Early detection of pancreatic cancer:the juicy details

Pancreatic cancer is a lethal disease, for which timely detection and early surgical resection provide the only chance of cure. In individuals with an increased risk of developing pancreatic cancer (high-risk individuals), including those with a hereditary predisposition or neoplastic pancreatic cyst, surveillance may lead to earlier detection and improved survival. However, it is debatable whether these benefits weigh up to its drawbacks, such as patient anxiety, harm by overtreatment and increased healthcare expenses.While malignant transformation is difficult to identify with current imaging modalities, (cancer) cells constantly shed various materials to surrounding tissues. We postulate that measuring these substances in blood and pancreatic juice may serve as indicators for high-grade dysplasia or early-stage cancer. The detection of a biomarker signature in blood and pancreatic juice may stratify high-risk individuals by cancer risk and bring forth a surveillance program with tailored intervals and modalities. The ultimate goal of such a marker panel is to detect pancreatic cancer at a curable stage, while minimizing surveillance-related harms.This thesis critically appraises current recommendations for pancreas surveillance (PART I) and evaluates the potential of biomarker analysis in blood and pancreatic juice (PART II).<br/

Liver Segmentation and its Application to Hepatic Interventions

The thesis addresses the development of an intuitive and accurate liver segmentation approach, its integration into software prototypes for the planning of liver interventions, and research on liver regeneration. The developed liver segmentation approach is based on a combination of the live wire paradigm and shape-based interpolation. Extended with two correction modes and integrated into a user-friendly workflow, the method has been applied to more than 5000 data sets. The combination of the liver segmentation with image analysis of hepatic vessels and tumors allows for the computation of anatomical and functional remnant liver volumes. In several projects with clinical partners world-wide, the benefit of the computer-assisted planning was shown. New insights about the postoperative liver function and regeneration could be gained, and most recent investigations into the analysis of MRI data provide the option to further improve hepatic intervention planning

Meta-analytic approaches for summarising and comparing the accuracy of medical tests

Medical tests are essential for patient care. Evidence-based assessment of the relative accuracy of competing diagnostic tests informs clinical and policy decision making. This thesis addresses questions centred on assessing the reliability and transparency of evidence from systematic reviews and meta-analyses of comparative test accuracy, including validity of meta-analytic methods. Case studies were used to highlight key methodological issues, and provided rationale and context for the thesis. Published systematic reviews of multiple tests were identified and used to provide a descriptive survey of recent practice. Availability of comparative accuracy studies and differences between meta-analyses of direct (head-to-head) and indirect (between-study) comparisons were assessed. Comparative meta-analysis methods were reviewed and those deemed statistically robust were empirically evaluated. Using simulation, performance of hierarchical methods for meta-analysis of a single test was investigated in challenging scenarios (e.g. few studies or sparse data) and implications for test comparisons were considered. Poor statistical methods and incomplete reporting threatens the reliability of comparative reviews. Differences exist between direct and indirect comparisons but direct comparisons were seldom feasible because comparative studies were unavailable. Furthermore, inappropriate use of meta-analytic methods generated misleading results and conclusions. Therefore, recommendations for use of valid methods and a reporting checklist were developed

Anti-apoptotic proteins and cholangiocarcinoma

Cholangiocarcinoma is refractory to treatment by chemotherapy and radiotherapy, which exert their effects on tumour cell growth mainly through the induction of apoptosis. The factors responsible for the poor response of this disease to the apoptosis inducing effect of chemotherapy and radiotherapy are unknown. Members of the Bcl-2 family of proteins play a central role as intracellular regulators of apoptosis. In vitro and in vivo studies have identified that in certain malignancies the expression by tumour cells of these mitochondrial targeting antiapoptotic proteins provide a survival advantage to these cells. The expression of these proteins by cancer cells may also reduce their response to cytotoxic therapy. The hypothesis of this thesis is that resistance to apoptosis may be one of the factors responsible for the poor response of cholangiocarcinoma to treatment, which may be a consequence of mitochondrial targeting antiapoptotic proteins. In the first section of the study, the expression of the antiapoptotic proteins Bcl-2, Mcl-l and BC1-XL was examined in 30 resected cases of cholangiocarcinoma, and 3 human cholangiocarcinoma cell lines using immunohistochemical and immunofluorescent techniques. In all the cholangiocarcinoma specimens examined, Mcl-l and BC1-XL proteins were co- expressed by the majority of the malignant cell population. Bcl-2 protein was not however detected in any of the specimens. This confirmed that antiapoptotic proteins are expressed by cholangiocarcinoma cells but provided no information on their biological effects. The second section analysed the kinetics of apoptosis in human cholangiocarcinoma cells after exposure to the therapeutic agents chemotherapy. X-ray and also UV irradiation to test the hypothesis that cholangiocarcinoma cells are resistant to cytotoxic therapy induced apoptosis. Human cholangiocarcinoma cell lines were incubated with various concentrations of chemotherapy drug or exposed to various doses of radiotherapy. The apoptotic responses were then monitored over a 96 hour period post treatment and then dose response graphs constucted. Cholangiocarcinoma cells were found to be resistant in vitro to chemotherapy and radiotherapy induced apoptosis. Finally, Pklll95 and diamide, drugs which target the mitochondria and functionally counteract antiapoptotic Bcl-2 proteins, were used to test the hypothesis that the inhibition of antiapoptotic proteins can increase the sensivity of cholangiocarcinoma cells to therapy. Experiments were carried out both in vitro and in vivo (xenografts on SCID/NOD mice). This study confirmed that in the presence of the Bcl-2 antagonists cholangiocarcinoma cell apoptosis was increased following chemotherapy and radiotherapy. This demonstrates for the first time an association between the expression of antiapoptotic proteins BC1-XL and Mcl-l and the susceptibility of cholangiocarcinoma cells to apoptosis. The work contained in this thesis demonstrates that human cholangiocarcinoma cells express the antiapoptotic proteins Mcl-l and BC1-XL and are resistant to chemotherapy and radiotherapy induced apoptosis. Antagonising the function of these proteins increases the sensitivity to both chemotherapy and radiotherapy in both cell cultures and an animal model. Inhibitors of the antiapoptotic proteins should be further investigated for their use in conjunction with conventional cytotoxic therapy for the treatment of CCA and may be of value in the treatment of other cancers

Automatic Pancreas Segmentation and 3D Reconstruction for Morphological Feature Extraction in Medical Image Analysis

The development of highly accurate, quantitative automatic medical image segmentation techniques, in comparison to manual techniques, remains a constant challenge for medical image analysis. In particular, segmenting the pancreas from an abdominal scan presents additional difficulties: this particular organ has very high anatomical variability, and a full inspection is problematic due to the location of the pancreas behind the stomach. Therefore, accurate, automatic pancreas segmentation can consequently yield quantitative morphological measures such as volume and curvature, supporting biomedical research to establish the severity and progression of a condition, such as type 2 diabetes mellitus. Furthermore, it can also guide subject stratification after diagnosis or before clinical trials, and help shed additional light on detecting early signs of pancreatic cancer. This PhD thesis delivers a novel approach for automatic, accurate quantitative pancreas segmentation in mostly but not exclusively Magnetic Resonance Imaging (MRI), by harnessing the advantages of machine learning and classical image processing in computer vision. The proposed approach is evaluated on two MRI datasets containing 216 and 132 image volumes, achieving a mean Dice similarity coefficient (DSC) of 84:1 4:6% and 85:7 2:3% respectively. In order to demonstrate the universality of the approach, a dataset containing 82 Computer Tomography (CT) image volumes is also evaluated and achieves mean DSC of 83:1 5:3%. The proposed approach delivers a contribution to computer science (computer vision) in medical image analysis, reporting better quantitative pancreas segmentation results in comparison to other state-of-the-art techniques, and also captures detailed pancreas boundaries as verified by two independent experts in radiology and radiography. The contributions’ impact can support the usage of computational methods in biomedical research with a clinical translation; for example, the pancreas volume provides a prognostic biomarker about the severity of type 2 diabetes mellitus. Furthermore, a generalisation of the proposed segmentation approach successfully extends to other anatomical structures, including the kidneys, liver and iliopsoas muscles using different MRI sequences. Thus, the proposed approach can incorporate into the development of a computational tool to support radiological interpretations of MRI scans obtained using different sequences by providing a “second opinion”, help reduce possible misdiagnosis, and consequently, provide enhanced guidance towards targeted treatment planning

Radiological perspective of the formation of pressure ulcers - a comparison of pressure and experience on two imaging surfaces

Introduction: Pressure ulcers are a high cost, high volume issue for health and medical care providers, affecting patients’ recovery and psychological wellbeing. The current research of pressure on support surfaces as a risk factor in the development of pressure ulcers is not relevant to the specialised, controlled environment of the radiological setting. Method: 38 healthy participants aged 19-51 were positioned supine on two different imaging surfaces (X-ray Table & Mattressed Table). Interface pressure data was acquired using the XSENSOR pressure mapping over a time of 2073 minutes, preceded by 6 minutes settling time to reduce measurement error. Qualitative data regarding participants’ opinion of pain and comfort was recorded using a questionnaire. Data analysis was performed using SPSS 22. Results: Data was collected from 30 participants aged 19 to 51 (mean 25.77, SD 7.72), BMI from 18.7 to 33.6 (mean 24.12, SD 3.29), for both imaging surfaces, following eight participant exclusions. Total average pressure, average pressure for jeopardy areas (head, sacrum & heels) and peak pressure for jeopardy areas were calculated as interface pressure in mmHg. Qualitative data showed that a significant difference (P<0.05) in experiences of pain and discomfort between the two surfaces. A significant difference is seen in average pressure between the two surfaces. Conclusion: Pain and comfort data also show a significant difference between the surfaces. All findings support the proposal for further investigation into the effects of radiological surfaces and overlays as a risk factor for the formation of pressure ulcers