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1.
Biomech Model Mechanobiol ; 19(6): 2643-2656, 2020 Dec.
Artículo en Inglés | MEDLINE | ID: mdl-32621161

RESUMEN

Aortic dissection (AD) is one of the most catastrophic cardiovascular diseases. AD occurs when a layer inside the aorta is disrupted and gives rise to the formation of a true lumen and a false lumen. These lumens can be connected through tears in the intimal flap which are known as entries. Despite being known for about two centuries, the effects of many factors on the morbidity and mortality of this disease are still unknown. As the blood interaction with the aorta is crucial in the severity and the progression of the aortic dissection, a biomechanical approach is chosen to investigate the influence of different morphologies on the severity of this disease. Using the finite element method (FEM) and the fluid-structure interaction (FSI) approach, we have evaluated the blood flow characteristics along the diseased aorta, in conjunction with the deformation of the aortic wall. In this study, an idealized geometry of a dissected descending aorta (type B) with two entries has been studied. The values for the diameter of the entry tear were chosen to be 5 mm and 10 mm. Therefore, a total of four conditions were investigated. According to our results, the retrograde flow through the proximal tear is dependent on the size of the distal re-entry and vice versa. Our results revealed that when both entry and re-entry tears are 10 mm in diameter, the flow passes through the true and false lumens with smaller resistance, resulting in a smaller flutter of the intimal flap, and therefore more stable intimal flap. Major oscillation frequencies of 2.5 Hz and 7.4 Hz were observed for the oscillation of the intimal flap, and amplitudes of the waves with higher frequencies were negligible.


Asunto(s)
Aneurisma de la Aorta Torácica/fisiopatología , Disección Aórtica/fisiopatología , Velocidad del Flujo Sanguíneo , Hemodinámica , Aorta , Simulación por Computador , Humanos , Imagenología Tridimensional , Modelos Cardiovasculares , Oscilometría , Flujo Sanguíneo Regional , Estrés Mecánico , Factores de Tiempo
2.
Science ; 358(6367)2017 12 01.
Artículo en Inglés | MEDLINE | ID: mdl-29191876

RESUMEN

Kim et al (Reports, 28 April 2017, p. 430) presented results for the solar-driven harvesting of water from air via metal-organic frameworks as a prodigious potential advance toward remedying global water shortages. Basic thermodynamics and a survey of multiple off-the-shelf technologies show that their approach is vastly inferior in efficiency (and thereby in feasibility) to available alternatives.


Asunto(s)
Luz Solar , Agua , Estructuras Metalorgánicas , Termodinámica
3.
Med Eng Phys ; 38(11): 1360-1368, 2016 11.
Artículo en Inglés | MEDLINE | ID: mdl-27717595

RESUMEN

A challenging problem of radiofrequency ablation (RFA) in liver surgery is to accurately estimate the shapes and sizes of RFA lesions whose formation depends on intrinsic variations of the thermal-electrical properties of soft tissue. Large tumors, which can be as long as 10 cm or more, further complicate the problem. In this paper, a probabilistic bio-heating finite element (FE) model is proposed and developed to predict RFA lesions. Uncertainties of RFA lesions are caused by the probabilistic nature of five thermal-electrical liver properties: thermal conductivity, liver tissue density, specific heat, blood perfusion rate and electrical conductivity. Confidence levels of shapes and sizes of lesions are generated by the FE model incorporated with the mean-value first-order second-moment (MVFOSM) method. Based on the probabilistic FE method, a workflow of RFA planning is introduced to enable clinicians to preoperatively view the predicted RFA lesions in three-dimension (3D) within a hepatic environment. Accurate planning of the RFA needle placements can then be achieved based on the interactive simulation and confidence level selection.


Asunto(s)
Ablación por Catéter , Análisis de Elementos Finitos , Neoplasias Hepáticas/patología , Neoplasias Hepáticas/cirugía , Modelos Estadísticos , Carga Tumoral , Método de Montecarlo
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