using-digital-image-correlation-to-characterize-local-strains-on

Using Digital Image Correlation to Characterize Local Strains on Vascular Tissue Specimens

Characterization of the mechanical behavior of biological and engineered soft tissues is a central component of fundamental biomedical research and ...

University of South Carolina

Computational modelling of physical and biochemical processes has emerged as a means of evaluating medical devices, offering new insights that explain current performance, inform future designs and even enable personalized use. Yet resource limitations force one to compromise with reduced order computational models and idealized assumptions that yield either qualitative descriptions or approximate, quantitative solutions to problems of interest. Considering endovascular drug delivery as an exemplary scenario, we used a supervised machine learning framework to process data generated from low fidelity coarse meshes and predict high fidelity solutions on refined mesh configurations. We considered two models simulating drug delivery to the arterial wall: (i) two-dimensional drug-coated balloons and (ii) three-dimensional drug-eluting stents. Simulations were performed on computational mesh configurations of increasing density. Supervised learners based on Gaussian process modelling were constructed from combinations of coarse mesh setting solutions of drug concentrations and nearest neighbourhood distance information as inputs, and higher fidelity mesh solutions as outputs. These learners were then used as computationally inexpensive surrogates to extend predictions using low fidelity information to higher levels of mesh refinement. The cross-validated, supervised learner-based predictions improved fidelity as compared with computational simulations performed at coarse level meshes--a result consistent across all outputs and computational models considered. Supervised learning on coarse mesh solutions can augment traditional physics-based modelling of complex physiologic phenomena. By obtaining efficient solutions at a fraction of the computational cost, this framework has the potential to transform how modelling approaches can be applied in the evaluation of medical technologies and their real-time administration in an increasingly personalized fashion.

Enhancing physiologic simulations using supervised learning on coarse mesh solutions.

The mechanical response of arteries under physiological loads can be delineated into passive and active components. The passive response is governed by the load-bearing constituents within the arterial wall, elastin, collagen, and water, while the active response is a result of vascular smooth muscle cell (SMC) contraction. In muscular blood vessels, such as the primary renal artery, high SMC wall content suggests an elevated importance of the active response in determining overall vessel behavior. This study is a continuation of our previous investigation, in which a four-fiber constitutive model of the passive response of the primary porcine renal artery was identified. Here we focus on the active response of this vessel, specifically in the case of maximal SMC contraction, and develop a constitutive model of the active stress-stretch relations. The results of this study demonstrate the existence of biaxial active stress in the vessel wall, and suggest the active mechanical response is a critical component of renal arterial performance.

The biaxial active mechanical properties of the porcine primary renal artery.

Tolosa-Hunt syndrome is a rare clinical syndrome characterized by painful ophthalmoplegia and ipsilateral cranial neuropathies. It is caused by an inflammatory process of unknown etiology.

Lymphoma of the orbit masquerading as Tolosa-Hunt syndrome.

Drug-eluting bioresorbable vascular scaffolds (BVSs) have the potential to restore lumen patency, enable recovery of the native vascular environment, and circumvent late complications associated with permanent endovascular devices. To ensure therapeutic effects persist for sufficient times prior to scaffold resorption and resultant functional loss, many factors dictating BVS performance must be identified, characterized and optimized. While some factors relate to BVS design and manufacturing, others depend on device deployment and intrinsic vascular properties. Importantly, these factors interact and cannot be considered in isolation. The objective of this study is to quantify the extent to which degree of radial expansion modulates BVS performance, specifically in the context of modifying device erosion kinetics and evolution of structural mechanics and local drug elution. We systematically varied degree of radial expansion in model BVS constructs composed of poly dl-lactide-glycolide and generated in vitro metrics of device microstructure, degradation, erosion, mechanics and drug release. Experimental data permitted development of computational models that predicted transient concentrations of scaffold-derived soluble species and drug in the arterial wall, thus enabling speculation on the short- and long-term effects of differential expansion. We demonstrate that degree of expansion significantly affects scaffold properties critical to functionality, underscoring its relevance in BVS design and optimization.

Degree of bioresorbable vascular scaffold expansion modulates loss of essential function.

Coronary artery bypass grafting (CABG) acutely disturbs the homeostatic state of the transplanted vessel making retention of graft patency dependent on chronic remodeling processes. The time course and extent to which remodeling restores vessel homeostasis will depend, in part, on the nature and magnitude of the mechanical disturbances induced upon transplantation. In this investigation, biaxial mechanical testing and histology were performed on the porcine left anterior descending artery (LAD) and analogs of common autografts, including the internal thoracic artery (ITA), radial artery (RA), great saphenous vein (GSV) and lateral saphenous vein (LSV). Experimental data were used to quantify the parameters of a structure-based constitutive model enabling prediction of the acute vessel mechanical response pre-transplantation and under coronary loading conditions. A novel metric Ξ was developed to quantify mechanical differences between each graft vessel in situ and the LAD in situ, while a second metric Ω compares the graft vessels in situ to their state under coronary loading. The relative values of these metrics among candidate autograft sources are consistent with vessel-specific variations in CABG clinical success rates with the ITA as the superior and GSV the inferior graft choices based on mechanical performance. This approach can be used to evaluate other candidate tissues for grafting or to aid in the development of synthetic and tissue engineered alternatives.

Article	Year
Enhancing physiologic simulations using supervised learning on coarse mesh solutions. Journal of the Royal Society, Interface / the Royal Society\| PubMed ID: 25652458	2015
The biaxial active mechanical properties of the porcine primary renal artery. Journal of the mechanical behavior of biomedical materials\| PubMed ID: 25913605	2015
Lymphoma of the orbit masquerading as Tolosa-Hunt syndrome. BMC ophthalmology\| PubMed ID: 25971316	2015
Degree of bioresorbable vascular scaffold expansion modulates loss of essential function. Acta biomaterialia\| PubMed ID: 26277377	2015
A mechanical argument for the differential performance of coronary artery grafts. Journal of the mechanical behavior of biomedical materials\| PubMed ID: 26437296	2016

Tarek Shazly

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