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Project Rhinodiagnost

SDL Engineering

Project duration

September, 1, 2017 - August, 31, 2020 (extended until December, 31, 2020)

Project partners

Funding

Rhinodiagnost is funded as a ZIM (Zentrales Innovationsprogramm Mittelstand) project by the Federal Ministry for Economic Affairs and Energy (BMWi) in Germany. The Austrian partner is funded by COIN (Cooperation and Innovation), Federal Ministry of Science, Research and Economy (BMWFW). The project runs under the auspices of IraSME (International research activities by SMEs).

Project description

Internationally recognized research centers and market-leading medical technology companies are cooperating via the Rhinodiagnost project in order to establish a coordinated morphological and functional diagnostics for ENT physicians. The Rhinodiagnost services shall be organized in a rapid network providing new, additional decision aids, such as 3D models and flow simulations, for ENT physicians and radiologists.

Approximately 11% of the European population suffer from a disability of nasal breathing or chronic inflammation of the nasal sinuses. In Germany, Austria and Switzerland, more than 100,000 operations are carried out on the nose or the nasal sinuses every year. The impairment of the quality of life (QoL) for these patients can be compared to the impairment of QoL for patients affected by chronic lung diseases or diabetes. In the US, some 500,000 operations are performed per year. The current diagnosis of nasal function is not sufficiently precise, which is the reason for a surgery error rate of between 10% and 40%.

The diagnostic quality is currently based primarily on the quality of the training of the practicing physician and his/her experience with clinical pictures. Functional diagnostics makes use of methods of medical imaging, such as computer or magnetic resonance tomography, in order to enable a well-founded diagnosis. Unfortunately, however, such analysis methods do not include any information on the respiratory comfort of a patient which is defined by flow-mechanical parameters. Frequently, rhinomanometry is used to determine the respiratory resistance when using inspiration in order to provide extended information about the patient’s respiratory capacity. Furthermore, current developments in the field of numerical flow mechanics and high-performance calculations allow for patient-individually computer-assisted flow predictions that can help to detect and limit the anatomical location of a pathology. The resultant information surplus allows the surgeons to even better adapt operation planning patient individually and to increase the chances of success for operations and treatment therapies. Unfortunately, due to their complexity and their costs, such methods have not yet been introduced into the day-to-day operations of hospitals.

In order to improve this situation, the implementation of a NOSE Service Center (NSC) is being prepared within this project. Rhinodiagnost will offer expanded possibilities of functional diagnostics and will provide a network of service points (National Relays).

Project publications with JSC involvement:

[1]Grosch, A., Waldmann, M., Göbbert, J. H., & Lintermann, A. (2021). A Web-Based Service Portal to Steer Numerical Simulations on High-Performance Computers. In T. Jarm, A. Cvetkoska, S. Mahnič-Kalamiza, & D. Miklavcic (Eds.), 8th European Medical and Biological Engineering Conference (EMBEC 2020), IFMBE Proceedings (Vol. 80, pp. 57–65). doi: 10.1007/978-3-030-64610-3_8
[2]Lintermann, A. (2020). Application of Computational Fluid Dynamics Methods to Understand Nasal Cavity Flows. In C. Cingi & N. B. Muluk (Eds.), All Around the Nose (1st ed., pp. 75–84). doi:10.1007/978-3-030-21217-9_106
[3]Lintermann, A. (2020). Computational Meshing for CFD Simulations. In K. Ithavong, N. Singh, E. Wong, & J. Tu (Eds.), Clinical and Biomedical Engineering in the Human Nose - A Computational Fluid Dynamics Approach (1st editio, pp. 85–115). doi:10.1007/978-981-15-6716-2_6
[4]Lintermann, A., & Schröder, W. (2020). Lattice–Boltzmann simulations for complex geometries on high-performance computers. CEAS Aeronautical Journal. doi:10.1007/s13272-020-00450-1
[5]Lintermann, A., Meinke, M., & Schröder, W. (2020). Zonal Flow Solver (ZFS): a highly efficient multi-physics simulation framework. International Journal of Computational Fluid Dynamics, 1–28. doi:10.1080/10618562.2020.1742328
[6]Waldmann, M., Lintermann, A., Choi, Y. J., & Schröder, W. (2020). Analysis of the Effects of MARME Treatment on Respiratory Flow Using the Lattice-Boltzmann Method. New Results in Numerical and Experimental Fluid Mechanics XII, 853–863. doi:10.1007/978-3-030-25253-3_80
[7]Grosch, A., Waldmann, M., Göbbert, J. H., & Lintermann, A. (2020). A Web-Based Service Portal to Steer Numerical Simulations on High-Performance Computers. 8th European Medical and Biological Engineering Conference, International Federation for Medical and Biological Engineering (IFMBE) Proceedings, submitted. Portorož, Slovenia: Springer Nature Switzerland AG.
[8]Lintermann, A., & Schröder, W. (2019). A Hierarchical Numerical Journey Through the Nasal Cavity: from Nose-Like Models to Real Anatomies. Flow, Turbulence and Combustion, 102(1), 89–116. doi.org:10.1007/s10494-017-9876-0
[9]Göbbert, J. H., Kreuzer, T., Grosch, A., Lintermann, A., & Riedel, M. (2018). Enabling Interactive Supercomputing at JSC Lessons Learned. In 33rd International Conference, ISC High Performance 2018, Lecture Notes in Computer Science (pp. 669–677). doi:10.1007/978-3-030-02465-9_48
[10]Kim, S.-Y., Park, Y.-C., Lee, K.-J., Lintermann, A., Han, S.-S., Yu, H.-S., & Choi, Y. J. (2018). Assessment of changes in the nasal airway after nonsurgical miniscrew-assisted rapid maxillary expansion in young adults. The Angle Orthodontist, 88(4), 435–441. doi:10.2319/092917-656.1
[11]Vogt, K., Bachmann-Harildstad, G., Wernecke, K.-D., Garyuk, O., Lintermann, A., Nechyporenko, A., & Peters, F. (2018). The new agreement of the international RIGA consensus conference on nasal airway function tests. Rhinology, 56(2), 133–143. doi:10.4193/Rhino17.084
[12]Lintermann, A., Göbbert, J. H., Vogt, K., Koch, W., & Hetzel, A. (2017). Rhinodiagnost - Morphological and functional precision diagnostics of nasal cavities. InSiDE, Innovatives Supercomputing in Deutschland, 15(2), 106–109.
[13]Lintermann, A. (2017). Strömende Bits und Bytes - Zusammenspiel von Höchstleistungsrechnern und Medizin. RWTH Themenheft, 20–28.
[14]Lintermann, A., Habbinga, S., & Göbbert, J. H. (2017). Comprehensive Visualization of Large-Scale Simulation Data Linked to Respiratory Flow Computations on HPC Systems. SC ’17: Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis, in press. Denver, Colorado, USA: ACM, New York, NY, USA.