RESUMEN
In the cardiovascular diseased (CVD) conditions, it is essential to choose a suitable rheological model for capturing the correct physics behind the hemodynamic in the multiply afflicted diseased arterial network. This study investigates the effect of blood rheology on hemodynamics in a blood vessel with abdominal aortic aneurysm (AAA) and right internal iliac stenosis (RIIAS). A model with AAA and RIIAS is reconstructed from a human subject's computed tomography (CT) data. Localized mesh generation and pulsatile inflow condition are considered. Non-Newtonian models such as the Power-law, Carreau, Cross, and Herschel Berkley models are used in simulations. The outcome from a validated computational model is compared with the Newtonian model to identify the suitable model for dealing with pathological complications under consideration. The capabilities and significance of various rheological models are also examined via Wall Pressure (WP), Wall Shear Stress (WSS), velocity, Global non-Newtonian importance factor (IG), Vorticity Streamlines, and Swirling Strength. It is noted that during the entire cardiac cycle, the IG factor of the cross model is found to be relatively more significant. Power Law depicts larger IG factor during peak systole and early diastole. Also, the cross model depicts larger WSS, WPS, swirling strength distribution and vorticity during the peak systolic and diastolic phases It is noted that IG â¼0.02 is an appropriate non-Newtonian blood activity cut-off value in the descending abdominal artery having AAA and RIIAS. The critical important WSS values are in the range of 0-9 Pa which is stated in WSS contour plot.
Asunto(s)
Aneurisma de la Aorta Abdominal , Hemodinámica , Humanos , Arterias , Aneurisma de la Aorta Abdominal/diagnóstico por imagen , Aorta , Reología , Estrés Mecánico , Modelos Cardiovasculares , Velocidad del Flujo SanguíneoRESUMEN
Diffusion MRI (dMRI) is a non-invasive tool for assessing the white matter region of the brain by approximating the fiber streamlines, structural connectivity, and estimation of microstructure. This modality can yield useful information for diagnosing several mental diseases as well as for surgical planning. The higher angular resolution diffusion imaging (HARDI) technique is helpful in obtaining more robust fiber tracts by getting a good approximation of regions where fibers cross. Moreover, HARDI is more sensitive to tissue changes and can accurately represent anatomical details in the human brain at higher magnetic strengths. In other words, magnetic strengths affect the quality of the image, and hence high magnetic strength has good tissue contrast with better spatial resolution. However, a higher magnetic strength scanner (like 7T) is costly and unaffordable to most hospitals. Hence, in this work, we have proposed a novel CNN architecture for the transformation of 3T to 7T dMRI. Additionally, we have also reconstructed the multi-shell multi-tissue fiber orientation distribution function (MSMT fODF) at 7T from single-shell 3T. The proposed architecture consists of a CNN-based ODE solver utilizing the Trapezoidal rule and graph-based attention layer alongwith L1 and total variation loss. Finally, the model has been validated on the HCP data set quantitatively and qualitatively.
Asunto(s)
Imagen de Difusión por Resonancia Magnética , Sustancia Blanca , Humanos , Imagen de Difusión por Resonancia Magnética/métodos , Encéfalo/diagnóstico por imagen , Sustancia Blanca/diagnóstico por imagen , Difusión , Procesamiento de Imagen Asistido por Computador/métodosRESUMEN
BACKGROUND AND OBJECTIVE: Diffusion MRI (dMRI) has been considered one of the most popular non-invasive techniques for studying the human brain's white matter (WM). dMRI is used to delineate the brain's microstructure by approximating the WM region's fiber tracts. The achieved fiber tracts can be utilized to assess mental diseases like Multiple sclerosis, ADHD, Seizures, Intellectual disability, and others. New techniques such as high angular resolution diffusion-weighted imaging (HARDI) have been developed, providing precise fiber directions, and overcoming the limitation of traditional DTI. Unlike Single-shell, Multi-shell HARDI provides tissue fractions for white matter, gray matter, and cerebrospinal fluid, resulting in a Multi-shell Multi-tissue fiber orientation distribution function (MSMT fODF). This MSMT fODF comes up with more precise fiber directions than a Single-shell, which helps to get correct fiber tracts. In addition, various multi-compartment diffusion models, including as CHARMED and NODDI, have been developed to describe the brain tissue microstructural information. This type of model requires multi-shell data to obtain more specific tissue microstructural information. However, a major concern with multi-shell is that it takes a longer scanning time restricting its use in clinical applications. In addition, most of the existing dMRI scanners with low gradient strengths commonly acquire a single b-value (shell) upto b=1000s/mm2 due to SNR (Signal-to-noise ratio) reasons and severe imaging artifacts. METHODS: To address this issue, we propose a CNN-based ordinary differential equations solver for the reconstruction of MSMT fODF from under-sampled and fully sampled Single-shell (b=1000s/mm2) dMRI. The proposed architecture consists of CNN-based Adams-Bash-forth and Runge-Kutta modules along with two loss functions, including L1 and total variation. RESULTS: We have shown quantitative results and visualization of fODF, fiber tracts, and structural connectivity for several brain regions on the publicly available HCP dataset. In addition, the obtained angular correlation coefficients for white matter and full brain are high, showing the proposed network's utility.Finally, we have also demonstrated the effect of noise by adjusting SNR from 5 to 50 and observed the network robustness. CONCLUSION: We can conclude that our model can accurately predict MSMT fODF from under-sampled or fully sampled Single-shell dMRI volumes.
Asunto(s)
Procesamiento de Imagen Asistido por Computador , Sustancia Blanca , Humanos , Procesamiento de Imagen Asistido por Computador/métodos , Encéfalo/diagnóstico por imagen , Imagen de Difusión por Resonancia Magnética/métodos , Sustancia Blanca/diagnóstico por imagen , Sustancia Gris/diagnóstico por imagenRESUMEN
The study of patient-specific human arterial flow dynamics is well known to face challenges like a) apt geometric modelling, b) bifurcation zone meshing, and c) capturing the hemodynamic prone to variations with multiple disease complications. Due to aneurysms and stenosis in the same arterial network, the blood flow dynamics get affected, which needs to be explored. This study develops a new protocol for accurate geometric modelling, bifurcation zone meshing and numerically investigates the arterial network with abdominal aortic aneurysms (AAA) and right internal iliac stenosis (RIIAS). A realistic arterial model is reconstructed from the computed tomography (CT) data of a human subject. To understand the combined effect of the aneurysm and aortoiliac occlusive diseases in a patient, an arterial network with AAA, RIIAS, multiple branches tapering, and curvature has been considered. Clinically significant pulsatile blood flow simulations have been carried out to trace the alteration in the flow dynamics with multiple pathological complications under consideration. The transient blood flow dynamics are investigated via wall shear stress, wall pressure, velocity contour, streamlines, vorticity, and swirling strength. During the systolic deceleration phase, the rhythmic nested rapid secondary oscillatory WSS, adverse pressure gradients, high WSS, and high WP bands are noticed. Also, the above studies will help researchers, clinicians, and doctors understand the influence of morphological changes on hemodynamics in cardiovascular studies.
Asunto(s)
Aneurisma de la Aorta Abdominal , Hemodinámica , Humanos , Constricción Patológica/diagnóstico por imagen , Hemodinámica/fisiología , Arterias , Aneurisma de la Aorta Abdominal/diagnóstico por imagen , Tomografía Computarizada por Rayos X , Modelos Cardiovasculares , Estrés Mecánico , Velocidad del Flujo Sanguíneo , Flujo PulsátilRESUMEN
Diffusion MRI (dMRI) is one of the most popular techniques for studying the brain structure, mainly the white matter region. Among several sampling methods in dMRI, the high angular resolution diffusion imaging (HARDI) technique has attracted researchers due to its more accurate fiber orientation estimation. However, the current single-shell HARDI makes the intravoxel structure challenging to estimate accurately. While multi-shell acquisition can address this problem, it takes a longer scanning time, restricting its use in clinical applications. In addition, most existing dMRI scanners with low gradient-strengths often acquire single-shell up to b=1000s/mm2 because of signal-to-noise ratio issues and severe image artefacts. Hence, we propose a novel generative adversarial network, VRfRNet, for the reconstruction of multi-shell multi-tissue fiber orientation distribution function from single-shell HARDI volumes. Such a transformation learning is performed in the spherical harmonics (SH) space, as raw input HARDI volume is transformed to SH coefficients to soften gradient directions. The proposed VRfRNet consists of several modules, such as multi-context feature enrichment module, feature level attention, and softmax level attention. In addition, three loss functions have been used to optimize network learning, including L1, adversarial, and total variation. The network is trained and tested using standard qualitative and quantitative performance metrics on the publicly available HCP data-set.
Asunto(s)
Procesamiento de Imagen Asistido por Computador , Sustancia Blanca , Algoritmos , Encéfalo/diagnóstico por imagen , Difusión , Imagen de Difusión por Resonancia Magnética/métodos , Procesamiento de Imagen Asistido por Computador/métodos , Sustancia Blanca/diagnóstico por imagenRESUMEN
In this study, the cardiac electro-mechanical model in a deforming domain is taken with the addition of mechanical feedback and stretch-activated channel current coupled with the ten Tusscher human ventricular cell level model that results in a coupled PDE-ODE system. The existence and uniqueness of such a coupled system in a deforming domain is proved. At first, the existence of a solution is proved in the deformed domain. The local existence of the solution is proved using the regularization and the Faedo-Galerkin technique. Then, the global existence is proved using the energy estimates in appropriate Banach spaces, Gronwall lemma, and the compactness procedure. The existence of the solution in an undeformed domain is proved using the lower semi-continuity of the norms. Uniqueness is proved using Young's inequality, Gronwall lemma, and the Cauchy-Schwartz inequality. For the application purpose, this model is applied to understand the electro-mechanical activity in ischemic cardiac tissue. It also takes care of the development of active tension, conductive, convective, and ionic feedback. The Second Piola-Kirchoff stress tensor arising in Lagrangian mapping between reference and moving frames is taken as a combination of active, passive, and volumetric components. We investigated the effect of varying strength of hyperkalemia and hypoxia, in the ischemic subregions of human cardiac tissue with local multiple ischemic subregions, on the electro-mechanical activity of healthy and ischemic zones. This system is solved numerically using the [Formula: see text] finite element method in space and the implicit-explicit Euler method in time. Discontinuities arising with the modeled multiple ischemic regions are treated to the desired order of accuracy by a simple regularization technique using the interpolating polynomials. We examined the cardiac electro-mechanical activity for several cases in multiple hyperkalemic and hypoxic human cardiac tissue. We concluded that local multiple ischemic subregions severely affect the cardiac electro-mechanical activity more, in terms of action potential (v) and mechanical parameters, intracellular calcium ion concentration [Formula: see text], active tension ([Formula: see text]), stretch ([Formula: see text]) and stretch rate ([Formula: see text]), of a healthy cell in its vicinity, compared to a single Hyperkalemic or Hypoxic subregion. The four moderate hypoxically generated ischemic subregions affect the waveform of the stretch along the fiber and the stretch rate more than a single severe ischemic subregion.
Asunto(s)
Algoritmos , Corazón , Potenciales de Acción/fisiología , Conductividad Eléctrica , Análisis de Elementos Finitos , HumanosRESUMEN
The aim of this study is to examine the interaction between two mild atherosclerotic proliferations spaced apart by a distance S by analyzing their influence on flow structure, pressure drop and stress field in an arterial vessel under pulsatile flow conditions. This has been achieved numerically by employing a time accurate, cell centered finite volume method in solving the Navier-Stokes equations governing the 3D unsteady flow dynamics in a conceptual model of an multiply constricted arterial vessel. In comparison to the pressure drop across a single stenosis, nearly a 50% increase in the late systolic and early diastolic pressure drops has been observed across the two mild constrictions when they are spaced within a distance of SAsunto(s)
Arterias/fisiopatología
, Arteriosclerosis/fisiopatología
, Modelos Cardiovasculares
, Hemorreología
, Humanos
, Estrés Mecánico