Dynamic Contrast Enhanced Computed Tomography Measurement of Perfusion in Hepatic Cancer

ABSTRACT In recent years, the incidence and mortality rate for hepatocellular carcinoma (HCC) have increased due to the emergence of hepatitis B, C and other diseases that cause cirrhosis. The progression from cirrhosis to HCC is characterized by abnormal vascularization and by a shift from a venous to an arterial blood supply. A knowledge of HCC vascularity which is manifested as alterations in liver blood flow may distinguish among different stages of liver disease and can be used to monitor response to treatment. Unfortunately, conventional diagnostic imaging techniques lack the ability to accurately quantify HCC vascularity. The purpose of this thesis was to validate and assess the diagnostic capabilities of dynamic contrast enhanced computed tomography (DCE-CT) and perfusion software designed to measure hepatic perfusion. Chapter 2 described a study designed to evaluate the accuracy and precision of hepatic perfusion measurement. The results showed a strong correlation between hepatic artery blood flow measurement with DCE-CT and radioactive microspheres under steady state in a rabbit model for HCC (VX2 carcinoma). Using repeated measurements and Monte Carlo simulations, DCE-CT perfusion measurements were found to be precise; with the highest precision in the tumor rim. In Chapter 3, we used fluorine-18 fluoro-2-deoxy-D-glucose (FDG) positron emission tomography and DCE-CT perfusion to determined an inverse correlation between glucose utilization and tumor blood flow; with an R of 0.727 (P \u3c 0.05). This suggests a limited supply of oxygen (possibly hypoxia) and that the tumor cells were surviving via anaerobic glycolysis. in In Chapter 4, hepatic perfusion data showed that thalidomide caused a reduction of tumor perfusion in the responder group during the first 8 days after therapy, P \u3c 0.05; while perfusion in the partial responder and control group remained unchanged, P \u3e 0.05. These changes were attributed to vascular remodeling and maturation resulting in a more functional network of endothelial tubes lined with pericytes. The results of this thesis demonstrate the accuracy and precision of DCE-CT hepatic perfusion measurements. It also showed that DCE-CT perfusion has the potential to enhance the functional imaging ability of hybrid PET/CT scanners and evaluate the efficacy of anti-angiogenesis therapy

Computer assisted analysis of contrast enhanced ultrasound images for quantification in vascular diseases

Contrast enhanced ultrasound (CEUS) with microbubble contrast agents has shown great potential in imaging microvasculature, quantifying perfusion and hence detecting vascular diseases. However, most existing perfusion quantification methods based on image intensity, and are susceptible to confounding factors such as attenuation artefacts. Improving reproducibility is also a key challenge to clinical translation. Therefore, this thesis aims at developing attenuation correction and quantification techniques in CEUS with applications for detection and quantification of microvascular flow / perfusion. Firstly, a technique for automatic correction of attenuation effects in vascular imaging was developed and validated on a tissue mimicking phantom. The application of this technique to studying contrast enhancement of carotid adventitial vasa vasorum as a biomarker of radiation-induced atherosclerosis was demonstrated. The results showed great potential in reducing attenuation artefact and improve quantification in CEUS of carotid arteries. Furthermore, contrast intensity was shown to significantly increase in irradiated carotid arteries and could be a useful imaging biomarker for radiation-induced atherosclerosis. Secondly, a robust and automated tool for quantification of microbubble identification in CEUS image sequences using a temporal and spatial analysis was developed and validated on a flow phantom. The application of this technique to evaluate human musculoskeletal microcirculation with contrast enhanced ultrasound was demonstrated. The results showed an excellent accuracy and repeatability in quantifying active vascular density. It has great potential for clinical translation in the assessment of lower limb perfusion. Finally, a new bubble activity identification and quantification technique based on differential intensity projection in CEUS was developed and demonstrated with an in-vivo study, and applied to the quantification of intraplaque neovascularisation in an irradiated carotid artery of patients who were previously treated for head and neck cancer. The results showed a significantly more specific identification of bubble signals and had good agreement between the differential intensity-based technique and clinical visual assessment. This technique has potential to assist clinicians to diagnose and monitor intraplque neovascularisation.Open Acces

A non-invasive image based system for early diagnosis of prostate cancer.

Prostate cancer is the second most fatal cancer experienced by American males. The average American male has a 16.15% chance of developing prostate cancer, which is 8.38% higher than lung cancer, the second most likely cancer. The current in-vitro techniques that are based on analyzing a patients blood and urine have several limitations concerning their accuracy. In addition, the prostate Specific Antigen (PSA) blood-based test, has a high chance of false positive diagnosis, ranging from 28%-58%. Yet, biopsy remains the gold standard for the assessment of prostate cancer, but only as the last resort because of its invasive nature, high cost, and potential morbidity rates. The major limitation of the relatively small needle biopsy samples is the higher possibility of producing false positive diagnosis. Moreover, the visual inspection system (e.g., Gleason grading system) is not quantitative technique and different observers may classify a sample differently, leading to discrepancies in the diagnosis. As reported in the literature that the early detection of prostate cancer is a crucial step for decreasing prostate cancer related deaths. Thus, there is an urgent need for developing objective, non-invasive image based technology for early detection of prostate cancer. The objective of this dissertation is to develop a computer vision methodology, later translated into a clinically usable software tool, which can improve sensitivity and specificity of early prostate cancer diagnosis based on the well-known hypothesis that malignant tumors are will connected with the blood vessels than the benign tumors. Therefore, using either Diffusion Weighted Magnetic Resonance imaging (DW-MRI) or Dynamic Contrast Enhanced Magnetic Resonance Imaging (DCE-MRI), we will be able to interrelate the amount of blood in the detected prostate tumors by estimating either the Apparent Diffusion Coefficient (ADC) in the prostate with the malignancy of the prostate tumor or perfusion parameters. We intend to validate this hypothesis by demonstrating that automatic segmentation of the prostate from either DW-MRI or DCE-MRI after handling its local motion, provides discriminatory features for early prostate cancer diagnosis. The proposed CAD system consists of three majors components, the first two of which constitute new research contributions to a challenging computer vision problem. The three main components are: (1) A novel Shape-based segmentation approach to segment the prostate from either low contrast DW-MRI or DCE-MRI data; (2) A novel iso-contours-based non-rigid registration approach to ensure that we have voxel-on-voxel matches of all data which may be more difficult due to gross patient motion, transmitted respiratory effects, and intrinsic and transmitted pulsatile effects; and (3) Probabilistic models for the estimated diffusion and perfusion features for both malignant and benign tumors. Our results showed a 98% classification accuracy using Leave-One-Subject-Out (LOSO) approach based on the estimated ADC for 30 patients (12 patients diagnosed as malignant; 18 diagnosed as benign). These results show the promise of the proposed image-based diagnostic technique as a supplement to current technologies for diagnosing prostate cancer

Quantification of tumour heterogenity in MRI

Cancer is the leading cause of death that touches us all, either directly or indirectly. It is estimated that the number of newly diagnosed cases in the Netherlands will increase to 123,000 by the year 2020. General Dutch statistics are similar to those in the UK, i.e. over the last ten years, the age-standardised incidence rate1 has stabilised at around 355 females and 415 males per 100,000. Figure 1 shows the cancer incidence per gender. In the UK, the rise in lifetime risk of cancer is more than one in three and depends on many factors, including age, lifestyle and genetic makeup

Signal Processing Methods for Quantitative Power Doppler Microvascular Angiography

Operator-dependent instrument settings and the likelihood of image artifacts are two challenges for reliably using three-dimensional (3-D) power Doppler angiography in flow depiction and quantification applications. To address the operator-dependent settings challenge, an automated method for wall filter cut-off selection, the wall filter selection curve (WFSC) method, was developed using flow-phantom images. The flow-phantom WFSCs guided the development of a theoretical signal model relating color pixel density (CPD) and wall filter cut-off frequency. Simulations using the theoretical model were used to define criteria for the WFSC method to be applied to unprocessed power Doppler signals from 3-D vasculature. The adapted WFSC method was combined with a 3-D skeletonization and vessel network reconstruction method to present a two-stage processing method aimed at improving vascular detection, visualization and quantification. The two-stage method was evaluated using two in vivo models; a murine tumor model was used to test the performance of the method in a flow quantification application and a chick embryo chorioallantoic membrane (CAM) model was used to evaluate the method’s value for flow depiction applications. Applying the WFSC method to flow-phantom images improved vessel delineation and vascular quantification to within 3% of the vascular volume fraction of the phantom. Criteria for the WFSC method from the simulations were to assess at least 100 cut-off frequencies and that the CPD variability should be less than 5% to ensure quantification accuracy. Large variations in the cut-off frequency selected using the WFSC among images acquired at different time points and across different animals in the murine tumor model signified the relevance of spatially and temporally adjusting the cut-off frequency. The two-stage method improved visualization of the vascular network and significantly reduced artifacts in both the tumor and CAM models in comparison to images using conventional Doppler processing. In the CAM model, vessel diameters measured in two-stage processed images were more accurate than measurements in images exported from a commercial scanner. The proposed signal processing methods increase accuracy and robustness of qualitative and quantitative studies using 3-D power Doppler angiography to assess vascular networks for flow depiction and quantification

Using Computed Tomography Perfusion to Evaluate the Blood-Brain-Barrier and Blood-Tumor-Barrier Response following Focused Ultrasound Sonication with Microbubble Administration

The blood-brain-barrier (BBB) is the single most limiting factor in the delivery of neurotherapeutics into the brain. Focused ultrasound sonication combined with intravenous microbubble administration (FUSwMB) is a novel technique that can transiently disrupt the BBB, with minimal vascular or tissue damage, allowing for localized drug delivery over the targeted region. The goals of this thesis are to: 1) use computed tomography (CT) perfusion to measure the permeability surface area product (PS) following USwMB in normal rabbits with an intact BBB, and 2) to evaluate the blood-tumor-barrier (BTB) PS response following FUSwMB in a C6 rat glioma model

Quantitative analysis of the focused ultrasound-induced blood-brain barrier opening with applications in neurodegenerative disorders

The blood-brain barrier poses a formidable impediment to the treatment of adult-onset neurodegenerative disorders, by prevention of most drugs from gaining access to the brain parenchyma. Focused ultrasound (FUS), in conjunction with systemically administered microbubbles, has been shown to open the blood-brain barrier (BBB) locally, reversibly and non invasively both in rodents and in non-human-primates. Initially, we demonstrate a monotonic increase of the BBB opening volume with close to normal incidence angle, detectable by diffusion tensor imaging; the employed contrast-free magnetic resonance protocol that revealed the anisotropic nature of the diffusion gradient. Implementation of this optimized BBB opening technique in Parkinsonian mice, coupled with the administration of trophic growth factors, induced restorative effects in the dopaminergic neurons, the main cellular target of the pathological process in Parkinson’s disease. The immune response initiated by the FUS-induced BBB disruption has been proven pivotal in reducing proteinaceous aggregates from the brain through the activation of a gliosis cascade. Therefore, we investigated this immunomodulatory effect in Alzheimer’s disease. The neuropathological hallmarks of Alzheimer’s disease include aggregation of amyloid beta into plaques and accumulation of tau protein into neurofibrillary tangles. Tau pathology correlates well with impaired neuronal activity and dementia and was found to be attenuated after the application of ultrasound that correlated with increased microglia activity. Given the beneficial effect of this methodology on the Alzheimer’s pathologies when studied separately, we explored the application of FUS in brains subjected concurrently to amyloidosis and tau phosphorylation. Our findings indicate the reduction of tau protein and decrease in the amyloid load from brains treated with ultrasound, accompanied by spatial memory improvement. Overall, in this dissertation, we established an optimized targeting and detection protocol, pre-clinical implementation of which confirmed its ameliorative effects as a drug-delivery adjuvant or an immune response stimulant. These preclinical findings support the immense potential of such a methodology that significantly contributes to the treatment of different neurodegenerative disorders curbing their progression