AUGMENTED REALITY AND INTRAOPERATIVE C-ARM CONE-BEAM COMPUTED TOMOGRAPHY FOR IMAGE-GUIDED ROBOTIC SURGERY

Minimally-invasive robotic-assisted surgery is a rapidly-growing alternative to traditionally open and laparoscopic procedures; nevertheless, challenges remain. Standard of care derives surgical strategies from preoperative volumetric data (i.e., computed tomography (CT) and magnetic resonance (MR) images) that benefit from the ability of multiple modalities to delineate different anatomical boundaries. However, preoperative images may not reflect a possibly highly deformed perioperative setup or intraoperative deformation. Additionally, in current clinical practice, the correspondence of preoperative plans to the surgical scene is conducted as a mental exercise; thus, the accuracy of this practice is highly dependent on the surgeon’s experience and therefore subject to inconsistencies. In order to address these fundamental limitations in minimally-invasive robotic surgery, this dissertation combines a high-end robotic C-arm imaging system and a modern robotic surgical platform as an integrated intraoperative image-guided system. We performed deformable registration of preoperative plans to a perioperative cone-beam computed tomography (CBCT), acquired after the patient is positioned for intervention. From the registered surgical plans, we overlaid critical information onto the primary intraoperative visual source, the robotic endoscope, by using augmented reality. Guidance afforded by this system not only uses augmented reality to fuse virtual medical information, but also provides tool localization and other dynamic intraoperative updated behavior in order to present enhanced depth feedback and information to the surgeon. These techniques in guided robotic surgery required a streamlined approach to creating intuitive and effective human-machine interferences, especially in visualization. Our software design principles create an inherently information-driven modular architecture incorporating robotics and intraoperative imaging through augmented reality. The system's performance is evaluated using phantoms and preclinical in-vivo experiments for multiple applications, including transoral robotic surgery, robot-assisted thoracic interventions, and cocheostomy for cochlear implantation. The resulting functionality, proposed architecture, and implemented methodologies can be further generalized to other C-arm-based image guidance for additional extensions in robotic surgery

Advanced tracking and image registration techniques for intraoperative radiation therapy

Mención Internacional en el título de doctorIntraoperative electron radiation therapy (IOERT) is a technique used to deliver radiation to the surgically opened tumor bed without irradiating healthy tissue. Treatment planning systems and mobile linear accelerators enable clinicians to optimize the procedure, minimize stress in the operating room (OR) and avoid transferring the patient to a dedicated radiation room. However, placement of the radiation collimator over the tumor bed requires a validation methodology to ensure correct delivery of the dose prescribed in the treatment planning system. In this dissertation, we address three well-known limitations of IOERT: applicator positioning over the tumor bed, docking of the mobile linear accelerator gantry with the applicator and validation of the dose delivery prescribed. This thesis demonstrates that these limitations can be overcome by positioning the applicator appropriately with respect to the patient’s anatomy. The main objective of the study was to assess technological and procedural alternatives for improvement of IOERT performance and resolution of problems of uncertainty. Image-to-world registration, multicamera optical trackers, multimodal imaging techniques and mobile linear accelerator docking are addressed in the context of IOERT. IOERT is carried out by a multidisciplinary team in a highly complex environment that has special tracking needs owing to the characteristics of its working volume (i.e., large and prone to occlusions), in addition to the requisites of accuracy. The first part of this dissertation presents the validation of a commercial multicamera optical tracker in terms of accuracy, sensitivity to miscalibration, camera occlusions and detection of tools using a feasible surgical setup. It also proposes an automatic miscalibration detection protocol that satisfies the IOERT requirements of automaticity and speed. We show that the multicamera tracker is suitable for IOERT navigation and demonstrate the feasibility of the miscalibration detection protocol in clinical setups. Image-to-world registration is one of the main issues during image-guided applications where the field of interest and/or the number of possible anatomical localizations is large, such as IOERT. In the second part of this dissertation, a registration algorithm for image-guided surgery based on lineshaped fiducials (line-based registration) is proposed and validated. Line-based registration decreases acquisition time during surgery and enables better registration accuracy than other published algorithms. In the third part of this dissertation, we integrate a commercial low-cost ultrasound transducer and a cone beam CT C-arm with an optical tracker for image-guided interventions to enable surgical navigation and explore image based registration techniques for both modalities. In the fourth part of the dissertation, a navigation system based on optical tracking for the docking of the mobile linear accelerator to the radiation applicator is assessed. This system improves safety and reduces procedure time. The system tracks the prescribed collimator location to solve the movements that the linear accelerator should perform to reach the docking position and warns the user about potentially unachievable arrangements before the actual procedure. A software application was implemented to use this system in the OR, where it was also evaluated to assess the improvement in docking speed. Finally, in the last part of the dissertation, we present and assess the installation setup for a navigation system in a dedicated IOERT OR, determine the steps necessary for the IOERT process, identify workflow limitations and evaluate the feasibility of the integration of the system in a real OR. The navigation system safeguards the sterile conditions of the OR, clears the space available for surgeons and is suitable for any similar dedicated IOERT OR.La Radioterapia Intraoperatoria por electrones (RIO) consiste en la aplicación de radiación de alta energía directamente sobre el lecho tumoral, accesible durante la cirugía, evitando radiar los tejidos sanos. Hoy en día, avances como los sistemas de planificación (TPS) y la aparición de aceleradores lineales móviles permiten optimizar el procedimiento, minimizar el estrés clínico en el entorno quirúrgico y evitar el desplazamiento del paciente durante la cirugía a otra sala para ser radiado. La aplicación de la radiación se realiza mediante un colimador del haz de radiación (aplicador) que se coloca sobre el lecho tumoral de forma manual por el oncólogo radioterápico. Sin embargo, para asegurar una correcta deposición de la dosis prescrita y planificada en el TPS, es necesaria una adecuada validación de la colocación del colimador. En esta Tesis se abordan tres limitaciones conocidas del procedimiento RIO: el correcto posicionamiento del aplicador sobre el lecho tumoral, acoplamiento del acelerador lineal con el aplicador y validación de la dosis de radiación prescrita. Esta Tesis demuestra que estas limitaciones pueden ser abordadas mediante el posicionamiento del aplicador de radiación en relación con la anatomía del paciente. El objetivo principal de este trabajo es la evaluación de alternativas tecnológicas y procedimentales para la mejora de la práctica de la RIO y resolver los problemas de incertidumbre descritos anteriormente. Concretamente se revisan en el contexto de la radioterapia intraoperatoria los siguientes temas: el registro de la imagen y el paciente, sistemas de posicionamiento multicámara, técnicas de imagen multimodal y el acoplamiento del acelerador lineal móvil. El entorno complejo y multidisciplinar de la RIO precisa de necesidades especiales para el empleo de sistemas de posicionamiento como una alta precisión y un volumen de trabajo grande y propenso a las oclusiones de los sensores de posición. La primera parte de esta Tesis presenta una exhaustiva evaluación de un sistema de posicionamiento óptico multicámara comercial. Estudiamos la precisión del sistema, su sensibilidad a errores cometidos en la calibración, robustez frente a posibles oclusiones de las cámaras y precisión en el seguimiento de herramientas en un entorno quirúrgico real. Además, proponemos un protocolo para la detección automática de errores por calibración que satisface los requisitos de automaticidad y velocidad para la RIO demostrando la viabilidad del empleo de este sistema para la navegación en RIO. Uno de los problemas principales de la cirugía guiada por imagen es el correcto registro de la imagen médica y la anatomía del paciente en el quirófano. En el caso de la RIO, donde el número de posibles localizaciones anatómicas es bastante amplio, así como el campo de trabajo es grande se hace necesario abordar este problema para una correcta navegación. Por ello, en la segunda parte de esta Tesis, proponemos y validamos un nuevo algoritmo de registro (LBR) para la cirugía guiada por imagen basado en marcadores lineales. El método propuesto reduce el tiempo de la adquisición de la posición de los marcadores durante la cirugía y supera en precisión a otros algoritmos de registro establecidos y estudiados en la literatura. En la tercera parte de esta tesis, integramos un transductor de ultrasonido comercial de bajo coste, un arco en C de rayos X con haz cónico y un sistema de posicionamiento óptico para intervenciones guiadas por imagen que permite la navegación quirúrgica y exploramos técnicas de registro de imagen para ambas modalidades. En la cuarta parte de esta tesis se evalúa un navegador basado en el sistema de posicionamiento óptico para el acoplamiento del acelerador lineal móvil con aplicador de radiación, mejorando la seguridad y reduciendo el tiempo del propio acoplamiento. El sistema es capaz de localizar el colimador en el espacio y proporcionar los movimientos que el acelerador lineal debe realizar para alcanzar la posición de acoplamiento. El sistema propuesto es capaz de advertir al usuario de aquellos casos donde la posición de acoplamiento sea inalcanzable. El sistema propuesto de ayuda para el acoplamiento se integró en una aplicación software que fue evaluada para su uso final en quirófano demostrando su viabilidad y la reducción de tiempo de acoplamiento mediante su uso. Por último, presentamos y evaluamos la instalación de un sistema de navegación en un quirófano RIO dedicado, determinamos las necesidades desde el punto de vista procedimental, identificamos las limitaciones en el flujo de trabajo y evaluamos la viabilidad de la integración del sistema en un entorno quirúrgico real. El sistema propuesto demuestra ser apto para el entorno RIO manteniendo las condiciones de esterilidad y dejando despejado el campo quirúrgico además de ser adaptable a cualquier quirófano similar.Programa Oficial de Doctorado en Multimedia y ComunicacionesPresidente: Raúl San José Estépar.- Secretario: María Arrate Muñoz Barrutia.- Vocal: Carlos Ferrer Albiac

Model-Based Iterative Reconstruction in Cone-Beam Computed Tomography: Advanced Models of Imaging Physics and Prior Information

Cone-beam computed tomography (CBCT) represents a rapidly developing imaging modality that provides three-dimensional (3D) volumetric images with sub-millimeter spatial resolution and soft-tissue visibility from a single gantry rotation. CBCT tends to have small footprint, mechanical simplicity, open geometry, and low cost compared to conventional diagnostic CT. Because of these features, CBCT has been used in a variety of specialty diagnostic applications, image-guided radiation therapy (on-board CBCT), and surgical guidance (e.g., C-arm based CBCT). However, the current generation of CBCT systems face major challenges in low-contrast, soft-tissue image quality – for example, in the detection of acute intracranial hemorrhage (ICH), which requires a fairly high level of image uniformity, spatial resolution, and contrast resolution. Moreover, conventional approaches in both diagnostic and image-guided interventions that involve a series of imaging studies fail to leverage the wealth of patient-specific anatomical information available from previous scans. Leveraging the knowledge gained from prior images holds the potential for major gains in image quality and dose reduction. Model-based iterative reconstruction (MBIR) attempts to make more efficient use of the measurement data by incorporating a forward model of physical detection processes. Moreover, MBIR allows incorporation of various forms of prior information into image reconstruction, ranging from image smoothness and sharpness to patient-specific anatomical information. By leveraging such advantages, MBIR has demonstrated improved tradeoffs between image quality and radiation dose in multi-detector CT in the past decade and has recently shown similar promise in CBCT. However, the full potential of MBIR in CBCT is yet to be realized. This dissertation explores the capabilities of MBIR in improving image quality (especially low-contrast, soft-tissue image quality) and reducing radiation dose in CBCT. The presented work encompasses new MBIR methods that: i) modify the noise model in MBIR to compensate for noise amplification from artifact correction; ii) design regularization by explicitly incorporating task-based imaging performance as the objective; iii) mitigate truncation effects in a computationally efficient manner; iv) leverage a wealth of patient-specific anatomical information from a previously acquired image; and v) prospectively estimate the optimal amount of prior image information for accurate admission of specific anatomical changes. Specific clinical challenges are investigated in the detection of acute ICH and surveillance of lung nodules. The results show that MBIR can substantially improve low-contrast, soft-tissue image quality in CBCT and enable dose reduction techniques in sequential imaging studies. The thesis demonstrates that novel MBIR methods hold strong potential to overcome conventional barriers to CBCT image quality and open new clinical applications that would benefit from high-quality 3D imaging