Thesis (MTech (Radiography))--Cape Peninsula University of Technology, 2006. / The knee is one of the most complicated joints in the body. The deep infrapatellar bursa being only a small water-pocket and forming a small part of the knee. The deep infrapatellar bursa can get inflamed and cause great discomfort, especially to professional sportsmen and -women. If such a inflammation is present, a common treament option are to inject a cortisone solution into the bursa for quick relieve and healing. This study was performed to investigate the specific ultrasound features of a normal deep infrapatellar bursa. Thus enableing more specific and accurate diagnosis of deep infrapatellar bursitis or not, which in turn leads to quicker recovery of the patients.

abstract: The goal of the works presented in this volume is to develop a magnetic resonance imaging (MRI) probe for non-invasive detection of extracellular matrix (ECM) underlying fenestrated endothelia. The ECM is the scaffold that supports tissue structure in all organs. In fenestrated structures the such as the kidney glomerulus and the hepatic sinusoid the ECM serves a unique role in blood filtration and is directly exposed to blood plasma. An assessment of the ECM in fenestrated organs such as the kidney and liver reports on the organ's ability to filter blood - a process critical to maintaining homeostasis. Unfortunately, clinical assessment of the ECM in most organs requires biopsy, which is focal and invasive. This work will focus on visualizing the ECM underlying fenestrated endothelia with natural nanoparticles and MRI. The superparamagnetic ferritin protein has been proposed as a useful naturally-derived, MRI-detectable nanoparticle due to its biocompatibility, ease of functionalization, and modifiable metallic core. We will show that cationized ferritin (CF) specifically binds to the anionic proteoglycans of the ECM underlying fenestrated endothelia and that its accumulation is MRI-detectable. We will then demonstrate the use of CF and MRI in identifying and measuring all glomeruli in the kidney. We will also explore the toxicity of intravenously injected CF and consider other avenues for its application, including detection of microstructural changes in the liver due to chronic liver disease. This work will show that CF is useful in detected fenestrated microstructures in small animals and humans alike, indicating that CF may find broad application in detecting and monitoring disease in both preclinical and clinical settings. / Dissertation/Thesis / Ph.D. Bioengineering 2012

Direct imaging of exoplanets requires establishing and maintaining a high-contrast dark field (DF) within the science image to a high degree of precision (10(-10)). Current approaches aimed at establishing the DF, such as electric field conjugation (EFC), have been demonstrated in the lab and have proven capable of high-contrast DF generation. The same approaches have been considered for the maintenance of the DF as well. However, these methods rely on phase diversity measurements, which require field modulation; this interrupts the DF and consequently competes with the science acquisition. We introduce and demonstrate spatial linear dark field control (LDFC) as an alternative technique by which the high-contrast DF can be maintained without modulation. Once the DF has been established by conventional EFC, spatial LDFC locks the high-contrast state of the DF by operating a closed loop around the linear response of the bright field (BF) to wavefront variations that modify both the BF and the DF. We describe the fundamental operating principles of spatial LDFC and provide numerical simulations of its operation as a DF stabilization technique that is capable of wavefront correction within the DF without interrupting science acquisition. (c) The Authors.

It is well known that a translating mask can optically encode low-resolution measurements from which higher resolution images can be computationally reconstructed. We experimentally demonstrate that this principle can be used to achieve substantial increase in image resolution compared to the size of the focal plane array (FPA). Specifically, we describe a scalable architecture with a translating mask (also referred to as a coded aperture) that achieves eightfold resolution improvement (or 64: 1 increase in the number of pixels compared to the number of focal plane detector elements). The imaging architecture is described in terms of general design parameters (such as field of view and angular resolution, dimensions of the mask, and the detector and FPA sizes), and some of the underlying design trades are discussed. Experiments conducted with different mask patterns and reconstruction algorithms illustrate how these parameters affect the resolution of the reconstructed image. Initial experimental results also demonstrate that the architecture can directly support task-specific information sensing for detection and tracking, and that moving objects can be reconstructed separately from the stationary background using motion priors. (C) 2017 Society of Photo-Optical Instrumentation Engineers (SPIE)

M.Tech. / To determine whether a combination of real-time B-Mode ultrasound, Doppler Color flow and Power Doppler flow mapping would be reliable in differentiating benign from malignant breast nodules in an attempt to avoid unnecessary biopsies, where after ultrasound guidelines would be formulated. A quantitative cross-sectional comparative descriptive design in a study population which consisted of 62 women over the age of 35 years who came to Klerksdorp Radiology services for mammography. Both breast ultrasound imaging and mammography was used as a routine procedure as part of the workup for the classification of breast nodules, before histologic specimens were obtained. All nodules were classified according to the ultrasonographic BI-RADS lexicon and compared with the pathologic results. Of the 63 patients, 63 breast nodules were detected and confirmed by biopsy. Thirty seven (59%) nodules were found to be malignant and 26 (41%) were benign according to biopsy results. Mammography had 87% sensitivity and ultrasound 60% sensitivity in detecting malignancy. It is recommended that B-mode, Color Doppler flow and Power Doppler flow mapping be used in combination with mammography for screening as a gold standard.

Poly(ADP-ribose)polymerase-1 and -2 (PARP1/2) are nuclear proteins involved in DNA repair. Tumors with defects in homologous recombination, including BRCA1- and BRCA2-deficient cancers, have been shown to be sensitive to PARP inhibition. The Weissleder group has synthesized fluorescent and radioactive derivatives of the PARP1/2 inhibitor AZD2281. We hypothesized that fluorescent and radioactive AZD2281-based imaging agents would quantify PARP1/2 expression in vitro and in vivo. To test this hypothesis, a panel of pancreatic ductal adenocarcinoma and ovarian carcinoma cell lines were characterized by immunocytochemistry for PARP1/2 expression. AZD2281-derived fluorescence signal correlated with anti-PARP antibody fluorescence signal strength in vitro. Four cell lines representing a range of PARP1/2 expression levels were then xenografted into Nu/Nu mice. Mice bearing four tumor types each were imaged with AZD2281-derived imaging agents, sacrificed, and their tumors excised for stand-alone imaging and Western blot. AZD2281-derived signal correlated with tumor PARP1/2 expression determined by Western blot, indicating that PARP1/2 expression level is a determinant of fluorescent signal strength and SUVs of AZD2281-derived agents in vivo. These data indicate that AZD2281-derived agents are useful tools for quantifying intracellular PARP1/2 both in vitro and in vivo, which could one day enable prospective identification of tumors likely to respond to PARP inhibitors.

Glioblastoma is the most common primary brain tumor in adults, and it is associated with a dismal prognosis with a median survival of 15 months. Despite treatment with chemotherapy, radiation therapy and surgery, patients inevitably have disease recurrence. Bevacizumab is a monoclonal humanized antibody that inhibits vascular endothelial growth factor signaling, and it has been shown to be effective in recurrent glioblastoma with respect to prolonging progression-free survival (PFS). The use of bevacizumab and other anti-angiogenic agents in recurrent glioblastoma have created novel challenges in interpreting magnetic resonance imaging (MRI) of patients. Furthermore, since only some patients appear to have a durable benefit from bevacizumab, there is a need for imaging biomarkers that can reliably identify this subgroup of patients. Partly due to the challenges created by anti-angiogenic agents, the Response Assessment in Neuro-Oncology (RANO) was proposed to address some of the limitations with traditional response assessment criteria. In the first part of this project, we attempted to validate the RANO criteria by performing a comparative analysis of the RANO criteria vs. the Macdonald criteria using imaging from the phase II BRAIN trial. As we hypothesized, the RANO criteria yielded a significantly decreased PFS by identifying a subset of patients who had progression of nonenhancing tumor evident on T2-weighted imaging. Additionally, response and progression as defined by the RANO criteria correlated with subsequent overall survival (OS) in landmark analyses. While this supports the implementation of RANO criteria for response assessment in glioma clinical trials, future research will be necessary to further improve response assessment by incorporating advanced techniques such as volumetric anatomic assessment, perfusion-weighted MR (PWI-MR), diffusion-weighted MR (DWI-MR), MR spectroscopy (MRS) and positron emission tomography (PET). Advanced imaging techniques are becoming increasingly recognized for their ability to provide objective, non-invasive assessment of treatment response but also to serve as predictive and prognostic biomarkers allowing for stratification of patient subgroups with better treatment outcome. In the second part of the project, we attempted to perform volumetric analysis of tumor size based on conventional MRI, as well as a histogram analysis of apparent diffusion coefficients (ADC) derived from diffusion-weighted MRI, to evaluate imaging parameters as predictors for PFS and OS in a single institution database of recurrent glioblastoma patients initiated on bevacizumab. Volumetric percentage change and absolute early post-treatment volume (3-6 weeks after initiation) of enhancing tumor can stratify survival for patients with recurrent glioblastoma receiving bevacizumab therapy. ADC histogram analysis using a multi-component curve-fitting technique within both enhancing and nonenhancing components of tumor prior to the initiation of bevacizumab can also be used to stratify OS in recurrent glioblastoma patients. While prospective studies are necessary to validate findings, future studies will increasingly incorporate multiparametric approaches to elucidate biomarkers that combine the value of conventional MRI with advanced techniques such as DWI-MR, PWI-MR, MRS and PET to obtain better predictors for PFS and OS in recurrent glioblastoma.

The development of improved models of seismic diffraction is assisted by the availability of accurate scattering data. An acoustic scatter-mapping system was developed for the purpose of providing such data rapidly and at low cost. This system uses a source-receiver pair suspended on a trolley over the structure to be mapped. Signal generation, acquisition, processing, and plotting are performed on an AT-compatible microcomputer and a laser printer. The entire process can be performed in an automated manner within five hours, generating scatter-mapping plots in a format familiar to the geophysical industry. The system hardware was similar to those of Hilterman [1] and others referenced by him, but used a controlled source transducer. The available processing power of a microcomputer allowed the use of a 1 to 15 KHz swept-frequency source signal, similar to that used in Vibroseis and Chirp Radar, which is later crosscorrelated with received signal to provide precise scatter-mapping data for the target structure. Several examples of theoretical and experimental acoustic scatter-mappings are provided for comparison. The novelty of this system lies in its use of a swept frequency source signal. While common in the fields of seismology and radar, swept frequency source signals are new to the area of acoustic scatter mapping. When compared to a similar system using a pulsed source signal, this system produces a better controlled source signal of greater energy, resulting in a more useful resultant signal and better mapping characteristics. The system was able to map scattering from features in the target structure smaller than one percent of the crosscorrelated source signal's 37 mm dominant wavelength. / Applied Science, Faculty of / Electrical and Computer Engineering, Department of / Graduate

<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

Photoacoustic (PA) Imaging is an emerging biomedical imaging modality based on the laser-generated ultrasound. The method has unique advantages in providing microvessel structure visualization, neuroimaging, and functional imaging provided by its physical principle. Photoacoustic microscopy (PAM) is one of the PA imaging instruments which provides high resolution and contrast imaging of a near-field target. Relying on the acoustic focusing, Acoustic-resolution PAM (AR-PAM) is capable of reaching a sub-centimeter of penetration depth with sub-millimeter resolution and is optimized for tissue samples and small animals. However, the state-of-art AR-PAMs are large in size and expensive in cost, which hinders its democratization. There are previous researches conducted on reducing the cost by introducing a low-cost optical source or ultrasound acquisition device. Few research has investigated the possibility of modification on actuator design. The total system cost should be further reduced by substituting the translation stage while maintaining the imaging quality. In this research, a delta configuration actuation is introduced to the AR-PAM. The delta-configuration actuation adapted from a low-cost off-the-shelf 3D printer has been implemented in the design. An economical PAM system that integrates the combination of hardware and software enhancement is designed and tested in this research. With the software approach, advanced beamforming methods such as Delay-and-Sum with Coherence Factor (DAS+CF) and Delay-Multiply-and-Sum (DMAS) algorithms are applied to obtaining the high-resolution PA image through 3D reconstruction. The preliminary phantom study demonstrated the applicability of low-cost delta configuration actuators for AR-PAM imaging. The simulation study shows the beamforming algorithms has capability to remove the device precision error and increasing the tolerance. The research suggests that the 3D reconstruction algorithms significantly improve the resolution and contrast of the image quality.