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Design for Mass Adaptation of the Neurointerventional Training Model HANNES with Patient-Specific Aneurysm Models

Published online by Cambridge University Press:  26 July 2019

Johanna Spallek
Affiliation:
Hamburg University of Technology;
Juliane Kuhl*
Affiliation:
Hamburg University of Technology;
Nadine Wortmann
Affiliation:
Hamburg University of Technology;
Jan-Hendrik Buhk
Affiliation:
University Medical Center Hamburg-Eppendorf
Andreas Maximilian Frölich
Affiliation:
University Medical Center Hamburg-Eppendorf
Marie Teresa Nawka
Affiliation:
University Medical Center Hamburg-Eppendorf
Anna Kyselyova
Affiliation:
University Medical Center Hamburg-Eppendorf
Jens Fiehler
Affiliation:
University Medical Center Hamburg-Eppendorf
Dieter Krause
Affiliation:
Hamburg University of Technology;
*
Contact: Kuhl, Juliane, Hamburg University of Technology, Institute of Product, Development and Mechanical Engineering Design, Germany, juliane.kuhl@tuhh.de

Abstract

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A neurointerventional training model called HANNES (Hamburg ANatomical NEurointerventional Simulator) has been developed to replace animal models in catheter-based aneurysm treatment training. A methodical approach to design for mass adaptation is applied so that patient-specific aneurysm models can be designed recurrently based on real patient data to be integrated into the training system.

HANNES’ modular product structure designed for mass adaptation consists of predefined and individualized modules that can be combined for various training scenarios. Additively manufactured, individualized aneurysm models enable high reproducibility of real patient anatomies. Due to the implementation of a standardized individualization process, order-related adaptation can be realized for each new patient anatomy with modest effort. The paper proves how the application of design for mass adaptation leads to a well-designed modular product structure of the neurointerventional training model HANNES, which supports quality treatment and provides an animal-free and patient-specific training environment.

Type
Article
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
Copyright
© The Author(s) 2019

References

Berlis, A. (2017), “Endovaskuläre Behandlung von Hirn-Aneurysmen Hirn- Aneurysma/ Angiom”, in: Berlis, A. and Schneebauer, C. (Eds.), Kompendium für Betroffene, Angehörige und Interessierte, Association for brain aneurysm sufferers, Der Lebenszweig e.V. (own publishing house), http://www.hirn-aneurysma.de/files/redakteur/Kompendium%20Testseiten.pdf, accessed date 29.11.2018Google Scholar
Blees, C., Jonas, H. and Krause, D. (2010), “Development of modular product families”, 12th International DSM Conference, Cambridge, 22-23 July 2010, Carl-Hanser-Verlag, Munich, pp. 169182Google Scholar
Bouzeghrane, F., Naggara, O., Kallmes, D.F., Berenstein and, A. and Raymond, J. (2010), “In vivo experimental intracranial aneurysm models: a systematic review”, American Journal of Neuroradiology, March 2010, Vol. 31 No. 3, pp. 418423, https://doi.org/10.3174/ajnr.A1853Google Scholar
FAIN-Biomedical (2018), Endovascular Surgery Training-Evaluation-Simulation EVE EndoVascular Evaluator, http://fain-biomedical.com/fbm_wp/wp-content/themes/fbm_ns/images/pdf/eve_fbm_e.pdf, accessed date 29.11.2018Google Scholar
Fiehler, J. (2012), “Nicht rupturierte intrakranielle aneurysmen: wann suchen, wann behandeln?RöFo : Fortschritte auf dem Gebiete der Röntgenstrahlen und der Nuklearmedizin, Vol. 184 No. 2, Georg Thieme Verlag KG, Stuttgart, pp. 97104, https://doi.org/10.1055/s-0031-1281984Google Scholar
Frölich, A.M.J., Spallek, J., Brehmer, L., Buhk, J.-H., Krause, D., Fiehler, J. and Kemmling, A. (2015), “3D printing of intracranial aneurysms using fused deposition modeling offers highly accurate replications”, AJNR American Journal of Neuroradiology, originally published online on August 20, 2015, https://doi.org/10.3174/ajnr.A4486Google Scholar
Hacke, W. and Poeck, K. (2010), Neurologie: Mit 83 Tabelle, 13th completely revised edition, Springer-Medizin-Verlag, Heidelberg, https://doi.org/10.1007/978-3-662-46892-0Google Scholar
Ionita, C.N., Mokin, M., Varble, N., Bednarek, D.R., Xiang, J., Snyder, K.V., Siddiqui, A.H., Levy, E.I., Meng, H. and Rudin, S. (2014), “Challenges and limitations of patient-specific vascular phantom fabrication using 3D Polyjet printing”, SPIE--the International Society for Optical Engineering, Vol. 9038 p. 90380M., https://doi.org/10.1117/12.2042266Google Scholar
Kipp, T. (2012), “Methodische unterstützung der variantengerechten produktgestaltung”.Dissertation TU Hamburg-Harburg, TuTech Verlag Hamburg, Hamburger Schriftenreihe Produktentwicklung und Konstruktionstechnik, Band 4, ISBN 978-3-941492-47-9Google Scholar
Krause, D. and Gebhardt, N. (2018), Methodische Entwicklung modularer Produktfamilien - Hohe Produktvielfalt beherrschbar entwickeln, Springer-Verlag, Hamburg, 2018, https://doi.org/10.1007/978-3-662-53040-5Google Scholar
Krause, D., Spallek, J., Blees, C. and Kipp, T. (2018), “Modulare Produktstrukturierung”, In: Rieg, F. and Steinhilper, R. (Ed.), Handbuch Konstruktion, Carl Hanser Verlag, München, pp. 719741, https://doi.org/10.3139/9783446434035Google Scholar
Nawka, M. T., Fiehler, J., Spallek, J., Buhk, J.-H. and Frölich, A.M. (2018), “Current status of training environments in neuro-interventional practice: are animal models still contemporary?”, Journal of Neurointerventional Surgery, 2018 Jul 26, https://doi.org/10.1136/neurintsurg-2018-014036Google Scholar
Neequaye, S. K., Aggarwal, R.,Van Herzeele, I., Darzi, A. and Cheshire, N.J. (2017), “Endovascular skills training and assessment”, Journal of vascular surgery, Vol. 46, pp. 10551064, https://doi.org/10.1016/j.jvs.2007.05.041Google Scholar
Rudberg, M. and Wikner, J. (2004), “Mass customization in terms of the customer order decoupling point”, Production Planning & Control Vol. 15 No. 4, S. 445458. https://doi.org/10.1080/0953728042000238764.Google Scholar
Russ, M., O'Hara, R., Setlur Nagesh, S. V., Mokin, M., Jimenez, C., Siddiqui, A., Bednarek, D., Rudin, S. and Ionita, C. (2015), “Treatment planning for image-guided neuro-vascular interventions using patient-specific 3d printed phantoms”, Proceedings of SPIE--the International Society for Optical Engineering 9417Google Scholar
Russell, W.M.S. and Burch, R.L. (1959), The Principles of Humane Experimental Technique, Methuen, LondonGoogle Scholar
Schmidt, P. (2018), “Konzeptentwicklung einer röntgenfreien trainingsumgebung für aneurysmabehandlungen”, Master Thesis at the Institute of Product Development and Mechanical Engineering Design, Hamburg University of TechnologyGoogle Scholar
Simgen, A., Junk, D. and Reith, W. (2012), “Flow diverter. eine neue therapiemöglichkeit für intrakranielle aneurysmen”, Der Radiologe, Vol. 52 No. 12, pp. 11181124Google Scholar
Simbionix USA Corporation (2017), ANGIO Mentor. The Most Advanced Endovascular Training, URL: http://simbionix.com/simulators/angio-mentor/, accessed date 29.11.2018Google Scholar
Spallek, J., Frölich, A., Buhk, J.H., Fiehler, J. and Krause, D. (2016a), “Comparing technologies of additive manufacturing for the development of vascular models”, Fraunhofer Direct Digital Manufacturing Conference DDMC, Fraunhofer Verlag, Berlin.Google Scholar
Spallek, J. and Krause, D. (2016b), “Process types of customisation and personalisation in design for additive manufacturing applied to vascular models”, 26th CIRP Design Conference, Vol. 50, Procedia CIRP, Elsevier, pp. 281286, http://doi.org/10.1016/j.procir.2016.05.022Google Scholar
Spallek, J., Sankowski, O. and Krause, D. (2016c), “Influences of additive manufacturing on design processes for customised products”, 14th International Design Conference - DESIGN 2016, Cavtat, Dubrovnik, Croatia, pp. 513522, https://doi.org/10.13140/RG.2.1.1112.4080Google Scholar
Vascular Simulations (2018), Optimize Your Performance, https://vascularsimulations.com/technology/, accessed date 29.11.2018Google Scholar