Computational biomechanics for medicine

Miller, Karol

doi:10.1002/cnm.1434

Cited by 5 publications

(5 citation statements)

References 8 publications

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“…A common process consists in using a biomechanical finite element (FE) model that simulates in a physically realistic way the deformations produced in both the surface and internal tissues of the breast during the mammographic acquisition. Finite element models have been widely used in various medical applications, including brain, heart, liver, lungs, or prostate imaging, composing a wide bibliography . In breast modeling, they have been used in several challenging problems, such as the colocalization of information between different image modalities, temporal studies, identifying lesions or tumors, tracking of these lesions during biopsy, review of the progress of suspicious lesions or evaluation of the effectiveness of treatments and, even, aiding implant selection for breast augmentation procedures …”

Section: Introductionmentioning

confidence: 99%

A step‐by‐step review on patient‐specific biomechanical finite element models for breast MRI to x‐ray mammography registration

et al. 2017

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Breast magnetic resonance imaging (MRI) and x-ray mammography are two image modalities widely used for the early detection and diagnosis of breast diseases in women. The combination of these modalities leads to a more accurate diagnosis and treatment of breast diseases. The aim of this paper is to review the registration between breast MRI and x-ray mammographic images using patient-specific finite element-based biomechanical models. Specifically, a biomechanical model is obtained from the patient's MRI volume and is subsequently used to mimic the mammographic acquisition. Due to the different patient positioning and movement restrictions applied in each image modality, the finite element analysis provides a realistic physics-based approach to perform the breast deformation. In contrast with other reviews, we do not only expose the overall process of compression and registration but we also include main ideas, describe challenges, and provide an overview of the used software in each step of the process. Extracting an accurate description from the MR images and preserving the stability during the finite element analysis require an accurate knowledge about the algorithms used, as well as the software and underlying physics. The wide perspective offered makes the paper suitable not only for expert researchers but also for graduate students and clinicians. We also include several medical applications in the paper, with the aim to fill the gap between the engineering and clinical performance.

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Section: Introductionmentioning

confidence: 99%

A step‐by‐step review on patient‐specific biomechanical finite element models for breast MRI to x‐ray mammography registration

et al. 2017

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“…This study is the first to comprehensively explore the effect of EV on the hemodynamics of the TS-SS junction. Finite element analysis, a powerful simulation tool in biomechanics ( Miller, 2009 ), was used to show the influence of the flow direction and afflux location of EVs on the hemodynamics of the TS-SS junction. Previous studies of the hemodynamics of venous PT mostly used CTV or digital subtraction angiography to construct CFD models ( Kao et al, 2017 ; Amans et al, 2018 ; Tian et al, 2019 ; Mu et al, 2020 ).…”

Section: Discussionmentioning

confidence: 99%

Effect of Emissary Vein on Hemodynamics of the Transverse- Sigmoid Sinus Junction

Qiu

Zhao

et al. 2021

Front. Hum. Neurosci.

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Objective: To investigate the effect of the blood flow direction and afflux location of emissary veins (EVs) on the hemodynamics of the transverse-sigmoid sinus (TS-SS) junction.Methods: A patient-specific geometric model was constructed using computed tomography venography (CTV) and 4D flow MR data from a venous pulsatile tinnitus (PT) patient. New EV models were assembled with the afflux at the superior, middle and inferior portions of the SS from the original model, and inlet and outlet directions were applied. Computational fluid dynamics (CFD) simulation was performed to analyze the wall pressure and flow pattern of the TS-SS junction in each condition.Results: Compared to the model without EVs, the wall pressure was greatly increased in models with inlet flow and greatly decreased in models with outlet flow. The more closely the EV approached the TS-SS, the larger the pressure in models with inlet flow, and the smaller the pressure in models with outlet flow. The flow streamline in the lateral part of the TS-SS junction was smooth in all models. The streamlines in the medial part were regular spirals in outlet models and chaotic in inlet models. The streamlines showed no obvious changes regardless of afflux location. The velocity at the TS-SS junction of inlet models were uniform, medium-low flow rate, while in control and outlet models were the lateral high flow rate and the central low flow rate.Conclusion: The flow direction and afflux location of EVs affect the hemodynamics of the TS-SS junction, which may influence the severity of PT.

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“…In section 3.2 and 3.3, the meshless results are compared with the results obtained using ABAQUS (version 16.14-1) (ABAQUS, 2018) -commercial FE software considered reliable in non-linear analysis and widely used in computational biomechanics (Miller and Nielsen, 2010). Identical geometry, material models and material properties are used in meshless and FE computations.…”

Section: Verification and Validation Of Mtledmentioning

confidence: 99%

Suite of meshless algorithms for accurate computation of soft tissue deformation for surgical simulation

Joldes

Bourantas

Zwick

et al. 2019

Medical Image Analysis

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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.

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Computational biomechanics for medicine

Cited by 5 publications

References 8 publications

A step‐by‐step review on patient‐specific biomechanical finite element models for breast MRI to x‐ray mammography registration

A step‐by‐step review on patient‐specific biomechanical finite element models for breast MRI to x‐ray mammography registration

Effect of Emissary Vein on Hemodynamics of the Transverse- Sigmoid Sinus Junction

Suite of meshless algorithms for accurate computation of soft tissue deformation for surgical simulation

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