Click here to read some interesting recently published papers from our community. If you have published an article in the field of in silico medicine, send it to us: we will include it in this section of the newsletter!
Springer Nature - Biomechanics and Modeling in Mechanobiology: Assessing calcification effects in TEVAR procedures: a computational analysis
Giuia De Campo et al
Abstract
Thoracic endovascular aortic repair (TEVAR) procedure is sometimes discouraged from clinical guidelines in the presence of calcifications and thrombus along the sealing zones. This computational study aims to understand which is the effect of calcification on stent graft displacement after TEVAR procedure, simulated in a patient-specific anatomy with a penetrating aortic ulcer (PAU).
A patient-specific anatomy without calcification is taken as reference, and four models with idealized calcifications positioned in different regions and with different material properties are analyzed. Opening area, von Mises stresses and contact pressures are evaluated to provide a reliable comparison between the calcified (Ca) and the non-calcified models (noCa), and among the calcified models themselves.
Comparing qualitatively the Ca and noCa models, no particular changes in the stent graft apposition are observed. In addition, in the Ca models the opening area results lower with respect to the noCa models, but no significant differences are observed among the Ca models. Regarding the von Mises stresses, it seems that the calcifications act as load-bearing structures, absorbing the stresses and reducing them on the aorta. Decreasing the Young modulus of the calcifications, this effect is reduced. Higher contact pressures are observed when the highest Young’s modulus of calcification is adopted, with all Ca models having greater pressures than the noCa model.
From this analysis, the stent graft seems to be positioned correctly inside the aorta, even in the presence of calcifications. In this setting, the calcifications seem to reduce the stresses on the aorta, thus reducing the likelihood of aneurysm rupture.
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Springer Nature - Physical and Engineering Sciences in Medicine: Clinical image analysis to build patient-specific models of acute ischemic stroke patients
Virginia Fregona et al
Abstract
Mechanical thrombectomy (MT) is an emergency treatment for acute ischemic stroke (AIS) to remove a clot occluding a large cerebral vessel. Histological analysis on retrieved thrombi have shown that they are mainly composed of red blood cells (RBCs), platelets and fibrin, and the outcome of MT appears to be influenced by clot composition. Therefore, being able to predict clot composition from routine medical images used for AIS diagnosis could support the choice of interventional strategy. Along with that, finite element simulations of the MT procedure can help provide insights into the impact of the procedural choices, the vessels morphology and the clot characteristics on the MT outcome. To achieve this, a realistic representation of the involved structures is necessary. In this context, this work aimed to (i) develop a methodology for the analysis of routine radiological images aiming at inferring information about clot characteristics (position, length, and composition) and (ii) develop a semi-automatic pipeline to position the clot in the patient-specific reconstructed geometry to build a patient-specific model which could be the starting point for the in silico replica of the MT procedure. However, image analysis alone could not distinguish between white and mixed clots, while a distinction between red and non-red clots was possible. Consequently, histological analyses were used to assign the clot composition, and thus the mechanical properties, in the positioning simulation. The resulting patient-specific model showed a strong similarity with pre-interventional clinical images.
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