To increase the effectiveness of conventional radiotherapy in the treatment of cancer, different drugs can be administered. The aim of this project is to investigate biodegradable polyanhydride carrier matrices (PCPP-SA; 20:80) as a localized slow release delivery system for halogenated pyrimidines, in our case Bromodeoxyuridine (BrdU). Our in vitro experiments show that RIF-1 cells which have incorporated BrdU into their DNA over 4 doublings show significant increase in the initial slope (alpha-value) of their radiation cell survival curves, indicating an increase in radiosensitivity. To investigate the radiosensitization potential of BrdU in vivo, biodegradable BrdU/polymer combinations (20% w/w) were prepared and implanted directly into RIF-1 tumors, grown subcutaneously on the backs of C3H/Km mice. Clonogenic/excision assays were done with these tumors exposed to BrdU/polymer implants for several cell cycles before irradiation in situ to determine the extent of radiosensitization on the basis of cell survival. Tumor growth delay (TGD) measurements were also used as an index of tumor control following different treatments (single dose or fractionated doses) with and without the drug/polymer implants. All results indicate that BrdU, combined with radiation, increases TGD, while having no effect on non-irradiated tumors. The extent of substitution of thymidine by BrdU in DNA were also determined. This project was supported by the National Cancer Institute of Canada.

<p>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 8&mu;L 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.</p><p>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&times;1.25&times;1.25 mm<super>3</super> 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.</p><p>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 <italic>in-vivo</italic> inplane resolution of 0.390&times;0.390&mu;m<super>2</super> and an investigation of the trade-offs between spatial resolution and cortical specificity was conducted within the connectome framework.</p> / Dissertation

<p>To date, image localization of mobile tumors prior to radiation delivery has primarily been confined to 2D and 3D technologies, such as fluoroscopy and 3D cone-beam CT (3D-CBCT). Due to the limited information from these images, larger volumes of healthy tissue are often irradiated in order to ensure the radiation field encompasses the entirety of the target motion. Since the overarching goal of radiation therapy is to deliver maximum dose to cancerous cells and simultaneously minimize the radiation delivered to healthy surrounding tissues, it would be ideal to use 4D imaging to obtain time-resolved volume images of the tumor motion during respiration. </p><p>4D-CBCT imaging has been previously investigated, but has not yet seen large clinical translation due to the obstacles of long acquisition time and large image radiation dose. Furthermore, 4D-CBCT currently requires the use of external surrogates to correlate the patient's respiration with the image acquisition process. This correlation has been under question by a multitude of studies demonstrating the uncertainties that exist between the surrogate and the actual motion of the internal anatomy. Errors in the correlation process may result in image artifacts, which could potentially lead to reconstructions with inaccurate target volumes, thereby defeating the purpose of even using 4D-CBCT. </p><p>It is therefore the aim of this dissertation to initially highlight an additional limitation of using 3D-CBCT for imaging respiratory motion and thereby reiterate the need for 4D-CBCT imaging in the treatment room, develop a simple and efficient technique to achieve markerless, self-sorted 4D-CBCT and finally to comprehensively evaluate its robustness across a variety of potential clinical scenarios with a digital human phantom. </p><p>People often spend a longer period of time exhaling as compared with inhaling, and some do so in an extremely disproportionate manner. To demonstrate the disadvantage of using 3D-CBCT in such instances, a dynamic thorax phantom was imaged with a large variety of simulated and patient-derived respiratory traces of ratios of time spent in the inspiration phase versus time spent in the expiration phase (I/E ratio). Canny edge detection and contrast measures were employed to compare the internal target volumes (ITVs) generated per profile. The results revealed that an I/E ratio of less than one can lead to potential underestimation of the ITV with the severity increasing as the inspiration becomes more disproportionate to the expiration. This occurs because of the loss of contrast in the inspiration phase, due to the fewer number of projections acquired there. The measured contrast reduction was as high as 94% for small targets (0.5 cm) moving large amplitudes (2.0 cm) and still as much as 22.3% for large targets (3.0 cm) moving small amplitudes (0.5 cm). This is alarming because the degraded visibility of the target in the inspiration phase may inaccurately impact the alignment of the planning ITV with that of the FB-CBCT and thereby affect the accuracy of the localization and consequent radiation delivery. These potential errors can be avoided with the use of 4D-CBCT instead, to form the composite volume and serve as the verification ITV for alignment.</p><p>In order to delineate accurate target volumes from 4D-CBCT phase images, it is crucial that the projections be properly associated with the patient's respiration. Thus, in order to improve previously developed 4D-CBCT techniques, the basics of Fourier Transform (FT) theory were utilized to extract the respiratory signal directly from the acquired projection data. Markerless, self-sorted 4D-CBCT reconstruction was achieved by developing methods based on the phase and magnitude information of the Fourier Transform. Their performance was subsequently compared to the gold standard of visual identification of peak-inspiration projections. Slow-gantry acquired projections of two sets of physical phantom data with sinusoidal respiratory cycles of 3 and 6 seconds as well as three patients were used as initial evaluation of the feasibility of the Fourier technique. Quantitative criteria consisted of average difference in respiratory phase (ADRP) and percentage of projections assigned within 10% respiratory phase of the gold standard (PP10). For all five projection datasets, the results supported feasibility of both FT-Phase and FT-Magnitude methods with ADRP values less than 5.3% and PP10 values of 87.3% and above. </p><p>Because the technique proved to be promising in the initial feasibility study, a more comprehensive evaluation was necessary in order to assess the robustness of the technique across a larger set of possibilities that may be encountered in the clinic. A 4D digital XCAT phantom was used to generate an array of respiratory and anatomical variables that affect the performance of the technique. The respiratory variables studied included: inspiration to expiration ratio, respiratory cycle length, diaphragmatic motion amplitude, AP chest wall expansion amplitude, breathing irregularities such as baseline shift and inconsistent peak-inspiration amplitude, as well as six breathing profiles derived from cine-MRI images of three healthy volunteers and three lung cancer patients. The anatomical variables studied included: male and female patient size (physical dimension and adipose content), body-mass-index (BMI) category, tumor location, and percentage of the lung in the field-of-view (FOV) of the projection data. CBCT projections of each XCAT phantom were then generated. Additional external imaging factors such as image noise and detector wobble were added to select cases with different percentages of lung in the projection FOV to investigate any effects on the robustness. FT-Phase and FT-Magnitude were each applied and quantitatively compared to the gold standard. Both methods proved to be robust across the studied scenarios with ADRP<10% and PP10>90%, when incorporating minor modifications to region-of-interest (ROI) selection and/or low-frequency location to certain cases of diaphragm amplitude and lung percentage in the FOV of the projection (for which a method may have previously struggled). Nevertheless, in the instance where one method initially faltered, the other method prevailed and successfully identified peak-inspiration projections. This is promising because it suggests that the two methods provide complementary information to each other. To ensure appropriate clinical adaptation of markerless, self-sorted 4D-CBCT, perhaps an optimal integration of the two methods can be developed.</p> / Dissertation

Chronic lateral instability of the ankle (CLI), defined as frequent sprains and recurrent giving way, difficulty in walking and running on uneven surface, is often connected with pain and swollen ankles. It occurs in 10 to 20 percent after acute ankle injuries. Mechanical instability of the talocrural and subtalar joint, peroneal weakness and impaired proprioception has been suggested as etiological factors. Aim. To investigate the natural course in conservatively treated patients with CLI. To assess the mechanical stability in patients with CLI by measuring the three dimensional motions in the talus, the fibula and the calcaneus in relation to the tibia during different testing procedures pre- and postoperatively. To determine if CLI is associated with proprioceptive deficiency. Patients and Methods. This Thesis includes 127 ankles in 78 patients (30 women, 48 men) with CLI. Thirty-seven patients were followed up 20 years after their first contact with the orthopaedic department because of CLI. Forty-six ankles were evaluated radiographically and the result was compared with a gender- and age - matched control-material. The neuromuscular response to a sudden angular displacement of the ankles was studied in 15 ankles in 13 patients using EMG. Thirty-six patients entered a prospective study using roentgen stereophotogrammetric analysis (RSA) in which the ankles were tested at manual adduction, adduction with predetermined torque, with and without external support and at drawer tests (40 N and 160N). Twenty-seven patients were followed five years postoperatively. Result. After 20 years 22 patients, conservatively treated still suffered from instability of the ankle and ten had recurrent giving way symptoms even on plane surface. Six ankles in the patient group and four in the control group displayed osteoarthritic changes Prolonged ipsilateral reaction time (m. per. long, and m. tib. ant.) was found in patients with CLI indicating proprioceptive insufficiency. Increased talar adduction and a tendency toward increased total translation of the talar center was found in ankles with CLI. Concomitant fibular rotations and translations were found but with no conclusive deviation in the ankles with symptoms. The talo-calcaneal adduction reached the same level in the patient and control groups regardless of symptoms. External support (ankle brace) increased the talar stability. The use of predetermined torque and constrained testing procedure did not add information compared with the manual test Twenty-five patients graded the result as excellent or good five years after lateral ligament reconstruction. Talar stability (decreased adduction and translation) was increased two years postoperatively and was improved or remained the same at five years without comprising the range of motion. Conclusion. In more than half the cases symptoms of CLI did not resolve spontaneously. Minor degenerative changes was found after twenty years, but not to a greater extent than in a control group. CLI was associated with proprioceptive insufficiency and talocrural but not subtalar instability. Increased ankle stability can be obtained by the use of an ankle brace and by an anatomical ligament reconstruction. / <p>Diss. (sammanfattning) Umeå : Umeå universitet, 1994</p> / digitalisering@umu

Radiology is rapidly changing in the 21st century and globally there is a transition of radiology departments to digital imaging technology. The major challenge confronting radiology practices is to obtain cost savings and productivity gains once PACS is established. The purpose of the study is to undertake an incremental cost analysis of PACS compared to a conventional radiology department. Cost savings of the system was also determined in terms of productivity gains. An incremental cost analysis for Chest X-rays, CT Brain scans with and without contrast, MRI Brain scans with and without contrast was performed. The overall incremental cost between a PACS site and a conventional radiography site was determined in the study. The net present value technique was also determined to evaluate the capital budgeting requirements for both systems. The incremental costs for capital, RIS and image production for the PACS as well as the conventional system were performed. The incremental costs for both capital and RIS show an increase. In contrast, the incremental PACS image cost shows a reduction. This study provides a number of South African Radiology Departments which plan to introduce PACS in the near future with a bench mark for the financial implications incurred during the implementation phase. It assists other facilities in deciding on implementing PACS and contributes to the development of methodologies within the South African context. / Thesis (M.Med.Sc.)-University of KwaZulu-Natal, 2012

<p>X-ray computed tomography (CT) is a non-destructive medical imaging technique for assessing the cross-sectional images of an object in terms of attenuation. As it is designed based on the physical processes involved in the x-ray and matter interactions, faithfully modeling the physics in the reconstruction procedure can yield accurate attenuation distribution of the scanned object. Otherwise, unrealistic physical assumptions can result in unwanted artifacts in reconstructed images. For example, the current reconstruction algorithms assume the photons emitted by the x-ray source are mono-energetic. This oversimplified physical model neglects the poly-energetic properties of the x-ray source and the nonlinear attenuations of the scanned materials, and results in the well-known beam-hardening artifacts (BHAs). The purpose of this work was to incorporate the poly-energetic nature of the x-ray spectrum and then to eliminate BHAs. By accomplishing this, I can improve the image quality, enable the quantitative reconstruction ability of the single-spectrum CT scanner, and potentially reduce unnecessary radiation dose to patients.</p><p>In this thesis, in order to obtain accurate spectrum for poly-energetic reconstruction, I first presented a novel spectral estimation technique, with which spectra across a large range of angular trajectories of the imaging field of view can be estimated with a single phantom and a single axial acquisition. The experimental results with a 16 cm diameter cylindrical phantom (composition: ultra-high-molecular-weight polyethylene [UHMWPE]) on a clinical scanner showed that the averaged absolute mean energy differences and the normalized root mean square differences with respect to the actual spectra across kVp settings (i.e., 80, 100, 120, 140) and angular trajectories were less than 0.61 keV and 3.41%, respectively</p><p>With the previous estimation of the x-ray spectra, three poly-energetic reconstruction algorithms are proposed for different clinical applications. The first algorithm (i.e., poly-energetic iterative FBP [piFBP]) can be applied to routine clinical CT exams, as the spectra of the x-ray source and the nonlinear attenuations of diverse body tissues and metal implant materials are incorporated to eliminate BHAs and to reduce metal artifacts. The simulation results showed that the variation range of the relative errors of various tissues across different phantom sizes (i.e., 16, 24, 32, and 40 cm in diameter) and kVp settings (80, 100, 120, 140) were reduced from [-7.5%, 17.5%] for conventional FBP to [-0.1%, 0.1%] for piFBP, while the noise was maintained at the same low level (about [0.3%, 1.7%]).</p><p>When iodinated contrast agents are involved and patient motions are not readily correctable (e.g., in myocardial perfusion exam), a second algorithm (i.e., poly-energetic simultaneous algebraic reconstruction technique [pSART]) can be applied to eliminate BHAs and to quantitatively determine the iodine concentrations of blood-iodine mixtures with our new technique. The phantom experiment on a clinical CT scanner indicated that the maximum absolute relative error across material inserts was reduced from 4.1% for conventional simultaneous algebraic reconstruction technique [SART] to 0.4% for pSART.</p><p>Extending the work beyond minimizing BHAs, if patient motions are correctable or negligible, a third algorithm (i.e., poly-energetic dynamic perfusion algorithm [pDP]) is developed to retrieve iodine maps of any iodine-tissue mixtures in any perfusion exams, such as breast, lung, or brain perfusion exams. The quantitative results of the simulations with a dynamic anthropomorphic thorax phantom indicated that the maximum error of iodine concentrations can be reduced from 1.1 mg/cc for conventional FBP to less than 0.1 mg/cc for pDP.</p><p>Two invention disclosure forms based on the work presented in this thesis have been submitted to Office of Licensing & Ventures of Duke University.</p> / Dissertation

<p>The cross-sectional images of computed tomography (CT) are calculated from a series of projections using reconstruction methods. Recently introduced on clinical CT scanners, iterative reconstruction (IR) method enables potential patient dose reduction with significantly reduced image noise, but is limited by its "waxy" texture and nonlinear nature. To balance the advantages and disadvantages of IR, evaluations are needed with diagnostic accuracy as the endpoint. Moreover, evaluations need to take into consideration the type of the imaging task (detection and quantification), the properties of the task (lesion size, contrast, edge profile, etc.), and other acquisition and reconstruction parameters. </p><p>To evaluate detection tasks, the more acceptable method is observer studies, which involve image preparation, graphical user interface setup, manual detection and scoring, and statistical analyses. Because such evaluation can be time consuming, mathematical models have been proposed to efficiently predict observer performance in terms of a detectability index (d'). However, certain assumptions such as system linearity may need to be made, thus limiting the application of the models to potentially nonlinear IR. For evaluating quantification tasks, conventional method can also be time consuming as it usually involves experiments with anthropomorphic phantoms. A mathematical model similar to d' was therefore proposed for the prediction of volume quantification performance, named the estimability index (e'). However, this prior model was limited in its modeling of the task, modeling of the volume segmentation process, and assumption of system linearity.</p><p>To expand prior d' and e' models to the evaluations of IR performance, the first part of this dissertation developed an experimental methodology to characterize image noise and resolution in a manner that was relevant to nonlinear IR. Results showed that this method was efficient and meaningful in characterizing the system performance accounting for the non-linearity of IR at multiple contrast and noise levels. It was also shown that when certain criteria were met, the measurement error could be controlled to be less than 10% to allow challenging measuring conditions with low object contrast and high image noise.</p><p>The second part of this dissertation incorporated the noise and resolution characterizations developed in the first part into the d' calculations, and evaluated the performance of IR and conventional filtered backprojection (FBP) for detection tasks. Results showed that compared to FBP, IR required less dose to achieve a threshold performance accuracy level, therefore potentially reducing the required dose. The dose saving potential of IR was not constant, but dependent on the task properties, with subtle tasks (small size and low contrast) enabling more dose saving than conspicuous tasks. Results also showed that at a fixed dose level, IR allowed more subtle tasks to exceed a threshold performance level, demonstrating the overall superior performance of IR for detection tasks.</p><p>The third part of this dissertation evaluated IR performance in volume quantification tasks with conventional experimental method. The volume quantification performance of IR was measured using an anthropomorphic chest phantom and compared to FBP in terms of accuracy and precision. Results showed that across a wide range of dose and slice thickness, IR led to accuracy significantly different from that of FBP, highlighting the importance of calibrating or expanding current segmentation software to incorporate the image characteristics of IR. Results also showed that despite IR's great noise reduction in uniform regions, IR in general had quantification precision similar to that of FBP, possibly due to IR's diminished noise reduction at edges (such as nodule boundaries) and IR's loss of resolution at low dose levels. </p><p>The last part of this dissertation mathematically predicted IR performance in volume quantification tasks with an e' model that was extended in three respects, including the task modeling, the segmentation software modeling, and the characterizations of noise and resolution properties. Results showed that the extended e' model correlated with experimental precision across a range of image acquisition protocols, nodule sizes, and segmentation software. In addition, compared to experimental assessments of quantification performance, e' was significantly reduced in computational time, such that it can be easily employed in clinical studies to verify quantitative compliance and to optimize clinical protocols for CT volumetry.</p><p>The research in this dissertation has two important clinical implications. First, because d' values reflect the percent of detection accuracy and e' values reflect the quantification precision, this work provides a framework for evaluating IR with diagnostic accuracy as the endpoint. Second, because the calculations of d' and e' models are much more efficient compared to conventional observer studies, the clinical protocols with IR can be optimized in a timely fashion, and the compliance of clinical performance can be examined routinely.</p> / Dissertation

Mammographic breast density (MBD) is a strong risk factor for developing breast cancer. MBD is typically estimated by manually selecting the area occupied by the dense tissue on a mammogram. There is interest in measuring the volume of dense tissue, or volumetric breast density (VBD), as it could potentially be a stronger risk factor. This dissertation presents and validates an algorithm to measure the VBD from digital mammograms. The algorithm is based on an empirical calibration of the mammography system, supplemented by physical modeling of x-ray imaging that includes the effects of beam polychromaticity, scattered radation, anti-scatter grid and detector glare. It also includes a method to estimate the compressed breast thickness as a function of the compression force, and a method to estimate the thickness of the breast outside of the compressed region. The algorithm was tested on 26 simulated mammograms obtained from computed tomography images, themselves deformed to mimic the effects of compression. This allowed the determination of the baseline accuracy of the algorithm. The algorithm was also used on 55 087 clinical digital mammograms, which allowed for the determination of the general characteristics of VBD and breast volume, as well as their variation as a function of age and time. The algorithm was also validated against a set of 80 magnetic resonance images, and compared against the area method on 2688 images. A preliminary study comparing association of breast cancer risk with VBD and MBD was also performed, indicating that VBD is a stronger risk factor. The algorithm was found to be accurate, generating quantitative density measurements rapidly and automatically. It can be extended to any digital mammography system, provided that the compression thickness of the breast can be determined accurately.

Studies of diagnostic accuracy often report paired tests for sensitivity and specificity that can be pooled separately to produce summary estimates in a meta-analysis. This was done recently for a systematic review of radiographers' reporting accuracy of plain radiographs. The problem with pooling sensitivities and specificities separately is that it does not acknowledge any possible (negative) correlation between these two measures. A possible cause of this negative correlation is that different thresholds are used in studies to define abnormal and normal radiographs because of implicit variations in thresholds that occur when radiographers' report plain radiographs. A method that allows for the correlation that can exist between pairs of sensitivity and specificity within a study using a random effects approach is the bivariate model. When estimates of accuracy as a fixed-effects model were pooled separately, radiographers' reported plain radiographs in clinical practice at 93% (95% confidence interval (CI) 92-93%) sensitivity and 98% (95% CI 98-98%) specificity. The bivariate model produced the same summary estimates of sensitivity and specificity but with wider confidence intervals (93% (95% CI 91-95%) and 98% (95% CI 96-98%), respectively) that take into account the heterogeneity beyond chance between studies. This method also allowed us to calculate a 95% confidence ellipse around the mean values of sensitivity and specificity and a 95% prediction ellipse for individual values of sensitivity and specificity. The bivariate model is an improvement on pooling sensitivity and specificity separately when there is a threshold effect, and it is the preferred method of choice.

<p>Image noise is a pervasive problem in medical imaging. It is a property endemic to all imaging modalities and one especially familiar in those modalities that employ ionizing radiation. Statistical uncertainty is a major limiting factor in the reduction of ionizing radiation dose; patient exposure must be minimized but high image quality must also be achieved to retain the clinical utility of medical images. One way to achieve the goal of radiation dose reduction is through the use of image post processing with noise reduction algorithms. By acquiring images at lower than normal exposure followed by algorithmic noise reduction, it is possible to restore image noise to near normal levels. However, many denoising algorithms degrade the integrity of other image quality components in the process. </p><p>In this dissertation, a new noise reduction algorithm is investigated: Correlated Polarity Noise Reduction (CPNR). CPNR is a novel noise reduction technique that uses a statistical approach to reduce noise variance while maintaining excellent resolution and a "normal" noise appearance. In this work, the algorithm is developed in detail with the introduction of several methods for improving polarity estimation accuracy and maintaining the normality of the residual noise intensity distribution. Several image quality characteristics are assessed in the production of this new algorithm including its effects on residual noise texture, residual noise magnitude distribution, resolution effects, and nonlinear distortion effects. An in-depth review of current linear methods for medical imaging system resolution analysis will be presented along with several newly discovered improvements to existing techniques. This is followed by the presentation of a new paradigm for quantifying the frequency response and distortion properties of nonlinear algorithms. Finally, the new CPNR algorithm is applied to computed tomography (CT) to assess its efficacy as a dose reduction tool in 3-D imaging.</p><p>It was found that the CPNR algorithm can be used to reduce x ray dose in projection radiography by a factor of at least two without objectionable degradation of image resolution. This is comparable to other nonlinear image denoising algorithms such as the bilateral filter and wavelet denoising. However, CPNR can accomplish this level of dose reduction with few edge effects and negligible nonlinear distortion of the anatomical signal as evidenced by the newly developed nonlinear assessment paradigm. In application to multi-detector CT, XCAT simulations showed that CPNR can be used to reduce noise variance by 40% with minimal blurring of anatomical structures under a filtered back-projection reconstruction paradigm. When an apodization filter was applied, only 33% noise variance reduction was achieved, but the edge-saving qualities were largely retained. In application to cone-beam CT for daily patient positioning in radiation therapy, up to 49% noise variance reduction was achieved with as little as 1% reduction in the task transfer function measured from reconstructed data at the cutoff frequency. </p><p>This work concludes that the CPNR paradigm shows promise as a viable noise reduction tool which can be used to maintain current standards of clinical image quality at almost half of normal radiation exposure This algorithm has favorable resolution and nonlinear distortion properties as measured using a newly developed set of metrics for nonlinear algorithm resolution and distortion assessment. Simulation studies and the initial application of CPNR to cone-beam CT data reveal that CPNR may be used to reduce CT dose by 40%-49% with minimal degradation of image resolution.</p> / Dissertation