Interventional radiology and the care of the oncology patient.

Interventional Radiology (IR) is occupying an increasingly prominent role in the care of patients with cancer, with involvement from initial diagnosis, right through to minimally invasive treatment of the malignancy and its complications. Adequate diagnostic samples can be obtained under image guidance by percutaneous biopsy and needle aspiration in an accurate and minimally invasive manner. IR techniques may be used to place central venous access devices with well-established safety and efficacy. Therapeutic applications of IR in the oncology patient include local tumour treatments such as transarterial chemo-embolisation and radiofrequency ablation, as well as management of complications of malignancy such as pain, organ obstruction, and venous thrombosis.

Bacteria and tumours: causative agents or opportunistic inhabitants?

Associations between different bacteria and various tumours have been reported in patients for decades. Studies involving characterisation of bacteria within tumour tissues have traditionally been in the context of tumourigenesis as a result of bacterial presence within healthy tissues, and in general, dogma holds that such bacteria are causative agents of malignancy (directly or indirectly). While evidence suggests that this may be the case for certain tumour types and bacterial species, it is plausible that in many cases, clinical observations of bacteria within tumours arise from spontaneous infection of established tumours. Indeed, growth of bacteria specifically within tumours following deliberate systemic administration has been demonstrated for numerous bacterial species at preclinical and clinical levels. We present the available data on links between bacteria and tumours, and propose that besides the few instances in which pathogens are playing a pathogenic role in cancer, in many instances, the prevalent relationship between solid tumours and bacteria is opportunistic rather than causative, and discuss opportunities for exploiting tumour-specific bacterial growth for cancer treatment.

Open-source virtual bronchoscopy for image guided navigation

This thesis describes the development of an open-source system for virtual bronchoscopy used in combination with electromagnetic instrument tracking. The end application is virtual navigation of the lung for biopsy of early stage cancer nodules. The open-source platform 3D Slicer was used for creating freely available algorithms for virtual bronchscopy. Firstly, the development of an open-source semi-automatic algorithm for prediction of solitary pulmonary nodule malignancy is presented. This approach may help the physician decide whether to proceed with biopsy of the nodule. The user-selected nodule is segmented in order to extract radiological characteristics (i.e., size, location, edge smoothness, calcification presence, cavity wall thickness) which are combined with patient information to calculate likelihood of malignancy. The overall accuracy of the algorithm is shown to be high compared to independent experts' assessment of malignancy. The algorithm is also compared with two different predictors, and our approach is shown to provide the best overall prediction accuracy. The development of an airway segmentation algorithm which extracts the airway tree from surrounding structures on chest Computed Tomography (CT) images is then described. This represents the first fundamental step toward the creation of a virtual bronchoscopy system. Clinical and ex-vivo images are used to evaluate performance of the algorithm. Different CT scan parameters are investigated and parameters for successful airway segmentation are optimized. Slice thickness is the most affecting parameter, while variation of reconstruction kernel and radiation dose is shown to be less critical. Airway segmentation is used to create a 3D rendered model of the airway tree for virtual navigation. Finally, the first open-source virtual bronchoscopy system was combined with electromagnetic tracking of the bronchoscope for the development of a GPS-like system for navigating within the lungs. Tools for pre-procedural planning and for helping with navigation are provided. Registration between the lungs of the patient and the virtually reconstructed airway tree is achieved using a landmark-based approach. In an attempt to reduce difficulties with registration errors, we also implemented a landmark-free registration method based on a balanced airway survey. In-vitro and in-vivo testing showed good accuracy for this registration approach. The centreline of the 3D airway model is extracted and used to compensate for possible registration errors. Tools are provided to select a target for biopsy on the patient CT image, and pathways from the trachea towards the selected targets are automatically created. The pathways guide the physician during navigation, while distance to target information is updated in real-time and presented to the user. During navigation, video from the bronchoscope is streamed and presented to the physician next to the 3D rendered image. The electromagnetic tracking is implemented with 5 DOF sensing that does not provide roll rotation information. An intensity-based image registration approach is implemented to rotate the virtual image according to the bronchoscope's rotations. The virtual bronchoscopy system is shown to be easy to use and accurate in replicating the clinical setting, as demonstrated in the pre-clinical environment of a breathing lung method. Animal studies were performed to evaluate the overall system performance.