Editorial: 3D Modelling of Mammalian Embryos and Organs

The main scope of this Special issue was to gain understanding on how tissues and organs are arranged into integrative hierarchical levels of complexity, from the molecular to the morphological organization. To understand the underlying complexity of the relationships among these levels during morphogenesis or in the adult we must learn how to resolve single-cell spatial relationships in the three-dimensional (3D) organisation of tissues, organs and even of the whole organisms.Fil: Garagna, Silvia. Universita Degli Studi Di Pavia; ItaliaFil: Cebral, Elisa. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Biodiversidad y Biología Experimental y Aplicada. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Biodiversidad y Biología Experimental y Aplicada; ArgentinaFil: Aréchaga, Juan. Universidad del País Vasco; EspañaFil: Zuccotti, Maurizio. Universita Degli Studi Di Pavia; Itali

Generation of non‐isotropic unstructured grids via directional enrichment

A procedure for the generation of highly stretched grids suitable for Reynolds‐averaged Navier–Stokes (RANS) calculations is presented. In a first stage, an isotropic (Euler) mesh is generated. In a second stage, this grid is successively enriched with points in order to achieve highly stretched elements. The element reconnection is carried out using a constrained Delaunay approach. Points are introduced from the regions of lowest stretching towards the regions of highest stretching. The procedure has the advantages of not requiring any type of surface recovery, not requiring extra passes or work to mesh concave ridges/corners, and guarantees a final mesh, an essential requirement for industrial environments. Given that point placement and element quality are highly dependent for the Delaunay procedure, special procedures were developed in order to obtain optimal point placement

Efficient simulation of blood flow past complex endovascular devices using an adaptive embedding technique

The simulation of blood flow past endovascular devices such as coils and stents is a challenging problem due to the complex geometry of the devices. Traditional unstructured grid computational fluid dynamics relies on the generation of finite element grids that conform to the boundary of the computational domain. However, the generation of such grids for patient-specific modeling of cerebral aneurysm treatment with coils or stents is extremely difficult and time consuming. This paper describes the application of an adaptive grid embedding technique previously developed for complex fluid structure interaction problems to the simulation of endovascular devices. A hybrid approach is used: the vessel walls are treated with body conforming grids and the endovascular devices with an adaptive mesh embedding technique. This methodology fits naturally in the framework of image-based computational fluid dynamics and opens the door for exploration of different therapeutic options and personalization of endovascular procedures

Parallel Advancing Front Grid Generation

A parallel advancing front scheme has been developed. The domain to be gridded is rst subdivided spatially using a relatively coarse octree. Boxes are then identiied and gridded in parallel. A scheme that resembles closely the advancing front technique on scalar machines is recovered by only considering the boxes of the active front that generate small elements. The procedure has been implemented on the SGI Origin class of machines using the shared memory paradigm. Timings for a variety of cases show speedups similar to those obtained for ow codes. The procedure has been used to generate grids in excess of a hundred million elements.&nbsp

Hemodynamic characteristics at anterior communicating artery before aneurysm initiation using patient-specific finite element blood flow simulations

The anterior communicating artery (AComA) is a unique vascular location that receives blood from two sources of inflow and redistributes it toward the anterior part of the brain through two efferent arteries. It is widely accepted that complexity in the flow pattern is associated with the high rate of aneurysm formation in that location observed in large studies. A previous computational hemodynamic study showed a possible association between high maximum intraaneurysmal wall shear stress (WSS) at the systolic peak with rupture in a cohort of AComA aneurysms. In another study it was observed a connection between location of aneurysm blebs and regions of high WSS in models where blebs were virtually removed. The purpose of this work is to study associations between hemodynamic patterns and AComA aneurysm initiation by comparing hemodynamics between the aneurysm models and the normal model where the aneurysm was computationally removed. Vascular models of both right and left circulation were independently reconstructed from three-dimensional rotational angiography images using deformable models after image registration of both images, and later fused using a surface merging algorithm. Afterwards, the geometric models were used to generate high-quality volumetric finite element grids composed several million tetrahedral elements with an advancing front technique. For each patient the second anatomical model was created by digitally removing the aneurysm. It was iteratively achieved by applying a Laplacian smoothing filter and remeshing the surface. Finite element blood flow numerical simulations were performed for both the pathological and normal models under the same flow conditions. Personalized pulsatile flow conditions were imposed at the inlets of both models with use of the Womersley solution. The Navier-Stokes equations were numerically integrated by using a fully implicit finite-element formulation. From analysis of WSS distributions it was observed that aneurysms initiated in regions of high and moderate WSS in the counterpart normal models. Adjacent or close to those regions, low WSS portions of the arterial wall were not affected by the disease. These results are in line with previous reported observations at other vascular locations.Fil: Castro, Marcelo Adrian. Universidad Tecnológica Nacional. Facultad Regional Buenos Aires; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. George Mason University; Estados UnidosFil: Putman, Christopher M.. Inova Fairfax Hospital; Estados UnidosFil: Cebral, Juan Raúl. George Mason University; Estados Unido

Hemodynamic characteristics at anterior communicating artery before aneurysm initiation using patient-specific finite element blood flow simulations

The anterior communicating artery (AComA) is a unique vascular location that receives blood from two sources of inflow and redistributes it toward the anterior part of the brain through two efferent arteries. It is widely accepted that complexity in the flow pattern is associated with the high rate of aneurysm formation in that location observed in large studies. A previous computational hemodynamic study showed a possible association between high maximum intraaneurysmal wall shear stress (WSS) at the systolic peak with rupture in a cohort of AComA aneurysms. In another study it was observed a connection between location of aneurysm blebs and regions of high WSS in models where blebs were virtually removed. The purpose of this work is to study associations between hemodynamic patterns and AComA aneurysm initiation by comparing hemodynamics between the aneurysm models and the normal model where the aneurysm was computationally removed. Vascular models of both right and left circulation were independently reconstructed from three-dimensional rotational angiography images using deformable models after image registration of both images, and later fused using a surface merging algorithm. Afterwards, the geometric models were used to generate high-quality volumetric finite element grids composed several million tetrahedral elements with an advancing front technique. For each patient the second anatomical model was created by digitally removing the aneurysm. It was iteratively achieved by applying a Laplacian smoothing filter and remeshing the surface. Finite element blood flow numerical simulations were performed for both the pathological and normal models under the same flow conditions. Personalized pulsatile flow conditions were imposed at the inlets of both models with use of the Womersley solution. The Navier-Stokes equations were numerically integrated by using a fully implicit finite-element formulation. From analysis of WSS distributions it was observed that aneurysms initiated in regions of high and moderate WSS in the counterpart normal models. Adjacent or close to those regions, low WSS portions of the arterial wall were not affected by the disease. These results are in line with previous reported observations at other vascular locations.Fil: Castro, Marcelo Adrian. Universidad Tecnológica Nacional. Facultad Regional Buenos Aires; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. George Mason University; Estados UnidosFil: Putman, Christopher M.. Inova Fairfax Hospital; Estados UnidosFil: Cebral, Juan Raúl. George Mason University; Estados Unido

Evaluation of predictive models of aneurysm focal growth and bleb development using machine learning techniques.

BACKGROUND: The presence of blebs increases the rupture risk of intracranial aneurysms (IAs). OBJECTIVE: To evaluate whether cross-sectional bleb formation models can identify aneurysms with focalized enlargement in longitudinal series. METHODS: Hemodynamic, geometric, and anatomical variables derived from computational fluid dynamics models of 2265 IAs from a cross-sectional dataset were used to train machine learning (ML) models for bleb development. ML algorithms, including logistic regression, random forest, bagging method, support vector machine, and K-nearest neighbors, were validated using an independent cross-sectional dataset of 266 IAs. The models ability to identify aneurysms with focalized enlargement was evaluated using a separate longitudinal dataset of 174 IAs. Model performance was quantified by the area under the receiving operating characteristic curve (AUC), the sensitivity and specificity, positive predictive value, negative predictive value, F1 score, balanced accuracy, and misclassification error. RESULTS: The final model, with three hemodynamic and four geometrical variables, along with aneurysm location and morphology, identified strong inflow jets, non-uniform wall shear stress with high peaks, larger sizes, and elongated shapes as indicators of a higher risk of focal growth over time. The logistic regression model demonstrated the best performance on the longitudinal series, achieving an AUC of 0.9, sensitivity of 85%, specificity of 75%, balanced accuracy of 80%, and a misclassification error of 21%. CONCLUSIONS: Models trained with cross-sectional data can identify aneurysms prone to future focalized growth with good accuracy. These models could potentially be used as early indicators of future risk in clinical practice