Purpose Endovascular aortic repair procedures are currently conducted with 2D fluoroscopy imaging. Tracking systems based on fiber Bragg gratings are an emerging technology for the navigation of minimally invasive instruments which can reduce the X-ray exposure and the used contrast agent. Shape sensing of flexible structures is challenging and includes many calculations steps which are prone to different errors. To reduce this errors, we present an optimized shape sensing model. Methods We analyzed for every step of the shape sensing process, which errors can occur, how the error affects the shape and how it can be compensated or minimized. Experiments were done with one multicore fiber system with 38 cm sensing length, and the effects of different methods and parameters were analyzed. Furthermore, we compared 3D shape reconstructions with the segmented shape of the corresponding CT scans of the fiber to evaluate the accuracy of our optimized shape sensing model. Finally, we tested our model in a realistic endovascular scenario by using a 3D printed vessel system created from patient data. Results Depending on the complexity of the shape, we reached an average error of 0.35–1.15 mm and maximal error of 0.75–7.53 mm over the whole 38 cm sensing length. In the endovascular scenario, we obtained an average and maximal error of 1.13 mm and 2.11 mm, respectively. Conclusion The accuracies of the 3D shape sensing model are promising, and we plan to combine the shape sensing based on fiber Bragg gratings with the position and orientation of an electromagnetic tracking to obtain the located catheter shape.

Introduction: Endovascular 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.Methods: The 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.Results: During 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).Conclusion: The 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: During endovascular aneurysm repair (EVAR) procedures, medical instruments are guided with two-dimensional (2D) fluoroscopy and conventional digital subtraction angiography. However, this requires X-ray exposure and contrast agent is used, and the depth information is missing. To overcome these drawbacks, a three-dimensional (3D) guidance approach based on tracking systems is introduced and evaluated. Methods: A multicore fiber with fiber Bragg gratings for shape sensing and three electromagnetic (EM) sensors for locating the shape were integrated into a stentgraft system. A model for obtaining the located shape of the first 38 cm of the stentgraft system with two EM sensors is introduced and compared with a method based on three EM sensors. Both methods were evaluated with a vessel phantom containing a 3D-printed vessel made of silicone and agar-agar simulating the surrounding tissue. Results: The evaluation of the guidance methods resulted in average errors from 1.35 to 2.43 mm and maximum errors from 3.04 to 6.30 mm using three EM sensors, and average errors from 1.57 to 2.64 mm and maximum errors from 2.79 to 6.27 mm using two EM sensors. Moreover, the videos made from the continuous measurements showed that a real-time guidance is possible with both approaches. Conclusion: The results showed that an accurate real-time guidance with two and three EM sensors is possible and that two EM sensors are already sufficient. Thus, the introduced 3D guidance method is promising to use it as navigation tool in EVAR procedures. Future work will focus on developing a method with less EM sensors and a detailed latency evaluation of the guidance method.

Currently, uoroscopy and conventional digital subtraction angiography are used for imaging guidance in endovascular aortic repair (EVAR) procedures. Drawbacks of these image modalities are X-ray exposure, the usage of contrast agents and the lack of depth information. To overcome these disadvantages, a catheter prototype containing a multicore fiber with fiber Bragg gratings for shape sensing and three electromagnetic (EM) sensors for locating the shape was built in this study. Furthermore, a model for processing the input data from the tracking systems to obtain the located 3D shape of the first 38 cm of the catheter was introduced: A spatial calibration between the optical fiber and each EM sensor was made in a calibration step and used to obtain the located shape of the catheter in subsequent experiments. The evaluation of our shape localization method with the catheter prototype in different shapes resulted in average errors from 0.99 to 2.29 mm and maximum errors from 1.73 to 2.99 mm. The experiments showed that an accurate shape localization with a multicore fiber and three EM sensors is possible, and that this catheter guidance is promising for EVAR procedures. Future work will be focused on the development of catheter guidance based on shape sensing with a multicore fiber, and the orientation and position of less than three EM sensors.

In Germany, local health departments are responsible for surveillance of the current pandemic situation. One of their major tasks is to monitor infected persons. For instance, the direct contacts of infectious persons at group meetings have to be traced and potentially quarantined. Such quarantine requirements may be revoked, when all contact persons obtain a negative polymerase chain reaction (PCR) test result. However, contact tracing and testing is time-consuming, costly and not always feasible. In this work, we present a statistical model for the probability that no transmission of COVID-19 occurred given an arbitrary number of negative test results among contact persons. Hereby, the time-dependent sensitivity and specificity of the PCR test are taken into account. We employ a parametric Bayesian model which combines an adaptable Beta-Binomial prior and two likelihood components in a novel fashion. This is illustrated for group events in German school classes. The first evaluation on a real-world dataset showed that our approach can support important quarantine decisions with the goal to achieve a better balance between necessary containment of the pandemic and preservation of social and economic life. Future work will focus on further refinement and evaluation of quarantine decisions based on our statistical model.