Towards a First-Person Perspective Mixed Reality Guidance System for Needle Interventions

While ultrasound (US) guidance has been used during central venous catheterization to reduce complications, including the puncturing of arteries, the rate of such problems remains non-negligible. To further reduce complication rates, mixed-reality systems have been proposed as part of the user interface for such procedures. We demonstrate the use of a surgical navigation system that renders a calibrated US image, and the needle and its trajectory, in a common frame of reference. We compare the effectiveness of this system, whereby images are rendered on a planar monitor and within a head-mounted display (HMD), to the standard-of-care US-only approach, via a phantom-based user study that recruited 31 expert clinicians and 20 medical students. These users performed needle-insertions into a phantom under the three modes of visualization. The success rates were significantly improved under HMD-guidance as compared to US-guidance, for both expert clinicians (94% vs. 70%) and medical students (70% vs. 25%). Users more consistently positioned their needle closer to the center of the vessel’s lumen under HMD-guidance compared to US-guidance. The performance of the clinicians when interacting with this monitor system was comparable to using US-only guidance, with no significant difference being observed across any metrics. The results suggest that the use of an HMD to align the clinician’s visual and motor fields promotes successful needle guidance, highlighting the importance of continued HMD-guidance research

Recent Developments and Future Challenges in Medical Mixed Reality

As AR technology matures, we have seen many applicationsemerge in entertainment, education and training. However, the useof AR is not yet common in medical practice, despite the great po-tential of this technology to help not only learning and training inmedicine, but also in assisting diagnosis and surgical guidance. Inthis paper, we present recent trends in the use of AR across all med-ical specialties and identify challenges that must be overcome tonarrow the gap between academic research and practical use of ARin medicine. A database of 1403 relevant research papers publishedover the last two decades has been reviewed by using a novel re-search trend analysis method based on text mining algorithm. Wesemantically identified 10 topics including varies of technologiesand applications based on the non-biased and in-personal cluster-ing results from the Latent Dirichlet Allocatio (LDA) model andanalysed the trend of each topic from 1995 to 2015. The statisticresults reveal a taxonomy that can best describes the developmentof the medical AR research during the two decades. And the trendanalysis provide a higher level of view of how the taxonomy haschanged and where the focus will goes. Finally, based on the valu-able results, we provide a insightful discussion to the current limi-tations, challenges and future directions in the field. Our objectiveis to aid researchers to focus on the application areas in medicalAR that are most needed, as well as providing medical practitioners with latest technology advancements

Evaluation of optical tracking and augmented reality for needle navigation in sacral nerve stimulation

Background and objective: Sacral nerve stimulation (SNS) is a minimally invasive procedure where an electrode lead is implanted through the sacral foramina to stimulate the nerve modulating colonic and urinary functions. One of the most crucial steps in SNS procedures is the placement of the tined lead close to the sacral nerve. However, needle insertion is very challenging for surgeons. Several x-ray projections are required to interpret the needle position correctly. In many cases, multiple punctures are needed, causing an increase in surgical time and patient's discomfort and pain. In this work we propose and evaluate two different navigation systems to guide electrode placement in SNS surgeries designed to reduce surgical time, minimize patient discomfort and improve surgical outcomes. Methods: We developed, for the first alternative, an open-source navigation software to guide electrode placement by real-time needle tracking with an optical tracking system (OTS). In the second method, we present a smartphone-based AR application that displays virtual guidance elements directly on the affected area, using a 3D printed reference marker placed on the patient. This guidance facilitates needle insertion with a predefined trajectory. Both techniques were evaluated to determine which one obtained better results than the current surgical procedure. To compare the proposals with the clinical method, we developed an x-ray software tool that calculates a digitally reconstructed radiograph, simulating the fluoroscopy acquisitions during the procedure. Twelve physicians (inexperienced and experienced users) performed needle insertions through several specific targets to evaluate the alternative SNS guidance methods on a realistic patient-based phantom. Results: With each navigation solution, we observed that users took less average time to complete each insertion (36.83 s and 44.43 s for the OTS and AR methods, respectively) and needed fewer average punctures to reach the target (1.23 and 1.96 for the OTS and AR methods respectively) than following the standard clinical method (189.28 s and 3.65 punctures). Conclusions: To conclude, we have shown two navigation alternatives that could improve surgical outcome by significantly reducing needle insertions, surgical time and patient's pain in SNS procedures. We believe that these solutions are feasible to train surgeons and even replace current SNS clinical procedures.Research supported by projects PI18/01625 and AC20/00102 (Ministerio de Ciencia, Innovación y Universidades, Instituto de Salud Carlos III, Asociación Española Contra el Cáncer and European Regional Development Fund "Una manera de hacer Europa"), IND2018/TIC-9753 (Comunidad de Madrid) and project PerPlanRT (ERA Permed). Funding for APC: Universidad Carlos III de Madrid (Read & Publish Agreement CRUE-CSIC 2022)

Evaluating Human Performance for Image-Guided Surgical Tasks

The following work focuses on the objective evaluation of human performance for two different interventional tasks; targeted prostate biopsy tasks using a tracked biopsy device, and external ventricular drain placement tasks using a mobile-based augmented reality device for visualization and guidance. In both tasks, a human performance methodology was utilized which respects the trade-off between speed and accuracy for users conducting a series of targeting tasks using each device. This work outlines the development and application of performance evaluation methods using these devices, as well as details regarding the implementation of the mobile AR application. It was determined that the Fitts’ Law methodology can be applied for evaluation of tasks performed in each surgical scenario, and was sensitive to differentiate performance across a range which spanned experienced and novice users. This methodology is valuable for future development of training modules for these and other medical devices, and can provide details about the underlying characteristics of the devices, and how they can be optimized with respect to human performance

Modular framework for a breast biopsy smart navigation system

Dissertação de mestrado em Informatics EngineeringBreast cancer is currently one of the most commonly diagnosed cancers and the fifth leading cause of cancer-related deaths. Its treatment has a higher survivorship rate when diagnosed in the disease’s early stages. The screening procedure uses medical imaging techniques, such as mammography or ultrasound, to discover possible lesions. When a physician finds a lesion that is likely to be malignant, a biopsy is performed to obtain a sample and determine its characteristics. Currently, real-time ultrasound is the preferred medical imaging modality to perform this procedure. The breast biopsy procedure is highly reliant on the operator’s skill and experience, due to the difficulty in interpreting ultrasound images and correctly aiming the needle. Robotic solutions, and the usage of automatic lesion segmentation in ultrasound imaging along with advanced visualization techniques, such as augmented reality, can potentially make this process simpler, safer, and faster. The OncoNavigator project, in which this dissertation integrates, aims to improve the precision of the current breast cancer interventions. To accomplish this objective various medical training and robotic biopsy aid were developed. An augmented reality ultrasound training solution was created and the device’s tracking capabilities were validated by comparing it with an electromagnetic tracking device. Another solution for ultrasound-guided breast biopsy assisted with augmented reality was developed. This solution displays real-time ultrasound video, automatic lesion segmentation, and biopsy needle trajectory display in the user’s field of view. The validation of this solution was made by comparing its usability with the traditional procedure. A modular software framework was also developed that focuses on the integration of a collaborative medical robot with real-time ultrasound imaging and automatic lesion segmentation. Overall, the developed solutions offered good results. The augmented reality glasses tracking capabilities proved to be as capable as the electromagnetic system, and the augmented reality assisted breast biopsy proved to make the procedure more accurate and precise than the traditional system.O cancro da mama é, atualmente, um dos tipos de cancro mais comuns a serem diagnosticados e a quinta principal causa de mortes relacionadas ao cancro. O seu tratamento tem maior taxa de sobrevivência quando é diagnosticado nas fases iniciais da doença. O procedimento de triagem utiliza técnicas de imagem médica, como mamografia ou ultrassom, para descobrir possíveis lesões. Quando um médico encontra uma lesão com probabilidade de ser maligna, é realizada uma biópsia para obter uma amostra e determinar as suas características. O ultrassom em tempo real é a modalidade de imagem médica preferida para realizar esse procedimento. A biópsia mamária depende da habilidade e experiência do operador, devido à dificuldade de interpretação das imagens ultrassonográficas e ao direcionamento correto da agulha. Soluções robóticas, com o uso de segmentação automática de lesões em imagens de ultrassom, juntamente com técnicas avançadas de visualização, nomeadamente realidade aumentada, podem tornar esse processo mais simples, seguro e rápido. O projeto OncoNavigator, que esta dissertação integra, visa melhorar a precisão das atuais intervenções ao cancro da mama. Para atingir este objetivo, vários ajudas para treino médico e auxílio à biópsia por meio robótico foram desenvolvidas. Uma solução de treino de ultrassom com realidade aumentada foi criada e os recursos de rastreio do dispositivo foram validados comparando-os com um dispositivo eletromagnético. Outra solução para biópsia de mama guiada por ultrassom assistida com realidade aumentada foi desenvolvida. Esta solução exibe vídeo de ultrassom em tempo real, segmentação automática de lesões e exibição da trajetória da agulha de biópsia no campo de visão do utilizador. A validação desta solução foi feita comparando a sua usabilidade com o procedimento tradicional. Também foi desenvolvida uma estrutura de software modular que se concentra na integração de um robô médico colaborativo com imagens de ultrassom em tempo real e segmentação automática de lesões. Os recursos de rastreio dos óculos de realidade aumentada mostraram-se tão capazes quanto o sistema eletromagnético, e a biópsia de mama assistida por realidade aumentada provou tornar o procedimento mais exato e preciso do que o sistema tradicional

Augmented and virtual reality in spine surgery, current applications and future potentials

BACKGROUND CONTEXT: The field of artificial intelligence (AI) is rapidly advancing, especially with recent improvements in deep learning (DL) techniques. Augmented (AR) and virtual reality (VR) are finding their place in healthcare, and spine surgery is no exception. The unique capabilities and advantages of AR and VR devices include their low cost, flexible integration with other technologies, user-friendly features and their application in navigation systems, which makes them beneficial across different aspects of spine surgery. Despite the use of AR for pedicle screw placement, targeted cervical foraminotomy, bone biopsy, osteotomy planning, and percutaneous intervention, the current applications of AR and VR in spine surgery remain limited. PURPOSE: The primary goal of this study was to provide the spine surgeons and clinical researchers with the general information about the current applications, future potentials, and accessibility of AR and VR systems in spine surgery. STUDY DESIGN/SETTING: We reviewed titles of more than 250 journal papers from google scholar and PubMed with search words: augmented reality, virtual reality, spine surgery, and orthopaedic, out of which 89 related papers were selected for abstract review. Finally, full text of 67 papers were analyzed and reviewed. METHODS: The papers were divided into four groups: technological papers, applications in surgery, applications in spine education and training, and general application in orthopaedic. A team of two reviewers performed paper reviews and a thorough web search to ensure the most updated state of the art in each of four group is captured in the review. RESULTS: In this review we discuss the current state of the art in AR and VR hardware, their preoperative applications and surgical applications in spine surgery. Finally, we discuss the future potentials of AR and VR and their integration with AI, robotic surgery, gaming, and wearables. CONCLUSIONS: AR and VR are promising technologies that will soon become part of standard of care in spine surgery. (C) 2021 Published by Elsevier Inc

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

Mixed-reality visualization environments to facilitate ultrasound-guided vascular access

Ultrasound-guided needle insertions at the site of the internal jugular vein (IJV) are routinely performed to access the central venous system. Ultrasound-guided insertions maintain high rates of carotid artery puncture, as clinicians rely on 2D information to perform a 3D procedure. The limitations of 2D ultrasound-guidance motivated the research question: “Do 3D ultrasound-based environments improve IJV needle insertion accuracy”. We addressed this by developing advanced surgical navigation systems based on tracked surgical tools and ultrasound with various visualizations. The point-to-line ultrasound calibration enables the use of tracked ultrasound. We automated the fiducial localization required for this calibration method such that fiducials can be automatically localized within 0.25 mm of the manual equivalent. The point-to-line calibration obtained with both manual and automatic localizations produced average normalized distance errors less than 1.5 mm from point targets. Another calibration method was developed that registers an optical tracking system and the VIVE Pro head-mounted display (HMD) tracking system with sub-millimetre and sub-degree accuracy compared to ground truth values. This co-calibration enabled the development of an HMD needle navigation system, in which the calibrated ultrasound image and tracked models of the needle, needle trajectory, and probe were visualized in the HMD. In a phantom experiment, 31 clinicians had a 96 % success rate using the HMD system compared to 70 % for the ultrasound-only approach (p= 0.018). We developed a machine-learning-based vascular reconstruction pipeline that automatically returns accurate 3D reconstructions of the carotid artery and IJV given sequential tracked ultrasound images. This reconstruction pipeline was used to develop a surgical navigation system, where tracked models of the needle, needle trajectory, and the 3D z-buffered vasculature from a phantom were visualized in a common coordinate system on a screen. This system improved the insertion accuracy and resulted in 100 % success rates compared to 70 % under ultrasound-guidance (p=0.041) across 20 clinicians during the phantom experiment. Overall, accurate calibrations and machine learning algorithms enable the development of advanced 3D ultrasound systems for needle navigation, both in an immersive first-person perspective and on a screen, illustrating that 3D US environments outperformed 2D ultrasound-guidance used clinically

On uncertainty propagation in image-guided renal navigation: Exploring uncertainty reduction techniques through simulation and in vitro phantom evaluation

Image-guided interventions (IGIs) entail the use of imaging to augment or replace direct vision during therapeutic interventions, with the overall goal is to provide effective treatment in a less invasive manner, as an alternative to traditional open surgery, while reducing patient trauma and shortening the recovery time post-procedure. IGIs rely on pre-operative images, surgical tracking and localization systems, and intra-operative images to provide correct views of the surgical scene. Pre-operative images are used to generate patient-specific anatomical models that are then registered to the patient using the surgical tracking system, and often complemented with real-time, intra-operative images. IGI systems are subject to uncertainty from several sources, including surgical instrument tracking / localization uncertainty, model-to-patient registration uncertainty, user-induced navigation uncertainty, as well as the uncertainty associated with the calibration of various surgical instruments and intra-operative imaging devices (i.e., laparoscopic camera) instrumented with surgical tracking sensors. All these uncertainties impact the overall targeting accuracy, which represents the error associated with the navigation of a surgical instrument to a specific target to be treated under image guidance provided by the IGI system. Therefore, understanding the overall uncertainty of an IGI system is paramount to the overall outcome of the intervention, as procedure success entails achieving certain accuracy tolerances specific to individual procedures. This work has focused on studying the navigation uncertainty, along with techniques to reduce uncertainty, for an IGI platform dedicated to image-guided renal interventions. We constructed life-size replica patient-specific kidney models from pre-operative images using 3D printing and tissue emulating materials and conducted experiments to characterize the uncertainty of both optical and electromagnetic surgical tracking systems, the uncertainty associated with the virtual model-to-physical phantom registration, as well as the uncertainty associated with live augmented reality (AR) views of the surgical scene achieved by enhancing the pre-procedural model and tracked surgical instrument views with live video views acquires using a camera tracked in real time. To better understand the effects of the tracked instrument calibration, registration fiducial configuration, and tracked camera calibration on the overall navigation uncertainty, we conducted Monte Carlo simulations that enabled us to identify optimal configurations that were subsequently validated experimentally using patient-specific phantoms in the laboratory. To mitigate the inherent accuracy limitations associated with the pre-procedural model-to-patient registration and their effect on the overall navigation, we also demonstrated the use of tracked video imaging to update the registration, enabling us to restore targeting accuracy to within its acceptable range. Lastly, we conducted several validation experiments using patient-specific kidney emulating phantoms using post-procedure CT imaging as reference ground truth to assess the accuracy of AR-guided navigation in the context of in vitro renal interventions. This work helped find answers to key questions about uncertainty propagation in image-guided renal interventions and led to the development of key techniques and tools to help reduce optimize the overall navigation / targeting uncertainty