<?xml version="1.0" encoding="utf-8"?>
<export-example>
  <doc>
    <id>7239</id>
    <completedYear/>
    <publishedYear>2019</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>9</pageFirst>
    <pageLast>13</pageLast>
    <pageNumber/>
    <edition/>
    <issue>1</issue>
    <volume>35</volume>
    <type>article</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2019-02-13</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">The Healthy Nasal Cavity - Characteristics of Morphology and Related Airflow Based on a Statistical Shape Model Viewed from a Surgeon’s Perspective</title>
    <abstract language="eng">Functional surgery on the nasal framework requires referential criteria to objectively assess nasal breathing for indication and follow-up. Thismotivated us to generate amean geometry of the nasal cavity based on a statistical shape model. In this study, the authors could demonstrate that the introduced nasal cavity’s mean geometry features characteristics of the inner shape and airflow, which are commonly observed in symptom-free subjects. Therefore, the mean geometry might serve as a reference-like model when one considers qualitative aspects. However, to facilitate quantitative considerations and statistical inference, further research is necessary. Additionally, the authorswere able to obtain details about the importance of the isthmus nasi and the inferior turbinate for the intranasal airstream.</abstract>
    <parentTitle language="eng">Facial Plastic Surgery</parentTitle>
    <identifier type="doi">10.1055/s-0039-1677721</identifier>
    <enrichment key="PeerReviewed">yes</enrichment>
    <enrichment key="AcceptedDate">2018-11-25</enrichment>
    <author>Thomas Hildebrandt</author>
    <submitter>Stefan Zachow</submitter>
    <author>Jan Joris Bruening</author>
    <author>Nora Laura Schmidt</author>
    <author>Hans Lamecker</author>
    <author>Werner Heppt</author>
    <author>Stefan Zachow</author>
    <author>Leonid Goubergrits</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>statistical shape model</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>nasal cavity</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>nasal breathing</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>nasal airflow</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>isthmus nasi</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>inferior turbinate</value>
    </subject>
    <collection role="institutes" number="vis">Visual Data Analysis</collection>
    <collection role="institutes" number="medplan">Therapy Planning</collection>
    <collection role="persons" number="lamecker">Lamecker, Hans</collection>
    <collection role="persons" number="zachow">Zachow, Stefan</collection>
    <collection role="projects" number="MODAL-MedLab">MODAL-MedLab</collection>
    <collection role="projects" number="Rhino-CFD">Rhino-CFD</collection>
    <collection role="projects" number="MODAL-Gesamt">MODAL-Gesamt</collection>
    <collection role="institutes" number="VDcC">Visual and Data-centric Computing</collection>
  </doc>
  <doc>
    <id>7240</id>
    <completedYear/>
    <publishedYear>2019</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>1</pageFirst>
    <pageLast>8</pageLast>
    <pageNumber/>
    <edition/>
    <issue>1</issue>
    <volume>35</volume>
    <type>article</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2019-02-13</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Digital Analysis of Nasal Airflow Facilitating Decision Support in Rhinosurgery</title>
    <abstract language="eng">Successful functional surgery on the nasal framework requires reliable and comprehensive diagnosis. In this regard, the authors introduce a new methodology: Digital Analysis of Nasal Airflow (diANA). It is based on computational fluid dynamics, a statistical shape model of the healthy nasal cavity and rhinologic expertise. diANA necessitates an anonymized tomographic dataset of the paranasal sinuses including the complete nasal cavity and, when available, clinical information. The principle of diANA is to compare the morphology and the respective airflow of an individual nose with those of a reference. This enablesmorphometric aberrations and consecutive flow field anomalies to localize and quantify within a patient’s nasal cavity. Finally, an elaborated expert opinion with instructive visualizations is provided. Using diANA might support surgeons in decision-making, avoiding unnecessary surgery, gaining more precision, and target-orientation for indicated operations.</abstract>
    <parentTitle language="eng">Facial Plastic Surgery</parentTitle>
    <identifier type="doi">10.1055/s-0039-1677720</identifier>
    <enrichment key="PeerReviewed">yes</enrichment>
    <enrichment key="AcceptedDate">2018-11-18</enrichment>
    <author>Thomas Hildebrandt</author>
    <submitter>Stefan Zachow</submitter>
    <author>Jan Joris Bruening</author>
    <author>Hans Lamecker</author>
    <author>Stefan Zachow</author>
    <author>Werner Heppt</author>
    <author>Nora Schmidt</author>
    <author>Leonid Goubergrits</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>nasal airflow simulation</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>nasal breathing</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>statistical shape model</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>diANA</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>nasal obstruction</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>rhinorespiratory homeostasis</value>
    </subject>
    <collection role="institutes" number="vis">Visual Data Analysis</collection>
    <collection role="institutes" number="medplan">Therapy Planning</collection>
    <collection role="persons" number="lamecker">Lamecker, Hans</collection>
    <collection role="persons" number="zachow">Zachow, Stefan</collection>
    <collection role="projects" number="MODAL-MedLab">MODAL-MedLab</collection>
    <collection role="projects" number="Rhino-CFD">Rhino-CFD</collection>
    <collection role="projects" number="MODAL-Gesamt">MODAL-Gesamt</collection>
    <collection role="institutes" number="VDcC">Visual and Data-centric Computing</collection>
  </doc>
  <doc>
    <id>7747</id>
    <completedYear/>
    <publishedYear>2020</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue>10</issue>
    <volume>3755</volume>
    <type>article</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2020-02-28</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Characterization of the Airflow within an Average Geometry of the Healthy Human Nasal Cavity</title>
    <abstract language="eng">This study’s objective was the generation of a standardized geometry of the healthy nasal cavity.&#13;
An average geometry of the healthy nasal cavity was generated using a statistical shape model based on 25 symptom-free subjects. Airflow within the average geometry and these geometries was calculated using fluid simulations. Integral measures of the nasal resistance, wall shear stresses (WSS) and velocities were calculated as well as cross-sectional areas (CSA). Furthermore, individual WSS and static pressure distributions were mapped onto the average geometry.&#13;
The average geometry featured an overall more regular shape that resulted in less resistance, reduced wall shear stresses and velocities compared to the median of the 25 geometries. Spatial distributions of WSS and pressure of average geometry agreed well compared to the average distributions of all individual geometries. The minimal CSA of the average geometry was larger than the median of all individual geometries (83.4 vs. 74.7 mm²).&#13;
The airflow observed within the average geometry of the healthy nasal cavity did not equal the average airflow of the individual geometries. While differences observed for integral measures were notable, the calculated values for the average geometry lay within the distributions of the individual parameters. Spatially resolved parameters differed less prominently.</abstract>
    <parentTitle language="eng">Scientific Reports</parentTitle>
    <identifier type="doi">10.1038/s41598-020-60755-3</identifier>
    <identifier type="url">https://rdcu.be/b2irD</identifier>
    <enrichment key="PeerReviewed">yes</enrichment>
    <enrichment key="AcceptedDate">17.02.2020</enrichment>
    <author>Jan Brüning</author>
    <submitter>Stefan Zachow</submitter>
    <author>Thomas Hildebrandt</author>
    <author>Werner Heppt</author>
    <author>Nora Schmidt</author>
    <author>Hans Lamecker</author>
    <author>Angelika Szengel</author>
    <author>Natalja Amiridze</author>
    <author>Heiko Ramm</author>
    <author>Matthias Bindernagel</author>
    <author>Stefan Zachow</author>
    <author>Leonid Goubergrits</author>
    <collection role="institutes" number="vis">Visual Data Analysis</collection>
    <collection role="institutes" number="medplan">Therapy Planning</collection>
    <collection role="persons" number="lamecker">Lamecker, Hans</collection>
    <collection role="persons" number="zachow">Zachow, Stefan</collection>
    <collection role="projects" number="Rhino-CFD">Rhino-CFD</collection>
    <collection role="institutes" number="VDcC">Visual and Data-centric Computing</collection>
  </doc>
  <doc>
    <id>3603</id>
    <completedYear>2013</completedYear>
    <publishedYear>2013</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>93</pageFirst>
    <pageLast>98</pageLast>
    <pageNumber/>
    <edition/>
    <issue>2</issue>
    <volume>29</volume>
    <type>article</type>
    <publisherName>Thieme</publisherName>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Evaluation of the Intranasal Flow Field through Computational Fluid Dynamics (CFD)</title>
    <parentTitle language="eng">Journal of Facial and Plastic Surgery</parentTitle>
    <identifier type="doi">10.1055/s-0033-1341591</identifier>
    <identifier type="url">https://www.thieme-connect.de/DOI/DOI?10.1055/s-0033-1341591</identifier>
    <enrichment key="PeerReviewed">yes</enrichment>
    <author>Thomas Hildebrandt</author>
    <author>Leonid Goubergrits</author>
    <author>Werner Heppt</author>
    <author>Stefan Bessler</author>
    <author>Stefan Zachow</author>
    <collection role="institutes" number="vis">Visual Data Analysis</collection>
    <collection role="institutes" number="medplan">Therapy Planning</collection>
    <collection role="persons" number="zachow">Zachow, Stefan</collection>
    <collection role="projects" number="Rhino-CFD">Rhino-CFD</collection>
    <collection role="institutes" number="VDcC">Visual and Data-centric Computing</collection>
  </doc>
  <doc>
    <id>6390</id>
    <completedYear/>
    <publishedYear>2017</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>388</pageFirst>
    <pageLast>395</pageLast>
    <pageNumber>8</pageNumber>
    <edition/>
    <issue>4</issue>
    <volume>33</volume>
    <type>article</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Numerical Analysis of Nasal Breathing - A Pilot Study</title>
    <abstract language="eng">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).&#13;
&#13;
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.&#13;
&#13;
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. &#13;
&#13;
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.</abstract>
    <parentTitle language="eng">Facial Plastic Surgery</parentTitle>
    <identifier type="doi">doi:10.1055/s-0037-1603789</identifier>
    <enrichment key="PeerReviewed">yes</enrichment>
    <author>Jan Brüning</author>
    <submitter>Stefan Zachow</submitter>
    <author>Leonid Goubergrits</author>
    <author>Werner Heppt</author>
    <author>Stefan Zachow</author>
    <author>Thomas Hildebrandt</author>
    <collection role="institutes" number="vis">Visual Data Analysis</collection>
    <collection role="institutes" number="medplan">Therapy Planning</collection>
    <collection role="persons" number="zachow">Zachow, Stefan</collection>
    <collection role="projects" number="Rhino-CFD">Rhino-CFD</collection>
    <collection role="institutes" number="VDcC">Visual and Data-centric Computing</collection>
  </doc>
</export-example>
