Sex-Specific Variances in Anatomy and Blood Flow of the Left Main Coronary Bifurcation: Implications for Coronary Artery Disease Risk

Studies have shown marked sex disparities in Coronary Artery Diseases (CAD) epidemiology, yet the underlying mechanisms remain unclear. We explored sex disparities in the coronary anatomy and the resulting haemodynamics in patients with suspected, but no significant CAD. Left Main (LM) bifurcations were reconstructed from CTCA images of 127 cases (42 males and 85 females, aged 38 to 81). Detailed shape parameters were measured for comparison, including bifurcation angles, curvature, and diameters, before solving the haemodynamic metrics using CFD. The severity and location of the normalised vascular area exposed to physiologically adverse haemodynamics were statistically compared between sexes for all branches. We found significant differences between sexes in potentially adverse haemodynamics. Females were more likely than males to exhibit adversely low Time Averaged Endothelial Shear Stress along the inner wall of a bifurcation (16.8% vs. 10.7%). Males had a higher percentage of areas exposed to both adversely high Relative Residence Time (6.1% vs 4.2%, p=0.001) and high Oscillatory Shear Index (4.6% vs 2.3%, p<0.001). However, the OSI values were generally small and should be interpreted cautiously. Males had larger arteries (M vs F, LM: 4.0mm vs 3.3mm, LAD: 3.6mm 3.0mm, LCX:3.5mm vs 2.9mm), and females exhibited higher curvatures in all three branches (M vs F, LM: 0.40 vs 0.46, LAD: 0.45 vs 0.51, LCx: 0.47 vs 0.55, p<0.001) and larger inflow angle of the LM trunk (M: 12.9{\deg} vs F: 18.5{\deg}, p=0.025). Haemodynamic differences were found between male and female patients, which may contribute, at least in part, to differences in CAD risk. This work may facilitate a better understanding of sex differences in the clinical presentation of CAD, contributing to improved sex-specific screening, especially relevant for women with CAD who currently have worse predictive outcomes.Comment: 14 pages, 5 figure

Adaptive Pneus

The research focuses on the performative capacities of a pneumatic material system in regards to the specific environmental conditions. The use of Adaptation as a mechanism to modulate environmental performance was the main focus of the design process and research. The location of the sun during the day acts as a trigger to adapt the system, allowing the system to passively augment the environmental conditions. A new form-finding method that combines digital and material processes has been the main method by which the experiments were undertaken. This approach necessitates a dramatic shift in the architectural design, from producing static to environmentally responsive objects. It requires a shift in thinking from buildings as static and non-active systems to material system existing over time within specific environments capable of complex environmental performances.

Secondary flow in bifurcations – Important effects of curvature, bifurcation angle and stents

Coronary bifurcations have complex flow patterns including secondary flow zones and helical flow, which directly affect pathophysiological mechanisms such as the development of atherosclerosis. The objective of this study was to generate insights into the effects of curvature, bifurcation angle and the presence of stents on flow patterns and resulting haemodynamics in coronary left main bifurcations. The blood flow and associated metrics were modelled in both idealised and patient-specific bifurcations with varying curvature and bifurcation angles with and without stents, resulting in a total of 128 geometries considered. The results showed that larger curvature of bifurcating vessels has a significant influence on secondary flow, especially with distance to the bifurcation region, causing a skew, spin and asymmetry of Dean vortices, an increase in helical flow intensity with symmetry loss, and a decrease in adversely low time-average wall shear stress (TAWSS). Generally, asymmetric flow patterns coincided with adversely low TAWSS regions. In identical stented geometries, the presence of the stents induced local recirculation immediately adjacent to the stent struts, thus generating adversely low TAWSS in these areas, with some effect on the overall secondary flow. Overall, the effect of stents outweighed the effect of curvature and BA. This new knowledge contributes to a better understanding of the joint effects of curvature, bifurcation angle, and stents on flow patterns and haemodynamics in coronary bifurcations

MedShapeNet -- A Large-Scale Dataset of 3D Medical Shapes for Computer Vision

16 pagesPrior to the deep learning era, shape was commonly used to describe the objects. Nowadays, state-of-the-art (SOTA) algorithms in medical imaging are predominantly diverging from computer vision, where voxel grids, meshes, point clouds, and implicit surface models are used. This is seen from numerous shape-related publications in premier vision conferences as well as the growing popularity of ShapeNet (about 51,300 models) and Princeton ModelNet (127,915 models). For the medical domain, we present a large collection of anatomical shapes (e.g., bones, organs, vessels) and 3D models of surgical instrument, called MedShapeNet, created to facilitate the translation of data-driven vision algorithms to medical applications and to adapt SOTA vision algorithms to medical problems. As a unique feature, we directly model the majority of shapes on the imaging data of real patients. As of today, MedShapeNet includes 23 dataset with more than 100,000 shapes that are paired with annotations (ground truth). Our data is freely accessible via a web interface and a Python application programming interface (API) and can be used for discriminative, reconstructive, and variational benchmarks as well as various applications in virtual, augmented, or mixed reality, and 3D printing. Exemplary, we present use cases in the fields of classification of brain tumors, facial and skull reconstructions, multi-class anatomy completion, education, and 3D printing. In future, we will extend the data and improve the interfaces. The project pages are: https://medshapenet.ikim.nrw/ and https://github.com/Jianningli/medshapenet-feedbac

MedShapeNet -- A Large-Scale Dataset of 3D Medical Shapes for Computer Vision

16 pagesPrior to the deep learning era, shape was commonly used to describe the objects. Nowadays, state-of-the-art (SOTA) algorithms in medical imaging are predominantly diverging from computer vision, where voxel grids, meshes, point clouds, and implicit surface models are used. This is seen from numerous shape-related publications in premier vision conferences as well as the growing popularity of ShapeNet (about 51,300 models) and Princeton ModelNet (127,915 models). For the medical domain, we present a large collection of anatomical shapes (e.g., bones, organs, vessels) and 3D models of surgical instrument, called MedShapeNet, created to facilitate the translation of data-driven vision algorithms to medical applications and to adapt SOTA vision algorithms to medical problems. As a unique feature, we directly model the majority of shapes on the imaging data of real patients. As of today, MedShapeNet includes 23 dataset with more than 100,000 shapes that are paired with annotations (ground truth). Our data is freely accessible via a web interface and a Python application programming interface (API) and can be used for discriminative, reconstructive, and variational benchmarks as well as various applications in virtual, augmented, or mixed reality, and 3D printing. Exemplary, we present use cases in the fields of classification of brain tumors, facial and skull reconstructions, multi-class anatomy completion, education, and 3D printing. In future, we will extend the data and improve the interfaces. The project pages are: https://medshapenet.ikim.nrw/ and https://github.com/Jianningli/medshapenet-feedbac