodevelopmental atlas data. Chapter 4 describes the creation and implementation of an ontology-based segmentation scheme for tracking changes in the developing brain. Chapters 5 and 6 pertain to analyses of volumetric changes and diffusion tensor parameter changes throughout rat postnatal neurodevelopment, respectively. Together, the first six chapters demonstrate many of the unique and scientifically valuable features of DT-MRH brain atlases in a popular animal model.

The final two chapters are concerned with translating the DT-MRH technique for use in human and non-human primate brain atlasing. Chapter 7 explores the validity of assumptions imposed by DT-MRH in the primate brain. Specifically, it analyzes computer models and experimental data to determine the extent to which intravoxel diffusion complexity exists in the rhesus macaque brain, a close model for the human brain. Finally, Chapter 8 presents conclusions and future directions for DT-MRH brain atlasing, and includes initial work in creating DT-MRH atlases of the human brain. In conclusion, this work demonstrates the utility of a DT-MRH brain atlasing with an atlas of rat postnatal neurodevelopment, and lays the foundation for creating a DT-MRH atlas of the human brain.

Diffusion tensor imaging (DTI) has emerged as a unique method to characterize brain tissue microstructure non-invasively. DTI typically provides the ability to study white matter structure with a standard voxel resolution of 8μL over imaging field-of-views of the extent of the human brain. As such, it has long been recognized as a promising tool not only in clinical research for the diagnostic and monitoring of white matter diseases, but also for investigating the fundamental biological principles underlying the organization of long and short-range cortical networks. However, the complexity of brain structure within an MRI voxel makes it difficult to dissociate the tissue origins of the measured anisotropy. The tensor characterization is a composite result of proton pools in different tissue and cell structures with diverse diffusion properties. As such, partial volume effects introduce a strong bias which can lead to spurious measurements, especially in regions with a complex tissue structure such as interdigitating crossing fibers or in convoluted cortical folds near the grey/white matter interface.

This dissertation focuses on the design and development of acquisition and image reconstruction strategies to improve the spatial resolution of diffusion imaging. After a brief review of the theory of diffusion MRI and of the basic principles of streamline tractography in the human brain, the main challenges to increasing the spatial resolution are discussed. A comprehensive characterization of artifacts due to motion and field inhomogeneities is provided and novel corrective methods are proposed to enable the acquisition of diffusion weighted data with 2D mulitslice imaging techniques with full brain coverage, increased SNR and high spatial resolutions of 1.25×1.25×1.25 mm3 within an acceptable scan time. The method is extended to a multishot k_{_z}-encoded 3D multislab spiral DTI and evaluated in normal human volunteers.

To demonstrate the increased SNR and enhanced resolution capability of the proposed methods and more generally to assess the value of high-spatial resolution in diffusion imaging, a study of cortical depth-dependence of fractional anisotropy was performed at an unprecedented in-vivo inplane resolution of 0.390×0.390μm2 and an investigation of the trade-offs between spatial resolution and cortical specificity was conducted within the connectome framework.

The kidney's major role in filtration depends on its high blood flow, concentrating mechanisms, and biochemical activation. The kidney's greatest strengths also lead to vulnerability for drug-induced nephrotoxicity and other renal injuries. The current standard to diagnose renal injuries is with a percutaneous renal biopsy, which can be biased and insufficient. In one particular case, biopsy of a kidney with renal cell carcinoma can actually initiate metastasis. Tools that are sensitive and specific to detect renal disease early are essential, especially noninvasive diagnostic imaging. While other imaging modalities (ultrasound and x-ray/CT) have their unique advantages and disadvantages, MRI has superb soft tissue contrast without ionizing radiation. More importantly, there is a richness of contrast mechanisms in MRI that has yet to be explored and applied to study renal disease.

The focus of this work is to advance preclinical imaging tools to study the structure and function of the renal system. Studies were conducted in normal and disease models to understand general renal physiology as well as pathophysiology. This dissertation is separated into two parts--the first is the identification of renal architecture with ex vivo MRI; the second is the characterization of renal dynamics and function with in vivo MRI. High resolution ex vivo imaging provided several opportunities including: 1) identification of fine renal structures, 2) implementation of different contrast mechanisms with several pulse sequences and reconstruction methods, 3) development of image-processing tools to extract regions and structures, and 4) understanding of the nephron structures that create MR contrast and that are important for renal physiology. The ex vivo studies allowed for understanding and translation to in vivo studies. While the structure of this dissertation is organized by individual projects, the goal is singular: to develop magnetic resonance imaging biomarkers for renal system.

The work presented here includes three ex vivo studies and two in vivo studies:

1) Magnetic resonance histology of age-related nephropathy in sprague dawley.

2) Quantitative susceptibility mapping of kidney inflammation and fibrosis in type 1 angiotensin receptor-deficient mice.

3) Susceptibility tensor imaging of the kidney and its microstructural underpinnings.

4) 4D MRI of renal function in the developing mouse.

5) 4D MRI of polycystic kidneys in rapamycin treated Glis3-deficient mice.

Image acquisition time is one of the most important considerations for magnetic resonance imaging (MRI). This is especially true for dynamic imaging (such as functional MRI or dynamic contrast enhanced MRI) which require multiple scans of the same volume over time. As such, increasing throughput has been a major focus of many advanced image reconstruction techniques. Many of the current techniques focus on an in-plane acceleration by reducing the amount of data acquired per scan. While these methods do increase data acquisition speed, they do not increase throughput proportionally to the data reduction. Moreover, by reducing the amount of data acquired, the signal-to-noise ratio (SNR) is also reduced. These particular shortcomings can be addressed with through-plane acceleration - imaging multiple volumes simultaneously. However, multi-slice parallel imaging is still susceptible to noise amplification due to non-ideal sensitivity profiles (i.e., g-factor). There is an additional decrease in SNR if the separation between excited bands is small. The purpose of this work is to present a novel reconstruction technique, M-PHENSE, which has been designed to reconcile these deficiencies.

M-PHENSE is a multi-slice imaging technique that integrates Hadamard slice encoding for a through-plane acceleration. This method allows for a time-dependent, preliminary image reconstruction and creation of complex, time-dependent, phase-constrained sensitivity profiles. M-PHENSE achieves this by using a slice-selective UNFOLD technique to perform the preliminary reconstruction. Through simulations of the technique, M-PHENSE is shown to be nearly independent of slice separation, while maintaining SNR for the R=2 case. Techniques for incorporating a number of slice excitations greater than two are explored, and the limitations of M-PHENSE are discussed. Additionally, M-PHENSE is found to be adaptable with in-plane acceleration methods, establishing a two-dimensional acceleration. A combination with UNFOLD is presented increasing the reduction factor to four and maintaining minimal SNR loss. Overall, the M-PHENSE technique is found to be a robust reconstruction method with many advantages over the currently available procedures.

Pulmonary fibrosis is the process of lung tissue becoming damaged and scarred, losing its elastic and diffusive properties needed for proper lung function. This change in tissue structure can make it difficult to draw in a breath (ventilation) and cause a decrease in the amount of oxygen and carbon dioxide that can transfer between the alveoli and blood vessels (gas exchange). Therefore, the most common symptom of progressive pulmonary fibrosis is shortness of breath, or dyspnea. Pulmonary fibrosis can be caused by environmental pollutants, treatment-related toxicity from a drug or therapy, or interstitial lung diseases.

Regardless of its origin, pulmonary fibrosis can have devastating outcomes for patients. For example, the median survival for patients with idiopathic pulmonary fibrosis (IPF), an interstitial lung disease of unknown origin, is historically less than 3 years. For patients with IPF, the path of clinical decline is often sporadic and plagued with acute exacerbations and hospitalizations. Idiopathic pulmonary fibrosis currently affects between 100,000-200,000 people in the United States alone, and over a million worldwide. Unfortunately, the tools currently available to classify disease severity, determine prognosis, and assess disease progression or treatment response are simply inadequate. Patients with IPF exhibit distinct and unpredictable clinical trajectories, and a tool with the ability to predict these trajectories could improve targeted interventions. One such set of tools, pulmonary function tests (PFTs) can measure global ventilation and gas exchange, but have high variability and no spatial information. Another, high resolution computed tomography (HRCT), provides a 3D image, but function must be inferred from tissue density or structure, which comes with a number of limitations. A new tool that can spatially resolve and quantify regional pulmonary function could be invaluable in improving the clinical management of IPF.

In addition to fibrotic lung diseases, such as IPF, pulmonary fibrosis may also transpire as a treatment-related toxicity. Over 100,000 people per year in the U.S. will receive thoracic radiation therapy (RT) as treatment for cancer, putting them at risk for radiation-induced lung injury (RILI). Approximately 5-25% of patients that receive conventional thoracic RT develop clinically significant symptomatic radiation pneumonitis (RP), the acute form of RILI, causing patients to experience dyspnea, persistent coughing, pain, and fever. Radiation pneumonitis can lead to chronic radiation pulmonary fibrosis (RPF), or even result in death for an estimated 1-2% of patients. Current methods to assess RILI and grade RP rely on a clinical diagnosis and patient- and physician-reported symptoms. This leads to large variability in toxicity grading for thoracic RT clinical trials, hampering the effort to design treatments that reduce side effects. Further, a recently proposed treatment planning technique, “functional avoidance”, was designed to preserve pulmonary function and reduce the incidence or severity of RP by minimizing radiation dose to areas with high pulmonary function. However, clinically available tools can only measure ventilation or perfusion, neither of which are a true representation of end-to-end pulmonary gas exchange, a fact that may be limiting the potential effectiveness of this technique. Once again, a tool that can spatially resolve and quantify regional pulmonary function could offer improvements to functional avoidance treatment planning and the prevention of RP. If such a tool was sensitive enough to detect radiation-induced changes in function, this could reduce the variability in the current guidelines for the toxicity grading of RP.

In this work, we investigated non-invasive hyperpolarized-129Xe gas exchange magnetic resonance imaging (MRI), which acquires 3D maps of lung ventilation, alveolar barrier uptake, and capillary red blood cell (RBC) transfer. This unique tool can quantify and spatially resolve the gas exchange capabilities of a human lung in a single 15-second breath-hold MRI acquisition. Currently limited to research studies, the clinical utility of this new technique is yet to be firmly established. Therefore, the objectives of this dissertation are to: 1) identify metrics from baseline 129Xe gas exchange MRI that are predictive of clinical outcomes in IPF; 2) quantify the extent to which ventilation and gas exchange distributions are spatially correlated, and the effect that this may have on functional avoidance treatment planning; and 3) establish a relationship between regional changes in gas exchange and local radiation therapy dose in RT patients.

First, we sought to identify 129Xe gas exchange MRI features in IPF patients, and establish 129Xe-based imaging metrics to be used for classifying patients into groups, as detailed in Chapter 3. As previously mentioned, subjects with IPF exhibit distinct clinical trajectories that are difficult to predict prospectively using currently available means. We acquired baseline 129Xe MRI for 12 newly diagnosed IPF patients, and prospectively grouped these subjects based on percentage-volumes of abnormal barrier uptake and RBC transfer, using thresholds we derived from 129Xe MRI of a healthy subject cohort (N=13). We then followed these subjects for 36 months and analyzed the clinically acquired PFT and outcome data. We examined the differences in clinical outcomes and temporal changes in PFTs based on these groupings. We also observed changes in 129Xe metrics over time for those subjects with serial time-point imaging. Our results indicated that 129Xe MRI characteristics appear to group disease in a way that was distinct from traditional clinical or radiographic approaches; in particular, excessive volumes of lung with elevated barrier uptake and reduced RBC transfer were associated with poor clinical outcome. This study provided preliminary evidence that IPF patients can be classified by 129Xe MRI, and that this classification may predict clinical outcomes. These results open the door for larger, prospective studies using 129Xe MRI in IPF. More generally, and perhaps most importantly, this work established 129Xe gas exchange MRI as a prognostic biomarker in fibrotic lung disease.

Our results from Chapter 3 established that, when accompanied by an increase in 129Xe MRI barrier signal, which is a hallmark characteristic of IPF, a reduction in RBC transfer signal is associated with clinical decline in IPF patients. Extending this work to fibrotic lung processes beyond IPF, we hypothesize that the RBC signal is an important marker for regional lung function, and preserving and protecting the volumes of lung exhibiting “healthy” RBC transfer could translate to preservation of overall pulmonary function. In RT treatment planning, the concept of avoiding excess radiation dose to highly functioning areas of lung is not new; “functional avoidance” (or “functional guidance”) has previously been proposed and implemented using both perfusion and ventilation imaging. In Chapter 4, however, we establish 129Xe gas exchange MRI as a unique marker of regional lung function compared to ventilation, which is the most popular functional avoidance planning technique due to its “free” derivation from the 4 dimensional (4D) CT acquired during the RT planning process. In this chapter, we examined the correlation of ventilation and RBC signals in a healthy volunteer cohort and a handful of thoracic RT patients. Our results indicated a weak-to-moderate correlation, which determined that the RBC signal was indeed spatially unique from the ventilation signal, but did not explore the extent to which this affects functional plans created using one or the other (ventilation or RBC gas exchange) for guidance. Therefore, Chapter 5 details our study of 11 patients that received RT for treatment of lung cancer in which we re-planned these patients’ clinically approved plans using ventilation and RBC gas exchange functional information. This study established a methodology for 129Xe gas exchange MRI functional avoidance planning, and the results showed that, for some RP-predictive metrics, gas exchange-guided planning produced significantly different dose distributions than ventilation-guided planning.

Finally, in Chapter 6 we focused on furthering our understanding of RILI in RT patients, and examined the sensitivity of 129Xe MRI for detecting pulmonary radiation damage. In this study, we quantified changes in regional gas exchange as a function of radiation dose for six patients undergoing conventional radiotherapy for lung cancer. As briefly described earlier, RT of tumors in or around the thorax is known to cause regional lung injury, with the acute injury phase symptoms of RP typically emerging 1-6 months after RT. Previous studies using SPECT have established that perfusion changes are dose-dependent and evident at 3-6 months after RT. Therefore, we acquired 129Xe MRI scans before RT and at 3- and 6-months after RT to evaluate the progression of the acute inflammatory phase of RILI, as it relates to changes in regional gas exchange. We co-registered the MRI data to the RT treatment planning data, to evaluate regional changes in ventilation, barrier uptake, and RBC transfer, as a function of delivered radiation dose. Our results indicated that the barrier uptake signal increased with radiation doses above 20 Gy, and that the magnitude of change was dose-dependent. This potentially confirms increased barrier uptake as a marker of regional inflammation. In addition, we observed that the RBC transfer signal decreased with radiation doses above 35 Gy, possibly quantifying a reduction in overall gas exchange properties of the tissue at these high doses. Our observations of this dose-dependent relationship are consistent with historic ventilation and perfusion data, and gives rise to the idea that 129Xe MRI may be a powerful tool in furthering understanding of the subclinical progression of RILI and potentially other causes of lung fibrosis.

Overall, we have demonstrated the potential of 129Xe-MRI gas exchange to 1) improve disease classification in IPF, 2) add unique functional information to the planning of thoracic radiation treatments, and 3) assess RT-associated subclinical changes in regional lung function. We have established a strong foundation for this non-invasive technology, enabling further development and validation of these MRI biomarkers in larger studies. The work presented herein marks the beginning of a journey to advance our understanding of fibrotic progression in IPF, RILI, and all other causes of pulmonary fibrosis.

Magnetic resonance imaging is a research and clinical tool that has been applied in a wide variety of sciences. One area of magnetic resonance imaging that has exhibited terrific promise and growth in the past decade is magnetic susceptibility imaging. Imaging tissue susceptibility provides insight into the microstructural organization and chemical properties of biological tissues, but this image contrast is not well understood. The purpose of this work is to develop effective approaches to image, assess, and model the mechanisms that generate both isotropic and anisotropic magnetic susceptibility contrast in biological tissues, including myocardium and central nervous system white matter.

This document contains the first report of MRI-measured susceptibility anisotropy in myocardium. Intact mouse heart specimens were scanned using MRI at 9.4 T to ascertain both the magnetic susceptibility and myofiber orientation of the tissue. The susceptibility anisotropy of myocardium was observed and measured by relating the apparent tissue susceptibility as a function of the myofiber angle with respect to the applied magnetic field. A multi-filament model of myocardial tissue revealed that the diamagnetically anisotropy α-helix peptide bonds in myofilament proteins are capable of producing bulk susceptibility anisotropy on a scale measurable by MRI, and are potentially the chief sources of the experimentally observed anisotropy.

The growing use of paramagnetic contrast agents in magnetic susceptibility imaging motivated a series of investigations regarding the effect of these exogenous agents on susceptibility imaging in the brain, heart, and kidney. In each of these organs, gadolinium increases susceptibility contrast and anisotropy, though the enhancements depend on the tissue type, compartmentalization of contrast agent, and complex multi-pool relaxation. In the brain, the introduction of paramagnetic contrast agents actually makes white matter tissue regions appear more diamagnetic relative to the reference susceptibility. Gadolinium-enhanced MRI yields tensor-valued susceptibility images with eigenvectors that more accurately reflect the underlying tissue orientation.

Despite the boost gadolinium provides, tensor-valued susceptibility image reconstruction is prone to image artifacts. A novel algorithm was developed to mitigate these artifacts by incorporating orientation-dependent tissue relaxation information into susceptibility tensor estimation. The technique was verified using a numerical phantom simulation, and improves susceptibility-based tractography in the brain, kidney, and heart. This work represents the first successful application of susceptibility-based tractography to a whole, intact heart.

The knowledge and tools developed throughout the course of this research were then applied to studying mouse models of Alzheimer’s disease in vivo, and studying hypertrophic human myocardium specimens ex vivo. Though a preliminary study using contrast-enhanced quantitative susceptibility mapping has revealed diamagnetic amyloid plaques associated with Alzheimer’s disease in the mouse brain ex vivo, non-contrast susceptibility imaging was unable to precisely identify these plaques in vivo. Susceptibility tensor imaging of human myocardium specimens at 9.4 T shows that susceptibility anisotropy is larger and mean susceptibility is more diamagnetic in hypertrophic tissue than in normal tissue. These findings support the hypothesis that myofilament proteins are a source of susceptibility contrast and anisotropy in myocardium. This collection of preclinical studies provides new tools and context for analyzing tissue structure, chemistry, and health in a variety of organs throughout the body.

Since the inception of hyperpolarized 129Xe MRI, the field has yearned for more efficient production of more highly polarized 129Xe. For nearly all polarizers built to date, both peak 129Xe polarization and production rate fall far below theoretical predictions. This thesis sought to develop a fundamental understanding of why the observed performance of large-scale 129Xe hyperpolarization lagged so badly behind theoretical predictions.

This is done by thoroughly characterizing a high-volume, continuous-flow polarizer using optical cells having three different internal volumes, and employing two different laser sources. For each of these 6 combinations, 129Xe polarization was carefully measured as a function of production rate across a range of laser absorption levels. The resultant peak polarizations were consistently a factor of 2-3 lower than predicted across a range of absorption levels, and scaling of production rates deviated badly from predictions based on spin exchange efficiency.

To bridge this gap, we propose that paramagnetic, activated Rb clusters form during spin exchange optical pumping (SEOP), and depolarize Rb and 129Xe, while unproductively scattering optical pumping light. When a model was built that incorporated the effects of clusters, its predictions matched observations for both polarization and production rate for all 6 systems studied. This permits us to place a limit on cluster number density of <2 × 109 cm-3.

The work culminates with deploying this framework to identify methods to improve polarization to above 50%, leaving the SEOP cell. Combined with additional methods of preserving polarization, the polarization of a 300-mL batch of 129Xe increased from an average of 9%, before this work began, to a recent value of 34%.

We anticipate that these developments will lay the groundwork for continued advancement and scaling up of SEOP-based hyperpolarization methods that may one day permit real-time, on-demand 129Xe MRI to become a reality.

Magnetic resonance imaging (MRI) generates anatomical images by utilizing a homogeneous static magnetic field (B0) generated by a magnet and radiofrequency (RF) signals transmitted to and received from the subject by RF coils. To enhance the acquired signal strength and improve the image signal-to-noise ratio, receive RF coils are placed close to the surface of the subject and multiple RF coil elements are typically combined to form an RF coil array. The number of RF coil elements in an array has continually increased over the years, requiring large cables, connectors, and added electronic components to be connected to the MRI scanner for imaging, which increases the integration complexity, cost, and weight of the RF coil arrays. Additionally, RF coil arrays are typically heavy and rigid, which makes them difficult and time consuming to setup and uncomfortable for the subjects. Finally, additional shim coils are required to correct for B0 inhomogeneities induced by the subject and to improve the image quality, but they currently provide suboptimal results. This work presents a highly innovative RF coil design to address all of these concerns.

First, a novel integrated RF/wireless coil design was proposed to enable simultaneous MR image acquisition and wireless communication with a single coil, thereby reducing or eliminating the wired connections for data transfer between the coil and the MRI scanner. Second, the RF/wireless coil design was combined with the integrated parallel reception, excitation, and shimming (iPRES) coil design to enable simultaneous MR image acquisition, wireless communication, and localized B0 shimming with a single coil, thereby further improving the B0 homogeneity and image quality (iPRES-W coil). Finally, the iPRES-W coil design was integrated with: 1) the revolutionary AIR coil technology to perform the same three functions, but with a flexible and ultra-lightweight coil, thereby increasing patient comfort and offering more flexible coil design opportunities and 2) a wireless bidirectional DC power supply for B0 shimming to further eliminate any cables between the MRI scanner and RF coil (iPRES-W AIR coil).

Experiments were conducted to demonstrate that the modifications made to the RF coil, to enable wireless communication and B0 shimming, did not degrade its imaging performance. Additionally, experiments were conducted to test the wireless data connection, transmission rate, and quality of the wireless link for the RF/wireless and iPRES-W coil designs. Finally, experiments were conducted to demonstrate the ability of the iPRES-W coil to simultaneously perform localized B0 shimming during wireless data transmission and image acquisition. The results presented show no degradation in image quality with the modifications made, excellent B0 shimming performance, and the ability to wirelessly transmit data within the MRI scanner bore. The iPRES-W coil design requires no modifications to the current MRI scanner and leads to a highly scalable, cost effective, wireless solution for a more efficient, comfortable, and beneficial MRI experience.

This dissertation focuses on a very special topic in the field of Nuclear Magnetic Resonance (NMR) in solution: Intermolecular Multiple Quantum Coherences, or iMQCs, which can only be created by intermolecular dipolar couplings. Since the very beginnings of NMR, it has been known that dipolar couplings dominate the solid-state linewidth for spin-1/2 nuclei, but the effects are still not fully understood. The angular dependency (1-3cos2θij) and distant dependency (rij-3) of dipolar coupling led to an oversimplified conclusion that it can be ignored in an isotropic liquid. Thus, it was surprising when COSY Revamped by Asymmetric Z-gradient Echo Detection (CRAZED) was first introduced in the early `90s and showed strong iMQC signals. Since then, CRAZED has inspired a wide range of applications for iMQCs and led to two different but equivalent mathematical frameworks to describes these effects, which we call the conventional DDF theory.

However, several disagreements between the conventional DDF theory and experiments have grasped our attention recently. This dissertation will: first, demonstrate how conventional picture fails by two examples, Multi-axis CRAZED (MAXCRAZED) and Gradient-embedded COSY Experiment (GRACE); second, provide a corrected DDF theory; and, third, discuss what impact this correction will bring.

Intermolecular double quantum coherences (iDQCs) are very sensitive to the local anisotropy (10μm - 1mm) and can be used to create positive contrast highlighting superparamagnetic iron oxide nanoparticles (SPIONs). This dissertation will show the design and optimization of iDQC anisotropy by a series of phantom experiments. A set of numerical simulations will then be provided for a sub-voxel level explanation. We will also demonstrate how the newly corrected DDF theory can be quickly adapted to improve the iDQC anisotropy.

Finally, as a side product of this research, the mechanism of diacetyl hydration/dehydration as solved by NMR will be provided.