Automated modeling of brain bioelectric activity within the 3D Slicer environment

Electrocorticography (ECoG) or intracranial electroencephalography (iEEG) monitors electric potential directly on the surface of the brain and can be used to inform treatment planning for epilepsy surgery when paired with numerical modeling. For solving the inverse problem in epilepsy seizure onset localization, accurate solution of the iEEG forward problem is critical which requires accurate representation of the patient's brain geometry and tissue electrical conductivity. In this study, we present an automatic framework for constructing the brain volume conductor model for solving the iEEG forward problem and visualizing the brain bioelectric field on a deformed patient-specific brain model within the 3D Slicer environment. We solve the iEEG forward problem on the predicted postoperative geometry using the finite element method (FEM) which accounts for patient-specific inhomogeneity and anisotropy of tissue conductivity. We use an epilepsy case study to illustrate the workflow of our framework developed and integrated within 3D Slicer

Cell-based maximum entropy approximants for three-dimensional domains: Application in large strain elastodynamics using the meshless total Lagrangian explicit dynamics method

We present the cell-based maximum entropy (CME) approximants in E3 space by constructing the smooth approximation distance function to polyhedral surfaces. CME is a meshfree approximation method combining the properties of the maximum entropy approximants and the compact support of element-based interpolants. The method is evaluated in problems of large strain elastodynamics for three-dimensional (3D) continua using the well-established meshless total Lagrangian explicit dynamics method. The accuracy and efficiency of the method is assessed in several numerical examples in terms of computational time, accuracy in boundary conditions imposition, and strain energy density error. Due to the smoothness of CME basis functions, the numerical stability in explicit time integration is preserved for large time step. The challenging task of essential boundary condition (EBC) imposition in noninterpolating meshless methods (eg, moving least squares) is eliminated in CME due to the weak Kronecker-delta property. The EBCs are imposed directly, similar to the finite element method. CME is proven a valuable alternative to other meshless and element-based methods for large-scale elastodynamics in 3D. A naive implementation of the CME approximants in E3 is available to download at https://www.mountris.org/software/mlab/cme.Fil: Mountris, Konstantinos A.. Universidad de Zaragoza; EspañaFil: Bourantas, George C.. University of Western Australia; AustraliaFil: Millán, Raúl Daniel. Universidad Nacional de Cuyo. Facultad de Ciencias Aplicadas a la Industria; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza; ArgentinaFil: Joldes, Grand R.. University of Western Australia; AustraliaFil: Miller, Karol. Cardiff University; Reino Unido. University of Western Australia; AustraliaFil: Pueyo, Esther. Centro de Investigacion Biomedica En Red.; España. Universidad de Zaragoza; EspañaFil: Wittek, Adam. University of Western Australia; Australi

Suite of Meshless Algorithms for Accurate Computation of Soft Tissue Deformation for Surgical Simulation

The ability to predict patient-specific soft tissue deformations is key for computer-integrated surgery systems and the core enabling technology for a new era of personalized medicine. Element-Free Galerkin (EFG) methods are better suited for solving soft tissue deformation problems than the finite element method (FEM) due to their capability of handling large deformation while also eliminating the necessity of creating a complex predefined mesh. Nevertheless, meshless methods based on EFG formulation, exhibit three major limitations: i) meshless shape functions using higher order basis cannot always be computed for arbitrarily distributed nodes (irregular node placement is crucial for facilitating automated discretization of complex geometries); ii) imposition of the Essential Boundary Conditions (EBC) is not straightforward; and, iii) numerical (Gauss) integration in space is not exact as meshless shape functions are not polynomial. This paper presents a suite of Meshless Total Lagrangian Explicit Dynamics (MTLED) algorithms incorporating a Modified Moving Least Squares (MMLS) method for interpolating scattered data both for visualization and for numerical computations of soft tissue deformation, a novel way of imposing EBC for explicit time integration, and an adaptive numerical integration procedure within the Meshless Total Lagrangian Explicit Dynamics algorithm. The appropriateness and effectiveness of the proposed methods is demonstrated using comparisons with the established non-linear procedures from commercial finite element software ABAQUS and experiments with very large deformations. To demonstrate the translational benefits of MTLED we also present a realistic brain-shift computation.Comment: Accepted for publication in Medical Image Analysi

Biomechanical assessment predicts aneurysm-related events in patients with abdominal aortic aneurysm

Objective To test whether aneurysm biomechanical ratio (ABR; a dimensionless ratio of wall stress and wall strength) can predict aneurysm related events. Methods In a prospective multicentre clinical study of 295 patients with an abdominal aortic aneurysm (AAA; diameter ≥ 40 mm), three dimensional reconstruction and computational biomechanical analyses were used to compute ABR at baseline. Participants were followed for at least two years and the primary end point was the composite of aneurysm rupture or repair. Results The majority were male (87%), current or former smokers (86%), most (72%) had hypertension (mean ± standard deviation [SD] systolic blood pressure 140 ± 22 mmHg), and mean ± SD baseline diameter was 49.0 ± 6.9 mm. Mean ± SD ABR was 0.49 ± 0.27. Participants were followed up for a mean ± SD of 848 ± 379 days and rupture (n = 13) or repair (n = 102) occurred in 115 (39%) cases. The number of repairs increased across tertiles of ABR: low (n = 24), medium (n = 34), and high ABR (n = 44) (p = .010). Rupture or repair occurred more frequently in those with higher ABR (log rank p = .009) and ABR was independently predictive of this outcome after adjusting for diameter and other clinical risk factors, including sex and smoking (hazard ratio 1.41; 95% confidence interval 1.09–1.83 [p = .010]). Conclusion It has been shown that biomechanical ABR is a strong independent predictor of AAA rupture or repair in a model incorporating known risk factors, including diameter. Determining ABR at baseline could help guide the management of patients with AAA

Numerical Simulation of Anisotropic Tissue Growth Using a Total Lagrangian Formulation

This paper describes a new method for simulating tissue growth which can handle anisotropic changes in volume. The method takes advantage of the total Lagrangian formulation which allows the computation of nodal forces for each element in a finite element mesh based on a theoretical stress-free configuration, obtained by considering the unconstrained anisotropic growth of the considered element. The method allows the modelling of shrinking (atrophy), swelling, or tissue growth and the computation of the resulting mechanical stresses in the surrounding tissue. The steady-state solution is obtained using an explicit integration method and dynamic relaxation. The proposed method allows the coupling of continuum mechanical simulations with underlying growth mechanisms, offering a tool for the multiscale study of tissue growth

MICCAI Computational Biomechanics for Medicine Workshop

Computational Biomechanics for Medicine: Solid and fluid mechanics for the benefit of patients contributions and papers from the MICCAI Computational Biomechanics for Medicine Workshop help in conjunction with Medical Image Computing and Computer Assisted Intervention conference (MICCAI 2019) in Shenzhen, China. The content is dedicated to research in the field of methods and applications of computational biomechanics to medical image analysis, image-guided surgery, surgical simulation, surgical intervention planning, disease prognosis and diagnostics, analysis of injury mechanisms, implant and prostheses design, as well as artificial organ design and medical robotics. These proceedings appeal to researchers, students and professionals in the field.