Dynamic contrast-enhanced (DCE) time series analysis techniques are hard to fully validate quantitatively as ground truth microvascular parameters are difficult to obtain from patient data. This thesis presents a software application for generating synthetic image data from known ground truth tracer kinetic model parameters. As an object oriented design has been employed to maximise flexibility and extensibility, the application can be extended to include different vascular input functions, tracer kinetic models and imaging modalities. Data sets can be generated for different anatomical and motion descriptions as well as different ground truth parameters. The application has been used to generate a synthetic DCE-MRI time series of a liver tumour with non-linear motion of the abdominal organs due to breathing. The utility of the synthetic data has been demonstrated in several applications: in the development of an Akaike model selection technique for assessing the spatially varying characteristics of liver tumours; the robustness of model fitting and model selection to noise, partial volume effects and breathing motion in liver tumours; and the benefit of using model-driven registration to compensate for breathing motion. When applied to synthetic data with appropriate noise levels, the Akaike model selection technique can distinguish between the single-input extended Kety model for tumour and the dual-input Materne model for liver, and is robust to motion. A significant difference between median Akaike probability value in tumour and liver regions is also seen in 5/6 acquired data sets, with the extended Kety model selected for tumour. Knowledge of the ground truth distribution for the synthetic data was used to demonstrate that, whilst median Ktrans does not change significantly due to breathing motion, model-driven registration restored the structure of the Ktrans histogram and so could be beneficial to tumour heterogeneity assessments.

Previous studies have suggested that iron PRBs, receiving high concentrations of inorganic constituents in groundwater, may experience passivation because of the accumulation of inorganic precipitates. In an iron PRB containing more highly reactive material, even though the initial contaminant removal rate is faster than for less reactive material, a faster migration of the contaminant removal front may occur due to the greater reactivity loss, caused by faster accumulation of secondary precipitates. In contrast, an iron PRB containing less reactive material may show a slower accumulation of precipitates, and thus will show a slower migration of the contaminant removal front over time. Thus, it is hypothesized that an iron material having moderate initial reactivity may be more advantageous than material having a higher reactivity in terms of long-term performance. The objective of this study was to test this hypothesis by evaluating the changes of the reactivities of different iron materials in the presence of dissolved CaCO₃. <br /><br /> Four different iron materials (Connelly, G-M, Ispat and Peerless) were selected for the column experiments. The changes in reactivities of the iron and formation of secondary precipitates over time were assessed, primarily by the iron corrosion rates, calculated from the hydrogen gas generation rates, by the cis-DCE removal rates and by the alkalinity profiles. The accumulation of precipitates in the four columns caused passivation of the iron. The passivation of the iron in turn resulted in migration of the mineral precipitation fronts as well as profiles of cis-DCE, TCE, VC, alkalinity, Eh, pH, and chloride. Connelly and G-M had longer periods of operation than Ispat and Peerless and thus their performance was the primary test of the hypothesis. G-M iron, which had the higher initial corrosion rate, compared to Connelly, showed a faster accumulation of precipitates near the influent end. The difference in accumulated precipitates resulted in a difference in the leading edge of the organic profiles and a significant difference in the pattern of passivation, indicating a faster passivation in the region near the influent end for G-M. <br /><br /> Model simulations were performed using the same fitting parameters but with different initial corrosion rate constants to further test the hypothesis. The model provided a reasonable representation of changing reactivities of the columns, being consistent with the observed data. In the simulation for long-term prediction, the cases of higher corrosion rates showed earlier breakthroughs and steeper curves than those of lower corrosion rates. Also, the predictions showed greater porosity loss for the case of higher corrosion rate. Thus, long-term predictions support the hypothesis. Accurate determination of model parameters such as cis-DCE degradation rate constants and iron corrosion rates are required for better predictions of long-term performance.

Previous studies have suggested that iron PRBs, receiving high concentrations of inorganic constituents in groundwater, may experience passivation because of the accumulation of inorganic precipitates. In an iron PRB containing more highly reactive material, even though the initial contaminant removal rate is faster than for less reactive material, a faster migration of the contaminant removal front may occur due to the greater reactivity loss, caused by faster accumulation of secondary precipitates. In contrast, an iron PRB containing less reactive material may show a slower accumulation of precipitates, and thus will show a slower migration of the contaminant removal front over time. Thus, it is hypothesized that an iron material having moderate initial reactivity may be more advantageous than material having a higher reactivity in terms of long-term performance. The objective of this study was to test this hypothesis by evaluating the changes of the reactivities of different iron materials in the presence of dissolved CaCO₃. <br /><br /> Four different iron materials (Connelly, G-M, Ispat and Peerless) were selected for the column experiments. The changes in reactivities of the iron and formation of secondary precipitates over time were assessed, primarily by the iron corrosion rates, calculated from the hydrogen gas generation rates, by the cis-DCE removal rates and by the alkalinity profiles. The accumulation of precipitates in the four columns caused passivation of the iron. The passivation of the iron in turn resulted in migration of the mineral precipitation fronts as well as profiles of cis-DCE, TCE, VC, alkalinity, Eh, pH, and chloride. Connelly and G-M had longer periods of operation than Ispat and Peerless and thus their performance was the primary test of the hypothesis. G-M iron, which had the higher initial corrosion rate, compared to Connelly, showed a faster accumulation of precipitates near the influent end. The difference in accumulated precipitates resulted in a difference in the leading edge of the organic profiles and a significant difference in the pattern of passivation, indicating a faster passivation in the region near the influent end for G-M. <br /><br /> Model simulations were performed using the same fitting parameters but with different initial corrosion rate constants to further test the hypothesis. The model provided a reasonable representation of changing reactivities of the columns, being consistent with the observed data. In the simulation for long-term prediction, the cases of higher corrosion rates showed earlier breakthroughs and steeper curves than those of lower corrosion rates. Also, the predictions showed greater porosity loss for the case of higher corrosion rate. Thus, long-term predictions support the hypothesis. Accurate determination of model parameters such as cis-DCE degradation rate constants and iron corrosion rates are required for better predictions of long-term performance.

Effective early detection and monitoring of patient response to cancer therapy is important for improved patient outcomes, avoiding unnecessary procedures and their associated toxicities, as well as the development of new therapies. Dynamic contrast-enhanced magnetic resonance imaging shows promise as a way to evaluate tumour vasculature and assess the efficacy of new anti-angiogenic drugs. However, unavoidable patient motion can decrease the accuracy of subsequent analyses rendering the data unusable. Motion correction algorithms are challenging to develop for contrast-enhanced data since intensity changes due to contrast-enhancement and patient motion must somehow be differentiated from one another. A novel method is presented that employs a motion-informed intensity correction in order to facilitate the registration of contrast enhanced data. The intensity correction simulates the presence or absence of contrast agent in the image volumes to be registered in an attempt to emulate the level of contrast-enhancement present in a single reference image volume.

Effective early detection and monitoring of patient response to cancer therapy is important for improved patient outcomes, avoiding unnecessary procedures and their associated toxicities, as well as the development of new therapies. Dynamic contrast-enhanced magnetic resonance imaging shows promise as a way to evaluate tumour vasculature and assess the efficacy of new anti-angiogenic drugs. However, unavoidable patient motion can decrease the accuracy of subsequent analyses rendering the data unusable. Motion correction algorithms are challenging to develop for contrast-enhanced data since intensity changes due to contrast-enhancement and patient motion must somehow be differentiated from one another. A novel method is presented that employs a motion-informed intensity correction in order to facilitate the registration of contrast enhanced data. The intensity correction simulates the presence or absence of contrast agent in the image volumes to be registered in an attempt to emulate the level of contrast-enhancement present in a single reference image volume.

This project focused on the pulmonary application of magnetic resonance (MR) quantitative equilibrium signal (qS0) mapping, dynamic oxygen-enhanced (OE-) magnetic resonance imaging (MRI) and dynamic contrast-enhanced (DCE-) MRI in asthma and chronic obstructive pulmonary disease (COPD). Initially, a retrospective analysis of MRI and X-ray computed tomography (CT) data from 24 COPD patients and 12 healthy controls demonstrated that MR qS0 mapping had good one-week reproducibility and was comparable to CT in the localization and quantification of emphysema in patients with COPD. In the same data, a reduced oxygen (O2) delivery signal was detected by dynamic OE-MRI in COPD patients regardless of the presence or absence of emphysema on CT, while a significantly reduced baseline spin-lattice relaxation time (T1air) was only observed in emphysematous COPD. Emphysematous COPD also showed significant correlations between dynamic OE-MRI readouts, i.e. enhancing fraction (EF) and the change in the partial pressure of O2 in lung parenchyma (ΔPO2max), and pulmonary diffusion capacity and CT estimates of emphysema. A prospective pilot study was conducted in 10 asthmatic patients which demonstrated that dynamic OE-MRI readouts, including EF, ΔPO2max and O2 wash-in time constant (τup), were reproducible within one month, sensitive to asthma severity and strongly correlated with spirometric readouts of airway function and lung volume. This was followed by a second prospective intervention study in 30 asthmatic patients and 10 healthy controls which revealed a pattern of decreased O2 delivery signal as a response to salbutamol inhalation in severe asthmatics but not in mild asthmatics or healthy controls using short-term repeated dynamic OE-MRI. In addition, DCE-MRI was also performed on 30 asthmatic patients and 10 healthy subjects. A semi-quantitative analysis demonstrated that contrast agent kinetics in asthmatic lungs were characterised by a reduced first-pass peak (SI%max) and a shallower downslope during the late redistribution phase (kwashout) than was observed in healthy controls, and that these were related to pulmonary function test measurements. An extended Tofts model-based quantitative analysis further revealed a significantly increased fractional extravascular extracellular space (ve) in patients with asthma than in healthy controls while the contrast agent transfer coefficient (Ktrans), an index related to vascular permeability, and the fractional blood plasma volume (vp), did not distinguish asthmatics from controls. In conclusion, this project demonstrated the promise of 1) MR qS0 mapping for the assessment of emphysema in COPD lungs, 2) dynamic OE-MRI for the assessment of impaired pulmonary oxygenation in COPD and asthma and for the monitoring of short-term treatment effects in asthma and 3) DCE-MRI for the evaluation of pulmonary microvascular inflammation in asthma. The non-invasive non-ionizing properties and simple setup requirements make these three proton MRI techniques attractive options in the assessment of structural and functional alterations of the lungs in asthma and COPD in clinical settings.

<p>Abstract</p><p>The goal of modern radiotherapy is to precisely deliver a prescribed radiation dose to delineated target volumes that contain a significant amount of tumor cells while sparing the surrounding healthy tissues/organs. Precise delineation of treatment and avoidance volumes is the key for the precision radiation therapy. In recent years, considerable clinical and research efforts have been devoted to integrate MRI into radiotherapy workflow motivated by the superior soft tissue contrast and functional imaging possibility. Dynamic contrast-enhanced MRI (DCE-MRI) is a noninvasive technique that measures properties of tissue microvasculature. Its sensitivity to radiation-induced vascular pharmacokinetic (PK) changes has been preliminary demonstrated. In spite of its great potential, two major challenges have limited DCE-MRI’s clinical application in radiotherapy assessment: the technical limitations of accurate DCE-MRI imaging implementation and the need of novel DCE-MRI data analysis methods for richer functional heterogeneity information. </p><p>This study aims at improving current DCE-MRI techniques and developing new DCE-MRI analysis methods for particular radiotherapy assessment. Thus, the study is naturally divided into two parts. The first part focuses on DCE-MRI temporal resolution as one of the key DCE-MRI technical factors, and some improvements regarding DCE-MRI temporal resolution are proposed; the second part explores the potential value of image heterogeneity analysis and multiple PK model combination for therapeutic response assessment, and several novel DCE-MRI data analysis methods are developed.</p><p>I. Improvement of DCE-MRI temporal resolution. First, the feasibility of improving DCE-MRI temporal resolution via image undersampling was studied. Specifically, a novel MR image iterative reconstruction algorithm was studied for DCE-MRI reconstruction. This algorithm was built on the recently developed compress sensing (CS) theory. By utilizing a limited k-space acquisition with shorter imaging time, images can be reconstructed in an iterative fashion under the regularization of a newly proposed total generalized variation (TGV) penalty term. In the retrospective study of brain radiosurgery patient DCE-MRI scans under IRB-approval, the clinically obtained image data was selected as reference data, and the simulated accelerated k-space acquisition was generated via undersampling the reference image full k-space with designed sampling grids. Two undersampling strategies were proposed: 1) a radial multi-ray grid with a special angular distribution was adopted to sample each slice of the full k-space; 2) a Cartesian random sampling grid series with spatiotemporal constraints from adjacent frames was adopted to sample the dynamic k-space series at a slice location. Two sets of PK parameters’ maps were generated from the undersampled data and from the fully-sampled data, respectively. Multiple quantitative measurements and statistical studies were performed to evaluate the accuracy of PK maps generated from the undersampled data in reference to the PK maps generated from the fully-sampled data. Results showed that at a simulated acceleration factor of four, PK maps could be faithfully calculated from the DCE images that were reconstructed using undersampled data, and no statistically significant differences were found between the regional PK mean values from undersampled and fully-sampled data sets. DCE-MRI acceleration using the investigated image reconstruction method has been suggested as feasible and promising. </p><p>Second, for high temporal resolution DCE-MRI, a new PK model fitting method was developed to solve PK parameters for better calculation accuracy and efficiency. This method is based on a derivative-based deformation of the commonly used Tofts PK model, which is presented as an integrative expression. This method also includes an advanced Kolmogorov-Zurbenko (KZ) filter to remove the potential noise effect in data and solve the PK parameter as a linear problem in matrix format. In the computer simulation study, PK parameters representing typical intracranial values were selected as references to simulated DCE-MRI data for different temporal resolution and different data noise level. Results showed that at both high temporal resolutions (<1s) and clinically feasible temporal resolution (~5s), this new method was able to calculate PK parameters more accurate than the current calculation methods at clinically relevant noise levels; at high temporal resolutions, the calculation efficiency of this new method was superior to current methods in an order of 102. In a retrospective of clinical brain DCE-MRI scans, the PK maps derived from the proposed method were comparable with the results from current methods. Based on these results, it can be concluded that this new method can be used for accurate and efficient PK model fitting for high temporal resolution DCE-MRI. </p><p>II. Development of DCE-MRI analysis methods for therapeutic response assessment. This part aims at methodology developments in two approaches. The first one is to develop model-free analysis method for DCE-MRI functional heterogeneity evaluation. This approach is inspired by the rationale that radiotherapy-induced functional change could be heterogeneous across the treatment area. The first effort was spent on a translational investigation of classic fractal dimension theory for DCE-MRI therapeutic response assessment. In a small-animal anti-angiogenesis drug therapy experiment, the randomly assigned treatment/control groups received multiple fraction treatments with one pre-treatment and multiple post-treatment high spatiotemporal DCE-MRI scans. In the post-treatment scan two weeks after the start, the investigated Rényi dimensions of the classic PK rate constant map demonstrated significant differences between the treatment and the control groups; when Rényi dimensions were adopted for treatment/control group classification, the achieved accuracy was higher than the accuracy from using conventional PK parameter statistics. Following this pilot work, two novel texture analysis methods were proposed. First, a new technique called Gray Level Local Power Matrix (GLLPM) was developed. It intends to solve the lack of temporal information and poor calculation efficiency of the commonly used Gray Level Co-Occurrence Matrix (GLCOM) techniques. In the same small animal experiment, the dynamic curves of Haralick texture features derived from the GLLPM had an overall better performance than the corresponding curves derived from current GLCOM techniques in treatment/control separation and classification. The second developed method is dynamic Fractal Signature Dissimilarity (FSD) analysis. Inspired by the classic fractal dimension theory, this method measures the dynamics of tumor heterogeneity during the contrast agent uptake in a quantitative fashion on DCE images. In the small animal experiment mentioned before, the selected parameters from dynamic FSD analysis showed significant differences between treatment/control groups as early as after 1 treatment fraction; in contrast, metrics from conventional PK analysis showed significant differences only after 3 treatment fractions. When using dynamic FSD parameters, the treatment/control group classification after 1st treatment fraction was improved than using conventional PK statistics. These results suggest the promising application of this novel method for capturing early therapeutic response. </p><p> The second approach of developing novel DCE-MRI methods is to combine PK information from multiple PK models. Currently, the classic Tofts model or its alternative version has been widely adopted for DCE-MRI analysis as a gold-standard approach for therapeutic response assessment. Previously, a shutter-speed (SS) model was proposed to incorporate transcytolemmal water exchange effect into contrast agent concentration quantification. In spite of richer biological assumption, its application in therapeutic response assessment is limited. It might be intriguing to combine the information from the SS model and from the classic Tofts model to explore potential new biological information for treatment assessment. The feasibility of this idea was investigated in the same small animal experiment. The SS model was compared against the Tofts model for therapeutic response assessment using PK parameter regional mean value comparison. Based on the modeled transcytolemmal water exchange rate, a biological subvolume was proposed and was automatically identified using histogram analysis. Within the biological subvolume, the PK rate constant derived from the SS model were proved to be superior to the one from Tofts model in treatment/control separation and classification. Furthermore, novel biomarkers were designed to integrate PK rate constants from these two models. When being evaluated in the biological subvolume, this biomarker was able to reflect significant treatment/control difference in both post-treatment evaluation. These results confirm the potential value of SS model as well as its combination with Tofts model for therapeutic response assessment. </p><p>In summary, this study addressed two problems of DCE-MRI application in radiotherapy assessment. In the first part, a method of accelerating DCE-MRI acquisition for better temporal resolution was investigated, and a novel PK model fitting algorithm was proposed for high temporal resolution DCE-MRI. In the second part, two model-free texture analysis methods and a multiple-model analysis method were developed for DCE-MRI therapeutic response assessment. The presented works could benefit the future DCE-MRI routine clinical application in radiotherapy assessment.</p> / Dissertation

The aim of this master thesis is to create two laboratory exercises in ns-3 network simulator for chosen communication protocols. The chosen protocols are BGP and ICMPv6. The first part of this thesis contains teoretical knowledge used in order to design laboratory exercise. It contains descriptions of funcionality of both protocols and messages they use. This chapter also includes brief description of three options which were considered for implementation of BGP protocol into ns-3 enviroment. The second chapter consists of actual laboratory exercises which were created as a purpose of this thesis. Exercise for BGP protocol deals with creating neighborhoods between routers at autonomous system level, analyzing the way routers communicate within their neighborhoods and how protocol reacts when the connection between two neighbor routers fails. Exercise created for ICMPv6 protocol is focused on its messages and their usage within multiple protocol funcionalities, such as address configuration, link address resolution and error detection.

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