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   <ow:Publication rdf:about="oai:ebiltegia.mondragon.edu:20.500.11984/1101">
      <dc:title>A novel soft tissue prediction methodology for orthognathic surgery based on probabilistic finite element modelling</dc:title>
      <dc:creator>RODRIGUEZ-FLOREZ, NAIARA</dc:creator>
      <dc:contributor>Knoops, P.G.M.</dc:contributor>
      <dc:contributor>Schievano, S.</dc:contributor>
      <dc:contributor>Dunaway, D.</dc:contributor>
      <dc:contributor>Jeelani, O.</dc:contributor>
      <dc:contributor>Marchetti, Claudio</dc:contributor>
      <dc:contributor>Breakey, Richard W. F.</dc:contributor>
      <dc:contributor>Bianchi, Alberto</dc:contributor>
      <dc:contributor>Borghi, Alessandro</dc:contributor>
      <dc:contributor>Ruggiero, Federica</dc:contributor>
      <dc:contributor>Badiali, Giovanni</dc:contributor>
      <dc:subject>maxillofacial surgery</dc:subject>
      <dc:subject>simulation</dc:subject>
      <dc:subject>deformations</dc:subject>
      <dc:subject>distraction</dc:subject>
      <dc:subject>validation</dc:subject>
      <dc:subject>deformity</dc:subject>
      <dc:subject>cartilage</dc:subject>
      <dc:subject>accuracy</dc:subject>
      <dc:subject>system</dc:subject>
      <dc:subject>skin</dc:subject>
      <dc:description>Repositioning of the maxilla in orthognathic surgery is carried out for functional and aesthetic&#xd;
purposes. Pre-surgical planning tools can predict 3D facial appearance by computing the&#xd;
response of the soft tissue to the changes to the underlying skeleton. The clinical use of&#xd;
commercial prediction software remains controversial, likely due to the deterministic nature&#xd;
of these computational predictions. A novel probabilistic finite element model (FEM) for the&#xd;
prediction of postoperative facial soft tissues is proposed in this paper. A probabilistic FEM&#xd;
was developed and validated on a cohort of eight patients who underwent maxillary repositioning&#xd;
and had pre- and postoperative cone beam computed tomography (CBCT) scans&#xd;
taken. Firstly, a variables correlation assessed various modelling parameters. Secondly, a&#xd;
design of experiments (DOE) provided a range of potential outcomes based on uniformly&#xd;
distributed input parameters, followed by an optimisation. Lastly, the second DOE iteration&#xd;
provided optimised predictions with a probability range. A range of 3D predictions was&#xd;
obtained using the probabilistic FEM and validated using reconstructed soft tissue surfaces&#xd;
from the postoperative CBCT data. The predictions in the nose and upper lip areas accurately&#xd;
include the true postoperative position, whereas the prediction under-estimates the&#xd;
position of the cheeks and lower lip. A probabilistic FEM has been developed and validated&#xd;
for the prediction of the facial appearance following orthognathic surgery. This method&#xd;
shows how inaccuracies in the modelling and uncertainties in executing surgical planning&#xd;
influence the soft tissue prediction and it provides a range of predictions including a minimum&#xd;
and maximum, which may be helpful for patients in understanding the impact of surgery&#xd;
on the face.</dc:description>
      <dc:date>2018-07-27T15:18:33Z</dc:date>
      <dc:date>2018-07-27T15:18:33Z</dc:date>
      <dc:date>2018</dc:date>
      <dc:type>http://purl.org/coar/resource_type/c_6501</dc:type>
      <dc:identifier>1932-6203</dc:identifier>
      <dc:identifier>https://katalogoa.mondragon.edu/janium-bin/janium_login_opac.pl?find&amp;ficha_no=147714</dc:identifier>
      <dc:identifier>https://hdl.handle.net/20.500.11984/1101</dc:identifier>
      <dc:language>eng</dc:language>
      <dc:rights>Attribution 4.0 International</dc:rights>
      <dc:rights>http://creativecommons.org/licenses/by/4.0/</dc:rights>
      <dc:rights>© 2018 Knoops et al.</dc:rights>
      <dc:publisher>PLOS</dc:publisher>
   </ow:Publication>
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