Association between blood flow pattern and rupture risk of abdominal aortic aneurysm based on computational fluid dynamics

Modeling Techniques and Boundary Conditions in Abdominal Aortic Aneurysm Analysis: Latest Developments in Simulation and Integration of Machine Learning and Data-Driven Approaches

Research on abdominal aortic aneurysms (AAAs) primarily focuses on developing a clear understanding of the initiation, progression, and treatment of AAA through improved model accuracy. High-fidelity hemodynamic and biomechanical predictions are essential for clinicians to optimize preoperative planning and minimize therapeutic risks. Computational fluid dynamics (CFDs), finite element analysis (FEA), and fluid-structure interaction (FSI) are widely used to simulate AAA hemodynamics and biomechanics. However, the accuracy of these simulations depends on the utilization of realistic and sophisticated boundary conditions (BCs), which are essential for properly integrating the AAA with the rest of the cardiovascular system. Recent advances in machine learning (ML) techniques have introduced faster, data-driven surrogates for AAA modeling. These approaches can accelerate segmentation, predict hemodynamics and biomechanics, and assess disease progression. However, their reliability depends on high-quality training data derived from CFDs and FEA simulations, where BC modeling plays a crucial role. Accurate BCs can enhance ML predictions, increasing the clinical applicability. This paper reviews existing BC models, discussing their limitations and technical challenges. Additionally, recent advancements in ML and data-driven techniques are explored, discussing their current states, future directions, common algorithms, and limitations.

Computational fluid dynamics modelling of hemodynamics in aortic aneurysm and dissection: a review

Hemodynamic analysis based on computational fluid dynamics (CFD) modelling is expected to improve risk stratification for patients with aortic aneurysms and dissections. However, the parameter settings in CFD simulations involve considerable variability and uncertainty. Additionally, the exact relationship between hemodynamic features and disease progression remains unclear. These challenges limit the clinical application of aortic hemodynamic models. This review presents a detailed overview of the workflow for CFD-based aortic hemodynamic analysis, with a focus on recent advancements in the field. We also conducted a systematic review of 27 studies with large sample sizes (n > 5) that examine the hemodynamic characteristics of aortic aneurysms and dissections. Some studies identified consistent relationships between hemodynamic features and disease progression, reinforcing the potential for clinical application of aortic hemodynamic models. However, limitations such as small sample sizes and oversimplified patient-specific models remain. These findings emphasize the need for larger, more detailed studies to refine CFD modelling strategies, strengthen the connection between hemodynamics and diseases, and ultimately facilitate the clinical use of aortic hemodynamic models in disease management.

Right-sided Aortic Torsion in Patients with Abdominal Aortic Aneurysms

OBJECTIVES

Altered flow dynamics within abdominal aortic aneurysms (AAA) may lead to changes in aneurysmal geometry, intraluminal thrombus (ILT) deposition, or aneurysmal progression. Aortic torsion is one geometric deviation that has been clinically observed but has not been formally evaluated in pre-operative AAAs. This pilot retrospective cohort study investigates the degree and directionality of aortic torsion in patients with and without AAAs.

METHODS

The inferior mesenteric artery (IMA-Angle) outlet angle was used to assess aortic torsion. Angles were measured with respect to the anterior-posterior axis in both aneurysmal (370) and non-aneurysmal (120) patients. Patient age, gender, maximum infrarenal aortic/AAA diameter (DMax), and presence/percentage of ILT were calculated.

RESULTS

370 AAA patients (Age: 74 [65:83], %Male: 88%, DMax: 50.1 mm [41.9 - 57.0 mm]) were retrospectively identified. ILT was present in 65% of cases and comprised 26.2% of the aneurysmal sac [18.6 - 36.7%]. Similarly, 120 patients without aneurysmal disease were identified (Age: 70 [63:81], %Male: 79%, DMax: 23.3 mm [21.5 - 25.6]). Median IMA-Angle [25th-75th%] in the aneurysmal cohort was 17.0° [8.6° - 25.3°] and closer to the AP axis compared to controls (38.5° [34.3° - 44.9°], p < 0.001). Presence, percentage, and classification of ILT (r = 0.01, p = 0.93) had negligible impact on IMA outlet angle.

CONCLUSION

This study highlights the right-sided IMA preference in AAA patients compared to non-aneurysmal controls. The pathophysiology underlying this rotation may be associated with a right-sided helical flow pattern in expanding aneurysmal sacs. This sets the foundation for future investigations.

A Comprehensive Review on Computational Analysis, Research Advances, and Major Findings on Abdominal Aortic Aneurysms for the Years 2021 to 2023

BACKGROUND

Abdominal aortic aneurysm (AAA) is a pathological condition characterized by the dilation of the lower part of the aorta, where significant hemodynamic forces are present. The prevalence and high mortality risk associated with AAA remain major concerns within the scientific community. There is a critical need for extensive research to understand the underlying mechanisms, pathophysiological characteristics, and effective detection methods for abdominal aortic abnormalities. Additionally, it is imperative to develop and refine both medical and surgical management strategies. This review aims to indicate the role of computational analysis in the comprehension and management of AAAs and covers recent research studies regarding the computational analysis approach conducted between 2021 and 2023. Computational analysis methods have emerged as sophisticated and noninvasive approaches, providing detailed insights into the complex dynamics of AAA and enhancing our ability to study and manage this condition effectively.

METHODS

Computational analysis relies on fluid mechanics principles applied to arterial flow, using the Navier-Stokes equations to model blood flow dynamics. Key hemodynamic indicators relevant to AAAs include Time-Average Wall Shear Stress, Oscillatory Shear Index, Endothelial Cell Activation Potential, and Relative Residence Time. The primary methods employed for simulating the abdominal aorta and studying its biomechanical environment are computational fluid dynamics and Finite Element Methods. This review article encompasses a thorough examination of recent literature, focusing on studies conducted between 2021 and 2023.

RESULTS

The latest studies have elucidated crucial insights into the blood flow characteristics and geometric attributes of AAAs. Notably, blood flow patterns within AAAs are associated with increased rupture risk, along with elevated intraluminal thrombus volume and specific calcification thresholds. Asymmetric AAAs exhibit heightened risks of rupture and thrombus formation due to low and oscillating wall shear stresses. Moreover, larger aneurysms demonstrate increased wall stress, pressure, and energy loss. Advanced modeling techniques have augmented predictive capabilities concerning growth rates and surgical thresholds. Additionally, the influence of material properties and thrombus volume on wall stress levels is noteworthy, while inlet velocity profiles significantly modulate blood flow dynamics within AAAs.

CONCLUSIONS

This review highlights the potential utility of computational modeling. However, the clinical applicability of computational modeling has been limited by methodological variability despite the ongoing accumulation of evidence supporting the prognostic significance of biomechanical and hemodynamic indices in this field. The establishment of standardized reporting is critical for clinical implementation.

Establishment of a diagnostic model for urinary calculi in pregnant women: A retrospective cohort study

OBJECTIVE

The diagnosis of symptomatic urinary stones during pregnancy is challenging; ultrasonography has a low specificity and sensitivity for diagnosing urinary stones. This study aimed to develop a clinical diagnostic model to assist clinicians in distinguishing symptomatic urinary stones in pregnant women.

METHODS

In this retrospective cohort study, we consecutively collected clinical data from pregnant women who presented with acute abdominal, lumbar, and lumbar and abdominal pain at the emergency department of our hospital between January 1, 2017, and December 31, 2019. To distinguish patients with urinary calculi from those without, we reviewed the follow-up records within 2 weeks post-consultation, ultrasonography results within 2 weeks, or self-reports of stone passage within 2 weeks. We selected risk factors from the baseline clinical and laboratory data of patients to establish a diagnostic model.

RESULTS

Of the total patients included in the study, 105 patients were diagnosed as having symptomatic urinary stones and 126 were determined to have abdominal pain for reasons other than urinary stones. The initial model had an area under the curve (AUC) of 0.9966. The No-Lab Model had an AUC of 0.9856. The Lab Model had an AUC of 0.832. The Stone Model had an AUC of 0.9952. The simplified Stone Model did not show a decrease in discriminative ability.

CONCLUSION

Of the four diagnostic models that we established for preliminary diagnosis of symptomatic urinary tract stones in pregnant women, the simplified Stone Model demonstrated excellent performance. Users can scan quick response codes to access web-based diagnostic model interfaces, facilitating easy clinical operation.

Analysis of High-Risk Factors and Mortality Prediction of Ruptured Abdominal Aortic Aneurysm

INTRODUCTION

Ruptured abdominal aortic aneurysms (RAAAs) are among the most dangerous emergencies in vascular surgery, with a high death rate and numerous risk factors influencing perioperative death. Therefore, identifying the critical risk factors for RAAAs is crucial to increasing their survival rate. Our aim was to identify those risk factors from a wide range of parameters.

METHODS

Retrospective analysis of hospitalized RAAA patients treated at this center between May 2004 and January 2023. After comparing the preoperative data of patients who survived and those who died, high-risk characteristics influencing the perioperative care of RAAA patients were identified, and logistic regression analysis was carried out. The mean follow-up time was 45.34 months.

RESULTS

During the study period, a total of 155 patients (average age 67.4 ± 71.93 years, 123 (78.85%) males, 32 (20.51%) females) were enrolled. The patients participating in the group were divided into survival group (n = 123) and death group (n = 27). The main differences included hemodynamic instability (51.9% vs 28.5%; P = 0.019), sudden cardiac arrest (14.8% vs 1.6%; P = 0.010), deterioration of consciousness (40.7% vs 17.1%; P = 0.007), renal impairment (22.2% vs 2.4%; P = 0.001), and chronic kidney disease (18.5% vs3.2%; P = 0.010). There is also a history of cancer (Ca) (18.5% vs 4.1%; P = 0.021). Risk factors for endovascular aneurysm repair (EVAR) include diastolic blood pressure ≤50 mm Hg (36.4% vs 8.0%; P = 0.025), renal function impairment (18.2% vs 0; P = 0.015), and chronic kidney disease (27.3% vs 4.0%; P = 0.028). Risk factors for open surgical repair (OSR) include diastolic blood pressure ≤50 mm Hg (40.0% vs 6.3%; P = 0.014). Finally, the previously mentioned statistically significant factors were analyzed by logistic regression analysis, and it was found that diastolic blood pressure ≤50 mm Hg, cardiac arrest, renal function damage, and Ca history were independent risk factors. We followed 123 individuals and 14 were lost to follow-up, with an overall survival rate of 43.8%.

CONCLUSIONS

Hemodynamics, which includes shock, blood pressure, cardiac arrest, deterioration of consciousness, and other conditions, are the primary risk factors for the perioperative death of a ruptured abdominal aortic aneurysm. Simultaneously, diastolic blood pressure ≤50 mm Hg was found to be associated with risk factors for OSR, whereas renal function impairment, chronic renal illness, and diastolic blood pressure ≤50 mm Hg were associated with the risk for EVAR.

Local Morphologic and Hemodynamic Analyses for the Prediction of Abdominal Aortic Aneurysm Rupture Based on Patient-Specific CTA and Computational Modeling

OBJECTIVE

Extensive research has focused on the evaluation of rupture risks in abdominal aortic aneurysms (AAAs) through comprehensive morphologic and hemodynamic analyses, primarily considering the AAA as a whole entity. This study tried to identify the high-risk rupture sites of AAAs more precisely before the fatal process based on morphologic and hemodynamic analyses at the local segment.

METHODS

Computed tomography angiography of a specific AAA patient was conducted at the follow-up 4 months before rupture, 1 day before rupture, the day of the rupture, and 15 days after endovascular aortic repair. The evolution of local morphology and the hemodynamic characteristics at these critical timepoints were investigated based on patient-specific reconstructions and computational fluid dynamics.

RESULTS

The morphologic and hemodynamic parameters of the rupture region vary continuously in the process of AAA development and rupture. The surface area and volume of the rupture segment were gradually enlarged at the follow-up 4 months before rupture (47.33 cm2; 67.35 mL), 1 day before rupture (57.23 cm2; 85.24 mL), and on the day of the rupture (62.41cm2; 104.73ml). A prominent decrease in time-averaged wall shear stress and velocity for the rupture segment is observed. The percentages of the lowest time-averaged wall shear stress (<0.1 Pa) area are increased in the AAA region (20.42%, 33.85%, and 53.00%, separately).

CONCLUSIONS

The results based on precisely rebuilt geometries for the complete follow-ups of patient-specific computed tomography angiography demonstrate that notable morphologic and hemodynamic evolutions have occurred in the local segment of the AAA, which was further proved at the rupture site. The significant changes occurring at the local segment may provide valuable information for the evaluation of aneurysm rupture risk and locate the most probable site of rupture.

CLINICAL IMPACT

Capturing the entire process of AAA rupture through CTA imaging is a rare occurrence in clinical practice. The evolution of morphology and hemodynamic characteristics observed in the illustrated results provides valuable insights for clinicians to monitor the state of AAA from a different perspective. These findings suggest that variations in morphology and hemodynamics within the local segment of the AAA might serve as an alternative approach for predicting the rupture risk of AAA.

An evidence update to explore molecular targets and protective mechanisms of apigenin against abdominal aortic aneurysms based on network pharmacology and experimental validation

Abdominal aortic aneurysms (AAA) is a life-threatening disease and the incidence of AAA is still on the rise in recent years. Numerous studies suggest that dietary moderate consumption of polyphenol exerts beneficial effects on cardiovascular disease. Apigenin (API) is a promising dietary polyphenol and possesses potent beneficial effects on our body. Although our previous study revealed protective effects of API on experimental AAA formation, up till now few studies were carried out to further investigate its involved molecular mechanisms. In the present study, network pharmacology combined molecular docking and experimental validation was used to explore API-related therapeutic targets and mechanisms in the treatment of AAA. Firstly, we collected 202 API-related therapeutic targets and 2475 AAA-related pathogenetic targets. After removing duplicates, a total of 68 potential therapeutic targets were obtained. Moreover, 5 targets with high degree including TNF, ACTB, INS, JUN, and MMP9 were identified as core targets of API for treating AAA. In addition, functional enrichment analysis indicated that API exerted pharmacological effects in AAA by affecting versatile mechanisms, including apoptosis, inflammation, blood fluid dynamics, and immune modulation. Molecular docking results further supported that API had strong affinity with the above core targets. Furthermore, protein level of core targets and related pathways were evaluated in a Cacl2-induced AAA model by using western blot and immunohistochemistry. The experimental validation results demonstrated that API significantly attenuated phosphorylation of JUN and protein level of predicted core targets. Taken together, based on network pharmacological and experimental validation, our study systematically explored associated core targets and potential therapeutic pathways of API for AAA treatment, which could supply valuable insights and theoretical basis for AAA treatment.

Effect of differences in proximal neck angles on biomechanics of abdominal aortic aneurysm based on fluid dynamics

BACKGROUND

This study aimed to analyze the effect of proximal neck angulation on the biomechanical indices of abdominal aortic aneurysms (AAA) and to investigate its impact on the risk of AAA rupture.

METHODS

CT angiography (CTA) data of patients with AAA from January 2015 to January 2022 were collected. Patients were divided into three groups based on the angle of the proximal neck: Group A (∠β ≤ 30°), Group B (30°<∠β ≤ 60°), and Group C (∠β > 60°). Biomechanical indices related to the rupture risk of AAA were analyzed using computational fluid dynamics modeling (CFD-Post) based on the collected data.

RESULTS

Group A showed slight turbulence in the AAA lumen with a mixed laminar flow pattern. Group B had a regular low-speed eddy line characterized by cross-flow dominated by lumen blood flow and turbulence. In Group C, a few turbulent lines appeared at the proximal neck, accompanied by eddy currents in the lumen expansion area following the AAA shape. Significant differences were found in peak wall stress, shear stress, and the maximum blood flow velocity impact among the three groups. The maximum blood flow velocity at the angle of the proximal neck impact indicated the influence of the proximal neck angle on the blood flow state in the lumen.

CONCLUSION

As the angle of the proximal neck increased, it caused stronger eddy currents and turbulent blood flow due to a high-speed area near the neck. The region with the largest diameter in the abdominal aortic aneurysm was prone to the highest stress, indicating a higher risk of rupture. The corner of the proximal neck experienced the greatest shear stress, potentially leading to endothelial injury and further enlargement of the aneurysm.

Preliminary establishment and validation of the inversion method for growth and remodeling parameters of patient-specific abdominal aortic aneurysm

Traditional medical imaging and biomechanical studies have challenges in analyzing the long-term evolution process of abdominal aortic aneurysm (AAA). The homogenized constrained mixture theory (HCMT) allows for quantitative analysis of the changes in the multidimensional morphology and composition of AAA. However, the accuracy of HCMT still requires further clinical verification. This study aims to establish a patient-specific AAA growth model based on HCMT, simulate the long-term growth and remodeling (G&R) process of AAA, and validate the feasibility and accuracy of the method using two additional AAA cases with five follow-up datasets. The media and adventitia layers of AAA were modeled as mixtures composed of elastin, collagen fibers, and smooth muscle cells (SMCs). The strain energy function was used to describe the continuous deposition and degradation effect of the mixture during the AAA evolution. Multiple sets of growth parameters were applied to finite element simulations, and the simulation results were compared with the follow-up data for gradually selecting the optimal growth parameters. Two additional AAA patients with different growth rates were used for validating this method, the optimal growth parameters were obtained using the first two follow-up imaging data, and the growth model was applied to simulate the subsequent four time points. The differences between the simulated diameters and the follow-up diameters of AAA were compared to validate the accuracy of the mechanistic model. The growth parameters, especially the stress-mediated substance deposition gain factor, are highly related to the AAA G&R process. When setting the optimal growth parameters to simulate AAA growth, the proportion of simulation results within the distance of less than 0.5 mm from the baseline models is above 80%. For the validating cases, the mean difference rates between the simulated diameter and the real-world diameter are within 2.5%, which basically meets the clinical demand for quantitatively predicting the AAA growth in maximum diameters. This study simulated the growth process of AAA, and validated the accuracy of this mechanistic model. This method was proved to be used to predict the G&R process of AAA caused by dynamic changes in the mixtures of the AAA vessel wall during long-term, assisting accurately and quantitatively predicting the multidimensional morphological development and mixtures evolution process of AAA in the clinic.

Factors associated with false lumen changes in patients with superior mesenteric artery dissection

BACKGROUND

False lumen changes (FLCs) are the main reference for the prognosis judgment and treatment plan selection for type IIa superior mesenteric artery dissection (SMAD).

METHODS

For this retrospective study, 55 patients with symptomatic type IIa SMAD were included. Computational fluid dynamics (CFD) analysis was used to explore the hemodynamic basis of FLCs. Correlation and multiple linear regression analyses were performed to identify clinical, morphological and hemodynamic factors associated with FLCs.

RESULTS

The FLCs of patients with successful conservative treatment (n = 29) are significantly higher than those with failed conservative treatment (n = 26) (58.5 ± 21.1% vs 10.9 ± 17.4%, p < 0.0001). Positive correlations were seen between FLCs and the morphological parameters false lumen length (FLL)/dissection entrance length (DEL) and FLL. In terms of hemodynamic parameters, negative correlations were seen between FLCs and time-averaged wall shear stress (TAWSS), vorticity, and high areas of TAWSS and vorticity, whereas positive correlations were seen between FLCs and oscillatory shear index (OSI), relative residence time (RRT), and high areas of OSI and RRT. Multiple linear regression analysis identified symptom duration (odds ratio [OR], 0.93; 95% CI, 0.91-0.96; p < 0.0001), FLL/DEL (OR, 1.30; 95% CI, 1.01-1.67; p = 0.044), and high RRT area (OR, 2.03; 95% CI, 1.48-2.78; p < 0.0001) as predictors of FLCs.

CONCLUSION

The clinical predictor symptom duration, morphological factor FLL/DEL, and the hemodynamic factor high RRT area can serve as predictors of FLCs in patients with symptomatic type IIa SMAD.

In-stent Restenosis After Stenting for Superior Mesenteric Artery Dissection Is Associated With Stent Landing Zone: From Clinical Prediction to Hemodynamic Mechanisms

OBJECTIVE

To identify risk factors for in-stent restenosis (ISR) in patients undergoing stent placement for superior mesenteric artery dissection (SMAD) and to determine the hemodynamic mechanism underlying ISR.

METHODS

For this retrospective study, patients with SMAD who had ISR after stent placement were included in the ISR group, and age- and sex-matched patients with SMAD who did not experience ISR after stent placement were included in the control group. Clinical, imaging, and hemodynamic data were assessed. Multivariable regression was used to identify independent ISR risk factors. Structural and fluid dynamics simulations were applied to determine the hemodynamic mechanism underlying the occurrence of ISR.

RESULTS

The study population included 26 patients with ISR and 26 control patients. Multivariate analysis demonstrated that stent-to-vascular (S/V) ratio (odds ratio [OR], 1.14; 95% confidence interval [CI]: 1.00-1.29; p=0.045), stent proximal position >10 mm away from the SMA root (OR, 108.67; 95% CI: 3.09-3816.42; p=0.010), and high oscillatory shear index (OSI) area (OR, 1.25; 95% CI: 1.02-1.52; p=0.029) were predictors of ISR. In structural and fluid dynamics simulations, a stent proximal position near the abdominal aorta (AA) or entering into the AA reduced the contact area between the proximal struts of the stent and the vascular wall, and alleviated the distal lumen overdilation.

CONCLUSION

The S/V ratio, stent proximal position away from the SMA root (>10 mm), and high OSI area are independent risk factors for ISR in patients with SMAD undergoing stent placement. Deploying the proximal end of the stent near the AA or entering into the AA appears to improve the hemodynamic environment in the SMA lumen and ultimately reduce the risk of ISR.

CLINICAL IMPACT

In-stent restenosis is an uncommon but potentially catastrophic complication after stent placement for the management of superior mesenteric artery dissection. This study identified risk factors for in-stent restenosis and demonstrated that, as long as the stent can fully cover the dissection range, deploying the proximal end of the stent near the abdominal aorta or less entering into the abdominal aorta may reduce the risk of in-stent restenosis in this patient population.

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.

Multimodality magnetic resonance evaluating the effect of enhanced physical exercise on the growth rate, flow haemodynamics, aneurysm wall and ventricular-aortic coupling of patients with small abdominal aortic aneurysms (AAA MOVE trial): a study protocol for an open-label randomised controlled trial

INTRODUCTION

The best lifestyle for small abdominal aortic aneurysms (sAAA) is essential for its conservative management. Physical exercise can improve the cardiopulmonary function of the patients, but it remains unclear which specific type of exercise is most beneficial for individuals with sAAA. The current study was designed to investigate the effect of physician-guided enhanced physical exercise programme on the aorto-cardiac haemodynamic environment, aneurysm sac wall, cardiac function and growth rate of sAAA by multimodality MRI.

METHODS AND ANALYSIS

AAA MOVE study is a prospective, parallel, equivalence, randomised controlled trial. Eligible individuals will be recruited if they are diagnosed with sAAA (focal dilation of abdominal aorta with maximum diameter <5 cm), without contraindication for MRI scanning, or severe heart failure, or uncontrolled arrhythmia. Participants will be randomly allocated to intervention group (physician-guided enhanced physical exercise programme: mainly aerobic training) and control group (standard clinical care) separately in a 1:1 ratio. The primary outcome is 12-month growth rate of sAAA. The first set of secondary outcomes involve multimodality MRI parameters covering flow haemodynamics, aortic wall inflammation and cardiac function. The other secondary outcome (safety end point) is a composite of exercise-related injury, aneurysm rupture and aneurysm intervention. Follow-up will be conducted at 6 and 12 months after intervention.

ETHICS AND DISSEMINATION

This study was approved by the Ethics Committee on Biomedical Research of West China Hospital (approval number: 2023-783) on 16 June 2023. Main findings from the trial will be disseminated through presentations at conferences, peer-reviewed publications and directly pushed to smartphone of participants.

TRIAL REGISTRATION NUMBER

ChiCTR2300073334.

A New and Practical Model of Human-Like Ascending Aorta Aneurysm in Rats

INTRODUCTION

Ascending aortic aneurysm is a serious health risk. In order to study ascending aortic aneurysms, elastase and calcium ion treatment for aneurysm formation are mainly used, but their aneurysm formation time is long and the aneurysm formation rate is low. Thus, this study aimed to construct a rat model of ascending aorta aneurysm with a short modeling time and high aneurysm formation rate, which may mimic the pathological processes of human ascending aorta aneurysm.

METHODS

Cushion needles with different pipe diameters (1.0, 1.2, 1.4, and 1.6 mm) were used to establish a human-like rat model of ascending aortic aneurysm by narrowing the ascending aorta of rats and increasing the force of blood flow on the vessel wall. The vascular diameters were evaluated using color Doppler ultrasonography after 2 weeks. The characteristics of ascending aortic aneurysm in rats were detected by Masson's trichrome staining, Verhoeff's Van Gieson staining, and hematoxylin and eosin staining, while real-time polymerase chain reaction was utilized to assess the total RNA of cytokine interleukin-1β, interleukin 6, transforming growth factor-beta 1, and metalloproteinase 2.

RESULTS

Two weeks after surgery, the ultrasound images and the statistical analysis demonstrated that the diameter of the ascending aorta in rats increased more than 1.5 times, similar to that in humans, indicating the success of animal modeling of ascending aortic aneurysm. Moreover, the optimal constriction diameter of the ascending aortic aneurysm model is 1.4 mm by the statistical analysis of the rate of ascending aortic aneurysm and mortality rate in rats with different constriction diameters.

CONCLUSIONS

The human-like ascending aortic aneurysm model developed in this study can be used for the studies of the pathological processes and mechanisms of ascending aortic aneurysm in a more clinically relevant fashion.

Modeling and evaluation of biomechanics and hemodynamic based on patient-specific small intracranial aneurysm using fluid-structure interaction

BACKGROUND AND OBJECTIVE

Rupture of small intracranial aneurysm (IA) often leads to the development of highly fatal clinical syndromes such as subarachnoid hemorrhage. Due to the patient specificity of small IA, there are many difficulties in evaluating the rupture risk of small IA such as multiple influencing factors, high clinical experience requirements and poor reusability.

METHODS

In this study, clinical methods such as transcranial doppler (TCD) and magnetic resonance imaging (MRI) are used to obtain patient-specific parameters, and the fluid-structure interaction method (FSI) is used to model and evaluate the biomechanics and hemodynamics of patient-specific small IA.

RESULTS

The results show that a spiral vortex stably exists in the patient-specific small IA. Due to the small size of the patient-specific small IA, the blood flow velocity still maintains a high value with maximum reaching 3 m/s. The inertial impact of blood flow and vortex convection have certain influence on hemodynamic and biomechanics parameters. They cause three high value areas of WSSM on the patient-specific small IA with maximum of 180 Pa, 130 Pa and 110 Pa, respectively. They also cause two types of WSS concentration points, positive normal stress peak value areas and negative normal stress peak value areas to appear.

CONCLUSION

This paper found that the factors affecting hemodynamic parameters and biomechanical parameters are different. Unlike hemodynamic parameters, biomechanical parameters are also affected by blood pressure in addition to blood flow velocity. This study reveals the relationship between the flow field distribution and changes of patient-specific small IA, biomechanics and hemodynamics.

Evaluation of associations between outflow morphology and rupture risk of abdominal aortic aneurysms

PURPOSE

This study aimed to evaluate the association between the outflow morphology and abdominal aortic aneurysm (AAA) rupture risk, to find risk factors for future prediction models.

MATERIALS AND METHODS

We retrospectively analyzed 46 patients with ruptured AAAs and 46 patients with stable AAAs using a 1:1 match for sex, age, and maximum aneurysm diameter. The chi-square test, paired t-test, and Wilcoxon signed-rank test were used to compare variables. Logistic regression was performed to evaluate variables potentially associated with AAA rupture. Receiver operating characteristic curve analysis and the area under the curve (AUC) were used to assess the regression models.

RESULTS

Ruptured AAAs had a shorter proximal aortic neck (median (interquartile range, IQR): 24.0 (9.4-34.2) mm vs. 33.3 (20.0-52.8) mm, p = 0.004), higher tortuosity (median(IQR): 1.35 (1.23-1.49) vs. 1.29 (1.23-1.39), p = 0.036), and smaller minimum luminal area of the right common iliac artery (CIA) (median (IQR): 86.7 (69.9-126.4) mm2 vs. 118.9 (86.3-164.1)mm2, p = 0.001) and left CIA (median(IQR): 92.2 (67.3,125.1) mm2 vs. 110.7 (80.12, 161.1) mm2, p = 0.010) than stable AAA did. Multiple regression analysis demonstrated significant associations of the minimum luminal area of the bilateral CIAs (odds ratio [OR] = 0.996, 95 % confidence interval [CI] 0.991-0.999, p = 0.037), neck length (OR = 0.969, 95 % CI 0.941-0.993, p = 0.017), and aneurysm tortuosity (OR = 1.031, 95 % CI 1.003-1.063, p = 0.038) with ruptured AAAs. The AUC of this regression model was 0.762 (95 % CI 0.664-0.860, p < 0.001).

CONCLUSIONS

The smaller minimum luminal area of the CIA is associated with an increased risk of rupture. This study highlights the potential of utilizing outflow parameters as novel and additional tools in risk assessment. It also provides a compelling rationale to further intensify research in this area.

Association Between Aneurysm Wall Inflammation Detected by Imaging Perivascular Fat and Secondary Intervention Risk for Abdominal Aortic Aneurysm Patients After Endovascular Repair

OBJECTIVE

To investigate the association between the imaging biomarker (volumetric perivascular characterization index [VPCI]) which indicates the aortic wall inflammation by mapping the spatial changes of perivascular fat attenuation on computed tomography angiography (CTA) and the reintervention risk for abdominal aortic aneurysm (AAA) patients after endovascular aortic repair (EVAR).

METHODS

This case-control study included AAA patients undergoing EVAR from a single center (n=260). Cases were AAA patients undergoing reintervention after EVAR and a 1:1 frequency-matched control group of AAA patients post-EVAR with a shrunken or ≥3-year stable sac and free of reintervention signs during the follow-up. The predictive variable (VPCI trajectory) was converted to binary variables according to the changing trend of VPCI with follow-up time. As a quasi-complete separation data pattern, least absolute shrinkage and selection operator (lasso) regression was used to screen and prove the VPCI trajectory as the best predictor, and the performance was evaluated by calculating the accuracy, sensitivity, and specificity.

RESULTS

Between 2010 and 2021, 15 AAA patients after EVAR with type I/III endoleak, aneurysm rupture, or impending rupture were included. Compared with the 1:1 frequency-matched controls with a shrunken or ≥3-year stable sac and free of reintervention signs during the follow-up, VPCI trajectories of the case group were all upward trends, whereas the controls showed 86.7% downward trends (p<0.001). The best predictive model of lasso regressions included 4 variables, and VPCI trajectory was the most outstanding, followed by the proximal landing zone, the distal landing zone, and the infrarenal β angle. The accuracy, sensitivity, and specificity of predicting the risk of reintervention were as follows, respectively: 93.3%, 100%, and 86.7%.

CONCLUSIONS

The wall inflammation detected by imaging perivascular adipose tissue based on the CTAs was strongly associated with the reintervention risk for AAA patients after EVAR, which might hold major promise as a new imaging biomarker for the mechanism and treatment study of human AAAs before and after EVAR.

CLINICAL IMPACT

The study introduces a novel imaging biomarker which indicates the aortic wall inflammation by mapping spatial changes of perivascular fat attenuation on CTA. This biomarker demonstrates a strong association with the reintervention risk in AAA patients after EVAR. Incorporation of VPCI into clinical practice has the potential to enhance the traditional surveillance methods (CT/CTAs) by providing clinicians with a non-invasive method to assess aortic wall inflammation and predict the risk of reintervention. Additionally, this study might offer a valuable tool for mechanism and treatment research in humans with AAAs both pre- and post-EVAR, ultimately improving patient outcomes and refining therapeutic strategies.

Influence of Blood Rheology and Turbulence Models in the Numerical Simulation of Aneurysms

An aneurysm is a vascular malformation that can be classified according to its location (cerebral, aortic) or shape (saccular, fusiform, and mycotic). Recently, the study of blood flow interaction with aneurysms has gained attention from physicians and engineers. Shear stresses, oscillatory shear index (OSI), gradient oscillatory number (GON), and residence time have been used as variables to describe the hemodynamics as well as the origin and evolution of aneurysms. However, the causes and hemodynamic conditions that promote their growth are still under debate. The present work presents numerical simulations of three types of aneurysms: two aortic and one cerebral. Simulation results showed that the blood rheology is not relevant for aortic aneurysms. However, for the cerebral aneurysm case, blood rheology could play a relevant role in the hemodynamics. The evaluated turbulence models showed equivalent results in both cases. Lastly, a simulation considering the fluid-structure interaction (FSI) showed that this phenomenon is the dominant factor for aneurysm simulation.

StrokeNet: An automated approach for segmentation and rupture risk prediction of intracranial aneurysm

Intracranial Aneurysms (IA) present a complex challenge for neurosurgeons as the risks associated with surgical intervention, such as Subarachnoid Hemorrhage (SAH) mortality and morbidity, may outweigh the benefits of aneurysmal occlusion in some cases. Hence, there is a critical need for developing techniques that assist physicians in assessing the risk of aneurysm rupture to determine which aneurysms require treatment. However, a reliable IA rupture risk prediction technique is currently unavailable. To address this issue, this study proposes a novel approach for aneurysm segmentation and multidisciplinary rupture prediction using 2D Digital Subtraction Angiography (DSA) images. The proposed method involves training a fully connected convolutional neural network (CNN) to segment aneurysm regions in DSA images, followed by extracting and fusing different features using a multidisciplinary approach, including deep features, geometrical features, Fourier descriptor, and shear pressure on the aneurysm wall. The proposed method also adopts a fast correlation-based filter approach to drop highly correlated features from the set of fused features. Finally, the selected fused features are passed through a Decision Tree classifier to predict the rupture severity of the associated aneurysm into four classes: Mild, Moderate, Severe, and Critical. The proposed method is evaluated on a newly developed DSA image dataset and on public datasets to assess its generalizability. The system's performance is also evaluated on DSA images annotated by expert neurosurgeons for the rupture risk assessment of the segmented aneurysm. The proposed system outperforms existing state-of-the-art segmentation methods, achieving an 85 % accuracy against annotated DSA images for the risk assessment of aneurysmal rupture.

Prevalence of risk factors associated with rupture of abdominal aortic aneurysm (AAA): a single center retrospective study

BACKGROUND

Abdominal aortic aneurysm (AAA) is a severe cardiovascular disease. The mortality rate for an AAA rupture is very high. Understanding the risk factors for AAA rupture would help AAA management, but little is known about these risk factors in the Chinese population.

METHODS

This retrospective study included patients that were diagnosed with AAA during the last 5 years in a large national hospital in southern China. AAA patients were divided into a rupture and non-rupture group. Clinical data were extracted from the hospital medical record system. Clinical features were compared between the rupture and non-rupture groups. The associations between potential risk factors and rupture risk were evaluated using a multivariate logistic regression analysis.

RESULTS

A total of 337 AAA patients were included for analysis in the present study. AAA diameter was significantly larger, and high-sensitivity C-reactive protein (hs-CRP) and serum creatinine levels were both significantly higher in AAA rupture patients. High-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C) and total cholesterol (TC) levels were significantly lower in AAA rupture patients. After adjustment, the multivariate logistic analysis found that AAA diameter and hs-CRP were independently positively associated with AAA rupture, and HDL-C level was adversely associated with AAA rupture.

CONCLUSIONS

Our data suggests that larger AAA diameter and higher hs-CRP level are associated with a higher risk of AAA rupture, and higher HDL-C level is associated with a lower risk of AAA rupture. The results of this study may be helpful for the management of AAA patients in southern China.

Shape-driven deep neural networks for fast acquisition of aortic 3D pressure and velocity flow fields

Computational fluid dynamics (CFD) can be used to simulate vascular haemodynamics and analyse potential treatment options. CFD has shown to be beneficial in improving patient outcomes. However, the implementation of CFD for routine clinical use is yet to be realised. Barriers for CFD include high computational resources, specialist experience needed for designing simulation set-ups, and long processing times. The aim of this study was to explore the use of machine learning (ML) to replicate conventional aortic CFD with automatic and fast regression models. Data used to train/test the model consisted of 3,000 CFD simulations performed on synthetically generated 3D aortic shapes. These subjects were generated from a statistical shape model (SSM) built on real patient-specific aortas (N = 67). Inference performed on 200 test shapes resulted in average errors of 6.01% ±3.12 SD and 3.99% ±0.93 SD for pressure and velocity, respectively. Our ML-based models performed CFD in ∼0.075 seconds (4,000x faster than the solver). This proof-of-concept study shows that results from conventional vascular CFD can be reproduced using ML at a much faster rate, in an automatic process, and with reasonable accuracy.

The loss of helical flow in the thoracic aorta might be an identifying marker for the risk of acute type B aortic dissection

BACKGROUND AND OBJECTIVE

The occurrence of acute type B aortic dissection (TBAD) remained unclear. This study aimed to investigate the association between flow features and hemodynamic parameters in aortas that demonstrated the risk of TBAD occurrence.

METHODS

The geometries of 15 hyperacute TBAD and 12 control patients (with healthy aorta) were reconstructed from computed tomography angiography images. Pre-TBAD models were then obtained by eliminating the dissection flaps. Flow features and hemodynamic parameters, including wall shear stress-related parameters and helicities, were compared between pre-TBAD and control models using computational fluid dynamics.

RESULTS

There were no significant differences in baseline characteristics and anatomical parameters between the two groups. Significant contralateral helical blood flow was present in the healthy thoracic aorta, while almost no helical flow was observed in the pre-TBAD group. In addition, the mean normal transverse wall shear stress (NtransWSS) was significantly higher in the pre-TBAD group (aortic arch 0.49±0.09 vs. 0.40±0.05, P = 0.04; descending aorta: 0.46±0.05 vs. 0.33±0.02, P<0.01). Moreover, a significantly negative correlation was found between helicity and NtransWSS in the descending aorta. Moreover, the location of primary tears in 12 pre-TABD subjects matched well with regions of high NtransWSS.

CONCLUSIONS

Loss of helical flow in the aortic arch and descending aorta may be a major flow feature in patients with underlying TBAD, resulting in increased flow disturbance and wall lesions.

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.

Fast and Accurate Computation of the Displacement Force of Stent Grafts after Endovascular Aneurysm Repair

Purpose: Currently, the displacement force of stent grafts is generally obtained using computational fluid dynamics (CFD), which requires professional CFD knowledge to perform the correct simulation. This study proposes a fast, simple, and clinician-friendly approach to calculating the patient-specific displacement force after endovascular aneurysm repair (EVAR). Methods: Twenty patient-specific post-EVAR computed tomography angiography images were used to reconstruct the patient-specific three-dimensional models, then the displacement forces were calculated using CFD and the proposed approaches, respectively, and their numerical differences were compared and analyzed. Results: Based on the derivation and simplification of the momentum theorem, the patient-specific displacement forces were obtained using the information of the patient-specific pressure, cross-sectional area, and angulation of the two stent graft ends, and the average relative error was no greater than 1.37% when compared to the displacement forces calculated by CFD. In addition, the linear regression analysis also showed good agreement between the displacement force values calculated by the new approach and CFD (R = 0.999). Conclusions: The proposed approach can quickly and accurately calculate the patient-specific displacement force on a stent graft and can therefore help clinicians quickly evaluate the post-EVAR displacement force.

Swedish snuff (snus) dipping, cigarette smoking, and risk of peripheral artery disease: a prospective cohort study

Tobacco smoking is an important risk factor for peripheral artery disease (PAD), but it remains unknown whether smokeless tobacco, such as Swedish snuff (snus), is also associated with this disease. We used data from the Cohort of Swedish Men including 24,085 men. Individuals were grouped into never, past, and current snus dippers as well as never, past quitting ≥ 10 years, past, quitting < 10 years, and current smokers. Incident PAD cases were defined by linkage of the cohort with the Swedish National Patient Register. Cox proportional hazards regression was used to analyze the data. Over a mean follow-up period of 9.1 years (from July 1, 2009 to December 31, 2019), 655 incident PAD cases were ascertained. Cigarette smoking but not Swedish snus dipping was associated with an increased risk of PAD. Compared with never snus dippers, the hazard ratio of PAD was 0.95 (95% confidence interval [CI] 0.73–1.24) for past snus dippers and 0.88 (95% CI 0.66–1.17) for current snus dippers. Compared to never smokers, the hazard ratio of PAD was 1.38 (95% CI 1.14–1.68) for past smoker who stopped smoking for ≥ 10 years, 2.61 (95% CI 1.89–3.61) for past smoker who stopped smoking for < 10 years, and 4.01 (95% CI 3.17, 5.08) for current smoker. In conclusion, cigarette smoking but not Swedish snus dipping increases the risk of PAD.