IntroductionEndovascular aortic repair (EVAR) is a minimal-invasive technique that prevents life-threatening rupture in patients with aortic pathologies by implantation of an endoluminal stent graft. During the endovascular procedure, device navigation is currently performed by fluoroscopy in combination with digital subtraction angiography. This study presents the current iterative process of biomedical engineering within the disruptive interdisciplinary project Nav EVAR, which includes advanced navigation, image techniques and augmented reality with the aim of reducing side effects (namely radiation exposure and contrast agent administration) and optimising visualisation during EVAR procedures. This article describes the current prototype developed in this project and the experiments conducted to evaluate it.MethodsThe current approach of the Nav EVAR project is guiding EVAR interventions in real-time with an electromagnetic tracking system after attaching a sensor on the catheter tip and displaying this information on Microsoft HoloLens glasses. This augmented reality technology enables the visualisation of virtual objects superimposed on the real environment. These virtual objects include three-dimensional (3D) objects (namely 3D models of the skin and vascular structures) and two-dimensional (2D) objects [namely orthogonal views of computed tomography (CT) angiograms, 2D images of 3D vascular models, and 2D images of a new virtual angioscopy whose appearance of the vessel wall follows that shown in ex vivo and in vivo angioscopies]. Specific external markers were designed to be used as landmarks in the registration process to map the tracking data and radiological data into a common space. In addition, the use of real-time 3D ultrasound (US) is also under evaluation in the Nav EVAR project for guiding endovascular tools and updating navigation with intraoperative imaging. US volumes are streamed from the US system to HoloLens and visualised at a certain distance from the probe by tracking augmented reality markers. A human model torso that includes a 3D printed patient-specific aortic model was built to provide a realistic test environment for evaluation of technical components in the Nav EVAR project. The solutions presented in this study were tested by using an US training model and the aortic-aneurysm phantom.ResultsDuring the navigation of the catheter tip in the US training model, the 3D models of the phantom surface and vessels were visualised on HoloLens. In addition, a virtual angioscopy was also built from a CT scan of the aortic-aneurysm phantom. The external markers designed for this study were visible in the CT scan and the electromagnetically tracked pointer fitted in each marker hole. US volumes of the US training model were sent from the US system to HoloLens in order to display them, showing a latency of 259±86 ms (mean±standard deviation).ConclusionThe Nav EVAR project tackles the problem of radiation exposure and contrast agent administration during EVAR interventions by using a multidisciplinary approach to guide the endovascular tools. Its current state presents several limitations such as the rigid alignment between preoperative data and the simulated patient. Nevertheless, the techniques shown in this study in combination with fibre Bragg gratings and optical coherence tomography are a promising approach to overcome the problems of EVAR interventions.
Purpose of Review This review provides an overview of the most recent robotic ultrasound systems that have contemporary emerged over the past five years, highlighting their status and future directions. The systems are categorized based on their level of robot autonomy (LORA). Recent Findings Teleoperating systems show the highest level of technical maturity. Collaborative assisting and autonomous systems are still in the research phase, with a focus on ultrasound image processing and force adaptation strategies. However, missing key factors are clinical studies and appropriate safety strategies. Future research will likely focus on artificial intelligence and virtual/augmented reality to improve image understanding and ergonomics. Summary A review on robotic ultrasound systems is presented in which first technical specifications are outlined. Hereafter, the literature of the past five years is subdivided into teleoperation, collaborative assistance, or autonomous systems based on LORA. Finally, future trends for robotic ultrasound systems are reviewed with a focus on artificial intelligence and virtual/augmented reality.
Intra-operative electron radiation therapy (IOERT) combines surgery and ionizing radiation applied directly to an exposed unresected tumour mass or to a post-resection tumour bed. The radiation is collimated and conducted by a specific applicator docked to the linear accelerator. The dose distribution in tissues to be irradiated and in organs at risk can be planned through a pre-operative computed tomography (CT) study. However, surgical retraction of structures and resection of a tumour affecting normal tissues significantly modify the patient's geometry. Therefore, the treatment parameters (applicator dimension, pose (position and orientation), bevel angle, and beam energy) may require the original IOERT treatment plan to be modified depending on the actual surgical scenario. We propose the use of a multi-camera optical tracking system to reliably record the actual pose of the IOERT applicator in relation to the patient's anatomy in an environment prone to occlusion problems. This information can be integrated in the radio-surgical treatment planning system in order to generate a real-time accurate description of the IOERT scenario. We assessed the accuracy of the applicator pose by performing a phantom-based study that resembled three real clinical IOERT scenarios. The error obtained (2 mm) was below the acceptance threshold for external radiotherapy practice, thus encouraging future implementation of this approach in real clinical IOERT scenarios.
Intraoperative electron radiation therapy (IOERT) involves irradiation of an unresected tumour or a post-resection tumour bed. The dose distribution is calculated from a preoperative computed tomography (CT) study acquired using a CT simulator. However, differences between the actual IOERT field and that calculated from the preoperative study arise as a result of patient position, surgical access, tumour resection and the IOERT set-up. Intraoperative CT imaging may then enable a more accurate estimation of dose distribution. In this study, we evaluated three kilovoltage (kV) CT scanners with the ability to acquire intraoperative images. Our findings indicate that current IOERT plans may be improved using data based on actual anatomical conditions during radiation. The systems studied were two portable systems ("O-arm", a cone-beam CT [CBCT] system, and "BodyTom", a multislice CT [MSCT] system) and one CBCT integrated in a conventional linear accelerator (LINAC) ("TrueBeam"). TrueBeam and BodyTom showed good results, as the gamma pass rates of their dose distributions compared to the gold standard (dose distributions calculated from images acquired with a CT simulator) were above 97% in most cases. The O-arm yielded a lower percentage of voxels fulfilling gamma criteria owing to its reduced field of view (which left it prone to truncation artefacts). Our results show that the images acquired using a portable CT or even a LINAC with on-board kV CBCT could be used to estimate the dose of IOERT and improve the possibility to evaluate and register the treatment administered to the patient.
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