Augmented navigation

Spinal fixation procedures have the inherent risk of causing damage to vulnerable anatomical structures such as the spinal cord, nerve roots, and blood vessels. To prevent complications, several technological aids have been introduced. Surgical navigation is the most widely used, and guides the surgeon by providing the position of the surgical instruments and implants in relation to the patient anatomy based on radiographic images. Navigation can be extended by the addition of a robotic arm to replace the surgeon’s hand to increase accuracy. Another line of surgical aids is tissue sensing equipment, that recognizes different tissue types and provides a warning system built into surgical instruments. All these technologies are under continuous development and the optimal solution is yet to be found. The aim of this thesis was to study the use of Augmented Reality (AR), Virtual Reality (VR), Artificial Intelligence (AI), and tissue sensing technology in spinal navigation to improve precision and prevent surgical errors. The aim of Paper I was to develop and validate an algorithm for automatizing the intraoperative planning of pedicle screws. An AI algorithm for automatic segmentation of the spine, and screw path suggestion was developed and evaluated. In a clinical study of advanced deformity cases, the algorithm could provide correct suggestions for 86% of all pedicles—or 95%, when cases with extremely altered anatomy were excluded. Paper II evaluated the accuracy of pedicle screw placement using a novel augmented reality surgical navigation (ARSN) system, harboring the above-developed algorithm. Twenty consecutively enrolled patients, eligible for deformity correction surgery in the thoracolumbar region, were operated on using the ARSN system. In this cohort, we found a pedicle screw placement accuracy of 94%, as measured according to the Gertzbein grading scale. The primary goal of Paper III was to validate an extension of the ARSN system for placing pedicle screws using instrument tracking and VR. In a porcine cadaver model, it was demonstrated that VR instrument tracking could successfully be integrated with the ARSN system, resulting in pedicle devices placed within 1.7 ± 1.0 mm of the planed path. Paper IV examined the feasibility of a robot-guided system for semi-automated, minimally invasive, pedicle screw placement in a cadaveric model. Using the robotic arm, pedicle devices were placed within 0.94 ± 0.59 mm of the planned path. The use of a semi-automated surgical robot was feasible, providing a higher technical accuracy compared to non-robotic solutions. Paper V investigated the use of a tissue sensing technology, diffuse reflectance spectroscopy (DRS), for detecting the cortical bone boundary in vertebrae during pedicle screw insertions. The technology could accurately differentiate between cancellous and cortical bone and warn the surgeon before a cortical breach. Using machine learning models, the technology demonstrated a sensitivity of 98% [range: 94-100%] and a specificity of 98% [range: 91-100%]. In conclusion, several technological aids can be used to improve accuracy during spinal fixation procedures. In this thesis, the advantages of adding AR, VR, AI and tissue sensing technology to conventional navigation solutions were studied

Augmented reality (AR) for surgical robotic and autonomous systems: State of the art, challenges, and solutions

Despite the substantial progress achieved in the development and integration of augmented reality (AR) in surgical robotic and autonomous systems (RAS), the center of focus in most devices remains on improving end-effector dexterity and precision, as well as improved access to minimally invasive surgeries. This paper aims to provide a systematic review of different types of state-of-the-art surgical robotic platforms while identifying areas for technological improvement. We associate specific control features, such as haptic feedback, sensory stimuli, and human-robot collaboration, with AR technology to perform complex surgical interventions for increased user perception of the augmented world. Current researchers in the field have, for long, faced innumerable issues with low accuracy in tool placement around complex trajectories, pose estimation, and difficulty in depth perception during two-dimensional medical imaging. A number of robots described in this review, such as Novarad and SpineAssist, are analyzed in terms of their hardware features, computer vision systems (such as deep learning algorithms), and the clinical relevance of the literature. We attempt to outline the shortcomings in current optimization algorithms for surgical robots (such as YOLO and LTSM) whilst providing mitigating solutions to internal tool-to-organ collision detection and image reconstruction. The accuracy of results in robot end-effector collisions and reduced occlusion remain promising within the scope of our research, validating the propositions made for the surgical clearance of ever-expanding AR technology in the future

Virtual and Augmented Reality in Medical Education

Virtual reality (VR) and augmented reality (AR) are two contemporary simulation models that are currently upgrading medical education. VR provides a 3D and dynamic view of structures and the ability of the user to interact with them. The recent technological advances in haptics, display systems, and motion detection allow the user to have a realistic and interactive experience, enabling VR to be ideal for training in hands-on procedures. Consequently, surgical and other interventional procedures are the main fields of application of VR. AR provides the ability of projecting virtual information and structures over physical objects, thus enhancing or altering the real environment. The integration of AR applications in the understanding of anatomical structures and physiological mechanisms seems to be beneficial. Studies have tried to demonstrate the validity and educational effect of many VR and AR applications, in many different areas, employed via various hardware platforms. Some of them even propose a curriculum that integrates these methods. This chapter provides a brief history of VR and AR in medicine, as well as the principles and standards of their function. Finally, the studies that show the effect of the implementation of these methods in different fields of medical training are summarized and presented

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

Augmented Reality Ultrasound Guidance in Anesthesiology

Real-time ultrasound has become a mainstay in many image-guided interventions and increasingly popular in several percutaneous procedures in anesthesiology. One of the main constraints of ultrasound-guided needle interventions is identifying and distinguishing the needle tip from needle shaft in the image. Augmented reality (AR) environments have been employed to address challenges surrounding surgical tool visualization, navigation, and positioning in many image-guided interventions. The motivation behind this work was to explore the feasibility and utility of such visualization techniques in anesthesiology to address some of the specific limitations of ultrasound-guided needle interventions. This thesis brings together the goals, guidelines, and best development practices of functional AR ultrasound image guidance (AR-UIG) systems, examines the general structure of such systems suitable for applications in anesthesiology, and provides a series of recommendations for their development. The main components of such systems, including ultrasound calibration and system interface design, as well as applications of AR-UIG systems for quantitative skill assessment, were also examined in this thesis. The effects of ultrasound image reconstruction techniques, as well as phantom material and geometry on ultrasound calibration, were investigated. Ultrasound calibration error was reduced by 10% with synthetic transmit aperture imaging compared with B-mode ultrasound. Phantom properties were shown to have a significant effect on calibration error, which is a variable based on ultrasound beamforming techniques. This finding has the potential to alter how calibration phantoms are designed cognizant of the ultrasound imaging technique. Performance of an AR-UIG guidance system tailored to central line insertions was evaluated in novice and expert user studies. While the system outperformed ultrasound-only guidance with novice users, it did not significantly affect the performance of experienced operators. Although the extensive experience of the users with ultrasound may have affected the results, certain aspects of the AR-UIG system contributed to the lackluster outcomes, which were analyzed via a thorough critique of the design decisions. The application of an AR-UIG system in quantitative skill assessment was investigated, and the first quantitative analysis of needle tip localization error in ultrasound in a simulated central line procedure, performed by experienced operators, is presented. Most participants did not closely follow the needle tip in ultrasound, resulting in 42% unsuccessful needle placements and a 33% complication rate. Compared to successful trials, unsuccessful procedures featured a significantly greater (p=0.04) needle-tip to image-plane distance. Professional experience with ultrasound does not necessarily lead to expert level performance. Along with deliberate practice, quantitative skill assessment may reinforce clinical best practices in ultrasound-guided needle insertions. Based on the development guidelines, an AR-UIG system was developed to address the challenges in ultrasound-guided epidural injections. For improved needle positioning, this system integrated A-mode ultrasound signal obtained from a transducer housed at the tip of the needle. Improved needle navigation was achieved via enhanced visualization of the needle in an AR environment, in which B-mode and A-mode ultrasound data were incorporated. The technical feasibility of the AR-UIG system was evaluated in a preliminary user study. The results suggested that the AR-UIG system has the potential to outperform ultrasound-only guidance

Augmented reality for computer assisted orthopaedic surgery

In recent years, computer-assistance and robotics have established their presence in operating theatres and found success in orthopaedic procedures. Benefits of computer assisted orthopaedic surgery (CAOS) have been thoroughly explored in research, finding improvements in clinical outcomes, through increased control and precision over surgical actions. However, human-computer interaction in CAOS remains an evolving field, through emerging display technologies including augmented reality (AR) – a fused view of the real environment with virtual, computer-generated holograms. Interactions between clinicians and patient-specific data generated during CAOS are limited to basic 2D interactions on touchscreen monitors, potentially creating clutter and cognitive challenges in surgery. Work described in this thesis sought to explore the benefits of AR in CAOS through: an integration between commercially available AR and CAOS systems, creating a novel AR-centric surgical workflow to support various tasks of computer-assisted knee arthroplasty, and three pre–clinical studies exploring the impact of the new AR workflow on both existing and newly proposed quantitative and qualitative performance metrics. Early research focused on cloning the (2D) user-interface of an existing CAOS system onto a virtual AR screen and investigating any resulting impacts on usability and performance. An infrared-based registration system is also presented, describing a protocol for calibrating commercial AR headsets with optical trackers, calculating a spatial transformation between surgical and holographic coordinate frames. The main contribution of this thesis is a novel AR workflow designed to support computer-assisted patellofemoral arthroplasty. The reported workflow provided 3D in-situ holographic guidance for CAOS tasks including patient registration, pre-operative planning, and assisted-cutting. Pre-clinical experimental validation on a commercial system (NAVIO®, Smith & Nephew) for these contributions demonstrates encouraging early-stage results showing successful deployment of AR to CAOS systems, and promising indications that AR can enhance the clinician’s interactions in the future. The thesis concludes with a summary of achievements, corresponding limitations and future research opportunities.Open Acces

Augmented Reality in Minimally Invasive Surgery

In the last 15 years Minimally Invasive Surgery, with techniques such as laparoscopy or endoscopy, has become very important and research in this field is increasing since these techniques provide the surgeons with less invasive means of reaching the patient’s internal anatomy and allow for entire procedures to be performed with only minimal trauma to the patient. The advantages of the use of this surgical method are evident for patients because the possible trauma is reduced, postoperative recovery is generally faster and there is less scarring. Despite the improvement in outcomes, indirect access to the operation area causes restricted vision, difficulty in hand-eye coordination, limited mobility handling instruments, two-dimensional imagery with a lack of detailed information and a limited visual field during the whole operation. The use of the emerging Augmented Reality technology shows the way forward by bringing the advantages of direct visualization (which you have in open surgery) back to minimally invasive surgery and increasing the physician's view of his surroundings with information gathered from patient medical images. Augmented Reality can avoid some drawbacks of Minimally Invasive Surgery and can provide opportunities for new medical treatments. After two decades of research into medical Augmented Reality, this technology is now advanced enough to meet the basic requirements for a large number of medical applications and it is feasible that medical AR applications will be accepted by physicians in order to evaluate their use and integration into the clinical workflow. Before seeing the systematic use of these technologies as support for minimally invasive surgery some improvements are still necessary in order to fully satisfy the requirements of operating physicians

Operator independent reliability of direct augmented reality navigated pedicle screw placement and rod bending

Background AR based navigation of spine surgeries may not only provide accurate surgical execution but also operator independency by compensating for potential skill deficits. “Direct” AR-navigation, namely superposing trajectories on anatomy directly, have not been investigated regarding their accuracy and operator's dependence. Purpose of this study was to prove operator independent reliability and accuracy of both AR assisted pedicle screw navigation and AR assisted rod bending in a cadaver setting. Methods Two experienced spine surgeons and two biomedical engineers (laymen) performed independently from each other pedicle screw instrumentations from L1-L5 in a total of eight lumbar cadaver specimens (20 screws/operator) using a fluoroscopy-free AR based navigation method. Screw fitting rods from L1 to S2-Ala-Ileum were bent bilaterally using an AR based rod bending navigation method (4 rods/operator). Outcome measures were pedicle perforations, accuracy compared to preoperative plan, registration time, navigation time, total rod bending time and operator's satisfaction for these procedures. Results 97.5% of all screws were safely placed (<2 mm perforation), overall mean deviation from planned trajectory was 6.8±3.9°, deviation from planned entry point was 4±2.7 mm, registration time per vertebra was 2:25 min (00:56 to 10:00 min), navigation time per screw was 1:07 min (00:15 to 12:43 min) rod bending time per rod was 4:22 min (02:07 to 10:39 min), operator's satisfaction with AR based screw and rod navigation was 5.38±0.67 (1 to 6, 6 being the best rate). Comparison of surgeons and laymen revealed significant difference in navigation time (1:01 min; 00:15 to 3:00 min vs. 01:37 min; 00:23 to 12:43 min; p = 0.004, respectively) but not in pedicle perforation rate. Conclusions Direct AR based screw and rod navigation using a surface digitization registration technique is reliable and independent of surgical experience. The accuracy of pedicle screw insertion in the lumbar spine is comparable with the current standard techniques