A novel soft tissue prediction methodology for orthognathic surgery based on probabilistic finite element modelling.
A novel soft tissue prediction methodology for orthognathic surgery based on probabilistic finite element modelling.
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DOI：
10.1371/journal.pone.0197209
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发表时间：
2018
期刊：
影响因子：
3.7
通讯作者：
Schievano S
中科院分区：
文献类型：
--
作者：
Knoops PGM;Borghi A;Ruggiero F;Badiali G;Bianchi A;Marchetti C;Rodriguez-Florez N;Breakey RWF;Jeelani O;Dunaway DJ;Schievano S
在正颌手术中，上颌的重新定位是为了功能和美观的目的。术前计划工具可以通过计算软组织对底层骨骼变化的反应来预测3D面部外观。商业预测软件的临床应用仍然存在争议，可能是由于这些计算预测的确定性。本文提出了一种用于面部术后软组织预测的概率有限元模型。在8名接受上颌复位并进行术前和术后锥形束计算机断层扫描（CBCT）的患者中建立了概率有限元模型并进行了验证。首先，变量相关性评估了各种建模参数。其次，实验设计（DOE）提供了基于均匀分布输入参数的一系列潜在结果，然后进行了优化。最后，第二次DOE迭代提供了具有概率范围的优化预测。使用概率FEM获得了一系列三维预测，并使用术后CBCT数据重建的软组织表面进行了验证。在鼻子和上唇区域的预测准确地包括了真实的术后位置，而预测低估了脸颊和下唇的位置。概率有限元法已被开发和验证用于预测面部外观后的正颌手术。该方法显示了建模的不准确性和执行手术计划的不确定性如何影响软组织预测，并提供了一系列预测，包括最小值和最大值，这可能有助于患者理解手术对面部的影响。
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.
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影响因子：
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