Orbital and Maxillofacial Computer Aided Surgery: Patient-Specific Finite Element Models To Predict Surgical Outcomes
Vincent Luboz, Matthieu Chabanas, Pascal Swider, Yohan Payan
Abstract
This paper addresses an important issue raised for the clinical relevance of Computer-Assisted Surgical applications, namely the methodology used to automatically build patient-specific Finite Element (FE) models of anatomical structures. From this perspective, a method is proposed, based on a technique called the Mesh-Matching method, followed by a process that corrects mesh irregularities. The Mesh-Matching algorithm generates patient-specific volume meshes from an existing generic model. The mesh regularization process is based on the Jacobian matrix transform related to the FE reference element and the current element. This method for generating patient-specific FE models is first applied to Computer-Assisted maxillofacial surgery, and more precisely to the FE elastic modelling of patient facial soft tissues. For each patient, the planned bone osteotomies (mandible, maxilla, chin) are used as boundary conditions to deform the FE face model, in order to predict the aesthetic outcome of the surgery. Seven FE patient-specific models were successfully generated by our method. For one patient, the prediction of the FE model is qualitatively compared with the patient's post-operative appearance, measured from a Computer Tomography scan. Then, our methodology is applied to Computer-Assisted orbital surgery. It is, therefore, evaluated for the generation of eleven patient-specific FE poroelastic models of the orbital soft tissues. These models are used to predict the consequences of the surgical decompression of the orbit. More precisely, an average law is extrapolated from the simulations carried out for each patient model. This law links the size of the osteotomy (i.e. the surgical gesture) and the backward displacement of the eyeball (the consequence of the surgical gesture).
Create a lesson
Related papers
Constrained estimation of rotational invariants of the cumulant expansion (RICE) for rapid tensor-valued diffusion MRI
Jinyang Yu, Oliver Gödicke, Frederik B. Laun et al.
Dose-PlanNet: Physics Based Radiotherapy Dose Prediction with Deep Learning
Ankit Bhattacharjee, Sougata Maity, Santam Chakraborty et al.
Sparse Delta Integration method for the calculation of spatiotemporal pressure fields of arbitrary ultrasound transducer geometries
Deyver E. Rivera, Charlie Demene, Mickael Tanter
Adapting the TG-43 formalism for use in Diffusing alpha-emitters Radiation Therapy
Guy Heger, Lior Epstein, Lior Arazi
Evaluation of the Exradin A30 Parallel Plate Ion Chamber as a Reference Dosimeter in Ultra-High Dose Rate (UHDR) Electron Beams
Mervat Alharbi, Kevin Liu, Brian Hooten et al.
Clustering of anterior corneal surface shapes in normal adults
Hala Bouazizi, Isabelle Brunette, Jean Meunier