CT-PET guided target delineation in head and neck cancer and implications for improved outcome

Aim: Fifty percent of patients with squamous cell carcinoma of the Head and Neck develop loco-regional recurrence after treatment. Factors leading to this failure are most likely altered intra-tumoural glucose metabolism and increased hypoxia. Tissue glucose utilisation and the degree of hypoxia can be visualised by CTPET imaging with 18FDG and hypoxic radio-nuclides. This thesis has investigated 18FDG CT-PET guided target volume delineation methods and attempted to validate 64Cu-ATSM as a hypoxic radio-nuclide in patients with squamous cell carcinoma of the Head and Neck. Materials and Methods: Eight patients with locally advanced disease underwent 18FDG CT-PET imaging before and during curative radiotherapy or chemo-radiotherapy. Fixed (SUV cut off and percentage threshold of the SUVmax) and adaptive thresholds were investigated. The functional volumes automatically delineated by these methods and SUVmax were compared at each point, and between thresholds. Four patients with locally advanced disease, two to seven days prior to surgery, underwent 3D dynamic CT-PET imaging immediately after injection of 64Cu- ATSM. Two patients were also imaged 18 hours after injection, and two underwent a dynamic contrast-enhanced CT to evaluate intra-tumoural perfusion. All patients received pimonidazole before surgery. The pimonidazole, GLUT1, CAIX, and HIF1a immuno-histochemical hypoxic fractions were defined. Staining was correlated with the retention pattern of 64Cu-ATSM at 3 time points. Hypoxic target volumes were delineated according to tumour to muscle, blood and background ratios. Results: 18FDG primary and lymph node target volumes significantly reduced with radiation dose by the SUV cut off method and correlated with the reduction in the SUVmax within the volume. Volume reduction was also found between thresholds by the same delineation method. The volumes delineated by the other methods were not significantly reduced (except the lymph node functional volume when defined by the adaptive threshold). 64Cu-ATSM correlated with hypoxic immuno-histochemical staining but not with blood flow. Tumour ratios increased with time after injection, which influenced the delineated hypoxic target volume. Conclusion: Dose-escalated image-guided radiotherapy strategies using these CT-PET guided functional volumes have the potential to improve loco-regional control in patients with squamous cell carcinoma of the Head and Neck. CT-PET 18FDG volume delineation is intricately linked to the method and threshold of delineation and the timing of the imaging. 64Cu-ATSM is promising as a hypoxic radio-nuclide and warrants further investigation

Prognostic radiological variables derived from oesophageal cancer staging investigations

Accurate radiological staging is vital in oesophageal cancer (OC). Radiological staging largely informs risk-stratification, treatment decisions and planning. However, the prognosis of OC remains poor, suggesting that radiological staging must improve. Therefore, the additional value of novel prognostic variables compared to current staging methods was assessed in a large cohort of OC patients managed by a regional upper gastrointestinal cancer network. Radiological-pathological correlation of resected lymph nodes assessed the accuracy of CT, EUS and PET/CT N-stage. The added value of PET-defined variables to predict circumferential resection margin (CRM) involvement was investigated. With EUS use declining, differences in PET and EUS measurements were assessed to understand potential implications for treatment planning should staging PET/CT be performed alone. Validation of two prognostic models; one in patients staged N0 on PET/CT and one incorporating novel PET features, was performed. The accuracy of CT, EUS and PET/CT N-stage was poor (54.5%, 55.4% and 57.1%, respectively) which greatly impacts on patient selection and treatment decisions. EUS continues to play an important role in OC staging, being significantly and independently associated with overall survival (OS;p=0.012) and CRM involvement (p=0.022). PET-defined variables had no additional value for predicting CRM status. The difference between PET and EUS length of disease was statistically significant (p<0.001), increasing the risk of geographical miss (38.1%) had PET/CT been used alone. Three novel PET image features (log (TLG), log(Histogram Energy) and Histogram Kurtosis) were independently associated with OS in the prognostic model. There was a significant OS difference between patient quartiles (p<0.001) in the development and validation cohorts. Incorporation of these image features added prognostic value and improved model performance compared to current staging methods. These significant data demonstrate radiological prognostic variables that add value in OC management and highlight the importance of improved radiological staging

Dynamic Thermal Imaging for Intraoperative Monitoring of Neuronal Activity and Cortical Perfusion

Neurosurgery is a demanding medical discipline that requires a complex interplay of several neuroimaging techniques. This allows structural as well as functional information to be recovered and then visualized to the surgeon. In the case of tumor resections this approach allows more fine-grained differentiation of healthy and pathological tissue which positively influences the postoperative outcome as well as the patient's quality of life. In this work, we will discuss several approaches to establish thermal imaging as a novel neuroimaging technique to primarily visualize neural activity and perfusion state in case of ischaemic stroke. Both applications require novel methods for data-preprocessing, visualization, pattern recognition as well as regression analysis of intraoperative thermal imaging. Online multimodal integration of preoperative and intraoperative data is accomplished by a 2D-3D image registration and image fusion framework with an average accuracy of 2.46 mm. In navigated surgeries, the proposed framework generally provides all necessary tools to project intraoperative 2D imaging data onto preoperative 3D volumetric datasets like 3D MR or CT imaging. Additionally, a fast machine learning framework for the recognition of cortical NaCl rinsings will be discussed throughout this thesis. Hereby, the standardized quantification of tissue perfusion by means of an approximated heating model can be achieved. Classifying the parameters of these models yields a map of connected areas, for which we have shown that these areas correlate with the demarcation caused by an ischaemic stroke segmented in postoperative CT datasets. Finally, a semiparametric regression model has been developed for intraoperative neural activity monitoring of the somatosensory cortex by somatosensory evoked potentials. These results were correlated with neural activity of optical imaging. We found that thermal imaging yields comparable results, yet doesn't share the limitations of optical imaging. In this thesis we would like to emphasize that thermal imaging depicts a novel and valid tool for both intraoperative functional and structural neuroimaging

A comparative evaluation for liver segmentation from spir images and a novel level set method using signed pressure force function

Thesis (Doctoral)--Izmir Institute of Technology, Electronics and Communication Engineering, Izmir, 2013Includes bibliographical references (leaves: 118-135)Text in English; Abstract: Turkish and Englishxv, 145 leavesDeveloping a robust method for liver segmentation from magnetic resonance images is a challenging task due to similar intensity values between adjacent organs, geometrically complex liver structure and injection of contrast media, which causes all tissues to have different gray level values. Several artifacts of pulsation and motion, and partial volume effects also increase difficulties for automatic liver segmentation from magnetic resonance images. In this thesis, we present an overview about liver segmentation methods in magnetic resonance images and show comparative results of seven different liver segmentation approaches chosen from deterministic (K-means based), probabilistic (Gaussian model based), supervised neural network (multilayer perceptron based) and deformable model based (level set) segmentation methods. The results of qualitative and quantitative analysis using sensitivity, specificity and accuracy metrics show that the multilayer perceptron based approach and a level set based approach which uses a distance regularization term and signed pressure force function are reasonable methods for liver segmentation from spectral pre-saturation inversion recovery images. However, the multilayer perceptron based segmentation method requires a higher computational cost. The distance regularization term based automatic level set method is very sensitive to chosen variance of Gaussian function. Our proposed level set based method that uses a novel signed pressure force function, which can control the direction and velocity of the evolving active contour, is faster and solves several problems of other applied methods such as sensitivity to initial contour or variance parameter of the Gaussian kernel in edge stopping functions without using any regularization term

Coupled Shape Models for the Diagnosis of Organ Motion Restriction

Annähernd 30% der weltweiten Todesfälle sind auf Erkrankungen des Herzens und der Lunge zurückzuführen, wobei die meisten dieser Erkrankungen während ihres Verlaufs die Mobilität des betroffenen Organs verändern. Viele dieser To-desfälle könnten durch eine frühzeitige Erkennung und Behandlung der Erkran-kung vermieden werden. Deshalb wurden im Zuge dieser Arbeit Methoden ent-wickelt, um aus Segmentierungen von dynamischen Magnetresonanztomogra-phie-Daten quantitative Kennzahlen für die funktionale Analyse der Herz- und Lungenbewegung zu generieren. Ein automatisiertes Segmentierungsverfahren basierend auf gekoppelten Formmodellen wurde entwickelt, welches wechsel-seitige Informationen der Form und Geometrie mehrerer korrelierter Objekte mit einbezieht, und somit 40% bessere Ergebnisse im Vergleich zur Verwendung einzelner Modelle erzielte. Im Fall des Herzens wurde ein Volumenberechnungs-fehler von unter 13% erreicht, was in der Größenordnung der Interobserver-Variabilität liegt. Für die Lunge konnte ein Volumenfehler von unter 70ml gezeigt werden. Aus den Segmentierungsergebnissen wurden funktionale Parameter der lokalen Organdynamik abgeleitet und visualisiert, die gegen konventionelle Diag-nosemethoden evaluiert wurden und dabei gute Übereinstimmung zeigen, dar-über hinaus jedoch eine lokal und regionale Mobilitätscharakterisierung erlau-ben

Automated Quantification of Atherosclerosis in CTA of Carotid Arteries

How is the human body built and how does it function? What are the causes of disease, and where is disease located? Throughout the history of mankind these questions were answered by the use of invasive methods that included the “opening” of the human body, mainly cadavers. Thanks to these invasive techniques the first precise and complete anatomy works started to appear in the 16th century. The most influential works were published by Leonardo da Vinci and the anatomist and physician Andreas Vesalius. The discovery of X-rays in 1895, and their use for medical applications, introduced a new era, in which non-invasive imaging of the functioning human body became feasible. Nowadays, medical imaging includes many different imaging modalities, such as X-ray, computed tomography (CT), magnetic resonance imaging (MRI), ultrasound (US), nuclear and optical imaging, and has become an indispensable diagnostic tool for a wide range of applications. Initially, the application of medical imaging focused on the visualization of anatomy and on the detection and localization of disease. However, with the development of different modalities it has evolved into a much more versatile tool providing important information on e.g. physiology and organ function, biochemistry and metabolism using nuclear imaging (mainly positron emission tomography (PET) imaging), molecular and processes on the molecular and cellular level using molecular imaging techniques