Special issue on patient-specific computational modelling

2010 ◽  
Vol 26 (1) ◽  
pp. 1-2 ◽  
Author(s):  
P. Nithiarasu ◽  
R. Löhner
Keyword(s):  
Computational Modelling ◽  
Patient Specific ◽  
Special Issue

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

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Kevin Linka ◽  
Amelie Schäfer ◽  
Markus Hillgärtner ◽  
Mikhail Itskov ◽  
Matthias Knobe ◽  
...  
Keyword(s):  
Articular Cartilage ◽  
Computational Modelling ◽  
Multiparametric Mri ◽  
Patient Specific

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

2014 ◽  
Vol 4 (5) ◽  
pp. 20140004 ◽  
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.

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

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.

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

Materials ◽  
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.

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

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.

scholarly journals euHeart: personalized and integrated cardiac care using patient-specific cardiovascular modelling

2011 ◽  
Vol 1 (3) ◽  
pp. 349-364 ◽  
Author(s):  
Nic Smith ◽  
Adelaide de Vecchi ◽  
Matthew McCormick ◽  
David Nordsletten ◽  
Oscar Camara ◽  
...  
Keyword(s):  
Imaging Techniques ◽  
Computational Modelling ◽  
Population Based ◽  
Individual Variability ◽  
Western Society ◽  
Patient Specific ◽  
Mortality And Morbidity ◽  
Multi Scale ◽  
Cardiac Pump Function

The loss of cardiac pump function accounts for a significant increase in both mortality and morbidity in Western society, where there is currently a one in four lifetime risk, and costs associated with acute and long-term hospital treatments are accelerating. The significance of cardiac disease has motivated the application of state-of-the-art clinical imaging techniques and functional signal analysis to aid diagnosis and clinical planning. Measurements of cardiac function currently provide high-resolution datasets for characterizing cardiac patients. However, the clinical practice of using population-based metrics derived from separate image or signal-based datasets often indicates contradictory treatments plans owing to inter-individual variability in pathophysiology. To address this issue, the goal of our work, demonstrated in this study through four specific clinical applications, is to integrate multiple types of functional data into a consistent framework using multi-scale computational modelling.

A platform for high-fidelity patient-specific structural modelling of atherosclerotic arteries: from intravascular imaging to three-dimensional stress distributions

2021 ◽  
Vol 18 (182) ◽  
Author(s):  
Karim Kadry ◽  
Max L. Olender ◽  
David Marlevi ◽  
Elazer R. Edelman ◽  
Farhad R. Nezami
Keyword(s):  
Mechanical Response ◽  
Plaque Rupture ◽  
Three Dimensional ◽  
Computational Modelling ◽  
Material Model ◽  
Patient Specific ◽  
Plaque Morphology ◽  
High Fidelity ◽  
Structural Behaviour ◽  
Heterogeneous Models

The pathophysiology of atherosclerotic lesions, including plaque rupture triggered by mechanical failure of the vessel wall, depends directly on the plaque morphology-modulated mechanical response. The complex interplay between lesion morphology and structural behaviour can be studied with high-fidelity computational modelling. However, construction of three-dimensional (3D) and heterogeneous models is challenging, with most previous work focusing on two-dimensional geometries or on single-material lesion compositions. Addressing these limitations, we here present a semi-automatic computational platform, leveraging clinical optical coherence tomography images to effectively reconstruct a 3D patient-specific multi-material model of atherosclerotic plaques, for which the mechanical response is obtained by structural finite-element simulations. To demonstrate the importance of including multi-material plaque components when recovering the mechanical response, a computational case study was conducted in which systematic variation of the intraplaque lipid and calcium was performed. The study demonstrated that the inclusion of various tissue components greatly affected the lesion mechanical response, illustrating the importance of multi-material formulations. This platform accordingly provides a viable foundation for studying how plaque micro-morphology affects plaque mechanical response, allowing for patient-specific assessments and extension into clinically relevant patient cohorts.

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