Investigation into the diffusion of water into HEMA-co-MOEP hydrogels

Cross-linked homopolymers and copolymers of 2-hydroxyethyl methacrylate, HEMA, and ethylene glycol methacrylate phosphate, MOEP, have been synthesized, and the diffusion of water into these systems has been investigated. Only polymers with 0-20 mot % MOEP exhibited ideal swelling behavior as extensive fracturing occurred in the systems with greater than 20 mot % MOEP as the polymers began to swell during water sorption. Gravimetric studies were used in conjunction with magnetic resonance imaging of the diffusion front to elucidate the diffusion mechanism for these systems. In the case of the cross-linked HEMA homopolymer gets, the water transport mechanism was determined to be concentration-independent Fickian diffusion. However, as the fraction of MOEP in the network increased, the transport mechanism became increasingly exponentially concentration-dependent but remained Fickian until the polymer consisted of 30 mot % MOEP where the water transport could no longer been described by Fickian diffusion.

Water diffusion in methacrylate based copolymer hydrogels of 2-hydroxyethyl methacrylate

The diffusion of water into cylinders of polyHEMA and copolymers of HEMA with THFMA, BMA and CHMA were studied over a range of copolymer compositions. The diffusion of water into the polymers was found to follow a Fickian, or case I mechanism. The diffusion coefficients of water were determined from mass measurements and NMR imaging studies. They were found to vary from 1.7 +/- 0.2 x 10(-11) m(2) s(-1) for polyHEMA at 37 degreesC to lower values for the copolymers. The mass of water absorbed at equilibrium relative to the mass of dry polymer varied from 52-58 wt% for polyHEMA to lower values for the copolymers.

NMR microscopy: A tool for measuring monomer diffusion in supercritical CO2

The diffusion of styrene into linear low density polyethylene in a solution of supercritical CO2 was investigated using NMR microimaging. For both pure styrene and styrene dissolved in supercritical CO2, the diffusion was found to follow Fickian kinetics. Supercritical CO2 was found to enhance the rate and extent of diffusion of styrene into the substrate by up to three times under the conditions of this investigation, compared to pure styrene. NMR imaging was used to measure the concentration profiles of the styrene penetrants in real time, and the results were fitted to a Fickian model for diffusion. At a CO2 pressure of 150 bar and temperature of 40 degrees C, the diffusion coefficient of a 30 wt-% solution of styrene into LLDPE was calculated to be 1 X 10(-11) m(2). s(-1). This is significantly faster than the diffusion coefficient measured for pure styrene diffusion at 40 degrees C (3 x 10(-12) m(2). s(-1)). The diffusion coefficients determined by gravimetric analysis were slightly higher than those determined by the imaging method. This was probably due to residual styrene and/or polystyrene adhering to the surface of the films in the gravimetric technique.

Pressure induced structural changes and gas diffusion pathways in monomeric fluorescent proteins

Fluorescent proteins (FPs) are extremely valuable biochemical markers which have found a wide range of applications in cellular and molecular biology research. The monomeric variants of red fluorescent proteins (RFPs), known as mFruits, have been especially valuable for in vivo applications in mammalian cell imaging. Fluorescent proteins consist of a chromophore caged in the beta-barrel protein scaffold. The photophysical properties of an FP is determined by its chromophore structure and its interactions with the protein barrel. Application of hydrostatic pressure on FPs results in the modification of the chromophore environment which allows a systematic study of the role of the protein-chromophore interactions on photophysical properties of FPs. Using Molecular Dynamics (MD) computer simulations, I investigated the pressure induced structural changes in the monomeric variants mCherry, mStrawberry, and Citrine. The results explain the molecular basis for experimentally observed pressure responses among FP variants. It is found that the barrel flexibility, hydrogen bonding interactions and chromophore planarity of the FPs can be correlated to their contrasting photophysical properties at vaious pressures. I also investigated the oxygen diffusion pathways in mOrange and mOrange2 which exhibit marked differences in oxygen sensitivities as well as photostability. Such computational identifications of structural changes and oxygen diffusion pathways are important in guiding mutagenesis efforts to design fluorescent proteins with improved photophysical properties.

Source localization of reaction-diffusion models for brain tumors

We propose a mathematically well-founded approach for locating the source (initial state) of density functions evolved within a nonlinear reaction-diffusion model. The reconstruction of the initial source is an ill-posed inverse problem since the solution is highly unstable with respect to measurement noise. To address this instability problem, we introduce a regularization procedure based on the nonlinear Landweber method for the stable determination of the source location. This amounts to solving a sequence of well-posed forward reaction-diffusion problems. The developed framework is general, and as a special instance we consider the problem of source localization of brain tumors. We show numerically that the source of the initial densities of tumor cells are reconstructed well on both imaging data consisting of simple and complex geometric structures.

Development and Optimization of Four-dimensional Magnetic Resonance Imaging (4D-MRI) for Radiation Therapy

A tenet of modern radiotherapy (RT) is to identify the treatment target accurately, following which the high-dose treatment volume may be expanded into the surrounding tissues in order to create the clinical and planning target volumes. Respiratory motion can induce errors in target volume delineation and dose delivery in radiation therapy for thoracic and abdominal cancers. Historically, radiotherapy treatment planning in the thoracic and abdominal regions has used 2D or 3D images acquired under uncoached free-breathing conditions, irrespective of whether the target tumor is moving or not. Once the gross target volume has been delineated, standard margins are commonly added in order to account for motion. However, the generic margins do not usually take the target motion trajectory into consideration. That may lead to under- or over-estimate motion with subsequent risk of missing the target during treatment or irradiating excessive normal tissue. That introduces systematic errors into treatment planning and delivery. In clinical practice, four-dimensional (4D) imaging has been popular in For RT motion management. It provides temporal information about tumor and organ at risk motion, and it permits patient-specific treatment planning. The most common contemporary imaging technique for identifying tumor motion is 4D computed tomography (4D-CT). However, CT has poor soft tissue contrast and it induce ionizing radiation hazard. In the last decade, 4D magnetic resonance imaging (4D-MRI) has become an emerging tool to image respiratory motion, especially in the abdomen, because of the superior soft-tissue contrast. Recently, several 4D-MRI techniques have been proposed, including prospective and retrospective approaches. Nevertheless, 4D-MRI techniques are faced with several challenges: 1) suboptimal and inconsistent tumor contrast with large inter-patient variation; 2) relatively low temporal-spatial resolution; 3) it lacks a reliable respiratory surrogate. In this research work, novel 4D-MRI techniques applying MRI weightings that was not used in existing 4D-MRI techniques, including T2/T1-weighted, T2-weighted and Diffusion-weighted MRI were investigated. A result-driven phase retrospective sorting method was proposed, and it was applied to image space as well as k-space of MR imaging. Novel image-based respiratory surrogates were developed, improved and evaluated.

Radiotherapy Assessment Using Diffusion Weighted MRI

Purpose: There are two goals of this study. The first goal of this study is to investigate the feasibility of using classic textural feature extraction in radiotherapy response assessment among a unique cohort of early stage breast cancer patients who received the single-dose preoperative radiotherapy. The second goal of this study is to investigate the clinical feasibility of using classic texture features as potential biomarkers which are supplementary to regional apparent diffusion coefficient in gynecological cancer radiotherapy response assessment.

Methods and Materials: For the breast cancer study, 15 patients with early stage breast cancer were enrolled in this retrospective study. Each patient received a single-fraction radiation treatment, and DWI and DCE-MRI scans were conducted before and after the radiotherapy. DWI scans were acquired using a spin-echo EPI sequence with diffusion weighting factors of b = 0 and b = 500 mm2/s, and the apparent diffusion coefficient (ADC) maps were calculated. DCE-MRI scans were acquired using a T1-weighted 3D SPGR sequence with a temporal resolution of about 1 minute. The contrast agent (CA) was intravenously injected with a 0.1 mmol/kg bodyweight dose at 2 ml/s. Two parameters, volume transfer constant (Ktrans) and kep were analyzed using the two-compartment Tofts pharmacokinetic model. For pharmacokinetic parametric maps and ADC maps, 33 textural features were generated from the clinical target volume (CTV) in a 3D fashion using the classic gray level co-occurrence matrix (GLCOM) and gray level run length matrix (GLRLM). Wilcoxon signed-rank test was used to determine the significance of each texture feature’s change after the radiotherapy. The significance was set to 0.05 with Bonferroni correction.

For the gynecological cancer study, 12 female patients with gynecologic cancer treated with fractionated external beam radiotherapy (EBRT) combined with high dose rate (HDR) intracavitary brachytherapy were studied. Each patient first received EBRT treatment followed by five fractions of HDR treatment. Before EBRT and before each fraction of brachytherapy, Diffusion Weighted MRI (DWI-MRI) and CT scans were acquired. DWI scans were acquired in sagittal plane utilizing a spin-echo echo-planar imaging sequence with weighting factors of b = 500 s/mm2 and b = 1000 s/mm2, one set of images of b = 0 s/mm2 were also acquired. ADC maps were calculated using linear least-square fitting method. Distributed diffusion coefficient (DDC) maps and stretching parameter α were calculated. For ADC and DDC maps, 33 classic texture features were generated utilizing the classic gray level run length matrix (GLRLM) and gray level co-occurrence matrix (GLCOM) from high-risk clinical target volume (HR-CTV). Wilcoxon signed-rank statistics test was applied to determine the significance of each feature’s numerical value change after radiotherapy. Significance level was set to 0.05 with multi-comparison correction if applicable.

Results: For the breast cancer study, regarding ADC maps calculated from DWI-MRI, 24 out of 33 CTV features changed significantly after the radiotherapy. For DCE-MRI pharmacokinetic parameters, all 33 CTV features of Ktrans and 33 features of kep changed significantly.

For the gynecological cancer study, regarding ADC maps, 28 out of 33 HR-CTV texture features showed significant changes after the EBRT treatment. 28 out of 33 HR-CTV texture features indicated significant changes after HDR treatments. The texture features that indicated significant changes after HDR treatments are the same as those after EBRT treatment. 28 out of 33 HR-CTV texture features showed significant changes after whole radiotherapy treatment process. The texture features that indicated significant changes for the whole treatment process are the same as those after HDR treatments.

Conclusion: Initial results indicate that certain classic texture features are sensitive to radiation-induced changes. Classic texture features with significant numerical changes can be used in monitoring radiotherapy effect. This might suggest that certain texture features might be used as biomarkers which are supplementary to ADC and DDC for assessment of radiotherapy response in breast cancer and gynecological cancer.

Inter-site and inter-scanner diffusion MRI data harmonization.

We propose a novel method to harmonize diffusion MRI data acquired from multiple sites and scanners, which is imperative for joint analysis of the data to significantly increase sample size and statistical power of neuroimaging studies. Our method incorporates the following main novelties: i) we take into account the scanner-dependent spatial variability of the diffusion signal in different parts of the brain; ii) our method is independent of compartmental modeling of diffusion (e.g., tensor, and intra/extra cellular compartments) and the acquired signal itself is corrected for scanner related differences; and iii) inter-subject variability as measured by the coefficient of variation is maintained at each site. We represent the signal in a basis of spherical harmonics and compute several rotation invariant spherical harmonic features to estimate a region and tissue specific linear mapping between the signal from different sites (and scanners). We validate our method on diffusion data acquired from seven different sites (including two GE, three Philips, and two Siemens scanners) on a group of age-matched healthy subjects. Since the extracted rotation invariant spherical harmonic features depend on the accuracy of the brain parcellation provided by Freesurfer, we propose a feature based refinement of the original parcellation such that it better characterizes the anatomy and provides robust linear mappings to harmonize the dMRI data. We demonstrate the efficacy of our method by statistically comparing diffusion measures such as fractional anisotropy, mean diffusivity and generalized fractional anisotropy across multiple sites before and after data harmonization. We also show results using tract-based spatial statistics before and after harmonization for independent validation of the proposed methodology. Our experimental results demonstrate that, for nearly identical acquisition protocol across sites, scanner-specific differences can be accurately removed using the proposed method.

Theranostic Fibers for Simultaneous Imaging and Drug Delivery

New methods for creating theranostic systems with simultaneous encapsulation of therapeutic, diagnostic, and targeting agents are much sought after. This work reports for the first time the use of coaxial electrospinning to prepare such systems in the form of core–shell fibers. Eudragit S100 was used to form the shell of the fibers, while the core comprised poly(ethylene oxide) loaded with the magnetic resonance contrast agent Gd(DTPA) (Gd(III) diethylenetriaminepentaacetate hydrate) and indomethacin as a model therapeutic agent. The fibers had linear cylindrical morphologies with clear core–shell structures, as demonstrated by electron microscopy. X-ray diffraction and differential scanning calorimetry proved that both indomethacin and Gd(DTPA) were present in the fibers in the amorphous physical form. This is thought to be a result of intermolecular interactions between the different components, the presence of which was suggested by infrared spectroscopy. In vitro dissolution tests indicated that the fibers could provide targeted release of the active ingredients through a combined mechanism of erosion and diffusion. The proton relaxivities for Gd(DTPA) released from the fibers into tris buffer increased (r1 = 4.79–9.75 s–1 mM–1; r2 = 7.98–14.22 s–1 mM–1) compared with fresh Gd(DTPA) (r1 = 4.13 s–1 mM–1 and r2 = 4.40 s–1 mM–1), which proved that electrospinning has not diminished the contrast properties of the complex. The new systems reported herein thus offer a new platform for delivering therapeutic and imaging agents simultaneously to the colon.

Tensor Completion for Multidimensional Inverse Problems with Applications to Magnetic Resonance Relaxometry

This thesis deals with tensor completion for the solution of multidimensional inverse problems. We study the problem of reconstructing an approximately low rank tensor from a small number of noisy linear measurements. New recovery guarantees, numerical algorithms, non-uniform sampling strategies, and parameter selection algorithms are developed. We derive a fixed point continuation algorithm for tensor completion and prove its convergence. A restricted isometry property (RIP) based tensor recovery guarantee is proved. Probabilistic recovery guarantees are obtained for sub-Gaussian measurement operators and for measurements obtained by non-uniform sampling from a Parseval tight frame. We show how tensor completion can be used to solve multidimensional inverse problems arising in NMR relaxometry. Algorithms are developed for regularization parameter selection, including accelerated k-fold cross-validation and generalized cross-validation. These methods are validated on experimental and simulated data. We also derive condition number estimates for nonnegative least squares problems. Tensor recovery promises to significantly accelerate N-dimensional NMR relaxometry and related experiments, enabling previously impractical experiments. Our methods could also be applied to other inverse problems arising in machine learning, image processing, signal processing, computer vision, and other fields.

Diagnostic value of diffusion weighted MRI and ADC in differential diagnosis of cavernous hemangioma of the liver.

Aims: To investigate the use of diffusion weighted magnetic resonance imaging (DWI) and the apparent diffusion coefficient (ADC) values in the diagnosis of hemangioma. Materials and methods: The study population consisted of 72 patients with liver masses larger than 1 cm (72 focal lesions). DWI examination with a b value of 600 s/mm2 was carried out for all patients. After DWI examination, an ADC map was created and ADC values were measured for 72 liver masses and normal liver tissue (control group). The average ADC values of normal liver tissue and focal liver lesions, the “cut-off” ADC values, and the diagnostic sensitivity and specificity of the ADC map in diagnosing hemangioma, benign and malignant lesions were researched. Results: Of the 72 liver masses, 51 were benign and 21 were malignant. Benign lesions comprised 38 hemangiomas and 13 simple cysts. Malignant lesions comprised 9 hepatocellular carcinomas, and 12 metastases. The highest ADC values were measured for cysts (3.782±0.53×10-3 mm2/s) and hemangiomas (2.705±0.63×10-3 mm2/s). The average ADC value of hemangiomas was significantly higher than malignant lesions and the normal control group (p<0.001). The average ADC value of cysts were significantly higher when compared to hemangiomas and normal control group (p<0.001). To distinguish hemangiomas from malignant liver lesions, the “cut-off” ADC value of 1.800×10-3 mm2/s had a sensitivity of 97.4% and a specificity of 90.9%. To distinguish hemangioma from normal liver parenchyma the “cut-off” value of 1.858×10-3 mm2/s had a sensitivity of 97.4% and a specificity of 95.7%. To distinguish benign liver lesions from malignant liver lesions the “cut-off” value of 1.800×10-3 mm2/s had a sensitivity of 96.1% and a specificity of 90.0%. Conclusion: DWI and quantitative measurement of ADC values can be used in differential diagnosis of benign and malignant liver lesions and also in the diagnosis and differentiation of hemangiomas. When dynamic examination cannot distinguish cases with vascular metastasis and lesions from hemangioma, DWI and ADC values can be useful in the primary diagnosis and differential diagnosis. The technique does not require contrast material, so it can safely be used in patients with renal failure. Keywords:

In vivo microvascular oximetry using multispectral imaging

This thesis describes the application of multispectral imaging to several novel oximetry applications. Chapter 1 motivates optical microvascular oximetry, outlines oxygen transport in the body, describes the theory of oximetry, and describes the challenges associated with in vivo oximetry, in particular imaging through tissue. Chapter 2 reviews various imaging techniques for quantitative in vivo oximetry of the microvasculature, including multispectral and hyperspectral imaging, photoacoustic imaging, optical coherence tomography, and laser speckle techniques. Chapter 3 describes a two-wavelength oximetry study of two microvascular beds in the anterior segment of the eye: the bulbar conjunctival and episcleral microvasculature. This study reveals previously unseen oxygen diffusion from ambient air into the bulbar conjunctival microvasculature, altering the oxygen saturation of the bulbar conjunctiva. The response of the bulbar conjunctival and episcleral microvascular beds to acute mild hypoxia is quantified and the rate at which oxygen diffuses into bulbar conjunctival vessels is measured. Chapter 4 describes the development and application of a highly novel non-invasive retinal angiography technique: Oximetric Ratio Contrast Angiography (ORCA). ORCA requires only multispectral imaging and a small perturbation of blood oxygen saturation to produce angiographic sequences. A pilot study of ORCA in human subjects was conducted. This study demonstrates that ORCA can produce angiographic sequences with features such as sequential vessel filling and laminar flow. The application and challenges of ORCA are discussed, with emphasis on comparison with other angiography techniques, such as fluorescein angiography. Chapter 5 describes the development of a multispectral microscope for oximetry in the spinal cord dorsal vein of rats. Measurements of blood oxygen saturation are made in the dorsal vein of both healthy rats, and in rats with the Experimental autoimmune encephalomyelitis (EAE) disease model of multiple sclerosis. The venous blood oxygen saturation of EAE disease model rats was found to be significantly lower than that of healthy controls, indicating increased oxygen uptake from blood in the EAE disease model of multiple sclerosis. Chapter 6 describes the development of video-rate red eye oximetry; a technique which could enable stand-off oximetry of the blood-supply of the eye with high temporal resolution. The various challenges associated with video-rate red eye oximetry are investigated and their influence quantified. The eventual aim of this research is to track circulating deoxygenation perturbations as they arrive in both eyes, which could provide a screening method for carotid artery stenosis, which is major risk-factor for stroke. However, due to time constraints, it was not possible to thoroughly investigate if video-rate red eye can detect such perturbations. Directions and recommendations for future research are outlined.

Pressure Induced Structural Changes and Gas Diffusion Pathways in Monomeric Fluorescent Proteins

Fluorescent proteins (FPs) are extremely valuable biochemical markers which have found a wide range of applications in cellular and molecular biology research. The monomeric variants of red fluorescent proteins (RFPs), known as mFruits, have been especially valuable for in vivo applications in mammalian cell imaging. Fluorescent proteins consist of a chromophore caged in the beta-barrel protein scaffold. The photophysical properties of an FP is determined by its chromophore structure and its interactions with the protein barrel. Application of hydrostatic pressure on FPs results in the modification of the chromophore environment which allows a systematic study of the role of the protein-chromophore interactions on photophysical properties of FPs. Using Molecular Dynamics (MD) computer simulations, I investigated the pressure induced structural changes in the monomeric variants mCherry, mStrawberry, and Citrine. The results explain the molecular basis for experimentally observed pressure responses among FP variants. It is found that the barrel flexibility, hydrogen bonding interactions and chromophore planarity of the FPs can be correlated to their contrasting photophysical properties at vaious pressures. I also investigated the oxygen diffusion pathways in mOrange and mOrange2 which exhibit marked differences in oxygen sensitivities as well as photostability. Such computational identifications of structural changes and oxygen diffusion pathways are important in guiding mutagenesis efforts to design fluorescent proteins with improved photophysical properties.

Tensor-Train decomposition for image classification problems

In these last years a great effort has been put in the development of new techniques for automatic object classification, also due to the consequences in many applications such as medical imaging or driverless cars. To this end, several mathematical models have been developed from logistic regression to neural networks. A crucial aspect of these so called classification algorithms is the use of algebraic tools to represent and approximate the input data. In this thesis, we examine two different models for image classification based on a particular tensor decomposition named Tensor-Train (TT) decomposition. The use of tensor approaches preserves the multidimensional structure of the data and the neighboring relations among pixels. Furthermore the Tensor-Train, differently from other tensor decompositions, does not suffer from the curse of dimensionality making it an extremely powerful strategy when dealing with high-dimensional data. It also allows data compression when combined with truncation strategies that reduce memory requirements without spoiling classification performance. The first model we propose is based on a direct decomposition of the database by means of the TT decomposition to find basis vectors used to classify a new object. The second model is a tensor dictionary learning model, based on the TT decomposition where the terms of the decomposition are estimated using a proximal alternating linearized minimization algorithm with a spectral stepsize.

Study Of The Homogeneity Of Drug Loaded In Polymeric Films Using Near-infrared Chemical Imaging And Split-plot Design.

Split-plot design (SPD) and near-infrared chemical imaging were used to study the homogeneity of the drug paracetamol loaded in films and prepared from mixtures of the biocompatible polymers hydroxypropyl methylcellulose, polyvinylpyrrolidone, and polyethyleneglycol. The study was split into two parts: a partial least-squares (PLS) model was developed for a pixel-to-pixel quantification of the drug loaded into films. Afterwards, a SPD was developed to study the influence of the polymeric composition of films and the two process conditions related to their preparation (percentage of the drug in the formulations and curing temperature) on the homogeneity of the drug dispersed in the polymeric matrix. Chemical images of each formulation of the SPD were obtained by pixel-to-pixel predictions of the drug using the PLS model of the first part, and macropixel analyses were performed for each image to obtain the y-responses (homogeneity parameter). The design was modeled using PLS regression, allowing only the most relevant factors to remain in the final model. The interpretation of the SPD was enhanced by utilizing the orthogonal PLS algorithm, where the y-orthogonal variations in the design were separated from the y-correlated variation.