Effect of laryngeal jet on dry powder inhaler aerosol deposition: a numerical simulation.

Although pulmonary drug delivery has been deeply investigated, the effect of the laryngeal jet on particle deposition during drug delivery with dry powder inhalers (DPI) has not been evaluated profoundly. In this study, the flow structure and particle deposition pattern of a DPI in two airway models, one with mouth-throat region including the larynx and the other one without it, are numerically investigated. The results revealed that the laryngeal jet has a considerable effect on particle deposition. The presence of laryngeal jet leads to 4-fold and 2-fold higher deposition efficiencies for inlet flow rates of 30 and 90 L/min, respectively.

Patient-specific multi-scale design optimization of transcatheter aortic valve stents.

BACKGROUND AND OBJECTIVE: Transcatheter aortic valve implantation (TAVI) has become the standard treatment for a wide range of patients with aortic stenosis. Although some of the TAVI post-operative complications are addressed in newer designs, other complications and lack of long-term and durability data on the performance of these prostheses are limiting this procedure from becoming the standard for heart valve replacements. The design optimization of these devices with the finite element and optimization techniques can help increase their performance quality and reduce the risk of malfunctioning. Most performance metrics of these prostheses are morphology-dependent, and the design and the selection of the device before implantation should be planned for each individual patient. METHODS: In this study, a patient-specific aortic root geometry was utilized for the crimping and implantation simulation of 50 stent samples. The results of simulations were then evaluated and used for developing regression models. The strut width and thickness, the number of cells and patterns, the size of stent cells, and the diameter profile of the stent were optimized with two sets of optimization processes. The objective functions included the maximum crimping strain, radial strength, anchorage area, and the eccentricity of the stent. RESULTS: The optimization process was successful in finding optimal models with up to 40% decrease in the maximum crimping strain, 261% increase in the radial strength, 67% reduction in the eccentricity, and about an eightfold increase in the anchorage area compared to the reference device. CONCLUSIONS: The stents with larger distal diameters perform better in the selected objective functions. They provide better anchorage in the aortic root resulting in a smaller gap between the device and the surrounding tissue and smaller contact pressure. This framework can be used in designing patient-specific stents and improving the performance of these devices and the outcome of the implantation process.

Cerebral aneurysm evolution modeling from microstructural computational models to machine learning: A review.

Predicting the future behavior of cerebral aneurysms was the target of several studies in recent years. When an unruptured cerebral aneurysm is diagnosed, the physician has to decide about the treatment method. Often more giant aneurysms are diagnosed at higher risk of rupture and are candidates for intervention. However, several clinical and morphological parameters are introduced as risk factors. Therefore, some small size aneurysms with a higher growth rate and rupture risk may be missed. Nowadays, computational models and artificial intelligence can help physicians make more precise decisions, not only according to the aneurysm size. Therefore, the target can be developing a tool that receives the patient history and medical images as input and gives the aneurysm growth rate and rupture risk as output. Achieving this target can be possible by developing a proper computational growth model and using artificial intelligence. This requires knowledge of the vascular microstructure and the procedure of disease development, including degradation and remodeling mechanisms. Moreover, geometrical and clinical risk factors should also be recognized and considered. The present article is a step-by-step indication of this concept. In this paper, first, a review of different computational growth models is presented. Then, the morphological and clinical risk factors are described, and at last, the methods of combining the computational growth models with machine learning are discussed. This review can help the researchers learn the fundamentals and take the proper future steps.

A computational optimization study of a self-expandable transcatheter aortic valve.

Developing an efficient stent frame for transcatheter aortic valves (TAV) needs thorough investigation in different design and functional aspects. In recent years, most TAV studies have focused on their clinical performance, leaflet design, and durability. Although several optimization studies on peripheral stents exist, the TAV stents have different functional requirements and need to be explicitly studied. The aim of this study is to develop a cost-effective optimization framework to find the optimal TAV stent design made of Ni-Ti alloy. The proposed framework focuses on minimizing the maximum strain occurring in the stent during crimping, making use of a simplified model of the stent to reduce computational cost. The effect of the strut cross-section of the stent, i.e., width and thickness, and the number and geometry of the repeating units of the stent (both influencing the cell size) on the maximum strain is investigated. Three-dimensional simulations of the crimping process are used to verify the validity of the simplified representation of the stent, and the radial force has been calculated for further evaluation. The results suggest the key role of the number of cells (repeating units) and strut width on the maximum strain and, consequently, on the stent design. The difference in terms of the maximum strain between the simplified and the 3D model was less than 5%, confirming the validity of the adopted modeling strategy and the robustness of the framework to improve the TAV stent designs through a simple, cost-effective, and reliable procedure.

Numerical investigation of the effect of vessel size and distance on the cryosurgery of an adjacent tumor.

Cryosurgery is an efficient cancer treatment which can be used for non-invasive ablation of some internal tumors such as liver and prostate. Tumors are usually located near the large blood vessels and the heat convection may affect the progression of the ice ball. Hence it is necessary to predict the surgery procedure and its consequences earlier. In spite of the recent studies it is still unclear that which arteries will significantly affect the freezing treatment of tumors and which can be ignored. Therefore a numerical model of a spherical 3 cm diameter liver tumor, subjected to cryosurgery was developed. The specific thermophysical properties were applied to the tumor and healthy tissues in frozen and unfrozen states. A simplified Hepatic artery with different anatomical diameters was placed in different positions relative to the tumor and energy and momentum equations were solved. The temperature distribution and the shape of the resultant ice ball were discussed. The results showed that a 4 mm diameter artery in the vicinity of a tumor will increase the minimum temperature achieved at the tumor boundary by 12.5 °C and therefore significantly affects the cryosurgery outcome. This may cause insufficient freezing which leads to incomplete death of tumor cells, failure of the surgery and tumor regenesis. Eventually it was shown that injection of gold and Fe3O4 nanoparticles to the surrounding tissue of the artery can enhance the heat transfer and progression of the ice ball, making temperature distribution similar to the no vessel state. Development of computational models can provide the physicians an applicable tool which helps them recognize how efficient a treatment method will be for a specific case and design a suitable cryosurgery plan.

Numerical simulation of mitral valve prolapse considering the effect of left ventricle.

Heart failure is one of the most important issues that has been investigated in recent research studies. Variations that occur in apparatus of mitral valve, such as chordae tendineaea rupture, can affect the valve function during ventricular contraction and lead to regurgitation from the left ventricle into the left atrium. One method for understanding mitral valve function in such conditions is computational analysis. In this paper, we develop a finite element model of mitral valve prolapse, considering the direct effect of left ventricular motion on blood flow interacting with the mitral valve. Ventricular wall motion is used as a constraint for fluid domain. Arbitrary Lagrangian-Eulerian finite element method formulation is used for numerical solution of transient dynamic equations of the fluid domain. Leaflets' stresses and chordal forces during prolapse are determined and compared to previous healthy results, as well as flow characteristics in the computational domain. Results show considerable increases in the stress magnitudes of interior and posterior leaflets in prolapse condition in comparison with previous healthy studies. In addition, chordae tendineae forces are distributed non-uniformly with higher maximum value here, as a result of other chordae tendineae rupture.

Microstructural modelling of cerebral aneurysm evolution through effective stress mediated destructive remodelling.

Recently, researchers have shown an increased interest in the biomechanical modelling of cerebral aneurysm development. In the present study a fluid-solid-growth model for the formation of a fusiform aneurysm has been presented in an axi-symmetric geometry of the internal carotid artery. This model is the result of two parallel mechanisms: first, defining arterial wall as a living tissue with the ability of degradation, growth and remodelling and second, full coupling of the wall and the blood flow. Here for the first time the degradation of elastin has been defined as a function of vascular wall effective stress to take into account the shear dependent nature of degradation and the mural-cell-mediated destructive activities. The model has been stabilized in size and mechanical properties and is consistent with other computational or clinical studies. Furthermore, the evolving microstructural properties of the wall during the evolution process have been predicted.