448 research outputs found

    Augmented Reality: Mapping Methods and Tools for Enhancing the Human Role in Healthcare HMI

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    Background: Augmented Reality (AR) represents an innovative technology to improve data visualization and strengthen the human perception. Among Human–Machine Interaction (HMI), medicine can benefit most from the adoption of these digital technologies. In this perspective, the literature on orthopedic surgery techniques based on AR was evaluated, focusing on identifying the limitations and challenges of AR-based healthcare applications, to support the research and the development of further studies. Methods: Studies published from January 2018 to December 2021 were analyzed after a comprehensive search on PubMed, Google Scholar, Scopus, IEEE Xplore, Science Direct, and Wiley Online Library databases. In order to improve the review reporting, the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines were used. Results: Authors selected sixty-two articles meeting the inclusion criteria, which were categorized according to the purpose of the study (intraoperative, training, rehabilitation) and according to the surgical procedure used. Conclusions: AR has the potential to improve orthopedic training and practice by providing an increasingly human-centered clinical approach. Further research can be addressed by this review to cover problems related to hardware limitations, lack of accurate registration and tracking systems, and absence of security protocols

    Augmented reality for computer assisted orthopaedic surgery

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    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

    Computer-assisted orthopedic training system for fracture fixation

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    Background: Surgical training has been greatly affected by the challenges of reduced training opportunities, shortened working hours, and financial pressures. There is an increased need for the use of training systems in developing psychomotor skills of the surgical trainee. Aims: To develop the training system for fracture fixation and validate its effectiveness in a cohort of junior orthopedic trainees. Training System: Computer-navigated training system uses the 2 sets of images from the c-arm while the registration phantom is placed in the fluoroscopic imaging space which permits determination of the position of the x-ray source and the image plane that then guides the trainee to navigate the surgical instruments into the three-dimensional space. No further c-arm exposures are taken during the entire procedure. Materials and Method: The training system was developed to simulate dynamic hip screw fixation. Twelve orthopedic senior house officers performed dynamic hip screw fixation before and after the training on the training system. The results were assessed based on the scoring system that included the amount of time taken, accuracy of guidewire placement, and the number of exposures requested to complete the procedure. Results: The result shows a significant improvement in the amount of time taken, accuracy of fixation, and the number of exposures after the training on the simulator system. The paired student t-test was used and statistically significant results were obtained (p-value< 0.05). Conclusion: Computer-navigated training system appears to be a good training tool for young orthopedic trainees. This system can be used to augment training in the operating room and trainees acquire their skills in a "nonthreatening and unhurried environment." The system has the potential to be used in various other orthopedic procedures for learning of technical skills in a manner aimed at ensuring a smooth escalation in task complexity leading to the better performance of procedures in the operating theater

    HAPPY: Hip Arthroscopy Portal Placement Using Augmented Reality

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    Correct positioning of the endoscope is crucial for successful hip arthroscopy. Only with adequate alignment can the anatomical target area be visualized and the procedure be successfully performed. Conventionally, surgeons rely on anatomical landmarks such as bone structure, and on intraoperative X-ray imaging, to correctly place the surgical trocar and insert the endoscope to gain access to the surgical site. One factor complicating the placement is deformable soft tissue, as it can obscure important anatomical landmarks. In addition, the commonly used endoscopes with an angled camera complicate hand-eye coordination and, thus, navigation to the target area. Adjusting for an incorrectly positioned endoscope prolongs surgery time, requires a further incision and increases the radiation exposure as well as the risk of infection. In this work, we propose an augmented reality system to support endoscope placement during arthroscopy. Our method comprises the augmentation of a tracked endoscope with a virtual augmented frustum to indicate the reachable working volume. This is further combined with an in situ visualization of the patient anatomy to improve perception of the target area. For this purpose, we highlight the anatomy that is visible in the endoscopic camera frustum and use an automatic colorization method to improve spatial perception. Our system was implemented and visualized on a head-mounted display. The results of our user study indicate the benefit of the proposed system compared to baseline positioning without additional support, such as an increased alignment speed, improved positioning error and reduced mental effort. The proposed approach might aid in the positioning of an angled endoscope, and may result in better access to the surgical area, reduced surgery time, less patient trauma, and less X-ray exposure during surgery

    Augmented Reality and Artificial Intelligence in Image-Guided and Robot-Assisted Interventions

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    In minimally invasive orthopedic procedures, the surgeon places wires, screws, and surgical implants through the muscles and bony structures under image guidance. These interventions require alignment of the pre- and intra-operative patient data, the intra-operative scanner, surgical instruments, and the patient. Suboptimal interaction with patient data and challenges in mastering 3D anatomy based on ill-posed 2D interventional images are essential concerns in image-guided therapies. State of the art approaches often support the surgeon by using external navigation systems or ill-conditioned image-based registration methods that both have certain drawbacks. Augmented reality (AR) has been introduced in the operating rooms in the last decade; however, in image-guided interventions, it has often only been considered as a visualization device improving traditional workflows. Consequently, the technology is gaining minimum maturity that it requires to redefine new procedures, user interfaces, and interactions. This dissertation investigates the applications of AR, artificial intelligence, and robotics in interventional medicine. Our solutions were applied in a broad spectrum of problems for various tasks, namely improving imaging and acquisition, image computing and analytics for registration and image understanding, and enhancing the interventional visualization. The benefits of these approaches were also discovered in robot-assisted interventions. We revealed how exemplary workflows are redefined via AR by taking full advantage of head-mounted displays when entirely co-registered with the imaging systems and the environment at all times. The proposed AR landscape is enabled by co-localizing the users and the imaging devices via the operating room environment and exploiting all involved frustums to move spatial information between different bodies. The system's awareness of the geometric and physical characteristics of X-ray imaging allows the exploration of different human-machine interfaces. We also leveraged the principles governing image formation and combined it with deep learning and RGBD sensing to fuse images and reconstruct interventional data. We hope that our holistic approaches towards improving the interface of surgery and enhancing the usability of interventional imaging, not only augments the surgeon's capabilities but also augments the surgical team's experience in carrying out an effective intervention with reduced complications

    Personalized medicine in surgical treatment combining tracking systems, augmented reality and 3D printing

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    Mención Internacional en el título de doctorIn the last twenty years, a new way of practicing medicine has been focusing on the problems and needs of each patient as an individual thanks to the significant advances in healthcare technology, the so-called personalized medicine. In surgical treatments, personalization has been possible thanks to key technologies adapted to the specific anatomy of each patient and the needs of the physicians. Tracking systems, augmented reality (AR), three-dimensional (3D) printing and artificial intelligence (AI) have previously supported this individualized medicine in many ways. However, their independent contributions show several limitations in terms of patient-to-image registration, lack of flexibility to adapt to the requirements of each case, large preoperative planning times, and navigation complexity. The main objective of this thesis is to increase patient personalization in surgical treatments by combining these technologies to bring surgical navigation to new complex cases by developing new patient registration methods, designing patient-specific tools, facilitating access to augmented reality by the medical community, and automating surgical workflows. In the first part of this dissertation, we present a novel framework for acral tumor resection combining intraoperative open-source navigation software, based on an optical tracking system, and desktop 3D printing. We used additive manufacturing to create a patient-specific mold that maintained the same position of the distal extremity during image-guided surgery as in the preoperative images. The feasibility of the proposed workflow was evaluated in two clinical cases (soft-tissue sarcomas in hand and foot). We achieved an overall accuracy of the system of 1.88 mm evaluated on the patient-specific 3D printed phantoms. Surgical navigation was feasible during both surgeries, allowing surgeons to verify the tumor resection margin. Then, we propose and augmented reality navigation system that uses 3D printed surgical guides with a tracking pattern enabling automatic patient-to-image registration in orthopedic oncology. This specific tool fits on the patient only in a pre-designed location, in this case bone tissue. This solution has been developed as a software application running on Microsoft HoloLens. The workflow was validated on a 3D printed phantom replicating the anatomy of a patient presenting an extraosseous Ewing’s sarcoma, and then tested during the actual surgical intervention. The results showed that the surgical guide with the reference marker can be placed precisely with an accuracy of 2 mm and a visualization error lower than 3 mm. The application allowed physicians to visualize the skin, bone, tumor and medical images overlaid on the phantom and patient. To enable the use of AR and 3D printing by inexperienced users without broad technical knowledge, we designed a step-by-step methodology. The proposed protocol describes how to develop an AR smartphone application that allows superimposing any patient-based 3D model onto a real-world environment using a 3D printed marker tracked by the smartphone camera. Our solution brings AR solutions closer to the final clinical user, combining free and open-source software with an open-access protocol. The proposed guide is already helping to accelerate the adoption of these technologies by medical professionals and researchers. In the next section of the thesis, we wanted to show the benefits of combining these technologies during different stages of the surgical workflow in orthopedic oncology. We designed a novel AR-based smartphone application that can display the patient’s anatomy and the tumor’s location. A 3D printed reference marker, designed to fit in a unique position of the affected bone tissue, enables automatic registration. The system has been evaluated in terms of visualization accuracy and usability during the whole surgical workflow on six realistic phantoms achieving a visualization error below 3 mm. The AR system was tested in two clinical cases during surgical planning, patient communication, and surgical intervention. These results and the positive feedback obtained from surgeons and patients suggest that the combination of AR and 3D printing can improve efficacy, accuracy, and patients’ experience In the final section, two surgical navigation systems have been developed and evaluated to guide electrode placement in sacral neurostimulation procedures based on optical tracking and augmented reality. Our results show that both systems could minimize patient discomfort and improve surgical outcomes by reducing needle insertion time and number of punctures. Additionally, we proposed a feasible clinical workflow for guiding SNS interventions with both navigation methodologies, including automatically creating sacral virtual 3D models for trajectory definition using artificial intelligence and intraoperative patient-to-image registration. To conclude, in this thesis we have demonstrated that the combination of technologies such as tracking systems, augmented reality, 3D printing, and artificial intelligence overcomes many current limitations in surgical treatments. Our results encourage the medical community to combine these technologies to improve surgical workflows and outcomes in more clinical scenarios.Programa de Doctorado en Ciencia y Tecnología Biomédica por la Universidad Carlos III de MadridPresidenta: María Jesús Ledesma Carbayo.- Secretaria: María Arrate Muñoz Barrutia.- Vocal: Csaba Pinte
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