Towards Patient-Specific Computational Modelling of Articular Cartilage on the Basis of Advanced Multiparametric MRI Techniques

Articular cartilage is a critical component in the movement of one bone against another. It possesses unique chemical properties allowing it to serve as a bearing surface, capable of transferring loads from one bone to another while simultaneously allowing the load bearing surfaces to articulate with low friction. Patient-specific finite element (FE) models incorporating articular cartilage provide insight into articular joint mechanics [1, 2]. To date, the methods/tools available to create accurate FE mesh definitions of the articular cartilage are limited. Semi-automated morphing methods have been developed, but many intermediate steps have to be performed to get the final cartilage mesh definition [3]. Commercially available software [4] is capable of generating tetrahedral/shell/pyramid element based meshes of the cartilage from the underlying bony surface, but hexahedral meshes are preferred over tetrahedral meshes [5]. IA-FEMesh currently provides the ability to project a pre-defined set of elements a uniform distance [6]. This technique has been adopted in several models [1, 2]. Cartilage does not necessarily exist as such; rather the thickness of the cartilage is non-uniform and varies over the surface. Consequently an accurate representation of the articular cartilage is crucial for an accurate contact FE analysis. The goal of this study was to develop an algorithm that will aid in the generation of anatomically accurate cartilage FE mesh definitions in a reliable manner based on patient-specific image data.

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Accuracy of Cartilage Geometry Reconstruction From Volumetric CT Data: A Phantom Study

ASME 2007 Summer Bioengineering Conference ◽

10.1115/sbc2007-174936 ◽

2007 ◽

Author(s):

Andrew E. Anderson ◽

Benjamin J. Ellis ◽

Christopher L. Peters ◽

Jeffrey A. Weiss

Keyword(s):

Articular Cartilage ◽

Contrast Agent ◽

Computational Models ◽

Image Data ◽

Cartilage Thickness ◽

Patient Specific ◽

Joint Spacing ◽

Ct Arthrography ◽

Diarthrodial Joints ◽

Joint Contact

Segmentation of medical image data is often used for the construction of computational models to study the mechanics of diarthrodial joints such as the hip and knee. The analyst must demonstrate that the reconstructed geometry is an accurate representation of the true continuum to ensure model validity. This becomes especially important for computational modeling of joint contact, which requires accurate reconstruction of articular cartilage. Although volumetric computed tomography (CT) is often used to image diarthrodial joints, the lower bounds for detecting articular cartilage thickness and the influence of imaging parameters on the ability to image cartilage have not been reported. The use of contrast agent (CT arthrography) is necessary to visualize the surface of articular cartilage in live patients. Thus, it is of primary interest to quantify the accuracy of CT arthrography to demonstrate the feasibility of patient-specific modeling. The objectives of this study were to assess the accuracy and detection limits of CT for measuring simulated cartilage thickness using a phantom and to quantify changes in accuracy due to alterations in contrast agent concentration, imaging plane direction, spatial resolution and joint spacing.

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Computational modelling of the inflammatory response in trauma, sepsis and wound healing: implications for modelling resilience

Interface Focus ◽

10.1098/rsfs.2014.0004 ◽

2014 ◽

Vol 4 (5) ◽

pp. 20140004 ◽

Cited By ~ 11

Author(s):

Yoram Vodovotz

Keyword(s):

Inflammatory Response ◽

Acute Inflammation ◽

Computational Modelling ◽

Data Driven ◽

Patient Specific ◽

Cell Tissue ◽

Organ Systems ◽

Forward Process

Resilience refers to the ability to recover from illness or adversity. At the cell, tissue, organ and whole-organism levels, the response to perturbations such as infections and injury involves the acute inflammatory response, which in turn is connected to and controlled by changes in physiology across all organ systems. When coordinated properly, inflammation can lead to the clearance of infection and healing of damaged tissues. However, when either overly or insufficiently robust, inflammation can drive further cell stress, tissue damage, organ dysfunction and death through a feed-forward process of inflammation → damage → inflammation. To address this complexity, we have obtained extensive datasets regarding the dynamics of inflammation in cells, animals and patients, and created data-driven and mechanistic computational simulations of inflammation and its recursive effects on tissue, organ and whole-organism (patho)physiology. Through this approach, we have discerned key regulatory mechanisms, recapitulated in silico key features of clinical trials for acute inflammation and captured diverse, patient-specific outcomes. These insights may allow for the determination of individual-specific tolerances to illness and adversity, thereby defining the role of inflammation in resilience.

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Computational Modelling of Multi-folded Balloon Delivery Systems for Coronary Artery Stenting: Insights into Patient-Specific Stent Malapposition

Annals of Biomedical Engineering ◽

10.1007/s10439-014-1237-8 ◽

2015 ◽

Vol 43 (8) ◽

pp. 1786-1802 ◽

Cited By ~ 5

Author(s):

Georgios E. Ragkousis ◽

Nick Curzen ◽

Neil W. Bressloff

Keyword(s):

Coronary Artery ◽

Computational Modelling ◽

Delivery Systems ◽

Patient Specific ◽

Coronary Artery Stenting

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Joint-specific distance thresholds for patient-specific approximations of articular cartilage modeling in the first ray of the foot

Medical & Biological Engineering & Computing ◽

10.1007/s11517-014-1179-1 ◽

2014 ◽

Vol 52 (9) ◽

pp. 773-779 ◽

Cited By ~ 4

Author(s):

G. L. S. Marchelli ◽

W. R. Ledoux ◽

V. Isvilanonda ◽

M. A. Ganter ◽

D. W. Storti

Keyword(s):

Articular Cartilage ◽

Patient Specific ◽

First Ray ◽

Specific Distance

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High Wall Shear Stress can Predict Wall Degradation in Ascending Aortic Aneurysms: An Integrated Biomechanics Study

Frontiers in Bioengineering and Biotechnology ◽

10.3389/fbioe.2021.750656 ◽

2021 ◽

Vol 9 ◽

Author(s):

M. Yousuf Salmasi ◽

Selene Pirola ◽

Sumesh Sasidharan ◽

Serena M. Fisichella ◽

Alberto Redaelli ◽

...

Keyword(s):

Shear Stress ◽

Wall Shear Stress ◽

Computational Modelling ◽

Vascular Wall ◽

Aortic Aneurysms ◽

Patient Specific ◽

Segmental Analysis ◽

4D Mri ◽

Wall Shear ◽

Mechanical And Microstructural Properties

Background: Blood flow patterns can alter material properties of ascending thoracic aortic aneurysms (ATAA) via vascular wall remodeling. This study examines the relationship between wall shear stress (WSS) obtained from image-based computational modelling with tissue-derived mechanical and microstructural properties of the ATAA wall using segmental analysis.Methods: Ten patients undergoing surgery for ATAA were recruited. Exclusions: bicuspid aortopathy, connective tissue disease. All patients had pre-operative 4-dimensional flow magnetic resonance imaging (4D-MRI), allowing for patient-specific computational fluid dynamics (CFD) analysis and anatomically precise WSS mapping of ATAA regions (6–12 segments per patient). ATAA samples were obtained from surgery and subjected to region-specific tensile and peel testing (matched to WSS segments). Computational pathology was used to characterize elastin/collagen abundance and smooth muscle cell (SMC) count.Results: Elevated values of WSS were predictive of: reduced wall thickness [coef −0.0489, 95% CI (−0.0905, −0.00727), p = 0.022] and dissection energy function (longitudinal) [−15,0, 95% CI (−33.00, −2.98), p = 0.048]. High WSS values also predicted higher ultimate tensile strength [coef 0.136, 95% CI (0 0.001, 0.270), p = 0.048]. Additionally, elevated WSS also predicted a reduction in elastin levels [coef −0.276, 95% (CI −0.531, −0.020), p = 0.035] and lower SMC count ([oef −6.19, 95% CI (−11.41, −0.98), p = 0.021]. WSS was found to have no effect on collagen abundance or circumferential mechanical properties.Conclusions: Our study suggests an association between elevated WSS values and aortic wall degradation in ATAA disease. Further studies might help identify threshold values to predict acute aortic events.

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An Automated Method for Creation of Patient-Specific Volumetric Articular Cartilage Elements in the Human Foot

Journal of Medical Devices ◽

10.1115/1.3589905 ◽

2011 ◽

Vol 5 (2) ◽

Cited By ~ 1

Author(s):

Grant L. S. Marchelli ◽

William R. Ledoux ◽

Vara Isvilanonda ◽

Duane W. Storti ◽

Mark A. Ganter

Keyword(s):

Articular Cartilage ◽

Patient Specific ◽

Human Foot ◽

Automated Method

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Patient-Specific Bone Multiscale Modelling, Fracture Simulation and Risk Analysis—A Survey

Materials ◽

10.3390/ma13010106 ◽

2019 ◽

Vol 13 (1) ◽

pp. 106

Author(s):

Amadeus C. S. Alcântara ◽

Israel Assis ◽

Daniel Prada ◽

Konrad Mehle ◽

Stefan Schwan ◽

...

Keyword(s):

Risk Analysis ◽

Bone Fracture ◽

Computational Modelling ◽

Bone Geometry ◽

Patient Specific ◽

Section 8 ◽

Fracture Simulation ◽

Starting Point ◽

Bone Section ◽

Selection Of

This paper provides a starting point for researchers and practitioners from biology, medicine, physics and engineering who can benefit from an up-to-date literature survey on patient-specific bone fracture modelling, simulation and risk analysis. This survey hints at a framework for devising realistic patient-specific bone fracture simulations. This paper has 18 sections: Section 1 presents the main interested parties; Section 2 explains the organzation of the text; Section 3 motivates further work on patient-specific bone fracture simulation; Section 4 motivates this survey; Section 5 concerns the collection of bibliographical references; Section 6 motivates the physico-mathematical approach to bone fracture; Section 7 presents the modelling of bone as a continuum; Section 8 categorizes the surveyed literature into a continuum mechanics framework; Section 9 concerns the computational modelling of bone geometry; Section 10 concerns the estimation of bone mechanical properties; Section 11 concerns the selection of boundary conditions representative of bone trauma; Section 12 concerns bone fracture simulation; Section 13 presents the multiscale structure of bone; Section 14 concerns the multiscale mathematical modelling of bone; Section 15 concerns the experimental validation of bone fracture simulations; Section 16 concerns bone fracture risk assessment. Lastly, glossaries for symbols, acronyms, and physico-mathematical terms are provided.

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Calculation of Carotid Artery Flow Rates Using Doppler Ultrasound: Implications of Velocity Profile Skewing

ASME 2012 Summer Bioengineering Conference, Parts A and B ◽

10.1115/sbc2012-80073 ◽

2012 ◽

Author(s):

Jonathan P. Mynard ◽

David A. Steinman

Keyword(s):

Carotid Artery ◽

Velocity Profile ◽

Doppler Ultrasound ◽

Computational Models ◽

Peak Velocity ◽

Computational Modelling ◽

Carotid Bifurcation ◽

Sample Volume ◽

Patient Specific ◽

Specific Flow

Doppler ultrasound (DUS) is a non-invasive means of obtaining patient-specific flow boundary conditions in computational modelling studies [1] or estimating volumetric flow in clinical studies [2, 3]. To convert velocity information to a flow waveform, three related assumptions are often applied, 1) that the peak velocity lies in the centre of a cylindrical vessel, 2) that a centrally-located sample volume will thus detect the peak velocity, and 3) that the velocity profile is fully-developed and axisymmetric, being well-approximated by a parabolic (Poiseuille) or Womersley profile. These assumptions may not always be valid, however, even for nominally straight vessels like the common carotid artery (CCA) [4, 5]. While one might expect that flow estimated from DUS would become increasingly inaccurate as the profile becomes less axisymmetric, the scale of such errors and their relation to the true profile shape have not been quantified for the CCA. Moreover, for a heavily skewed velocity profile, the peak velocity may not lie within the DUS sample volume, and hence the choice of sample volume or beam-vessel orientation may also affect the accuracy of flow calculations. In this study, we investigate these issues by performing an idealized virtual DUS on data from image-based computational models of the carotid bifurcation.

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