An eFTD-VP framework for efficiently generating patient-specific anatomically detailed facial soft tissue FE mesh for craniomaxillofacial surgery simulation

Accurate surgical planning and prediction of craniomaxillofacial surgery outcome requires simulation of soft tissue changes following osteotomy. This can only be achieved by using an anatomically detailed facial soft tissue model. The current state-of-the-art of model generation is not appropriate to clinical applications due to the time-intensive nature of manual segmentation and volumetric mesh generation. The conventional patient-specific finite element (FE) mesh generation methods are to deform a template FE mesh to match the shape of a patient based on registration. However, these methods commonly produce element distortion. Additionally, the mesh density for patients depends on that of the template model. It could not be adjusted to conduct mesh density sensitivity analysis. In this study, we propose a new framework of patient-specific facial soft tissue FE mesh generation. The goal of the developed method is to efficiently generate a high-quality patient-specific hexahedral FE mesh with adjustable mesh density while preserving the accuracy in anatomical structure correspondence. Our FE mesh is generated by eFace template deformation followed by volumetric parametrization. First, the patient-specific anatomically detailed facial soft tissue model (including skin, mucosa, and muscles) is generated by deforming an eFace template model. The adaptation of the eFace template model is achieved by using a hybrid landmark-based morphing and dense surface fitting approach followed by a thin-plate spline interpolation. Then, high-quality hexahedral mesh is constructed by using volumetric parameterization. The user can control the resolution of hexahedron mesh to best reflect clinicians’ need. Our approach was validated using 30 patient models and 4 visible human datasets. The generated patient-specific FE mesh showed high surface matching accuracy, element quality, and internal structure matching accuracy. They can be directly and effectively used for clinical simulation of facial soft tissue change.     

The mesh-matching algorithm: an automatic 3D mesh generator for finite element structures

Several authors have employed finite element analysis for stress and strain analysis in orthopaedic biomechanics. Unfortunately, the definition of three-dimensional models is time consuming (mainly because of the manual 3D meshing process) and consequently the number of analyses to be performed is limited. The authors have investigated a new patient-specific method allowing automatically 3D mesh generation for structures as complex as bone for example. This method, called the mesh-matching (M-M) algorithm, generated automatically customized 3D meshes of anatomical structures from an already existing model. The M-M algorithm has been used to generate FE models of 10 proximal human femora from an initial one which had been experimentally validated. The automatically generated meshes seemed to demonstrate satisfying results.     

The use of sparse CT datasets for auto-generating accurate FE models of the femur and pelvis

The finite element (FE) method when coupled with computed tomography (CT) is a powerful tool in orthopaedic biomechanics. However, substantial data is required for patient-specific modelling. Here we present a new method for generating a FE model with a minimum amount of patient data. Our method uses high order cubic Hermite basis functions for mesh generation and least-square fits the mesh to the dataset. We have tested our method on seven patient data sets obtained from CT assisted osteodensitometry of the proximal femur. Using only 12 CT slices we generated smooth and accurate meshes of the proximal femur with a geometric root mean square (RMS) error of less than 1 mm and peak errors less than 8 mm. To model the complex geometry of the pelvis we developed a hybrid method which supplements sparse patient data with data from the visible human data set. We tested this method on three patient data sets, generating FE meshes of the pelvis using only 10 CT slices with an overall RMS error less than 3 mm. Although we have peak errors about 12 mm in these meshes, they occur relatively far from the region of interest (the acetabulum) and will have minimal effects on the performance of the model. Considering that linear meshes usually require about 70-100 pelvic CT slices (in axial mode) to generate FE models, our method has brought a significant data reduction to the automatic mesh generation step. The method, that is fully automated except for a semi-automatic bone/tissue boundary extraction part, will bring the benefits of FE methods to the clinical environment with much reduced radiation risks and data requirement.     

3-D finite element modelling of facial soft tissue and preliminary application in orthodontics

Prediction of soft tissue aesthetics is important for achieving an optimal outcome in orthodontic treatment planning. Previously, applicable procedures were mainly restricted to 2-D profile prediction. In this study, a generic 3-D finite element (FE) model of the craniofacial soft and hard tissue was constructed, and individualisation of the generic model based on cone beam CT data and mathematical transformation was investigated. The result indicated that patient-specific 3-D facial FE model including different layers of soft tissue could be obtained through mathematical model transformation. Average deviation between the transformed model and the real reconstructed one was 0.47?±?0.77?mm and 0.75?±?0.84?mm in soft and hard tissue, respectively. With boundary condition defined according to treatment plan, such FE model could be used to predict the result of orthodontic treatment on facial soft tissue.     

From high-resolution CT data to finite element models: development of an integrated modular framework

This work introduces a novel method of automating the process of patient-specific finite element (FE) model development using a mapped mesh technique. The objective is to map a predefined mesh (template) of high quality directly onto a new bony surface (target) definition, thereby yielding a similar mesh with minimal user interaction. To bring the template mesh into correspondence with the target surface, a deformable registration technique based on the FE method has been adopted. The procedure has been made hierarchical allowing several levels of mesh refinement to be used, thus reducing the time required to achieve a solution. Our initial efforts have focused on the phalanx bones of the human hand. Mesh quality metrics, such as element volume and distortion were evaluated. Furthermore, the distance between the target surface and the final mapped mesh were measured. The results have satisfactorily proven the applicability of the proposed method.     

Magnetic Resonance Image-Based Modeling for Neurosurgical Interventions

Surgeries such as implantation of deep brain stimulation devices require accurate placement of devices within the brain. Because placement affects performance, image guidance and robotic assistance techniques have been widely adopted. These methods require accurate prediction of brain deformation during and following implantation. In this study, a magnetic resonance (MR) image-based finite element (FE) model was proposed by using a coupled Eulerian-Lagrangian method. Anatomical accuracy was achieved by mapping image voxels directly to the volumetric mesh space. The potential utility was demonstrated by evaluating the effect of different surgical approaches on the deformation of the corpus callosum (CC) region. The results showed that the maximum displacement of the corpus callosum increase with an increase of interventional angle with respect to the midline. The maximum displacement of the corpus callosum for different interventional locations was predicted, which is related to the brain curvature and the distance between the interventional area and corpus callosum (CC). The estimated displacement magnitude of the CC region followed those obtained from clinical observations. The proposed method provided an automatic pipeline for generating realistic computational models for interventional surgery. Results also demonstrated the potential of constructing patient-specific models for image-guided, robotic neurological surgery.     

Automated hexahedral meshing of anatomic structures using deformable registration

This work introduces a novel method of automating the process of patient-specific finite element (FE) model development using a mapped mesh technique. The objective is to map a predefined mesh (template) of high quality directly onto a new bony surface (target) definition, thereby yielding a similar mesh with minimal user interaction. To bring the template mesh into correspondence with the target surface, a deformable registration technique based on the FE method has been adopted. The procedure has been made hierarchical allowing several levels of mesh refinement to be used, thus reducing the time required to achieve a solution. Our initial efforts have focused on the phalanx bones of the human hand. Mesh quality metrics, such as element volume and distortion were evaluated. Furthermore, the distance between the target surface and the final mapped mesh were measured. The results have satisfactorily proven the applicability of the proposed method.     

3-D finite element modelling of facial soft tissue and preliminary application in orthodontics

Prediction of soft tissue aesthetics is important for achieving an optimal outcome in orthodontic treatment planning. Previously, applicable procedures were mainly restricted to 2-D profile prediction. In this study, a generic 3-D finite element (FE) model of the craniofacial soft and hard tissue was constructed, and individualisation of the generic model based on cone beam CT data and mathematical transformation was investigated. The result indicated that patient-specific 3-D facial FE model including different layers of soft tissue could be obtained through mathematical model transformation. Average deviation between the transformed model and the real reconstructed one was 0.47 ± 0.77 mm and 0.75 ± 0.84 mm in soft and hard tissue, respectively. With boundary condition defined according to treatment plan, such FE model could be used to predict the result of orthodontic treatment on facial soft tissue.     

Finite element simulations of a hip joint with femoroacetabular impingement

In this study, a three-dimensional finite element (FE) model based on the specific anatomy of a patient presenting a femoroacetabular impingement of the ‘cam’-type is developed. The FE meshes of the structures of interest are obtained from arthrographic magnetic resonance images. All soft tissues are considered linear elastic and isotropic, and the bones were assumed rigid. A compression of the femur on the acetabular cavity as well as flexural movements and internal rotations are applied. Stresses and contact pressures are evaluated in this patient-specific model in order to better interpret the mechanism of aggression of the femoral and acetabular cartilages. The corresponding results are presented and discussed. The values obtained for the contact pressures are similar to those reported by other models based on idealised geometries. An FE analysis of a non-cam hip is also performed for comparison with the pathological case.     

Patient-specific finite element model of the spine and spinal cord to assess the neurological impact of scoliosis correction: preliminary application on two cases with and without intraoperative neurological complications

Scoliosis is a 3D deformation of the spine and rib cage. For severe cases, surgery with spine instrumentation is required to restore a balanced spine curvature. This surgical procedure may represent a neurological risk for the patient, especially during corrective maneuvers. This study aimed to computationally simulate the surgical instrumentation maneuvers on a patient-specific biomechanical model of the spine and spinal cord to assess and predict potential damage to the spinal cord and spinal nerves. A detailed finite element model (FEM) of the spine and spinal cord of a healthy subject was used as reference geometry. The FEM was personalized to the geometry of the patient using a 3D biplanar radiographic reconstruction technique and 3D dual kriging. Step by step surgical instrumentation maneuvers were simulated in order to assess the neurological risk associated to each maneuver. The surgical simulation methodology implemented was divided into two parts. First, a global multi-body simulation was used to extract the 3D displacement of six vertebral landmarks, which were then introduced as boundary conditions into the personalized FEM in order to reproduce the surgical procedure. The results of the FEM simulation for two cases were compared to published values on spinal cord neurological functional threshold. The efficiency of the reported method was checked considering one patient with neurological complications detected during surgery and one control patient. This comparison study showed that the patient-specific hybrid model reproduced successfully the biomechanics of neurological injury during scoliosis correction maneuvers.     

Meshless algorithm for soft tissue cutting in surgical simulation

Computation of soft tissue mechanical responses for surgery simulation and image-guided surgery has been dominated by the finite element (FE) method that utilises a mesh of interconnected elements as a computational grid. Shortcomings of such mesh-based discretisation in modelling of surgical cutting include high computational cost and the need for re-meshing in the vicinity of cutting-induced discontinuity. The meshless total Lagrangian adaptive dynamic relaxation (MTLADR) algorithm we present here does not exhibit such shortcomings, as it relies on spatial discretisation in a form of a cloud of nodes. The cutting-induced discontinuity is modelled solely through changes in nodal domains of influence, which is done through efficient implementation of the visibility criterion using the level set method. Accuracy of our MTLADR algorithm with visibility criterion is confirmed against the established nonlinear solution procedures available in the commercial FE code Abaqus.     

Predicting the subject-specific primary stability of cementless implants during pre-operative planning: preliminary validation of subject-specific finite-element models

Pre-operative planning help the surgeon in taking the proper clinical decision. The ultimate goal of this work is to develop numerical models that allow the surgeon to estimate the primary stability during the pre-operative planning session. The present study was aimed to validate finite-element (FE) models accounting for patient and prosthetic size and position as planned by the surgeon. For this purpose, the FE model of a cadaveric femur was generated starting from the CT scan and the anatomical position of a cementless stem derived by a skilled surgeon using a pre-operative CT-based planning simulation software. In-vitro experimental measurements were used as benchmark problem to validate the bone-implant relative micromotions predicted by the patient-specific FE model. A maximum torque in internal rotation of 11.4 Nm was applied to the proximal part of the hip stem. The error on the maximum predicted micromotion was 12% of the peak micromotion measured experimentally. The average error over the entire range of applied torques was only 7% of peak measurement. Hence, the present study confirms that it is possible to accurately predict the level of primary stability achieved for cementless stems using numerical models that account for patient specificity and surgical variability.     

A novel methodology for generating 3D finite element models of the hip from 2D radiographs

Finite element (FE) modelling has been proposed as a tool for estimating fracture risk and patient-specific FE models are commonly based on computed tomography (CT). Here, we present a novel method to automatically create personalised 3D models from standard 2D hip radiographs. A set of geometrical parameters of the femur were determined from seven a–p hip radiographs and compared to the 3D femoral shape obtained from CT as training material; the error in reconstructing the 3D model from the 2D radiographs was assessed. Using the geometry parameters as the input, the 3D shape of another 21 femora was built and meshed, separating a cortical and trabecular compartment. The material properties were derived from the homogeneity index assessed by texture analysis of the radiographs, with focus on the principal tensile and compressive trabecular systems. The ability of these FE models to predict failure load as determined by experimental biomechanical testing was evaluated and compared to the predictive ability of DXA. The average reconstruction error of the 3D models was 1.77 mm (±1.17 mm), with the error being smallest in the femoral head and neck, and greatest in the trochanter. The correlation of the FE predicted failure load with the experimental failure load was r²=64% for the reconstruction FE model, which was significantly better (p<0.05) than that for DXA (r²=24%). This novel method for automatically constructing a patient-specific 3D finite element model from standard 2D radiographs shows encouraging results in estimating patient-specific failure loads.     

Strategies towards rapid generation of forefoot model incorporating realistic geometry of metatarsals encapsulated into lumped soft tissues for personalized finite element analysis

Use of finite element (FE) foot model as a clinical diagnostics tool is likely to improve the specificity of foot injury predictions in the diabetic population. Here we proposed a novel workflow for rapid construction of foot FE model incorporating realistic geometry of metatarsals encapsulated into lumped forefoot’s soft tissues. Custom algorithms were implemented to perform unsupervised segmentation and mesh generation to directly convert CT data into a usable FE model. The automatically generated model provided higher efficiency and comparable numerical accuracy when compared to the model constructed using a traditional solid-based mesh process. The entire procedure uses MATLAB as the main platform, and makes the present approach attractive for creating personalized foot models to be used in clinical studies.     

Towards patient-specific medializing calcaneal osteotomy for adult flatfoot: a finite element study

Clinically in medializing calcaneal osteotomy (MCO), foot and ankle surgeons are facing difficulties in choosing appropriate surgical parameters due to the individual differences in deformities among flatfoot patients. Traditional cadaveric studies have provided important information regarding the biomechanical effects of tendons, ligaments, and plantar fascia, but limitations have been reached when dealing with individual differences and tailoring patient-specific surgeries. Therefore, this study aimed at implementing the finite element (FE) method to investigate the effect of different MCO parameters to help foot and ankle surgeons performing patient-specific surgeries. This study constructed FE models of a flatfoot and a healthy foot based on computed tomography (CT) images. After validating the FE models with experimental measurements, differences in plantar stress were compared between two models and a criterion was established for evaluating the performance of surgical simulations. Four MCO parameters were then studied through FE simulations. Results suggested that the transverse angle, β, and translation distance, d, affected surgical performance. Therefore, special attentions may be recommended when choosing these two parameters clinically. However, the sagittal angle, α, and osteotomy position, p, were found to have less effect on the MCO performance.     

Identification process based on shear wave propagation within a phantom using finite element modelling and magnetic resonance elastography

Magnetic resonance elastography (MRE), based on shear wave propagation generated by a specific driver, is a non-invasive exam performed in clinical practice to improve the liver diagnosis. The purpose was to develop a finite element (FE) identification method for the mechanical characterisation of phantom mimicking soft tissues investigated with MRE technique. Thus, a 3D FE phantom model, composed of the realistic MRE liver boundary conditions, was developed to simulate the shear wave propagation with the software ABAQUS. The assumptions of homogeneity and elasticity were applied to the FE phantom model. Different ranges of mesh size, density and Poisson's ratio were tested in order to develop the most representative FE phantom model. The simulated wave displacement was visualised with a dynamic implicit analysis. Subsequently, an identification process was performed with a cost function and an optimisation loop provided the optimal elastic properties of the phantom. The present identification process was validated on a phantom model, and the perspective will be to apply this method on abdominal tissues for the set-up of new clinical MRE protocols that could be applied for the follow-up of the effects of treatments.     

Finite element simulation of spinal deformities correction by in situ contouring technique

Biomechanical models have been proposed in order to simulate the surgical correction of spinal deformities. With these models, different surgical correction techniques have been examined: distraction and rod rotation. The purpose of this study was to simulate another surgical correction technique: the in situ contouring technique. In this way, a comprehensive three-dimensional Finite Element (FE) model with patient-specific geometry and patient-specific mechanical properties was used. The simulation of the surgery took into account elasto-plastic behavior of the rod and multiple moments loading and unloading representing the surgical maneuvers. The simulations of two clinical cases of hyperkyphosis and scoliosis were coherent with the surgeon's experience. Moreover, the results of simulation were compared to post-operative 3D measurements. The mean differences were under 5 degrees for vertebral rotations and 5 mm for spinal lines. These simulations open the way for future predictive tools for surgical planning.     

Computational modelling and optimisation of soft tissue outcome in cranio-maxillofacial surgery planning

Cranio-maxillofacial (CMF) surgery operations are associated with rearrangement of facial hard and soft tissues, leading to dramatic changes in facial geometry. Often, correction of the aesthetical patient's appearance is the primary objective of the surgical intervention. Due to the complexity of the facial anatomy and the biomechanical behaviour of soft tissues, the result of the surgical impact cannot always be predicted on the basis of surgeon's intuition and experience alone. Computational modelling of soft tissue outcome using individual tomographic data and consistent numerical simulation of soft tissue mechanics can provide valuable information for surgeons during the planning stage. In this article, we present a general framework for computer-assisted planning of CMF surgery interventions that is based on the reconstruction of patient's anatomy from 3D computer tomography images and finite element analysis of soft tissue deformations. Examples from our clinical case studies that deal with the solution of direct and inverse surgical problems (i.e. soft tissue prediction, inverse implant shape design) demonstrate that the developed approach provides a useful tool for accurate prediction and optimisation of aesthetic surgery outcome.     

Finite element simulation of spinal deformities correction by in situ contouring technique

Biomechanical models have been proposed in order to simulate the surgical correction of spinal deformities. With these models, different surgical correction techniques have been examined: distraction and rod rotation. The purpose of this study was to simulate another surgical correction technique: the in situ contouring technique. In this way, a comprehensive three-dimensional Finite Element (FE) model with patient-specific geometry and patient-specific mechanical properties was used. The simulation of the surgery took into account elasto–plastic behavior of the rod and multiple moments loading and unloading representing the surgical maneuvers. The simulations of two clinical cases of hyperkyphosis and scoliosis were coherent with the surgeon's experience. Moreover, the results of simulation were compared to post-operative 3D measurements. The mean differences were under 5° for vertebral rotations and 5 mm for spinal lines. These simulations open the way for future predictive tools for surgical planning.     

An anatomically based patient-specific finite element model of patella articulation: towards a diagnostic tool

A 3D anatomically based patient-specific finite element (FE) model of patello-femoral (PF) articulation is presented to analyse the main features of patella biomechanics, namely, patella tracking (kinematics), quadriceps extensor forces, surface contact and internal patella stresses. The generic geometries are a subset from the model database of the International Union of Physiological Sciences (IUPS) (http://www.physiome.org.nz) Physiome Project with soft tissue derived from the widely used visible human dataset, and the bones digitised from an anatomically accurate physical model with muscle attachment information. The models are customised to patient magnetic resonance images using a variant of free-form deformation, called 'host-mesh' fitting. The continuum was solved using the governing equation of finite elasticity, with the multibody problem coupled through contact mechanics. Additional constraints such as tissue incompressibility are also imposed. Passive material properties are taken from the literature and implemented for deformable tissue with a non-linear micro-structurally based constitutive law. Bone and cartilage are implemented using a 'St-Venant Kirchoff' model suitable for rigid body rotations. The surface fibre directions have been estimated from anatomy images of cadaver muscle dissections and active muscle contraction was based on a steady-state calcium-tension relation. The 3D continuum model of muscle, tendon and bone is compared with experimental results from the literature, and surgical simulations performed to illustrate its clinical assessment capabilities (a Maquet procedure for reducing patella stresses and a vastus lateralis release for a bipartite patella). Finally, the model limitations, issues and future improvements are discussed.