Poster Open Access

TOWARDS A FRAMEWORK FOR PREDICTIVE MATHEMATICAL MODELING OF THE BIOMECHANICAL FORCES CAUSING BRAIN TUMOR MASS-EFFECT

Abler, Daniel; Rockne, Russell; Büchler , Philippe


MARC21 XML Export

<?xml version='1.0' encoding='UTF-8'?>
<record xmlns="http://www.loc.gov/MARC21/slim">
  <leader>00000nam##2200000uu#4500</leader>
  <datafield tag="041" ind1=" " ind2=" ">
    <subfield code="a">eng</subfield>
  </datafield>
  <controlfield tag="005">20190215164446.0</controlfield>
  <controlfield tag="001">1127747</controlfield>
  <datafield tag="711" ind1=" " ind2=" ">
    <subfield code="d">16-19 November 2017</subfield>
    <subfield code="g">SNO 2017</subfield>
    <subfield code="a">Annual Meeting of Society of Neuro-Oncology 2017</subfield>
    <subfield code="c">San Francisco, CA, USA</subfield>
  </datafield>
  <datafield tag="700" ind1=" " ind2=" ">
    <subfield code="u">Beckman Research Institute, City of Hope</subfield>
    <subfield code="a">Rockne, Russell</subfield>
  </datafield>
  <datafield tag="700" ind1=" " ind2=" ">
    <subfield code="u">University of Bern</subfield>
    <subfield code="a">Büchler , Philippe</subfield>
  </datafield>
  <datafield tag="856" ind1="4" ind2=" ">
    <subfield code="s">6287447</subfield>
    <subfield code="z">md5:db39390f1c84265780b1ea23680a0482</subfield>
    <subfield code="u">https://zenodo.org/record/1127747/files/2017-11_SNO_poster.pdf</subfield>
  </datafield>
  <datafield tag="542" ind1=" " ind2=" ">
    <subfield code="l">open</subfield>
  </datafield>
  <datafield tag="856" ind1="4" ind2=" ">
    <subfield code="y">Conference website</subfield>
    <subfield code="u">https://www.soc-neuro-onc.org/SNO/My_SNO/2017_SNO_Annual_Meeting/SNO/2017Annual/2017AnnualHome.aspx</subfield>
  </datafield>
  <datafield tag="260" ind1=" " ind2=" ">
    <subfield code="c">2017-11-06</subfield>
  </datafield>
  <datafield tag="909" ind1="C" ind2="O">
    <subfield code="p">openaire</subfield>
    <subfield code="o">oai:zenodo.org:1127747</subfield>
  </datafield>
  <datafield tag="100" ind1=" " ind2=" ">
    <subfield code="u">University of Bern / Beckman Research Institute, City of Hope</subfield>
    <subfield code="a">Abler, Daniel</subfield>
  </datafield>
  <datafield tag="245" ind1=" " ind2=" ">
    <subfield code="a">TOWARDS A FRAMEWORK FOR PREDICTIVE MATHEMATICAL MODELING OF THE BIOMECHANICAL FORCES CAUSING BRAIN TUMOR MASS-EFFECT</subfield>
  </datafield>
  <datafield tag="536" ind1=" " ind2=" ">
    <subfield code="c">753878</subfield>
    <subfield code="a">Patient-specific tumour growth model for quantification of mechanical 'markers' in malignant gliomas: Implications for treatment outcomes.</subfield>
  </datafield>
  <datafield tag="536" ind1=" " ind2=" ">
    <subfield code="c">600841</subfield>
    <subfield code="a">Computational Horizons In Cancer (CHIC): Developing Meta- and Hyper-Multiscale Models and Repositories for In Silico Oncology</subfield>
  </datafield>
  <datafield tag="540" ind1=" " ind2=" ">
    <subfield code="u">http://creativecommons.org/licenses/by/4.0/legalcode</subfield>
    <subfield code="a">Creative Commons Attribution 4.0 International</subfield>
  </datafield>
  <datafield tag="650" ind1="1" ind2="7">
    <subfield code="a">cc-by</subfield>
    <subfield code="2">opendefinition.org</subfield>
  </datafield>
  <datafield tag="520" ind1=" " ind2=" ">
    <subfield code="a">&lt;p&gt;GBMs present with different growth phenotypes, ranging from invasive lesions without notable mass-effect to strongly displacing lesions that induce mechanical stresses and result in healthy-tissue deformation, midline shift or herniation. Biomechanical forces, such as those resulting from displacive tumor growth, are recognized to shape the tumor environment and to contribute to tumor progression. We therefore expect that biomechanical forces exerted by lesions on the brain parenchyma have implications on the biophysical level, and that they may affect treatment response and outcome. To better understand the role of biomechanics in the formation of different GBM phenotypes we started developing a framework for the predictive mathematical modeling of mechanical tumor-healthy tissue interaction on the macroscopic level. The tumor&amp;rsquo;s mass-effect is represented by a solid-mechanics model of brain tissue that computes tumor-induced strain based on local tumor cell concentration. The framework allows to seed tumors at multiple locations in a human brain atlas. It simulates tumor evolution over time and across different brain regions using literature-based parameter estimates for tumor cell proliferation, as well as isotropic motility, and mechanical tissue properties. Despite its simplicity, the mathematical model yielded realistic estimates of the mechanical impact of a growing tumor on intra-cranial pressure. However, comparison to publicly available GBM imaging data showed that asymmetric shapes could not be reproduced by isotropic growth assumptions. Here we present and evaluate an extended version of this mechanically-coupled reaction-diffusion model that takes into account tissue anisotropies based on MRI diffusion tensor imaging (MR-DTI). Structural anisotropies in brain tissue have been found to affect the directionality of tumor cell migration and are critical to mechanical behavior. This makes them likely to play a role also in the development of GBM phenotypes.&lt;/p&gt;</subfield>
  </datafield>
  <datafield tag="773" ind1=" " ind2=" ">
    <subfield code="n">doi</subfield>
    <subfield code="i">isSupplementTo</subfield>
    <subfield code="a">10.1093/neuonc/nox168.999</subfield>
  </datafield>
  <datafield tag="773" ind1=" " ind2=" ">
    <subfield code="n">doi</subfield>
    <subfield code="i">isVersionOf</subfield>
    <subfield code="a">10.5281/zenodo.1127746</subfield>
  </datafield>
  <datafield tag="024" ind1=" " ind2=" ">
    <subfield code="a">10.5281/zenodo.1127747</subfield>
    <subfield code="2">doi</subfield>
  </datafield>
  <datafield tag="980" ind1=" " ind2=" ">
    <subfield code="a">poster</subfield>
  </datafield>
</record>
13
8
views
downloads
All versions This version
Views 1313
Downloads 88
Data volume 50.3 MB50.3 MB
Unique views 1111
Unique downloads 77

Share

Cite as