Low Shear Stress at Baseline Predicts Expansion and Aneurysm-Related Events in Patients With Abdominal Aortic Aneurysm

CTA-Based Radiomics and Area Change Rate Predict Infrarenal Abdominal Aortic Aneurysms Patients Events: A Multicenter Study

RATIONALE AND OBJECTIVES

Clinical assessment of abdominal aortic aneurysm (AAA) intervention and rupture risk relies primarily on maximum diameter, but studies have shown that sole dependence on diameter has limitations. CTA-based radiomics, aneurysm and lumen area change rates (AACR, LACR) are measured to predict potential AAA events.

MATERIALS AND METHODS

Between January 2017 and November 2022, 260 AAA patients from four centers who underwent two preoperative CTA examinations were included in this retrospective study. The endpoint event is defined as AAA rupture or repair. Patients were categorized into event and no-event groups based on the occurrence of endpoint event during follow-up. AACR and LACR were assessed using baseline and follow-up CTA, with radiomics features extracted from the baseline images. C-statistics and the Kaplan-Meier analysis were used to evaluate the predictive performance.

RESULTS

A total of 193 eligible infrarenal AAA patients were included, 176 (91.2%) were man and 17 (8.8%) were woman. The median follow-up was 33.4 (14.2, 57.4) months. Seven models were constructed, comprising the aneurysm-based Radscore model, lumen-based Radscore model, intraluminal thrombus (ILT)-based Radscore model, AACR model, LACR model, clinical model (including high-density lipoprotein, D-dimer, and baseline aneurysm diameter), and a merged model. On the external validation set, the C-index of seven models were 0.713 (0.574-0.853), 0.642 (0.499-0.786), 0.727 (0.600-0.854), 0.619 (0.484-0.753), 0.680 (0.530-0.830), 0.690 (0.557-0.824) and 0.760 (0.651-0.869), in that order. In the Kaplan-Meier analysis, the merged model was best-divided patients into high/low-risk groups with Log-rank p < 0.0001. The AARC and LARC between non-event and event groups have significant differences (AACR: 1.4 cm2/y vs. 2.3 cm2/y, p < 0.0001; LACR: 0.3 cm2/y vs. 1.1 cm2/y, p < 0.0001).

CONCLUSION

CTA-based radiomics, AACR and LACR have good predictive value for outcome event in infrarenal AAA patients.

Single-cell sequencing reveals the impact of endothelial cell PIEZO1 expression on thoracic aortic aneurysm

INTRODUCTION

Thoracic aortic aneurysm (TAA) is a severe vascular disease that threatens human life, characterized by focal dilatation of the entire aortic wall, with a diameter 1.5 times larger than normal. PIEZO1, a mechanosensitive cationic channel, monitors mechanical stimulations in the environment, transduces mechanical signals into electrical signals, and converts them into biological signals to activate intracellular signaling pathways. However, the role of PIEZO1 in TAA is still unclear.

METHODS

We analyzed a single-cell database to investigate the expression level of PIEZO1 in TAA. We constructed a conditional knockout mouse model of Piezo1 and used the PIEZO1 agonist Yoda1 to intervene in the TAA model mice established by co-administration of BAPN and ANG-II. Finally, we explored the effect of Yoda1 on TAA in vitro.

RESULTS AND DISCUSSION

We observed decreased PIEZO1 expression in TAA at both RNA and protein levels. Single-cell sequencing identified a specific reduction in Piezo1 expression in endothelial cells. Administration of PIEZO1 agonist Yoda1 prevented the formation of TAA. In PIEZO1 endothelial cell conditional knockout mice, Yoda1 inhibited TAA formation by interfering with PIEZO1. In vivo and in vitro experiments demonstrated that the effect of Yoda1 on endothelial cells involved macrophage infiltration, extracellular matrix degradation, and neovascularization. This study highlights the role of PIEZO1 in TAA and its potential as a therapeutic target, providing opportunities for clinical translation.

Measurement of Abdominal Aortic Aneurysm Strain Using MR Deformable Image Registration: Accuracy and Relationship to Recent Aneurysm Progression

BACKGROUND

Management of asymptomatic abdominal aortic aneurysm (AAA) based on maximum aneurysm diameter and growth rate fails to preempt many ruptures. Assessment of aortic wall biomechanical properties may improve assessment of progression and rupture risk. This study aimed to assess the accuracy of AAA wall strain measured by cine magnetic resonance imaging (MRI) deformable image registration (MR strain) and investigate its relationship with recent AAA progression.

METHODS

The MR strain accuracy was evaluated in silico against ground truth strain in 54 synthetic MRIs generated from a finite element model simulation of an AAA patient's abdomen for different aortic pulse pressures, tissue motions, signal intensity variations, and image noise. Evaluation included bias with 95% confidence interval (CI) and correlation analysis. Association of MR strain with AAA growth rate was assessed in 25 consecutive patients with >6 months of prior surveillance, for whom cine balanced steady-state free-precession imaging was acquired at the level of the AAA as well as the proximal, normal-caliber aorta. Univariate and multivariate regressions were used to associate growth rate with clinical variables, maximum AAA diameter (D max ), and peak circumferential MR strain through the cardiac cycle. The MR strain interoperator variability was assessed using bias with 95% CI, intraclass correlation coefficient, and coefficient of variation.

RESULTS

In silico experiments revealed an MR strain bias of 0.48% ± 0.42% and a slope of correlation to ground truth strain of 0.963. In vivo, AAA MR strain (1.2% ± 0.6%) was highly reproducible (bias ± 95% CI, 0.03% ± 0.31%; intraclass correlation coefficient, 97.8%; coefficient of variation, 7.14%) and was lower than in the nonaneurysmal aorta (2.4% ± 1.7%). D max ( β = 0.087) and MR strain ( β = -1.563) were both associated with AAA growth rate. The MR strain remained an independent factor associated with growth rate ( β = -0.904) after controlling for D max .

CONCLUSIONS

Deformable image registration analysis can accurately measure the circumferential strain of the AAA wall from standard cine MRI and may offer patient-specific insight regarding AAA progression.

Uncertainty quantification of the impact of peripheral arterial disease on abdominal aortic aneurysms in blood flow simulations

Peripheral arterial disease (PAD) and abdominal aortic aneurysms (AAAs) often coexist and pose significant risks of mortality, yet their mutual interactions remain largely unexplored. Here, we introduce a fluid mechanics model designed to simulate the haemodynamic impact of PAD on AAA-associated risk factors. Our focus lies on quantifying the uncertainty inherent in controlling the flow rates within PAD-affected vessels and predicting AAA risk factors derived from wall shear stress. We perform a sensitivity analysis on nine critical model parameters through simulations of three-dimensional blood flow within a comprehensive arterial geometry. Our results show effective control of the flow rates using two-element Windkessel models, although specific outlets need attention. Quantities of interest like endothelial cell activation potential (ECAP) and relative residence time are instructive for identifying high-risk regions, with ECAP showing greater reliability and adaptability. Our analysis reveals that the uncertainty in the quantities of interest is 187% of that of the input parameters. Notably, parameters governing the amplitude and frequency of the inlet velocity exert the strongest influence on the risk factors' variability and warrant precise determination. This study forms the foundation for patient-specific simulations involving PAD and AAAs which should ultimately improve patient outcomes and reduce associated mortality rates.

Sutton-Kadir Syndrome can be treated safely with endovascular embolisation alone

INTRODUCTION

Sutton-Kadir Syndrome (SKS) describes true inferior pancreaticoduodenal artery (IPDA) aneurysms in the setting of coeliac artery (CA) stenosis or occlusion. Although rare, SKS aneurysms can rupture and cause morbidity. Due to its rarity and lack of controlled treatment data, correct treatment for the CA lesion is currently unknown. Our aim was to assess if endovascular embolisation alone was safe and effective in treatment of SKS aneurysms, in emergent and elective settings. Secondary objectives were to describe presentation and imaging findings.

METHODS

A retrospective cohort study of patients treated at Sir Charles Gairdner Hospital between January 2014 and December 2021 was done. Data on presentation, diagnostics, aneurysm characteristics, CA lesion aetiology, treatment and outcomes were extracted from chart review.

RESULTS

Twenty-four aneurysms in 14 patients were identified. Rupture was seen in 7/15 patients. Most aneurysms (22/24) were in the IPDA or one of its anterior or posterior branches. Median arcuate ligament (MAL) compression was identified in all. There was no difference in median (IQR) maximal transverse diameter between ruptured and non-ruptured aneurysms (6 mm (9), 12 mm (6), P = 0.18). Of ruptures, 6/7 had successful endovascular embolisation and 1/7 open surgical ligation. Of non-ruptures, 6/7 had successful endovascular embolisation, 1/7 open MAL division then endovascular CA stenting and aneurysm embolisation. No recurrences or new aneurysms were detected with computed tomography or magnetic resonance angiography over a median (IQR) follow-up period of 30 (10) months in 12 patients.

CONCLUSION

Endovascular embolisation of SKS aneurysms without treatment of MAL compression is safe and effective in both the emergent and elective settings.

Smoothed particle hydrodynamics based FSI simulation of the native and mechanical heart valves in a patient-specific aortic model

The failure of the aortic heart valve is common, resulting in deterioration of the pumping function of the heart. For the end stage valve failure, bi-leaflet mechanical valve (most popular artificial valve) is implanted. However, due to its non-physiological behaviour, a significant alteration is observed in the normal haemodynamics of the aorta. While in-vivo experimentation of a human heart valve (native and artificial) is a formidable task, in-silico study using computational fluid dynamics (CFD) with fluid structure interaction (FSI) is an effective and economic tool for investigating the haemodynamics of natural and artificial heart valves. In the present work, a haemodynamic model of a natural and mechanical heart valve has been developed using meshless particle-based smoothed particle hydrodynamics (SPH). In order to further enhance its clinical relevance, this study employs a patient-specific vascular geometry and presents a successful validation against traditional finite volume method and 4D magnetic resonance imaging (MRI) data. The results have demonstrated that SPH is ideally suited to simulate the heart valve function due to its Lagrangian description of motion, which is a favourable feature for FSI. In addition, a novel methodology for the estimation of the wall shear stress (WSS) and other related haemodynamic parameters have been proposed from the SPH perspective. Finally, a detailed comparison of the haemodynamic parameters has been carried out for both native and mechanical aortic valve, with a particular emphasis on the clinical risks associated with the mechanical valve.

Astragaloside IV Protects against Shear Stress-Induced Glycocalyx Damage and Alleviates Abdominal Aortic Aneurysm by Regulating miR-17-3p/Syndecan-1

Background

The present study aimed to analyze the impact of astragaloside IV (AS-IV) on abdominal aortic aneurysm (AAA) and the glycocalyx, elucidating the potential mechanism of AS-IV.

Methods

Rat models of AAA were established using porcine pancreatic elastase. The effects of intraperitoneal AS-IV injection on the morphology, diameter, and glycocalyx of the aorta and the expression of miR-17-3p and Syndecan-1 (SDC1) protein were examined. Differentially expressed miRNAs from peripheral blood samples of healthy individuals, untreated patients with AAA, and treated patients with AAA were identified through sequencing. The relationship between miR-17-3p and SDC1 was validated using a dual-luciferase reporter assay. In vitro, shear stress was induced in human aortic endothelial cells (HAECs) to simulate AAA. Overexpression of miR-17-3p was performed to assess the effects of AS-IV on miR-17-3p and SDC1 expressions, apoptosis, and glycocalyx in HAECs.

Results

AS-IV mitigated aortic damage in AAA rats, reducing the aortic diameter and alleviating glycocalyx damage. In addition, it suppressed the increase in miR-17-3p expression and promoted SDC1 expression in AAA rats. Peripheral blood miR-17-3p levels were significantly higher in patients with AAA than in healthy individuals. miR-17-3p inhibited the SDC1 protein expression in HAECs. In the in vitro AAA environment, miR-17-3p was upregulated and SDC1 was downregulated in HAECs. AS-IV inhibited miR-17-3p expression, promoted SDC1 expression, and mitigated shear stress-induced apoptosis and glycocalyx damage in HAECs. Overexpression of miR-17-3p blocked AS-IV-induced SDC1 expression promotion, glycocalyx protection, and apoptosis suppression in HAECs.

Conclusion

miR-17-3p may damage the glycocalyx of aortic endothelial cells by targeting SDC1. AS-IV may promote SDC1 expression by inhibiting miR-17-3p, thereby protecting the glycocalyx and alleviating AAA.

Characterization of small abdominal aortic aneurysms' growth status using spatial pattern analysis of aneurismal hemodynamics

Aneurysm hemodynamics is known for its crucial role in the natural history of abdominal aortic aneurysms (AAA). However, there is a lack of well-developed quantitative assessments for disturbed aneurysmal flow. Therefore, we aimed to develop innovative metrics for quantifying disturbed aneurysm hemodynamics and evaluate their effectiveness in predicting the growth status of AAAs, specifically distinguishing between fast-growing and slowly-growing aneurysms. The growth status of aneurysms was classified as fast (≥ 5 mm/year) or slow (< 5 mm/year) based on serial imaging over time. We conducted computational fluid dynamics (CFD) simulations on 70 patients with computed tomography (CT) angiography findings. By converting hemodynamics data (wall shear stress and velocity) located on unstructured meshes into image-like data, we enabled spatial pattern analysis using Radiomics methods, referred to as "Hemodynamics-informatics" (i.e., using informatics techniques to analyze hemodynamic data). Our best model achieved an AUROC of 0.93 and an accuracy of 87.83%, correctly identifying 82.00% of fast-growing and 90.75% of slowly-growing AAAs. Compared with six classification methods, the models incorporating hemodynamics-informatics exhibited an average improvement of 8.40% in AUROC and 7.95% in total accuracy. These preliminary results indicate that hemodynamics-informatics correlates with AAAs' growth status and aids in assessing their progression.

AI-powered assessment of biomarkers for growth prediction of abdominal aortic aneurysms

Objective

The purpose of this study was to employ biomechanics-based biomarkers to locally characterize abdominal aortic aneurysm (AAA) tissue and investigate their relation to local aortic growth by means of an artificial intelligence model.

Methods

The study focused on a population of 36 patients with AAAs undergoing serial monitoring with electrocardiogram-gated multiphase computed tomography angiography acquisitions. The geometries of the aortic lumen and wall were reconstructed from the baseline scans and used for the baseline assessment of regional aortic weakness with three functional biomarkers, time-averaged wall-shear stress, in vivo principal strain, and intra-luminal thrombus thickness. The biomarkers were encoded as regional averages on axial and circumferential sections perpendicularly to the aortic centerline. Local diametric growth was obtained as difference in diameter between baseline and follow-up at the level of each axial section. An artificial intelligence model was developed to predict accelerated aneurysmal growth with the Extra Trees algorithm used as a binary classifier where the positive class represented regions that grew more than 2.5 mm/year. Additional clinical biomarkers, such as maximum aortic diameter at baseline, were also investigated as predictors of growth.

Results

The area under the curve for the constructed receiver operating characteristic curve for the Extra Trees classifier showed a very good performance in predicting relevant aortic growth (area under the curve = 0.92), with the three biomechanics-based functional biomarkers being objectively selected as the main predictors of growth.

Conclusions

The use of features based on the functional and local characterization of the aortic tissue resulted in a superior performance in terms of growth prediction when compared with models based on geometrical assessments. With rapid growth linked to increasing risk for patients with AAAs, the ability to access functional information related to tissue weakening and disease progression at baseline has the potential to support early clinical decisions and improve disease management.

Pathogenesis and management of abdominal aortic aneurysm

Abdominal aortic aneurysm (AAA) causes ∼170 000 deaths annually worldwide. Most guidelines recommend asymptomatic small AAAs (30 to <50 mm in women; 30 to <55 mm in men) are monitored by imaging and large asymptomatic, symptomatic, and ruptured AAAs are considered for surgical repair. Advances in AAA repair techniques have occurred, but a remaining priority is therapies to limit AAA growth and rupture. This review outlines research on AAA pathogenesis and therapies to limit AAA growth. Genome-wide association studies have identified novel drug targets, e.g. interleukin-6 blockade. Mendelian randomization analyses suggest that treatments to reduce low-density lipoprotein cholesterol such as proprotein convertase subtilisin/kexin type 9 inhibitors and smoking reduction or cessation are also treatment targets. Thirteen placebo-controlled randomized trials have tested whether a range of antibiotics, blood pressure-lowering drugs, a mast cell stabilizer, an anti-platelet drug, or fenofibrate slow AAA growth. None of these trials have shown convincing evidence of drug efficacy and have been limited by small sample sizes, limited drug adherence, poor participant retention, and over-optimistic AAA growth reduction targets. Data from some large observational cohorts suggest that blood pressure reduction, particularly by angiotensin-converting enzyme inhibitors, could limit aneurysm rupture, but this has not been evaluated in randomized trials. Some observational studies suggest metformin may limit AAA growth, and this is currently being tested in randomized trials. In conclusion, no drug therapy has been shown to convincingly limit AAA growth in randomized controlled trials. Further large prospective studies on other targets are needed.

How does hemodynamics affect rupture tissue mechanics in abdominal aortic aneurysm: Focus on wall shear stress derived parameters, time-averaged wall shear stress, oscillatory shear index, endothelial cell activation potential, and relative residence time

An abdominal aortic aneurysm (AAA) is a critical health condition with a risk of rupture, where the diameter of the aorta enlarges more than 50% of its normal diameter. The incidence rate of AAA has increased worldwide. Currently, about three out of every 100,000 people have aortic diseases. The diameter and geometry of AAAs influence the hemodynamic forces exerted on the arterial wall. Therefore, a reliable assessment of hemodynamics is crucial for predicting the rupture risk. Wall shear stress (WSS) is an important metric to define the level of the frictional force on the AAA wall. Excessive levels of WSS deteriorate the remodeling mechanism of the arteries and lead to abnormal conditions. At this point, WSS-related hemodynamic parameters, such as time-averaged WSS (TAWSS), oscillatory shear index (OSI), endothelial cell activation potential (ECAP), and relative residence time (RRT) provide important information to evaluate the shear environment on the AAA wall in detail. Calculation of these parameters is not straightforward and requires a physical understanding of what they represent. In addition, computational fluid dynamics (CFD) solvers do not readily calculate these parameters when hemodynamics is simulated. This review aims to explain the WSS-derived parameters focusing on how these represent different characteristics of disturbed hemodynamics. A representative case is presented for spatial and temporal formulation that would be useful for interested researchers for practical calculations. Finally, recent hemodynamics investigations relating WSS-related parameters with AAA rupture risk assessment are presented. This review will be useful to understand the physical representation of WSS-related parameters in cardiovascular flows and how they can be calculated practically for AAA investigations.

Mechanosignals in abdominal aortic aneurysms

Cumulative evidence has shown that mechanical and frictional forces exert distinct effects in the multi-cellular aortic layers and play a significant role in the development of abdominal aortic aneurysms (AAA). These mechanical cues collectively trigger signaling cascades relying on mechanosensory cellular hubs that regulate vascular remodeling programs leading to the exaggerated degradation of the extracellular matrix (ECM), culminating in lethal aortic rupture. In this review, we provide an update and summarize the current understanding of the mechanotransduction networks in different cell types during AAA development. We focus on different mechanosensors and stressors that accumulate in the AAA sac and the mechanotransduction cascades that contribute to inflammation, oxidative stress, remodeling, and ECM degradation. We provide perspectives on manipulating this mechano-machinery as a new direction for future research in AAA.

Large Vessel Cell Heterogeneity and Plasticity: Focus in Aortic Aneurysms

Smooth muscle cells and endothelial cells have a remarkable level of plasticity in vascular pathologies. In thoracic and abdominal aortic aneurysms, smooth muscle cells have been suggested to undergo phenotypic switching and to contribute to degradation of the aortic wall structure in response to, for example, inflammatory mediators, dysregulation of growth factor signaling or oxidative stress. Recently, endothelial-to-mesenchymal transition, and a clonal expansion of degradative smooth muscle cells and immune cells, as well as mesenchymal stem-like cells have been suggested to contribute to the progression of aortic aneurysms. What are the factors driving the aortic cell phenotype changes and how vascular flow, known to affect aortic wall structure and to be altered in aortic aneurysms, could affect aortic cell remodeling? In this review, we summarize the current literature on aortic cell heterogeneity and phenotypic switching in relation to changes in vascular flow and aortic wall structure in aortic aneurysms in clinical samples with special focus on smooth muscle and endothelial cells. The differences between thoracic and abdominal aortic aneurysms are discussed.