A Computational Framework for Patient-Specific Multi-Scale Cardiac Modeling

The calculation of range of motion (ROM) is a key factor during preoperative planning of total hip replacements (THR), to reduce the risk of impingement and dislocation of the artificial hip joint. To support the preoperative assessment of THR, a magnetic resonance imaging (MRI)-based computational framework was generated; this enabled the estimation of patient-specific ROM and type of impingement (bone-to-bone, implant-to-bone, and implant-to-implant) postoperatively, using a three-dimensional computer-aided design (CAD) to visualize typical clinical joint movements. Hence, patient-specific CAD models from 19 patients were generated from MRI scans and a conventional total hip system (Bicontact® hip stem and Plasmacup® SC acetabular cup with a ceramic-on-ceramic bearing) was implanted virtually. As a verification of the framework, the ROM was compared between preoperatively planned and the postoperatively reconstructed situations; this was derived based on postoperative radiographs (n = 6 patients) during different clinically relevant movements. The data analysis revealed there was no significant difference between preoperatively planned and postoperatively reconstructed ROM (∆ROM) of maximum flexion (∆ROM = 0°, p = 0.854) and internal rotation (∆ROM = 1.8°, p = 0.917). Contrarily, minor differences were observed for the ROM during maximum external rotation (∆ROM = 9°, p = 0.046). Impingement, of all three types, was in good agreement with the preoperatively planned and postoperatively reconstructed scenarios during all movements. The calculated ROM reached physiological levels during flexion and internal rotation movement; however, it exceeded physiological levels during external rotation. Patients, where implant-to-implant impingement was detected, reached higher ROMs than patients with bone-to-bone impingement. The proposed framework provides the capability to predict postoperative ROM of THRs.

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A flexible framework for sequential estimation of model parameters in computational hemodynamics

Advanced Modeling and Simulation in Engineering Sciences ◽

10.1186/s40323-020-00186-x ◽

2020 ◽

Vol 7 (1) ◽

Author(s):

Christopher J. Arthurs ◽

Nan Xiao ◽

Philippe Moireau ◽

Tobias Schaeffter ◽

C. Alberto Figueroa

Keyword(s):

Unscented Kalman Filter ◽

Three Dimensional ◽

Synthetic Data ◽

Sequential Estimation ◽

Wall Material ◽

Patient Specific ◽

Model Parameters ◽

Computational Framework ◽

Lumped Parameter ◽

Estimation Of Model Parameters

AbstractA major challenge in constructing three dimensional patient specific hemodynamic models is the calibration of model parameters to match patient data on flow, pressure, wall motion, etc. acquired in the clinic. Current workflows are manual and time-consuming. This work presents a flexible computational framework for model parameter estimation in cardiovascular flows that relies on the following fundamental contributions. (i) A Reduced-Order Unscented Kalman Filter (ROUKF) model for data assimilation for wall material and simple lumped parameter network (LPN) boundary condition model parameters. (ii) A constrained least squares augmentation (ROUKF-CLS) for more complex LPNs. (iii) A “Netlist” implementation, supporting easy filtering of parameters in such complex LPNs. The ROUKF algorithm is demonstrated using non-invasive patient-specific data on anatomy, flow and pressure from a healthy volunteer. The ROUKF-CLS algorithm is demonstrated using synthetic data on a coronary LPN. The methods described in this paper have been implemented as part of the CRIMSON hemodynamics software package.

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A multi-scale computational framework for modeling the freeze-drying of microparticles in packed-beds

Powder Technology ◽

10.1016/j.powtec.2018.11.067 ◽

2019 ◽

Vol 343 ◽

pp. 834-846 ◽

Cited By ~ 4

Author(s):

Luigi C. Capozzi ◽

Antonello A. Barresi ◽

Roberto Pisano

Keyword(s):

Freeze Drying ◽

Packed Beds ◽

Computational Framework ◽

Multi Scale

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Multi-scale models of the heart for patient-specific simulations

Artificial Intelligence for Computational Modeling of the Heart ◽

10.1016/b978-0-12-817594-1.00011-5 ◽

2020 ◽

pp. 3-42

Author(s):

Viorel Mihalef ◽

Tiziano Passerini ◽

Tommaso Mansi

Keyword(s):

Patient Specific ◽

Multi Scale ◽

Scale Models

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Multi-Scale Virtual Reality of Sintering

Materials Science Forum ◽

10.4028/www.scientific.net/msf.534-536.573 ◽

2007 ◽

Vol 534-536 ◽

pp. 573-576

Author(s):

Eugene Olevsky

Keyword(s):

Global Scale ◽

Initial State ◽

Model Framework ◽

Time Step ◽

Computational Framework ◽

Multi Scale ◽

Scale Modeling ◽

History Of ◽

On Line ◽

Damage Criteria

The directions of further developments in the modeling of sintering are pointed out, including multi-scale modeling of sintering, on-line sintering damage criteria, particle agglomeration, sintering with phase transformations. A true multi-scale approach is applied for the development of a new meso-macro methodology for modeling of sintering. The developed macroscopic level computational framework envelopes the mesoscopic simulators. No closed forms of constitutive relationships are assumed for the parameters of the material. When a time-step of the calculations is finished for one macroscopic element, the mesostructures of the next element are restored from the initial state according to the history of loading. The model framework is able to predict the final dimensions of the sintered specimen on a global scale and identify the granular structure in any localized area for prediction of the material properties.

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Patient-Specific Modelling of Intracranial Aneurysm Evolution

ASME 2011 Summer Bioengineering Conference, Parts A and B ◽

10.1115/sbc2011-53223 ◽

2011 ◽

Author(s):

Paul N. Watton ◽

Marc Homer ◽

Justin Penrose ◽

Harry Thompson ◽

Haoyu Chen ◽

...

Keyword(s):

Arterial Wall ◽

Adult Population ◽

Computational Simulation ◽

Clinical Intervention ◽

Patient Specific ◽

Computational Framework ◽

Important Concern ◽

Risk Of Rupture ◽

Appropriate Therapy ◽

Insight Into

Intracranial aneurysms appear as sac-like outpouchings of the cerebral vasculature wall; inflated by the pressure of the blood that fills them. They are relatively common and affect up to 5% of the adult population. Fortunately, most remain asymptomatic. However, there is a small but inherent risk of rupture: 0.1% to 1% of detected aneurysms rupture every year. If rupture does occur there is a 30% to 50% chance of fatality. Consequently, if an aneurysm is detected, clinical intervention may be deemed appropriate. Therapy is currently aimed at pre-rupture detection and preventative treatment. However, interventional procedures are not without risk to the patient. The improvement and optimization of interventional techniques is an important concern for patient welfare and is necessary for rationalisation of healthcare priorities. Hence there is a need to develop methodologies to assist in identifying those ICAs most at risk of rupture. We focus on the mathematical modelling and computational simulation of ICA evolution. Models must take into consideration: (i) the biomechanics of the arterial wall; (ii) the biology of the arterial wall and (iii) the complex interplay between (i) and (ii), i.e. the mechanobiology of the arterial wall. The ultimate ambition of such models is to aid clinical diagnosis on a patient-specific basis. However, due to the significant biological complexity coupled with limited histological information such models are still in their relative infancy. Current research focuses on simulating the evolution of an ICA with an aim to yield insight into the growth and remodelling (G&R) processes that give rise to inception, enlargement, stabilisation and rupture. We present a novel Fluid-Structure-Growth computational framework for modelling aneurysm evolution.

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A computational framework for patient-specific surgical planning of type 1 thyroplasty

JASA Express Letters ◽

10.1121/10.0009084 ◽

2021 ◽

Vol 1 (12) ◽

pp. 125203

Author(s):

Mohammadreza Movahhedi ◽

Biao Geng ◽

Qian Xue ◽

Xudong Zheng

Keyword(s):

Surgical Planning ◽

Patient Specific ◽

Computational Framework

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Coupling biomechanics to a cellular level model: An approach to patient-specific image driven multi-scale and multi-physics tumor simulation

Progress in Biophysics and Molecular Biology ◽

10.1016/j.pbiomolbio.2011.06.007 ◽

2011 ◽

Vol 107 (1) ◽

pp. 193-199 ◽

Cited By ~ 20

Author(s):

Christian P. May ◽

Eleni Kolokotroni ◽

Georgios S. Stamatakos ◽

Philippe Büchler

Keyword(s):

Cellular Level ◽

Patient Specific ◽

Multi Scale ◽

Level Model ◽

Tumor Simulation

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Multi-scale approach for modeling stability, aggregation, and network formation of nanoparticles suspended in aqueous solutions

Nanoscale ◽

10.1039/c8nr08782b ◽

2019 ◽

Vol 11 (9) ◽

pp. 3979-3992 ◽

Cited By ~ 11

Author(s):

Annalisa Cardellini ◽

Matteo Alberghini ◽

Ananth Govind Rajan ◽

Rahul Prasanna Misra ◽

Daniel Blankschtein ◽

...

Keyword(s):

Aqueous Solutions ◽

Network Formation ◽

Computational Framework ◽

Multi Scale ◽

Coated Nanoparticles

Multi-scale computational framework to investigate interactions between bare and surfactant-coated nanoparticles in aqueous solutions beyond classical DLVO and aggregation theories.

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