Effect of macro-calcification on the failure mechanics of intracranial aneurysmal wall tissue

Comapping Cellular Content and Extracellular Matrix with Hemodynamics in Intact Arterial Tissues Using Scanning Immunofluorescent Multiphoton Microscopy

Deviation of blood flow from an optimal range is known to be associated with the initiation and progression of vascular pathologies. Important open questions remain about how the abnormal flow drives specific wall changes in pathologies such as cerebral aneurysms where the flow is highly heterogeneous and complex. This knowledge gap precludes the clinical use of readily available flow data to predict outcomes and improve treatment of these diseases. As both flow and the pathological wall changes are spatially heterogeneous, a crucial requirement for progress in this area is a methodology for acquiring and comapping local vascular wall biology data with local hemodynamic data. Here, we developed an imaging pipeline to address this pressing need. A protocol that employs scanning multiphoton microscopy was developed to obtain three-dimensional (3D) datasets for smooth muscle actin, collagen, and elastin in intact vascular specimens. A cluster analysis was introduced to objectively categorize the smooth muscle cells (SMC) across the vascular specimen based on SMC actin density. Finally, direct quantitative comparison of local flow and wall biology in 3D intact specimens was achieved by comapping both heterogeneous SMC data and wall thickness to patient-specific hemodynamic results.

Phenotyping calcification in vascular tissues using artificial intelligence

Vascular calcification is implicated as an important factor in major adverse cardiovascular events (MACE), including heart attack and stroke. A controversy remains over how to integrate the diverse forms of vascular calcification into clinical risk assessment tools. Even the commonly used calcium score for coronary arteries, which assumes risk scales positively with total calcification, has important inconsistencies. Fundamental studies are needed to determine how risk is influenced by the diverse calcification phenotypes. However, studies of these kinds are hindered by the lack of high-throughput, objective, and non-destructive tools for classifying calcification in imaging data sets. Here, we introduce a new classification system for phenotyping calcification along with a semi-automated, non-destructive pipeline that can distinguish these phenotypes in even atherosclerotic tissues. The pipeline includes a deep-learning-based framework for segmenting lipid pools in noisy μ-CT images and an unsupervised clustering framework for categorizing calcification based on size, clustering, and topology. This approach is illustrated for five vascular specimens, providing phenotyping for thousands of calcification particles across as many as 3200 images in less than seven hours. Average Dice Similarity Coefficients of 0.96 and 0.87 could be achieved for tissue and lipid pool, respectively, with training and validation needed on only 13 images despite the high heterogeneity in these tissues. By introducing an efficient and comprehensive approach to phenotyping calcification, this work enables large-scale studies to identify a more reliable indicator of the risk of cardiovascular events, a leading cause of global mortality and morbidity.

On the major role played by the lumen curvature of intracranial aneurysms walls in determining their mechanical response, local hemodynamics, and rupture likelihood

The properties of intracranial aneurysms (IAs) walls are known to be driven by the underlying hemodynamics adjacent to the IA sac. Different pathways exist explaining the connections between hemodynamics and local tissue properties. The emergence of such theories is essential if one wishes to compute the mechanical response of a patient-specific IA wall and predict its rupture. Apart from the hemodynamics and tissue properties, one could assume that the mechanical response also depends on the local morphology, more specifically, the curvature of the luminal surface, with larger values at highly-curved wall portions. Nonetheless, this contradicts observations of IA rupture sites more often found at the dome, where the curvature is lower. This seeming contradiction indicates a complex interaction between the hemodynamics adjacent to the aneurysm wall, its morphology, and mechanical response, which warrants further investigation. This was the main goal of this work. We accomplished this by analyzing the stress and stretch fields in different regions of the wall for a sample of IAs, which have been classified based on particular hemodynamics conditions and lumen curvature. Pulsatile numerical simulations were performed using the one-way fluid-solid interaction strategy implemented in OpenFOAM (solids4foam toolbox). We found that the variable best correlated with regions of high stress and stretch was the lumen curvature. Additionally, our data suggest a connection between the local curvature and particular hemodynamics conditions adjacent to the wall, indicating that the lumen curvature is a property that could be used to assess both mechanical response and hemodynamic conditions, and, moreover, suggest new rupture indicators based on the curvature.

Lipids and cardiovascular calcification: contributions to plaque vulnerability

PURPOSE OF REVIEW

Cardiovascular calcification, a common feature of atherosclerotic lesions, has long been known to associate with cardiovascular risk. The roles of lipoproteins in atherosclerosis are also established, and lipid-modifying therapies have shown capacity for plaque regression. However, the association of lipid-modifying therapies with calcification is more complex, and currently no medical therapies have been found to reverse or attenuate calcification in patients. In this review, we summarize recent developments in our understanding of the interplay between lipids and cardiovascular calcification, as well as new imaging modalities for assessing calcified atherosclerotic plaque vulnerability.

RECENT FINDINGS

Recent clinical studies have highlighted the associations of lipoprotein subtypes, such as low-density and high-density lipoprotein particles, as well as lipoprotein (a) [Lp(a)], with coronary calcification and calcific aortic valve disease. Further, evidence continues to emerge for the utility of fused 18F-sodium fluoride positron-emission tomographic and computed tomographic (18F-NaF PET/CT) imaging in characterizing the microarchitecture and vulnerability of atherosclerotic plaque, in both humans and animal models.

SUMMARY

The relationship between lipids and cardiovascular calcification is complex, and new imaging techniques, such as 18F-NaF PET/CT imaging, may allow for better identification of disease-modifying therapies and prediction of calcified plaque progression and stability to help guide clinical management.

Complex wall modeling for hemodynamic simulations of intracranial aneurysms based on histologic images

Purpose

For the evaluation and rupture risk assessment of intracranial aneurysms, clinical, morphological and hemodynamic parameters are analyzed. The reliability of intracranial hemodynamic simulations strongly depends on the underlying models. Due to the missing information about the intracranial vessel wall, the patient-specific wall thickness is often neglected as well as the specific physiological and pathological properties of the vessel wall.

Methods

In this work, we present a model for structural simulations with patient-specific wall thickness including different tissue types based on postmortem histologic image data. Images of histologic 2D slices from intracranial aneurysms were manually segmented in nine tissue classes. After virtual inflation, they were combined into 3D models. This approach yields multiple 3D models of the inner and outer wall and different tissue parts as a prerequisite for subsequent simulations.

Result

We presented a pipeline to generate 3D models of aneurysms with respect to the different tissue textures occurring in the wall. First experiments show that including the variance of the tissue in the structural simulation affect the simulation result. Especially at the interfaces between neighboring tissue classes, the larger influence of stiffer components on the stability equilibrium became obvious.

Conclusion

The presented approach enables the creation of a geometric model with differentiated wall tissue. This information can be used for different applications, like hemodynamic simulations, to increase the modeling accuracy.