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<export-example>
  <doc>
    <id>5799</id>
    <completedYear/>
    <publishedYear>2018</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>conferencepresentation</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2023-02-13</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Linking flow conditions in membrane oxygenators to arrangements of multimeric von-Willebrand-factor as indication for coagulation</title>
    <abstract language="eng">Introduction&#13;
Shear induced multimerisation of von-Willebrand-factor (vWF) is supposed to play an important role in coagulation inside extracorporeal membrane oxygenators. However, there is no proof that links observed vWF structures to computed or measured flow conditions.&#13;
&#13;
Methods&#13;
The structures of multimeric vWF fibers, observed in clinically used membrane oxygenators is examined using immunofluorescence microscopy (IFM) using Carstairs’ staining method (positive ethics committee vote). The flow around the membrane fibres inside the oxygenator is investigated in terms of shear rate, wall shear velocity and streamlines by using CFD (RANS, Carreau-Yasuda viscosity, geometry remodelled after high-resolution µCT-scans). By interpreting the histological and numerical results in this common context, indications for shear induced coagulation mechanisms can be identified.&#13;
&#13;
Results&#13;
The fibre structures of multimeric vWF build regular but not exactly symmetric formations around the contact face (CF) between the crosswise stacked oxygenator fibres (OF), see fig.1B, vWF marked red. Annular around the CF arranged, cells are likely to be found, see fig.1B, nuclei marked blue. &#13;
The computed streamlines around the OF show attached flow around the circular fibres. However, the irregular arrangement of real OF produce considerable cross flow between the interconnected neighbouring channels, in contrast to previous 2D-simulations. Thus, the CF are washed around closely by blood, also from neighbouring channels. The wall shear velocity streamlines form regular, slightly asymmetric shapes around the contact faces. The occurring maximum shear rates are in the range of 1,000 1/s.&#13;
Discussion&#13;
The shapes of vWF structures found in clinically used oxygenators match the computational results in terms of wall shear velocity and streamlines well. The accumulation of cells close to the CF can also be explained by fluid mechanics, as there are small shear gradients and slow velocities. However, occurring shear rates between OFs are too low to trigger multimerisation of vWF. That raises the question where in the circuit the actual activation of vWF is started and how, at least partly chained, vWF multimeres are attracted towards the OF surface. A next step will be the investigation of the actual shear rate triggered (or mediated) multimerisation of vWF. Towards this end, microfluidic experiments with shear triggered coagulation will be performed. Also of big interest is the computation of the flow situation in the oxygenator in proximity to chaining threads, which have been ignored in computations so far. However, first a realistic representation of the effective viscosity in computations is needed, which is not available yet.</abstract>
    <parentTitle language="eng">World Congress of Biomechanics 2018, Convention Centre Dublin, 8.-12. Juli 2018</parentTitle>
    <enrichment key="opus.source">publish</enrichment>
    <licence>Keine Lizenz - Es gilt das deutsche Urheberrecht: § 53 UrhG</licence>
    <author>Clemens Birkenmaier</author>
    <author>Lars Krenkel</author>
    <author>Karla Lehle</author>
    <collection role="institutes" number="FAKMB">Fakultät Maschinenbau</collection>
    <collection role="institutes" number="RCBE">Regensburg Center of Biomedical Engineering - RCBE</collection>
    <collection role="othforschungsschwerpunkt" number="16314">Lebenswissenschaften und Ethik</collection>
    <collection role="institutes" number="">Labor Biofluidmechanik</collection>
  </doc>
  <doc>
    <id>3491</id>
    <completedYear/>
    <publishedYear>2021</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject</type>
    <publisherName>CIMNE</publisherName>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Convolutional Neural Networks for Approximation of Internal Non-Newtonian Multiphase Flow Fields</title>
    <abstract language="eng">Neural networks (NNs) as an alternative method for universal approximation of differential equations have proven to be computationally efficient and still sufficiently accurate compared to established methods such as the finite volume method (FVM). Additionally, analysing weights and biases can give insights into the underlying physical laws. FVM and NNs are both based upon spacial discretisation. Since a Cartesian and equidistant grid is a raster graphics, image-to-image regression techniques can be used to predict phase velocity fields as well as particle and pressure distributions from simple mass flow boundary conditions. The impact of convolution layer depth and number of channels of a ConvolutionDeconvolution Regression Network (CDRN), on prediction performance of internal non-Newtownian multiphase flows is investigated. Parametric training data with 2055 sets is computed using FVM. To capture significant non-Newtownian effects of a particle-laden fluid (e.g. blood) flowing through small and non-straight channels, an Euler-Euler multiphase approach is used. The FVM results are normalized and mapped onto an equidistant grid as supervised learning target. The investigated NNs consist of n= {3, 5, 7} corresponding encoding/decoding blocks and different skip connections. Regardless of the convolution depth (i.e. number of blocks), the deepest spacial down-sampling via strided convolution is adjusted to result in a 1 × 1 × f · 2nfeature map, with f = {8, 16, 32}. The prediction performance expressed is as channel-averaged normalized root mean squared error (NRMSE). With a NRMSE of &lt; 2 · 10-3, the best preforming NN has f = 32 initial feature maps, a kernel size of k = 4, n = 5 blocks and dense skip connections. Average inference time from this NN takes &lt; 7 · 10-3s. Worst accuracy at NRMSE of approx 9 · 10-3is achieved without any skips, at k = 2, f = 16 and n = 3, but deployment takes only &lt; 2 · 10-3s Given an adequate training, the prediction accuracy improves with convolution depth, where more features have higher impact on deeper NNs. Due to skip connections and batch normalisation, training is similarly efficient, regardless of the depth. This is further improved by blocks with dense connections, but at the price of a drastically larger model. Depending on geometrical complexity, spacial resolution is critical, as it increases the number of learnables and memory requirements massively.</abstract>
    <parentTitle language="eng">14th World Congress on Computational Mechanics (WCCM), ECCOMAS Congress 2020: 19–24 July 2020, Paris, France</parentTitle>
    <identifier type="doi">10.23967/wccm-eccomas.2020.107</identifier>
    <enrichment key="opus.import.date">2022-04-10T10:02:46+00:00</enrichment>
    <enrichment key="opus.source">sword</enrichment>
    <enrichment key="opus.import.user">importuser</enrichment>
    <licence>Creative Commons - CC BY-NC-SA - Namensnennung - Nicht kommerziell -  Weitergabe unter gleichen Bedingungen 4.0 International</licence>
    <author>Clemens Birkenmaier</author>
    <author>Lars Krenkel</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Deep Learning</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Convolutional neural networks</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Non-Newtonian multiphase flow</value>
    </subject>
    <collection role="institutes" number="FAKMB">Fakultät Maschinenbau</collection>
    <collection role="institutes" number="RCBE">Regensburg Center of Biomedical Engineering - RCBE</collection>
    <collection role="institutes" number="RCHST">Regensburg Center of Health Sciences and Technology - RCHST</collection>
    <collection role="persons" number="krenkellbfmconf">Krenkel, Lars (Prof. Dr.), Präsentationen - Labor Biofluidmechanik</collection>
    <collection role="othforschungsschwerpunkt" number="16314">Lebenswissenschaften und Ethik</collection>
    <collection role="institutes" number="">Labor Biofluidmechanik</collection>
  </doc>
  <doc>
    <id>3164</id>
    <completedYear/>
    <publishedYear>2018</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>1</pageFirst>
    <pageLast>10</pageLast>
    <pageNumber/>
    <edition/>
    <issue>6</issue>
    <volume>13</volume>
    <type>article</type>
    <publisherName>PLOS</publisherName>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Life span of different extracorporeal membrane systems for severe respiratory failure in the clinical practice</title>
    <abstract language="eng">Over the past decade, veno-venous extracorporeal membrane oxygenation (vvECMO) has been increasingly utilized in respiratory failure in patients. This study presents our institution´s experience focusing on the life span of ECMO systems reflecting the performance of a particular system. A retrospective review of our ECMO database identified 461 adult patients undergoing vvECMO (2010-2017). Patients that required more than one system and survived the first exchange &gt;24 hours (n = 139) were included. Life span until the first exchange and exchange criteria were analyzed for all systems (PLS, Cardiohelp HLS-set, both Maquet Cardiopulmonary, Rastatt, Germany; Deltastream/Hilite7000LT, iLA-activve, Xenios/NovaLung, Heilbronn, Germany; ECC.O5, LivaNova, Mirandola, Italy). At our ECMO center, the frequency of a system exchange was 30%. The median (IQR) life span was 9 (6-12) days. There was no difference regarding the different systems (p = 0.145 and p = 0.108, respectively). However, the Deltastream systems were exchanged more frequently due to elective technical complications (e. g. worsened gas transfer, development of coagulation disorder, increased bleedings complications) compared to the other exchanged systems (p = 0.013). In summary, the used ECMO systems are safe and effective for acute respiratory failure. There is no evidence for the usage of a specific system. Only the increased predictability of an imminent exchange preferred the usage of a Deltastream system. However, the decision to use a particular system should not depend solely on the possible criteria for an exchange.</abstract>
    <parentTitle language="eng">PLOS ONE</parentTitle>
    <identifier type="doi">10.1371/journal.pone.0198392</identifier>
    <enrichment key="opus.import.date">2022-03-17T06:33:09+00:00</enrichment>
    <enrichment key="opus.source">sword</enrichment>
    <enrichment key="opus.import.user">importuser</enrichment>
    <enrichment key="BegutachtungStatus">peer-reviewed</enrichment>
    <licence>Creative Commons - CC BY - Namensnennung 4.0 International</licence>
    <author>Alois Philipp</author>
    <author>Filip de Somer</author>
    <author>Maik Foltan</author>
    <author>Andre Bredthauer</author>
    <author>Lars Krenkel</author>
    <author>Florian Zeman</author>
    <author>Karla Lehle</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Equipment Failure Analysis/statistics &amp; numerical data</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Extracorporeal Membrane Oxygenation/instrumentation</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Membrane/classification/standards/statistics &amp; numerical data</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Primary Health Care/statistics &amp; numerical data</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Respiratory Distress Syndrome/therapy</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Retrospective Studies</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Severity of Illness Index</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Time factors</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>MULTIDETECTOR COMPUTED-TOMOGRAPHY</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>THROMBOTIC DEPOSITS</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>ECMO SYSTEMS</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Flow</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>OXYGENATION</value>
    </subject>
    <collection role="ddc" number="610">Medizin und Gesundheit</collection>
    <collection role="institutes" number="FAKMB">Fakultät Maschinenbau</collection>
    <collection role="institutes" number="RCBE">Regensburg Center of Biomedical Engineering - RCBE</collection>
    <collection role="oaweg" number="">Gold Open Access- Erstveröffentlichung in einem/als Open-Access-Medium</collection>
    <collection role="othforschungsschwerpunkt" number="16314">Lebenswissenschaften und Ethik</collection>
    <collection role="institutes" number="">Labor Biofluidmechanik</collection>
    <collection role="persons" number="krenkellbfmpub">Krenkel, Lars (Prof. Dr.), Publikationen - Labor Biofluidmechanik</collection>
  </doc>
</export-example>
