A comprehensive description of the competencies required for the performance of an ultrasound-guided axillary brachial plexus blockade

We addressed four research questions, each relating to the training and assessment of the competencies associated with the performance of ultrasound-guided axillary brachial plexus blockade (USgABPB). These were: (i) What are the most important determinants of learning of USgABPB? (ii) What is USgABPB? What are the errors most likely to occur when trainees learn to perform this procedure? (iii) How should end-user input be applied to the development of a novel USgABPB simulator? (iv) Does structured simulation based training influence novice learning of the procedure positively? We demonstrated that the most important determinants of learning USgABPB are: (a) Access to a formal structured training programme. (b) Frequent exposure to clinical learning opportunity in an appropriate setting (c) A clinical learning opporunity requires an appropriate patient, trainee and teacher being present at the same time, in an appropriate environment. We carried out a comprehensive description of the procedure. We performed a formal task analysis of USgABPB, identifying (i) 256 specific tasks associated with the safe and effective performance of the procedure, and (ii) the 20 most critical errors likely to occur in this setting. We described a methodology for this and collected data based on detailed, sequential evaluation of prototypes by trainees in anaesthesia. We carried out a pilot randomised control trial assessing the effectiveness of a USgABPB simulator during its development. Our data did not enable us to draw a reliable conclusion to this question; the trail did provide important new learning (as a pilot) to inform future investigation of this question. We believe that the ultimate goal of designing effective simulation-based training and assessment of ultrasound-guided regional anaesthesia is closer to realisation as a result of this work. It remains to be proven if this approach will have a positive impact on procedural performance, and more importantly improve patient outcomes.

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.