Real-time Prostate Motion Tracking For Robot-assisted Laparoscopic Radical Prostatectomy

Radical prostatectomy surgery (RP) is the gold standard for treatment of localized prostate cancer (PCa). Recently, emergence of minimally invasive techniques such as Laparoscopic Radical Prostatectomy (LRP) and Robot-Assisted Laparoscopic Radical Prostatectomy (RARP) has improved the outcomes for prostatectomy. However, it remains difficult for surgeons to make informed decisions regarding resection margins and nerve sparing since the location of the tumour within the organ is not usually visible in a laparoscopic view. While MRI enables visualization of the salient structures and cancer foci, its efficacy in LRP is reduced unless it is fused into a stereoscopic view such that homologous structures overlap. Registration of the MRI image and peri-operative ultrasound image either via visual manual alignment or using a fully automated registration can potentially be exploited to bring the pre-operative information into alignment with the patient coordinate system at the beginning of the procedure. While doing so, prostate motion needs to be compensated in real-time to synchronize the stereoscopic view with the pre-operative MRI during the prostatectomy procedure. In this thesis, two tracking methods are proposed to assess prostate rigid rotation and translation for the prostatectomy. The first method presents a 2D-to-3D point-to-line registration algorithm to measure prostate motion and translation with respect to an initial 3D TRUS image. The second method investigates a point-based stereoscopic tracking technique to compensate for rigid prostate motion so that the same motion can be applied to the pre-operative images

Optical techniques for 3D surface reconstruction in computer-assisted laparoscopic surgery

One of the main challenges for computer-assisted surgery (CAS) is to determine the intra-opera- tive morphology and motion of soft-tissues. This information is prerequisite to the registration of multi-modal patient-specific data for enhancing the surgeon’s navigation capabilites by observ- ing beyond exposed tissue surfaces and for providing intelligent control of robotic-assisted in- struments. In minimally invasive surgery (MIS), optical techniques are an increasingly attractive approach for in vivo 3D reconstruction of the soft-tissue surface geometry. This paper reviews the state-of-the-art methods for optical intra-operative 3D reconstruction in laparoscopic surgery and discusses the technical challenges and future perspectives towards clinical translation. With the recent paradigm shift of surgical practice towards MIS and new developments in 3D opti- cal imaging, this is a timely discussion about technologies that could facilitate complex CAS procedures in dynamic and deformable anatomical regions

Ultrasound-Augmented Laparoscopy

Laparoscopic surgery is perhaps the most common minimally invasive procedure for many diseases in the abdomen. Since the laparoscopic camera provides only the surface view of the internal organs, in many procedures, surgeons use laparoscopic ultrasound (LUS) to visualize deep-seated surgical targets. Conventionally, the 2D LUS image is visualized in a display spatially separate from that displays the laparoscopic video. Therefore, reasoning about the geometry of hidden targets requires mentally solving the spatial alignment, and resolving the modality differences, which is cognitively very challenging. Moreover, the mental representation of hidden targets in space acquired through such cognitive medication may be error prone, and cause incorrect actions to be performed. To remedy this, advanced visualization strategies are required where the US information is visualized in the context of the laparoscopic video. To this end, efficient computational methods are required to accurately align the US image coordinate system with that centred in the camera, and to render the registered image information in the context of the camera such that surgeons perceive the geometry of hidden targets accurately. In this thesis, such a visualization pipeline is described. A novel method to register US images with a camera centric coordinate system is detailed with an experimental investigation into its accuracy bounds. An improved method to blend US information with the surface view is also presented with an experimental investigation into the accuracy of perception of the target locations in space

Robot Autonomy for Surgery

Autonomous surgery involves having surgical tasks performed by a robot operating under its own will, with partial or no human involvement. There are several important advantages of automation in surgery, which include increasing precision of care due to sub-millimeter robot control, real-time utilization of biosignals for interventional care, improvements to surgical efficiency and execution, and computer-aided guidance under various medical imaging and sensing modalities. While these methods may displace some tasks of surgical teams and individual surgeons, they also present new capabilities in interventions that are too difficult or go beyond the skills of a human. In this chapter, we provide an overview of robot autonomy in commercial use and in research, and present some of the challenges faced in developing autonomous surgical robots

Appearance Modelling and Reconstruction for Navigation in Minimally Invasive Surgery

Minimally invasive surgery is playing an increasingly important role for patient care. Whilst its direct patient benefit in terms of reduced trauma, improved recovery and shortened hospitalisation has been well established, there is a sustained need for improved training of the existing procedures and the development of new smart instruments to tackle the issue of visualisation, ergonomic control, haptic and tactile feedback. For endoscopic intervention, the small field of view in the presence of a complex anatomy can easily introduce disorientation to the operator as the tortuous access pathway is not always easy to predict and control with standard endoscopes. Effective training through simulation devices, based on either virtual reality or mixed-reality simulators, can help to improve the spatial awareness, consistency and safety of these procedures. This thesis examines the use of endoscopic videos for both simulation and navigation purposes. More specifically, it addresses the challenging problem of how to build high-fidelity subject-specific simulation environments for improved training and skills assessment. Issues related to mesh parameterisation and texture blending are investigated. With the maturity of computer vision in terms of both 3D shape reconstruction and localisation and mapping, vision-based techniques have enjoyed significant interest in recent years for surgical navigation. The thesis also tackles the problem of how to use vision-based techniques for providing a detailed 3D map and dynamically expanded field of view to improve spatial awareness and avoid operator disorientation. The key advantage of this approach is that it does not require additional hardware, and thus introduces minimal interference to the existing surgical workflow. The derived 3D map can be effectively integrated with pre-operative data, allowing both global and local 3D navigation by taking into account tissue structural and appearance changes. Both simulation and laboratory-based experiments are conducted throughout this research to assess the practical value of the method proposed

Spatial Orientation in Cardiac Ultrasound Images Using Mixed Reality: Design and Evaluation

Spatial orientation is an important skill in structural cardiac imaging. Until recently, 3D cardiac ultrasound has been visualized on a flat screen by using volume rendering. Mixed reality devices enhance depth perception, spatial awareness, interaction, and integration in the physical world, which can prove advantageous with 3D cardiac ultrasound images. In this work, we describe the design of a system for rendering 4D (3D + time) cardiac ultrasound data as virtual objects and evaluate it for ease of spatial orientation by comparing it with a standard clinical viewing platform in a user study. The user study required eight participants to do timed tasks and rate their experience. The results showed that virtual objects in mixed reality provided easier spatial orientation and morphological understanding despite lower perceived image quality. Participants familiar with mixed reality were quicker to orient in the tasks. This suggests that familiarity with the environment plays an important role, and with improved image quality and increased use, mixed reality applications may perform better than conventional 3D echocardiography viewing systems.publishedVersio

Exploiting Temporal Image Information in Minimally Invasive Surgery

Minimally invasive procedures rely on medical imaging instead of the surgeons direct vision. While preoperative images can be used for surgical planning and navigation, once the surgeon arrives at the target site real-time intraoperative imaging is needed. However, acquiring and interpreting these images can be challenging and much of the rich temporal information present in these images is not visible. The goal of this thesis is to improve image guidance for minimally invasive surgery in two main areas. First, by showing how high-quality ultrasound video can be obtained by integrating an ultrasound transducer directly into delivery devices for beating heart valve surgery. Secondly, by extracting hidden temporal information through video processing methods to help the surgeon localize important anatomical structures. Prototypes of delivery tools, with integrated ultrasound imaging, were developed for both transcatheter aortic valve implantation and mitral valve repair. These tools provided an on-site view that shows the tool-tissue interactions during valve repair. Additionally, augmented reality environments were used to add more anatomical context that aids in navigation and in interpreting the on-site video. Other procedures can be improved by extracting hidden temporal information from the intraoperative video. In ultrasound guided epidural injections, dural pulsation provides a cue in finding a clear trajectory to the epidural space. By processing the video using extended Kalman filtering, subtle pulsations were automatically detected and visualized in real-time. A statistical framework for analyzing periodicity was developed based on dynamic linear modelling. In addition to detecting dural pulsation in lumbar spine ultrasound, this approach was used to image tissue perfusion in natural video and generate ventilation maps from free-breathing magnetic resonance imaging. A second statistical method, based on spectral analysis of pixel intensity values, allowed blood flow to be detected directly from high-frequency B-mode ultrasound video. Finally, pulsatile cues in endoscopic video were enhanced through Eulerian video magnification to help localize critical vasculature. This approach shows particular promise in identifying the basilar artery in endoscopic third ventriculostomy and the prostatic artery in nerve-sparing prostatectomy. A real-time implementation was developed which processed full-resolution stereoscopic video on the da Vinci Surgical System

Characterization of biaxial mechanical properties of rubber and skin

textBreast cancer is one of the most frequently diagnosed cancers affecting women in the United States. An ongoing objective of many research groups is to develop a biomechanical breast model for different applications, ranging from surgical outcome predictions for patients undergoing breast reconstruction surgery, to image registration for planning plastic surgery. Achieving the goal of developing a physics based biomechanical model of the human breast requires the determination of material properties of the various tissues constituting the breast. The objective of this thesis is to develop an appropriate hybrid experimental-numerical technique to enable the calibration of material parameters of skin for different constitutive models (commonly used for skin). The quantification of the material parameters thus obtained validates the bulge test method to be used in testing soft tissue specimens like skin. A bulge test device was custom-built for this work; it consists of a pressure chamber, two digital cameras, and a syringe pump as its main components. The syringe pump provides a constant flow rate of water into the pressure chamber and results in the bulging of specimens with a diameter between 45 mm and 80 mm. Three-dimensional Digital Image Correlation technique is used to obtain full field displacement measurements of the three dimensional shape of the bulge. Tests were performed on commercial rubber sheets of different thickness and on porcine skin specimens; in these tests, the bulge shape was measured at monotonically increasing and decreasing pressure levels, as well as during cyclic loading allowing determination of the deformation and strain fields over the specimen surface. In order to extract the material properties, a hybrid experimental-numerical method was used: the experiment was modeled numerically using the finite element analysis software Abaqus, imposing the commonly used Mooney-Rivlin model for isotropic materials and the Gasser-Ogden-Holzapfel model for anisotropic materials. A comparison between the experimentally measured and numerically simulated bulge shapes was used to determine the optimized material parameters under biaxial loading conditions over a large range of stretch levels.Biomedical Engineerin

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