2026-04-08T19:45:17Zhttps://ebiltegia.mondragon.edu/oai/requestoai:ebiltegia.mondragon.edu:20.500.11984/11012024-03-04T11:33:12Zcom_20.500.11984_473col_20.500.11984_478
eBiltegia
author
RODRIGUEZ-FLOREZ, NAIARA
other
Knoops, P.G.M.
other
Schievano, S.
other
Dunaway, D.
other
Jeelani, O.
other
Marchetti, Claudio
other
Breakey, Richard W. F.
other
Bianchi, Alberto
other
Borghi, Alessandro
other
Ruggiero, Federica
other
Badiali, Giovanni
2018-07-27T15:18:33Z
2018-07-27T15:18:33Z
2018
1932-6203
https://katalogoa.mondragon.edu/janium-bin/janium_login_opac.pl?find&ficha_no=147714
https://hdl.handle.net/20.500.11984/1101
Repositioning of the maxilla in orthognathic surgery is carried out for functional and aesthetic
purposes. Pre-surgical planning tools can predict 3D facial appearance by computing the
response of the soft tissue to the changes to the underlying skeleton. The clinical use of
commercial prediction software remains controversial, likely due to the deterministic nature
of these computational predictions. A novel probabilistic finite element model (FEM) for the
prediction of postoperative facial soft tissues is proposed in this paper. A probabilistic FEM
was developed and validated on a cohort of eight patients who underwent maxillary repositioning
and had pre- and postoperative cone beam computed tomography (CBCT) scans
taken. Firstly, a variables correlation assessed various modelling parameters. Secondly, a
design of experiments (DOE) provided a range of potential outcomes based on uniformly
distributed input parameters, followed by an optimisation. Lastly, the second DOE iteration
provided optimised predictions with a probability range. A range of 3D predictions was
obtained using the probabilistic FEM and validated using reconstructed soft tissue surfaces
from the postoperative CBCT data. The predictions in the nose and upper lip areas accurately
include the true postoperative position, whereas the prediction under-estimates the
position of the cheeks and lower lip. A probabilistic FEM has been developed and validated
for the prediction of the facial appearance following orthognathic surgery. This method
shows how inaccuracies in the modelling and uncertainties in executing surgical planning
influence the soft tissue prediction and it provides a range of predictions including a minimum
and maximum, which may be helpful for patients in understanding the impact of surgery
on the face.
eng
© 2018 Knoops et al.
maxillofacial surgery
simulation
deformations
distraction
validation
deformity
cartilage
accuracy
system
skin
A novel soft tissue prediction methodology for orthognathic surgery based on probabilistic finite element modelling
http://purl.org/coar/resource_type/c_6501
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URL
http://ebiltegia.mondragon.edu/xmlui/bitstream/20.500.11984/1101/1/journal.pone.0197209.pdf
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http://ebiltegia.mondragon.edu/xmlui/bitstream/20.500.11984/1101/4/journal.pone.0197209.pdf.txt
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