@article{BrueningGoubergritsHepptetal., author = {Br{\"u}ning, Jan and Goubergrits, Leonid and Heppt, Werner and Zachow, Stefan and Hildebrandt, Thomas}, title = {Numerical Analysis of Nasal Breathing - A Pilot Study}, series = {Facial Plastic Surgery}, volume = {33}, journal = {Facial Plastic Surgery}, number = {4}, doi = {doi:10.1055/s-0037-1603789}, pages = {388 -- 395}, abstract = {Background: Currently, there is no fully sufficient way to differentiate between symptomatic and normal nasal breathing. Using the nose's total resistance is disputed as a valid means to objectify nasal airflow, and the need for a more comprehensive diagnostic method is increasing. This work's aim was to test a novel approach considering intranasal wall shear stress as well as static pressure maps obtained by computational fluid dynamics (CFD). Methods: X-ray computed tomography (CT) scan data of six symptom-free subjects and seven symptomatic patients were used. Patient-specific geometries of the nasal cavity were segmented from these data sets. Inspiratory and expiratory steady airflow simulations were performed using CFD. Calculated static pressures and wall shear stresses (WSS) were mapped onto a common template of the nasal septum, allowing for comparison of these parameters between the two patient groups. Results: Significant differences in wall shear stress distributions during the inspiratory phase could be identified between the two groups, whereas no differences were found for the expiratory phase. It is assumed that one essential feature of normal nasal breathing probably consists in distinctively different intranasal flow fields for inspiration and expiration. This is in accordance with previous investigations. Conclusion: The proposed method seems to be a promising tool for developing a new kind of patient-specific assessment of nasal breathing. However, more studies and a greater case number of data with an expanded focus, would be ideal.}, language = {en} } @article{HuttaryGoubergritsSchuetteetal., author = {Huttary, Rudolf and Goubergrits, Leonid and Sch{\"u}tte, Christof and Bernhard, Stefan}, title = {Simulation, Identification and Statistical Variation in Cardiovascular Analysis (SISCA) - a Software Framework for Multi-compartment Lumped Modeling}, series = {Computers in Biology and Medicine}, volume = {87}, journal = {Computers in Biology and Medicine}, doi = {10.1016/j.compbiomed.2017.05.021}, pages = {104 -- 123}, language = {en} }