186 research outputs found

    Image-Based Robotic System for Enhanced Minimally Invasive Intra-Articular Fracture Surgeries

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    Abstract: Robotic assistance can bring significant improvements to orthopedic fracture surgery: facilitate more accurate fracture fragment repositioning without open access and obviate problems related to the current minimally invasive fracture surgery techniques by providing a better clinical outcome, reduced recovery time, and health-related costs. This paper presents a new design of the robot-assisted fracture surgery (RAFS) system developed at Bristol Robotics Laboratory, featuring a new robotic architecture, and real-time 3D imaging of the fractured anatomy. The technology presented in this paper focuses on distal femur fractures, but can be adapted to the larger domain of fracture surgeries, improving the state-of-the-art in robot assistance in orthopedics. To demonstrate the enhanced performance of the RAFS system, 10 reductions of a distal femur fracture are performed using the system on a bone model. The experimental results clearly demonstrate the accuracy, effectiveness, and safety of the new RAFS system. The system allows the surgeon to precisely reduce the fractures with a reduction accuracy of 1.15 mm and 1.3°, meeting the clinical requirements for this procedure

    RAFS: A computer-assisted robotic system for minimally invasive joint fracture surgery, based on pre- and intra-operative imaging

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    The integration of minimally invasive robotic assistance and image-guidance can have positive impact on joint fracture surgery, providing a better clinical outcome with respect to the current open procedure. In this paper, a new design of the RAFS surgical system is presented. The redesign of the robotic system and its integration with a novel 3D navigation system through a new clinical workflow, overcomes the drawbacks of the earlier prototype. This makes the RAFS surgical system more suitable to clinical scenarios in the operating theatre. System accuracy and effectiveness are successfully demonstrated through laboratory trials and preliminary cadaveric trials. The experimental results demonstrate that the system allows the surgeon to reduce a 2-fragment distal femur fracture in a cadaveric specimen, with a reduction accuracy of up to 0.85 mm and 2.2°. Preliminary cadaveric trials also provided a positive and favorable outcome pointing to the usability and safety of the RAFS system in the operating theatre, potentially enhancing the capacity of joint fracture surgeries

    Image-Guided Surgical Robotic System for Percutaneous Reduction of Joint Fractures

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    Complex joint fractures often require an open surgical procedure, which is associated with extensive soft tissue damages and longer hospitalization and rehabilitation time. Percutaneous techniques can potentially mitigate these risks but their application to joint fractures is limited by the current sub-optimal 2D intra-operative imaging (fluoroscopy) and by the high forces involved in the fragment manipulation (due to the presence of soft tissue, e.g., muscles) which might result in fracture malreduction. Integration of robotic assistance and 3D image guidance can potentially overcome these issues. The authors propose an image-guided surgical robotic system for the percutaneous treatment of knee joint fractures, i.e., the robot-assisted fracture surgery (RAFS) system. It allows simultaneous manipulation of two bone fragments, safer robot-bone fixation system, and a traction performing robotic manipulator. This system has led to a novel clinical workflow and has been tested both in laboratory and in clinically relevant cadaveric trials. The RAFS system was tested on 9 cadaver specimens and was able to reduce 7 out of 9 distal femur fractures (T- and Y-shape 33-C1) with acceptable accuracy (≈1 mm, ≈5°), demonstrating its applicability to fix knee joint fractures. This study paved the way to develop novel technologies for percutaneous treatment of complex fractures including hip, ankle, and shoulder, thus representing a step toward minimally-invasive fracture surgeries

    Robot-assistive minimally invasive surgery:trends and future directions

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    The evolution of medical technologies—such as surgical devices and imaging techniques—has transformed all aspects of surgery. A key area of development is robot-assisted minimally invasive surgery (MIS). This review paper provides an overview of the evolution of robotic MIS, from its infancy to our days, and envisioned future challenges. It provides an outlook of breakthrough surgical robotic platforms, their clinical applications, and their evolution over the years. It discusses how the integration of robotic, imaging, and sensing technologies has contributed to create novel surgical platforms that can provide the surgeons with enhanced dexterity, precision, and surgical navigation while reducing the invasiveness and efficacy of the intervention. Finally, this review provides an outlook on the future of robotic MIS discussing opportunities and challenges that the scientific community will have to address in the coming decade. We hope that this review serves to provide a quick and accessible way to introduce the readers to this exciting and fast-evolving area of research, and to inspire future research in this field

    Intra-operative fiducial-based CT/fluoroscope image registration framework for image-guided robot-assisted joint fracture surgery

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    Purpose Joint fractures must be accurately reduced minimising soft tissue damages to avoid negative surgical outcomes. To this regard, we have developed the RAFS surgical system, which allows the percutaneous reduction of intra-articular fractures and provides intra-operative real-time 3D image guidance to the surgeon. Earlier experiments showed the effectiveness of the RAFS system on phantoms, but also key issues which precluded its use in a clinical application. This work proposes a redesign of the RAFS’s navigation system overcoming the earlier version’s issues, aiming to move the RAFS system into a surgical environment. Methods The navigation system is improved through an image registration framework allowing the intra-operative registration between pre-operative CT images and intra-operative fluoroscopic images of a fractured bone using a custom-made fiducial marker. The objective of the registration is to estimate the relative pose between a bone fragment and an orthopaedic manipulation pin inserted into it intra-operatively. The actual pose of the bone fragment can be updated in real time using an optical tracker, enabling the image guidance. Results Experiments on phantom and cadavers demonstrated the accuracy and reliability of the registration framework, showing a reduction accuracy (sTRE) of about 0.88 ±0.2mm (phantom) and 1.15±0.8mm (cadavers). Four distal femur fractures were successfully reduced in cadaveric specimens using the improved navigation system and the RAFS system following the new clinical workflow (reduction error 1.2±0.3mm, 2±1∘). Conclusion Experiments showed the feasibility of the image registration framework. It was successfully integrated into the navigation system, allowing the use of the RAFS system in a realistic surgical application

    Robot-Bone Attachment Device for Robot-Assisted Percutaneous Bone Fragment Manipulation

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    The treatment of joint-fractures is a common task in orthopaedic surgery causing considerable health costs and patient disabilities. Percutaneous techniques have been developed to mitigate the problems related to open surgery (e.g. soft tissue damage), although their application to joint-fractures is limited by the sub-optimal intra-operative imaging (2D-fluoroscopy) and by the high forces involved. Our earlier research toward improving percutaneous reduction of intra-articular fractures has resulted in the creation of a robotic system prototype, i.e. RAFS (Robot-Assisted Fracture Surgery) system. We propose a robot-bone attachment device for percutaneous bone manipulation, which can be anchored to the bone fragment through one small incision, ensuring the required stability and reducing the “biological cost” of the procedure. The device has been evaluated through the reduction of 9 distal femur fractures on human cadavers using the RAFS system

    Design and Evaluation of a Percutaneous Fragment Manipulation Device for Minimally Invasive Fracture Surgery

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    Reduction of fractures in the minimally invasive (MI) manner can avoid risks associated with open fracture surgery. The MI approach requires specialized tools called percutaneous fragment manipulation devices (PFMD) to enable surgeons to safely grasp and manipulate fragments. PFMDs developed for long-bone manipulation are not suitable for intra-articular fractures where small bone fragments are involved. With this study, we offer a solution to potentially move the current fracture management practice closer to the use of a MI approach. We investigate the design and testing of a new PFMD design for manual as well as robot-assisted manipulation of small bone fragments. This new PFMD design is simulated using FEA in three loading scenarios (force/torque: 0 N/2.6 Nm, 75.7 N/3.5 N, 147 N/6.8 Nm) assessing structural properties, breaking points, and maximum bending deformations. The PFMD is tested in a laboratory setting on Sawbones models (0 N/2.6 Nm), and on ex-vivo swine samples (F = 80 N ± 8 N, F = 150 ± 15 N). A commercial optical tracking system was used for measuring PFMD deformations under external loading and the results were verified with an electromagnetic tracking system. The average error difference between the tracking systems was 0.5 mm, being within their accuracy limits. Final results from reduction maneuvers performed both manually and with the robot assistance are obtained from 7 human cadavers with reduction forces in the range of (F = 80 N ± 8 N, F = 150 ± 15 N, respectively). The results show that structurally, the system performs as predicted by the simulation results. The PFMD did not break during ex-vivo and cadaveric trials. Simulation, laboratory, and cadaveric tests produced similar results regarding the PFMD bending. Specifically, for forces applied perpendicularly to the axis of the PFMD of 80 N ± 8 N deformations of 2.8, 2.97, and 3.06 mm are measured on the PFMD, while forces of 150 ± 15 N produced deformations of 5.8, 4.44, and 5.19 mm. This study has demonstrated that the proposed PFMD undergoes predictable deformations under typical bone manipulation loads. Testing of the device on human cadavers proved that these deformations do not affect the anatomic reduction quality. The PFMD is, therefore, suitable to reliably achieve and maintain fracture reductions, and to, consequently, allow external fracture fixation

    Recent trends, technical concepts and components of computer-assisted orthopedic surgery systems: A comprehensive review

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    Computer-assisted orthopedic surgery (CAOS) systems have become one of the most important and challenging types of system in clinical orthopedics, as they enable precise treatment of musculoskeletal diseases, employing modern clinical navigation systems and surgical tools. This paper brings a comprehensive review of recent trends and possibilities of CAOS systems. There are three types of the surgical planning systems, including: systems based on the volumetric images (computer tomography (CT), magnetic resonance imaging (MRI) or ultrasound images), further systems utilize either 2D or 3D fluoroscopic images, and the last one utilizes the kinetic information about the joints and morphological information about the target bones. This complex review is focused on three fundamental aspects of CAOS systems: their essential components, types of CAOS systems, and mechanical tools used in CAOS systems. In this review, we also outline the possibilities for using ultrasound computer-assisted orthopedic surgery (UCAOS) systems as an alternative to conventionally used CAOS systems.Web of Science1923art. no. 519

    Robotic Assisted Fracture Surgery

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    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
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