Disturbed flow's impact on cellular changes indicative of vascular aneurysm initiation, expansion, and rupture: A pathological and methodological review

Sunderland, Kevin; Jiang, Jingfeng; Zhao, Feng

doi:10.1002/jcp.30569

Cited by 19 publications

(10 citation statements)

References 267 publications

(458 reference statements)

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“…118 In addition, vascular endothelial growth factor (VEGF) and cell adhesion molecules vascular cell adhesion molecule 1 (VCAM-1) and intercellular adhesion molecule 1 (ICAM-1) have been found to be upregulated in high shear stress, leading to gaps between ECs while increasing the adhesion of inflammatory cells to ECs and VSMCs. 113,119,120 Intraluminal thrombus. Almost 75% of AAAs have intraluminal thrombus (ILT) formation, 121 which has been mentioned in several articles and reviews.…”

Section: Endothelial Cellsmentioning

confidence: 99%

The mechanism and therapy of aortic aneurysms

Gao

Cao

et al. 2023

Sig Transduct Target Ther

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Aortic aneurysm is a chronic aortic disease affected by many factors. Although it is generally asymptomatic, it poses a significant threat to human life due to a high risk of rupture. Because of its strong concealment, it is difficult to diagnose the disease in the early stage. At present, there are no effective drugs for the treatment of aneurysms. Surgical intervention and endovascular treatment are the only therapies. Although current studies have discovered that inflammatory responses as well as the production and activation of various proteases promote aortic aneurysm, the specific mechanisms remain unclear. Researchers are further exploring the pathogenesis of aneurysms to find new targets for diagnosis and treatment. To better understand aortic aneurysm, this review elaborates on the discovery history of aortic aneurysm, main classification and clinical manifestations, related molecular mechanisms, clinical cohort studies and animal models, with the ultimate goal of providing insights into the treatment of this devastating disease. The underlying problem with aneurysm disease is weakening of the aortic wall, leading to progressive dilation. If not treated in time, the aortic aneurysm eventually ruptures. An aortic aneurysm is a local enlargement of an artery caused by a weakening of the aortic wall. The disease is usually asymptomatic but leads to high mortality due to the risk of artery rupture.

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Section: Endothelial Cellsmentioning

confidence: 99%

The mechanism and therapy of aortic aneurysms

Gao

Cao

et al. 2023

Sig Transduct Target Ther

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“…Morphologically, saccular and fusiform aneurysms are common while serpentine and blood blister-like aneurysms (BBA) are less common. Different appearances of IA may be associated with different etiological underpinnings, but factors predisposing to IA progression can be summarized in two categories: direct damage to the IA wall from high wall shear stress and low wall shear stress accompanying inflammation-mediated IA wall remodeling 1,59 . These features can be glimpsed in histological studies, with the limitations of the size of usual IA.…”

Section: Discussionmentioning

confidence: 99%

Single-cell transcriptome analysis reveals the cellular atlas of human intracranial aneurysm and highlights inflammation features associated with aneurysm rupture

Sun

et al. 2023

Preprint

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Intracranial aneurysm (IA) is pouch-like pathological dilations of cerebral arteries, which often affects middle-aged people and culminates in life-threatening hemorrhagic stroke. A deeper knowledge of the cellular and gene expression perturbations in human IA tissue deepens our understanding of disease mechanisms and facilitates developing pharmacological targets for unruptured IA. In this study, 21,332 qualified cells were obtained from cell-sparse ruptured and unruptured human IA tissues and a detailed cellular profile was determined, including conventional endothelial cells, smooth muscle cells (SMC), fibroblasts and the newly identified pericytes. Notably, striking proportion of immune cells were identified in IA tissue, with the number of monocyte/macrophages and neutrophils being remarkably higher in ruptured IA. By leveraging external datasets and machine learning algorithms, a subset of macrophages characterized by high expression of CCL3 and CXCL3, and transcriptional activation of NF-κB and HIVEP2 was identified as the cell most associated with IA rupture. Further, the interactome of CCL3/CXCL3 macrophages disclosed their role in regulating vascular cell survival and orchestrating inflammation. In summary, this study illustrated the profile and interactions of vascular and immune cells in human IA tissue and the opportunities for targeting local chronic inflammation.

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“…It is worth noting that high TA LSA Std 2 values often correspond to flow stagnation within an IA dome. Slow flow or flow stagnation promotes inflammation-related changes at the aneurysm wall that weaken its structural integrity [44].…”

Section: Model Interpretation 411 Comparison Of Reasoning Behind Six ...mentioning

confidence: 99%

Can we explain machine learning-based prediction for rupture status assessments of intracranial aneurysms?

Rezaeitaleshmahalleh

Lyu

et al. 2023

Biomed. Phys. Eng. Express

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Although applying machine learning (ML) algorithms to rupture risk assessment of intracranial aneurysms (IA) has yielded promising results, the opaqueness of some ML methods has limited their clinical translation. We present the first explainability comparison of six commonly used ML algorithms: multivariate logistic regression (LR), support vector machine (SVM), random forest (RF), extreme gradient boosting (XGBoost), multi-layer perceptron neural network (MLPNN), and Bayesian additive regression trees (BART). A total of 128 IAs with known rupture status were selected for this study. The ML-based classification used two anatomical features, nine hemodynamic parameters, and thirteen morphologic variables. We utilized permutation feature importance, local interpretable model-agnostic explanations (LIME), and SHapley Additive exPlanations (SHAP) algorithms to explain and analyze 6 ML algorithms. All models performed comparably: LR area under curve (AUC) were 0.71; SVM AUC was 0.76; RF AUC was 0.73; XGBoost AUC was 0.78; MLPNN AUC was 0.73; BART AUC was 0.73. Our interpretability analysis demonstrated consistent results across methods, i.e., the utility of the top 12 features was broadly consistent. Furthermore, contributions of 7 important features (aneurysm area, aneurysm location, aneurysm type, wall shear stress maximum during systole, size ratio between aneurysm width and parent vessel diameter, (parent) vessel diameter, one standard deviation among time-averaged low shear area) were nearly the same. This research suggests that ML classifiers can provide explainable predictions consistent with general domain knowledge concerning IA rupture. With the improved understanding of ML algorithms, clinicians' trust in ML algorithms will be enhanced, accelerating their clinical translation.

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Disturbed flow's impact on cellular changes indicative of vascular aneurysm initiation, expansion, and rupture: A pathological and methodological review

Cited by 19 publications

References 267 publications

The mechanism and therapy of aortic aneurysms

The mechanism and therapy of aortic aneurysms

Single-cell transcriptome analysis reveals the cellular atlas of human intracranial aneurysm and highlights inflammation features associated with aneurysm rupture

Can we explain machine learning-based prediction for rupture status assessments of intracranial aneurysms?

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