Sonja Jäckle1, Tim Eixmann2, Hinnerk Schulz-Hildebrandt2,3,4, Gereon Hüttmann2,3,4, Torben Pätz5. 1. Fraunhofer MEVIS, Institute for Digital Medicine, Lübeck, Maria-Goeppert-Straße 3, 23562, Lübeck, Germany. sonja.jaeckle@mevis.fraunhofer.de. 2. Medical Laser Center Lübeck GmbH, Peter-Monnik-Weg 4, 23562, Lübeck, Germany. 3. Institute of Biomedical Optics, Universität zu Lübeck, Peter-Monnik-Weg 4, 23562, Lübeck, Germany. 4. German Center for Lung Research, DZL, Airways Research Center North, 22927, Großhansdorf, Germany. 5. Fraunhofer MEVIS, Institute for Digital Medicine, Bremen, Am Fallturm 1, 28359, Bremen, Germany.
Abstract
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.
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.
Authors: M Ourak; J Smits; L Esteveny; G Borghesan; A Gijbels; L Schoevaerdts; Y Douven; J Scholtes; E Lankenau; T Eixmann; H Schulz-Hildebrandt; G Hüttmann; M Kozlovszky; G Kronreif; K Willekens; P Stalmans; K Faridpooya; M Cereda; A Giani; G Staurenghi; D Reynaerts; E B Vander Poorten Journal: Int J Comput Assist Radiol Surg Date: 2018-07-28 Impact factor: 2.924
Authors: Mischa Megens; Merel D Leistikow; Anneke van Dusschoten; Martin B van der Mark; Jeroen J L Horikx; Elbert G van Putten; Gert W 't Hooft Journal: Med Phys Date: 2021-06-28 Impact factor: 4.506