OpenMandible: An open-source framework for highly realistic numerical modelling of lower mandible physiology.

OBJECTIVE: Computer modeling of lower mandible physiology remains challenging because prescribing realistic material characteristics and boundary conditions from medical scans requires advanced equipment and skill sets. The objective of this study is to provide a framework that could reduce simplifications made and inconsistency (in terms of geometry, materials, and boundary conditions) among further studies on the topic. METHODS: The OpenMandible framework offers: 1) the first publicly available multiscale model of the mandible developed by combining cone beam computerized tomography (CBCT) and µCT imaging modalities, and 2) a C++ software tool for the generation of simulation-ready models (tet4 and hex8 elements). In addition to the application of conventional (Neumann and Dirichlet) boundary conditions, OpenMandible introduces a novel geodesic wave propagation - based approach for incorporating orthotropic micromechanical characteristics of cortical bone, and a unique algorithm for modeling muscles as uniformly directed vectors. The base intact model includes the mandible (spongy and compact bone), 14 teeth (comprising dentin, enamel, periodontal ligament, and pulp), simplified temporomandibular joints, and masticatory muscles (masseter, temporalis, medial, and lateral pterygoid). RESULTS: The complete source code, executables, showcases, and sample data are freely available on the public repository: https://github.com/ArsoVukicevic/OpenMandible. It has been demonstrated that by slightly editing the baseline model, one can study different "virtual" treatments or diseases, including tooth restoration, placement of implants, mandible bone degradation, and others. SIGNIFICANCE: OpenMandible eases the community to undertake a broad range of studies on the topic, while increasing their consistency and reproducibility. At the same time, the needs for dedicated equipment and skills for developing realistic simulation models are significantly reduced.

Assessment of cortical bone fracture resistance curves by fusing artificial neural networks and linear regression.

Bone injures (BI) represents one of the major health problems, together with cancer and cardiovascular diseases. Assessment of the risks associated with BI is nontrivial since fragility of human cortical bone is varying with age. Due to restrictions for performing experiments on humans, only a limited number of fracture resistance curves (R-curves) for particular ages have been reported in the literature. This study proposes a novel decision support system for the assessment of bone fracture resistance by fusing various artificial intelligence algorithms. The aim was to estimate the R-curve slope, toughness threshold and stress intensity factor using the two input parameters commonly available during a routine clinical examination: patients age and crack length. Using the data from the literature, the evolutionary assembled Artificial Neural Network was developed and used for the derivation of Linear regression (LR) models of R-curves for arbitrary age. Finally, by using the patient (age)-specific LR models and diagnosed crack size one could estimate the risk of bone fracture under given physiological conditions. Compared to the literature, we demonstrated improved performances for estimating nonlinear changes of R-curve slope (R2 = 0.82 vs. R2 = 0.76) and Toughness threshold with ageing (R2 = 0.73 vs. R2 = 0.66).

Three-dimensional reconstruction and NURBS-based structured meshing of coronary arteries from the conventional X-ray angiography projection images.

Despite its two-dimensional nature, X-ray angiography (XRA) has served as the gold standard imaging technique in the interventional cardiology for over five decades. Accordingly, demands for tools that could increase efficiency of the XRA procedure for the quantitative analysis of coronary arteries (CA) are constantly increasing. The aim of this study was to propose a novel procedure for three-dimensional modeling of CA from uncalibrated XRA projections. A comprehensive mathematical model of the image formation was developed and used with a robust genetic algorithm optimizer to determine the calibration parameters across XRA views. The frames correspondences between XRA acquisitions were found using a partial-matching approach. Using the same matching method, an efficient procedure for vessel centerline reconstruction was developed. Finally, the problem of meshing complex CA trees was simplified to independent reconstruction and meshing of connected branches using the proposed nonuniform rational B-spline (NURBS)-based method. Because it enables structured quadrilateral and hexahedral meshing, our method is suitable for the subsequent computational modelling of CA physiology (i.e. coronary blood flow, fractional flow reverse, virtual stenting and plaque progression). Extensive validations using digital, physical, and clinical datasets showed competitive performances and potential for further application on a wider scale.

Trauma of the Frontal Region Is Influenced by the Volume of Frontal Sinuses. A Finite Element Study.

Anatomy of frontal sinuses varies individually, from differences in volume and shape to a rare case when the sinuses are absent. However, there are scarce data related to influence of these variations on impact generated fracture pattern. Therefore, the aim of this study was to analyse the influence of frontal sinus volume on the stress distribution and fracture pattern in the frontal region. The study included four representative Finite Element models of the skull. Reference model was built on the basis of computed tomography scans of a human head with normally developed frontal sinuses. By modifying the reference model, three additional models were generated: a model without sinuses, with hypoplasic, and with hyperplasic sinuses. A 7.7 kN force was applied perpendicularly to the forehead of each model, in order to simulate a frontal impact. The results demonstrated that the distribution of impact stress in frontal region depends on the frontal sinus volume. The anterior sinus wall showed the highest fragility in case with hyperplasic sinuses, whereas posterior wall/inner plate showed more fragility in cases with hypoplasic and undeveloped sinuses. Well-developed frontal sinuses might, through absorption of the impact energy by anterior wall, protect the posterior wall and intracranial contents.

Automated development of artificial neural networks for clinical purposes: Application for predicting the outcome of choledocholithiasis surgery.

Among various expert systems (ES), Artificial Neural Network (ANN) has shown to be suitable for the diagnosis of concurrent common bile duct stones (CBDS) in patients undergoing elective cholecystectomy. However, their application in practice remains limited since the development of ANNs represents a slow process that requires additional expertize from potential users. The aim of this study was to propose an ES for automated development of ANNs and validate its performances on the problem of prediction of CBDS. Automated development of the ANN was achieved by applying the evolutionary assembling approach, which assumes optimal configuring of the ANN parameters by using Genetic algorithm. Automated selection of optimal features for the ANN training was performed using a Backward sequential feature selection algorithm. The assessment of the developed ANN included the evaluation of predictive ability and clinical utility. For these purposes, we collected data from 303 patients who underwent surgery in the period from 2008 to 2014. The results showed that the total bilirubin, alanine aminotransferase, common bile duct diameter, number of stones, size of the smallest calculus, biliary colic, acute cholecystitis and pancreatitis had the best prognostic value of CBDS. Compared to the alternative approaches, the ANN obtained by the proposed ES had better sensitivity and clinical utility, which are considered to be the most important for the particular problem. Besides the fact that it enabled the development of ANNs with better performances, the proposed ES significantly reduced the complexity of ANNs' development compared to previous studies that required manual selection of optimal features and/or ANN configuration. Therefore, it is concluded that the proposed ES represents a robust and user-friendly framework that, apart from the prediction of CBDS, could advance and simplify the application of ANNs for solving a wider range of problems.

Impact of the lower third molar presence and position on the fragility of mandibular angle and condyle: A Three-dimensional finite element study.

The aim of the present study was to investigate the influences of the presence and position of a lower third molar (M3) on the fragility of mandibular angle and condyle, using finite element analysis. From computed tomographic scans of a human mandible with normally erupted M3, two additional virtual models were generated: a mandibular model with partially impacted M3 and a model without M3. Two cases of impact were considered: a frontal and a lateral blow. The results are based on the chromatic analysis of the distributed von Mises and principal stresses, and calculation of their failure indices. In the frontal blow, the angle region showed the highest stress in the case with partially impacted M3, and the condylar region in the case without M3. Compressive stresses were dominant but caused no failure. Tensile stresses were recorded in the retromolar areas, but caused failure only in the case with partially impacted M3. In the lateral blow, the stress concentrated at the point of impact, in the ipsilateral and contralateral angle and condylar regions. The highest stresses were recorded in the case with partially impacted M3. Tensile stresses caused the failure on the ipsilateral side, whereas compressive stresses on the contralateral side.

Influence of dental restorations and mastication loadings on dentine fatigue behaviour: Image-based modelling approach.

OBJECTIVES: The aim of this study was to use Finite Element Analysis (FEA) to estimate the influence of various mastication loads and different tooth treatments (composite restoration and endodontic treatment) on dentine fatigue. The analysis of fatigue behaviour of human dentine in intact and composite restored teeth with root-canal-treatment using FEA and fatigue theory was performed. METHODS: Dentine fatigue behaviour was analysed in three virtual models: intact, composite-restored and endodontically-treated tooth. Volumetric change during the polymerization of composite was modelled by thermal expansion in a heat transfer analysis. Low and high shrinkage stresses were obtained by varying the linear shrinkage of composite. Mastication forces were applied occlusally with the load of 100, 150 and 200N. Assuming one million cycles, Fatigue Failure Index (FFI) was determined using Goodman's criterion while residual fatigue lifetime assessment was performed using Paris-power law. RESULTS: The analysis of the Goodman diagram gave both maximal allowed crack size and maximal number of cycles for the given stress ratio. The size of cracks was measured on virtual models. For the given conditions, fatigue-failure is not likely to happen neither in the intact tooth nor in treated teeth with low shrinkage stress. In the cases of high shrinkage stress, crack length was much larger than the maximal allowed crack and failure occurred with 150 and 200N loads. The maximal allowed crack size was slightly lower in the tooth with root canal treatment which induced somewhat higher FFI than in the case of tooth with only composite restoration. CONCLUSIONS: Main factors that lead to dentine fatigue are levels of occlusal load and polymerization stress. However, root canal treatment has small influence on dentine fatigue. CLINICAL SIGNIFICANCE: The methodology proposed in this study provides a new insight into the fatigue behaviour of teeth after dental treatments. Furthermore, it estimates maximal allowed crack size and maximal number of cycles for a specific case.

Finite element analysis of uncommonly large renal arteriovenous malformation--adjacent renal cyst complex.

BACKGROUND: Renal arteriovenous malformation (RAVM) represents abnormal communication between the intrarenal arterial and venous system. The purpose of this study was to investigate hemodynamics and biomechanics quantities which may influence the instability of RAVM and imply clinical complications. METHODS: A detailed 3D reconstruction of RAVM was obtained from the patient CT scans, aortic inlet flow was measured by color-flow Doppler ultrasound, while material characteristics were adopted from the literature. A numerical finite element analysis (FEA) of the blood flow was performed by solving the governing equations for the viscous incompressible flow. The physical quantities calculated at the systolic and diastolic peak moment were velocity, pressure, shear stress and drag forces. RESULTS: We reported a case of a 50-year-old patient with a large RAVM and adjacent renal cyst, who unsuccessfully underwent two attempts of embolization that resulted in the consequent nephrectomy. FEA showed that the cyst had a very low pressure intensity and velocity field (with unstable flow in diastolic peak). For both systolic and diastolic moments, increased values of wall shear stress were found on the places with intensive wall calcification. Unusually high values of drag force which would likely explain the presence of pressure in the cystic formation were found on the infero-medial side where the cyst wall was the thinnest and where the flow streamlines converged. CONCLUSIONS: FEA showed that the hemodynamics of the cyst-RAVM complex was unstable making it prone to rupture. Clinically established diagnosis of imminent rupture together with unfavorable hemodynamics of the lesion consequently made additional attempts of embolization risky and unsuccessful leading to total nephrectomy.

Occlusal load distribution through the cortical and trabecular bone of the human mid-facial skeleton in natural dentition: a three-dimensional finite element study.

Understanding of the occlusal load distribution through the mid-facial skeleton in natural dentition is essential because alterations in magnitude and/or direction of occlusal forces may cause remarkable changes in cortical and trabecular bone structure. Previous analyses by strain gauge technique, photoelastic and, more recently, finite element (FE) methods provided no direct evidence for occlusal load distribution through the cortical and trabecular bone compartments individually. Therefore, we developed an improved three-dimensional FE model of the human skull in order to clarify the distribution of occlusal forces through the cortical and trabecular bone during habitual masticatory activities. Particular focus was placed on the load transfer through the anterior and posterior maxilla. The results were presented in von Mises stress (VMS) and the maximum principal stress, and compared to the reported FE and strain gauge data. Our qualitative stress analysis indicates that occlusal forces distribute through the mid-facial skeleton along five vertical and two horizontal buttresses. We demonstrated that cortical bone has a priority in the transfer of occlusal load in the anterior maxilla, whereas both cortical and trabecular bone in the posterior maxilla are equally involved in performing this task. Observed site dependence of the occlusal load distribution may help clinicians in creating strategies for implantology and orthodontic treatments. Additionally, the magnitude of VMS in our model was significantly lower in comparison to previous FE models composed only of cortical bone. This finding suggests that both cortical and trabecular bone should be modeled whenever stress will be quantitatively analyzed.

Modeling of liver metastatic disease with applied drug therapy.

Colorectal carcinoma is acknowledged as the second leading cause of total cancer-related death in the European Region. The majority of deaths related to colorectal carcinoma are connected with liver metastatic disease. Approximately, in 25% of all patients, liver metastatic disease is diagnosed at the same time as the primary diagnosis, while up to a quarter of others would develop liver metastases in the course of the illness. In this study, we developed reaction-diffusion model and analyzed the effect of drug therapy on liver metastatic disease for a specific patient. Tumor volumes in specific time points were obtained using CT scan images. The nonlinear function for cell proliferation rate as well as data about clinically applied drug therapy was included in the model. Fitting procedure was used for parameter estimation. Good agreement of numerical and experimental results shows the feasibility and efficacy of the proposed system.

Computer methods for follow-up study of hemodynamic and disease progression in the stented coronary artery by fusing IVUS and X-ray angiography.

Despite a lot of progress in the fields of medical imaging and modeling, problem of estimating the risk of in-stent restenosis and monitoring the progress of the therapy following stenting still remains. The principal aim of this paper was to propose architecture and implementation details of state of the art of computer methods for a follow-up study of disease progression in coronary arteries stented with bare-metal stents. The 3D reconstruction of coronary arteries was performed by fusing X-ray angiography and intravascular ultrasound (IVUS) as the most dominant modalities in interventional cardiology. The finite element simulation of plaque progression was performed by coupling the flow equations with the reaction-diffusion equation applying realistic boundary conditions at the wall. The alignment of baseline and follow-up data was performed automatically by temporal alignment of IVUS electrocardiogram-gated frames. The assessment was performed using three six-month follow-ups of right coronary artery. Simulation results were compared with the ground truth data measured by clinicians. In all three data sets, simulation results indicated the right places as critical. With the obtained difference of 5.89 ± ~4.5% between the clinical measurements and the results of computer simulations, we showed that presented framework is suitable for tracking the progress of coronary disease, especially for comparing face-to-face results and data of the same artery from distinct time periods.