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The improvement in congenital heart disease (CHD) treatment and management has increased the life expectancy in infants. However, the long-term efficacy is difficult to assess and thus, computational modelling has been applied for evaluating this. Here, we provide an overview of the applications of computational modelling in CHD based on three categories; CHD involving large blood vessels only, heart chambers only, and CHD that occurs at multiple heart structures. We highlight the advancement of computational simulation of CHD that uses multiscale and multiphysics modelling to ensure a complete representation of the heart and circulation. We provide a brief future direction of computational modelling of CHD such as to include growth and remodelling, detailed conduction system, and occurrence of myocardial infarction. We also proposed validation technique using advanced three-dimensional (3D) printing and particle image velocimetry (PIV) technologies to improve the model accuracy.
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Brain oedema or tissue swelling that develops after ischaemic stroke can cause detrimental effects, including brain herniation and increased intracranial pressure (ICP). These effects can be reduced by performing a decompressive craniectomy (DC) operation, in which a portion of the skull is removed to allow swollen brain tissue to expand outside the skull. In this study, a poroelastic model is used to investigate the effect of brain ischaemic infarct size and location on the severity of brain tissue swelling. Furthermore, the model will also be used to evaluate the effectiveness of DC surgery as a treatment for brain tissue swelling after ischaemia. The poroelastic model consists of two equations: one describing the elasticity of the brain tissue and the other describing the changes in the interstitial tissue pressure. The model is applied on an idealized brain geometry, and it is found that infarcts with radius larger than approximately 14 mm and located near the lateral ventricle produce worse brain midline shift, measured through lateral ventricle compression. Furthermore, the model is also able to show the positive effect of DC treatment in reducing the brain midline shift by allowing part of the brain tissue to expand through the skull opening. However, the model does not show a decrease in the interstitial pressure during DC treatment. Further improvement and validation could enhance the capability of the proposed poroelastic model in predicting the occurrence of brain tissue swelling and DC treatment post ischaemia.
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A computational approach is used to investigate potential risk factors for distal stent graft-induced new entry (dSINE) in aortic dissection (AD) patients. Patient-specific simulations were performed based on computed tomography images acquired from six AD patients (three dSINE and three non-dSINE) to analyze the correlation between anatomical characteristics and stress/strain distributions. Sensitivity analysis was carried out using idealized models to independently assess the effect of stent graft length, stent tortuosity and wedge apposition angle at the landing zone on key biomechanical variables. Mismatch of biomechanical properties between the stented and nonstented regions led to high stress at the distal stent graft-vessel interface in all patients, as well as shear strain in the neighboring region, which coincides with the location of tear formation. Stress was observed to increase with the increase of stent tortuosity (from 263 kPa at a tortuosity angle of 50 deg to 313 kPa at 30 deg). It was further amplified by stent graft landing at the inflection point of a curve. Malapposition of the stent graft led to an asymmetrical segment within the aorta, therefore changing the location and magnitude of the maximum von Mises stress substantially (up to +25.9% with a +25 deg change in the distal wedge apposition angle). In conclusion, stent tortuosity and wedge apposition angle serve as important risk predictors for dSINE formation in AD patients.
Assuntos
StentsRESUMO
Reperfusion of the blood flow to ischemic myocardium is the standard treatment for patients suffering myocardial infarction. However, the reperfusion itself can also induce myocardial injury, in which the actual mechanism and its risk factors remain unclear. This work aims to study the mechanism of ischemia-reperfusion treatment using a three-dimensional (3D) oxygen diffusion model. An electrical model is then coupled to an oxygen model to identify the possible region of myocardial damage. Our findings show that the value of oxygen exceeds its optimum (>1.0) at the ischemic area during early reperfusion period. This complication was exacerbated in a longer ischemic period. While a longer reperfusion time causes a continuous excessive oxygen supply to the ischemic area throughout the reperfusion time. This work also suggests the use of less than 0.8 of initial oxygen concentration in the reperfusion treatment to prevent undesired upsurge at the early reperfusion period and further myocardial injury. We also found the region at risk for myocardial injury is confined in the ischemic vicinity revealed by its electrical conductivity impairment. Although there is a risk that reperfusion leads to myocardial injury for excessive oxygen accumulation, the reperfusion treatment is helpful in reducing the infarct size.