Critical Pressure of Intramural Delamination in Aortic Dissection

Retearing of type B blind cystic aortic dissection: computational fluid dynamics analysis

Aortic dissection (AD) is a serious life-threatening vascular disease. However, research on type B blind cystic AD is still insufficient. This type of AD involves only one proximal intimal tear, and the distal end of the aortic false lumen (FL) is a blind sac. The purpose of this study was to explore the haemodynamic indicators of retearing and high-risk areas for FL rupture in type B blind cystic AD patients. This study included 4 cases of type B blind cystic AD rupture death, which revealed the pathological characteristics of the aorta. In addition, imaging data from one deceased and four patients with type B AD (TBAD) with multiple intimal tears were collected, and two groups of models (n = 10) were constructed. The pressure, velocity, time-averaged wall shear stress (TAWSS), and relative residence time (RRT) were compared to interpret our autopsy results. In type B blind cystic AD patients, the FL is characterized by high pressure, a low TAWSS, and high RRT. There was a relatively high TAWSS in the FL adjacent to the proximal intimal tear; at the same time, both the blood flow velocity and the pressure difference in the true lumen (TL) significantly changed. In addition, the greater the curvature of the aorta is, the more drastic the change in the luminal pressure difference. In type B blind cystic AD, high pressure may be the main reason for FL rupture, and the FL adjacent to the proximal intimal tear may be a high-risk rupture area. In addition, alterations in blood flow velocity and differential pressure may cause distal intimal retears. Tortuosity is an important indicator for studying pressure changes.

Association of sleep disturbance and sleep apnea with the size of the thoracic aorta and the main pulmonary artery

Obstructive sleep apnea (OSA) is associated with an increased prevalence of aortic aneurysm, but the impact of OSA on the subclinical damage of large thoracic vessels remains controversial. Short sleep duration and poor sleep quality has been reported to be related with higher arterial stiffness. In the current study, we aimed to investigate the association of sleep disturbance and sleep apnea with the size of the ascending aorta (AA), descending thoracic aorta (DTA), and main pulmonary artery (MPA). One hundred and fifty-five newly diagnosed OSA patients free of cardiovascular disease and medication were included. In-laboratory polysomnography (PSG) and chest computed tomography (CT) scanning were performed. The sleep duration was defined as total sleep time (TST) as recorded during overnight PSG, with TST < 6 h defined as short sleep duration. Sleep latency (SL), sleep efficiency (SE) and wake after sleep onset (WASO) were used to assess the objective sleep quality, and the Epworth Sleepiness Scale (ESS) was used to assess EDS (excessive daytime sleepiness). The diameter of AA was positively associated with age (B = 0.199, P < 0.001) and diastolic blood pressure (DBP) (B = 0.103, P < 0.001), and was negatively associated with mean pulse oxygen saturation (SpO2mean) (B = - 0.176, P = 0.022). The diameter of DTA was positively associated with age (B = 0.112, P < 0.001), body mass index (BMI) (B = 0.184, P = 0.041), and DBP (B = 0.033, P = 0.024), and was negatively associated with TST (B = - 0.006, P = 0.023). Neither nocturnal hypoxia nor TST were associated with the diameter of MPA or the ratio of MPA to AA (PA/A). The aortic or MPA measurements were not associated with SL, SE, WASO or ESS. In patients with OSA, nocturnal hypoxia and sleep duration were associated with the diameter of AA and DTA, respectively. It is suggested that sleep apnea and sleep disturbance may exert effects on the remodeling and enlargement of thoracic large vessels through distinctive mechanisms.

Mechanisms of aortic dissection: From pathological changes to experimental and in silico models

Aortic dissection continues to be responsible for significant morbidity and mortality, although recent advances in medical data assimilation and in experimental and in silico models have improved our understanding of the initiation and progression of the accumulation of blood within the aortic wall. Hence, there remains a pressing necessity for innovative and enhanced models to more accurately characterize the associated pathological changes. Early on, experimental models were employed to uncover mechanisms in aortic dissection, such as hemodynamic changes and alterations in wall microstructure, and to assess the efficacy of medical implants. While experimental models were once the only option available, more recently they are also being used to validate in silico models. Based on an improved understanding of the deteriorated microstructure of the aortic wall, numerous multiscale material models have been proposed in recent decades to study the state of stress in dissected aortas, including the changes associated with damage and failure. Furthermore, when integrated with accessible patient-derived medical data, in silico models prove to be an invaluable tool for identifying correlations between hemodynamics, wall stresses, or thrombus formation in the deteriorated aortic wall. They are also advantageous for model-guided design of medical implants with the aim of evaluating the deployment and migration of implants in patients. Nonetheless, the utility of in silico models depends largely on patient-derived medical data, such as chosen boundary conditions or tissue properties. In this review article, our objective is to provide a thorough summary of medical data elucidating the pathological alterations associated with this disease. Concurrently, we aim to assess experimental models, as well as multiscale material and patient data-informed in silico models, that investigate various aspects of aortic dissection. In conclusion, we present a discourse on future perspectives, encompassing aspects of disease modeling, numerical challenges, and clinical applications, with a particular focus on aortic dissection. The aspiration is to inspire future studies, deepen our comprehension of the disease, and ultimately shape clinical care and treatment decisions.

Mathematical modeling and numerical simulation of arterial dissection based on a novel surgeon's view

This paper presents a mathematical model for arterial dissection based on a novel hypothesis proposed by a surgeon, Axel Haverich, see Haverich (Circulation 135(3):205-207, 2017. https://doi.org/10.1161/circulationaha.116.025407 ). In an attempt and based on clinical observations, he explained how three different arterial diseases, namely atherosclerosis, aneurysm and dissection have the same root in malfunctioning Vasa Vasorums (VVs) which are micro capillaries responsible for artery wall nourishment. The authors already proposed a mathematical framework for the modeling of atherosclerosis which is the thickening of the artery walls due to an inflammatory response to VVs dysfunction. A multiphysics model based on a phase-field approach coupled with mechanical deformation was proposed for this purpose. The kinematics of mechanical deformation was described using finite strain theory. The entire model is three-dimensional and fully based on a macroscopic continuum description. The objective here is to extend that model by incorporating a damage mechanism in order to capture the tearing (rupture) in the artery wall as a result of micro-injuries in VV. Unlike the existing damage-based model of the dissection in the literature, here the damage is driven by the internal bleeding (hematoma) rather than purely mechanical external loading. The numerical implementation is carried out using finite element method (FEM).

The Role of Location, Length, and Thickness of the Intimal Flap in the Propagation of Stanford Type B Aortic Dissection Based on Ex Vivo Porcine Aorta Models

PURPOSE

To explore the role of location, length, and thickness of the intimal flap in the propagation of Stanford type B aortic dissection (TBAD) based on ex vivo porcine aorta models based on ex vivo porcine aorta models.

MATERIALS AND METHODS

The porcine aortas were harvested and randomly divided into 6 groups to create various TBAD aortic models. We constructed intimal flaps for different locations (group A [entry tear on outer curvature] and group B [entry tear on inner curvature]), lengths (group C [long] and group D [short]), and thicknesses (group E [thick] and group F [thin]). For the ex vivo perfusion experiments conducted on model aortas, an experimental circulation loop (ECL) was employed. The pressure in false lumen (FL) was constantly monitored. A comparison was made between the morphological data collected before and after the experiment to quantify the changes in the FL after the experiment.

RESULTS

Compared the results with group B, the mean peak pressures of the FL in group A were lower (106.87±15.55 vs. 124.01±22.75 mm Hg, p=0.028). The mean axial propagation length in group A was shown to be shorter than that of group B (88.14±33.38 vs. 197.43±41.65 mm, p<0.001). The mean peak pressure was higher in group C than in group D (144.04±19.37 vs. 92.51±26.70 mm Hg, p<0.001). The mean peak pressure of group E was higher than that of group F (160.83±32.83 vs. 109.33±15.62 mm Hg, p<0.001), as was the mean axial propagation length of group E (143.11±39.73 vs. 100.45±35.44 mm, p=0.021). According to the results of multivariable linear regression, axial propagation length=45.873-0.703×length of initial FL+0.863× peak pressure (p<0.001).

CONCLUSION

There was a relationship between FL propagation and the location, length, and thickness of the intimal flap. The axial propagation length was related to the length of the intimal flap and the peak pressure of propagation. It may be helpful to evaluate the risk of propagation in patients with TBAD.

CLINICAL IMPACT

This study found that the locations, lengths, and thickness of the intimal flap significantly contributed to propagation pressure of FL. Using dissection flap characteristics, a physician can predict FL development in a patient and formulate a treatment plan.The purpose was to investigate the relationship between the dissection flap characteristics (location, length, and thickness) and the propagation of the FL, which is not clear at present. This study employed porcine models to create an experimental circulation loop. The perfusion experiment was conducted using a FL without distal re-entry and a non-pulsating flow.

Unraveling the Links between Chronic Inflammation, Autoimmunity, and Spontaneous Cervicocranial Arterial Dissection

Advances in imaging techniques have led to a rise in the diagnosis of spontaneous cervicocranial arterial dissection (SCCAD), which is now considered a common cause of stroke in young adults. However, our understanding of the pathophysiological mechanisms underlying SCCAD remains limited. Prior studies have proposed various factors contributing to arterial wall weakness or stress as potential causes for SCCAD. A combination of biopsies, case reports, and case-control studies suggests that inflammatory changes and autoimmunity may play roles in the cascade of events leading to SCCAD. In this review, we examine the close relationship between SCCAD, chronic inflammation, and autoimmune diseases, aiming to explore potential underlying pathophysiological mechanisms connecting these conditions. While some relevant hypotheses and studies exist, direct evidence on this topic is still relatively scarce. Further investigation of the underlying mechanisms in larger clinical cohorts is needed, and the exploration of animal models may provide novel insights.

Fracture of the porcine aorta. Part 2: FEM modelling and inverse parameter identification

The mechanics of vascular tissue, particularly its fracture properties, are crucial in the onset and progression of vascular diseases. Vascular tissue properties are complex, and the identification of fracture mechanical properties relies on robust and efficient numerical tools. In this study, we propose a parameter identification pipeline to extract tissue properties from force-displacement and digital image correlation (DIC) data. The data has been acquired by symconCT testing porcine aorta wall specimens. Vascular tissue is modelled as a non-linear viscoelastic isotropic solid, and an isotropic cohesive zone model describes tissue fracture. The model closely replicated the experimental observations and identified the fracture energies of 1.57±0.82 kJ m^-2 and 0.96±0.34 kJ m^-2 for rupturing the porcine aortic media along the axial and circumferential directions, respectively. The identified strength was always below 350 kPa, a value significantly lower than identified through classical protocols, such as simple tension, and sheds new light on the resilience of the aorta. Further refinements to the model, such as considering rate effects in the fracture process zone and tissue anisotropy, could have improved the simulation results. STATEMENT OF SIGNIFICANCE: This paper identified porcine aorta's biomechanical properties using data acquired through a previously developed experimental protocol, the symmetry-constraint compact tension test. An implicit finite element method model mimicked the test, and a two-step approach identified the material's elastic and fracture properties directly from force-displacement curves and digital image correlation-based strain measurements. Our findings show a lower strength of the abdominal aorta as compared to the literature, which may have significant implications for the clinical evaluation of the risk of aortic rupture.

Fracture of the porcine aorta. Part 1: symconCT fracture testing and DIC

Tissue failure and damage are inherent parts of vascular diseases and tightly linked to clinical events. Additionally, experimental set-ups designed to study classical engineering materials are suboptimal in the exploration of vessel wall fracture properties. The classical Compact Tension (CT) test was augmented to enable stable fracture propagation, resulting in the symmetry-constraint Compact Tension (symconCT) test, a suitable set-up for fracture testing of vascular tissue. The test was combined with Digital Image Correlation (DIC) to study tissue fracture in 45 porcine aorta specimens. Test specimens were loaded in axial and circumferential directions in a physiological solution at 37∘ C. Loading the aortic vessel wall in the axial direction resulted in mode I tissue failure and a fracture path aligned with the circumferential vessel direction. Circumferential loading resulted in mode I-dominated failure with multiple deflections of the fracture path. The aorta ruptured at a principal Green-Lagrange strain of approximately 0.7, and strain rate peaks that develop ahead of the crack tip reached nearly 400 times the strain rate on average over the test specimen. It required approximately 70% more external work to fracture the aorta by circumferential than axial load; normalised with the fracture surface, similar energy levels are, however, observed. The symconCT test resulted in a stable fracture propagation, which, combined with DIC, provided a set-up for the in-depth analysis of vascular tissue failure. The high strain rates ahead of the crack tip indicate the significance of rate effects in the constitutive description of vascular tissue fracture. STATEMENT OF SIGNIFICANCE: This paper represents a significant step forward in understanding the fracture properties of porcine aorta. Inspired by the Compact Tension test, we developed an ad hoc experimental protocol to investigate stable crack propagation in soft materials, providing new insights into the mechanical processes that lead to the rupture of vascular tissue. The set-up enables the assessment of strains and strain rates ahead of the crack tip, and our findings could improve the clinical risk assessment of vascular pathologies as well as optimize medical device design.

Review article: Non-penetrating neck artery dissection in young adults: Not to be missed!

Young adults who present to the ED with neck pain following non-penetrating, seemingly trivial trauma to the neck, are at risk of neck artery dissection and subsequent stroke. Sport-related neck injury is the chief cause. Physical examination may often be unremarkable, and although there may be reluctance to expose young patients to radiation, radiological imaging is central to making a diagnosis of arterial wall disruption. A comprehensive literature search was performed in relation to neck artery dissection, and the evidence was scrutinised. We discuss the typical mechanism of injury, symptoms, anatomical considerations and clinical aids in diagnosis of neck artery dissection. Although the incidence is low, neck artery dissection has a mortality of 7%. As such, it is important for front-line physicians to have a high suspicion of the diagnosis and a low threshold to organise radiological examinations, specifically computerised tomography. Early detection of neck artery dissection will trigger clinical protocols that call for multi-disciplinary team management of this condition. In general, guideline-based recommendation for the management of neck artery dissection involving an intimal flap is by anti-platelet therapy while treatment of neck artery dissection that results in a pseudo-aneurysm or thrombosis is managed by surgical intervention or endovascular techniques. Close follow up combined with antithrombotic treatment is recommended in these individuals, the goal being prevention of stroke.

Low Wall Shear Stress and High Intra-aneurysmal Pressure are Associated with Ruptured Status of Vertebral Artery Dissecting Aneurysms

PURPOSE

The morphological and hemodynamic features of patients with vertebral artery dissecting aneurysms (VADAs) are yet unknown. This study sought to elucidate morphological and hemodynamic features of patients with ruptured and unruptured VADAs based on computed flow simulation.

METHODS

Fifty-two patients (31 unruptured and 21 ruptured VADAs) were admitted to two hospitals between March 2016 and October 2021. All VADAs were located in the intradural segment, and their clinical, morphological, and hemodynamic parameters were retrospectively analyzed. The hemodynamic parameters were determined through computational fluid dynamics simulations. Univariate statistical and multivariable logistic regression analyses were employed to select significantly different parameters and identify key factors. Receiver operating characteristic (ROC) analysis was used to assess the discrimination for each key factor.

RESULTS

Four hemodynamic parameters were observed to significantly differ between ruptured and unruptured VADAs, including wall shear stress (WSS), low shear area, intra-aneurysmal pressure (IAP), and relative residence time. However, no significant differences were observed in morphological parameters between ruptured and unruptured VADAs. Multivariable logistic regression analysis revealed that low WSS and high IAP were significantly observed in the ruptured VADAs and demonstrated adequate discrimination.

CONCLUSIONS

This research indicates significant hemodynamic differences, but no morphological differences were observed between ruptured and unruptured VADAs. The ruptured group had significantly lower WSS and higher IAP than the unruptured group. To further confirm the roles of low WSS and high IAP in the rupture of VADAs, large prospective studies and long-term follow-up of unruptured VADAs are required.

Evolving Mural Defects, Dilatation, and Biomechanical Dysfunction in Angiotensin II-Induced Thoracic Aortopathies

BACKGROUND

Thoracic aortopathy associates with extracellular matrix remodeling and altered biomechanical properties. We sought to quantify the natural history of thoracic aortopathy in a common mouse model and to correlate measures of wall remodeling such as aortic dilatation or localized mural defects with evolving microstructural composition and biomechanical properties of the wall.

METHODS

We combined a high-resolution multimodality imaging approach (panoramic digital image correlation and optical coherence tomography) with histopathologic examinations and biaxial mechanical testing to correlate spatially, for the first time, macroscopic mural defects and medial degeneration within the ascending aorta with local changes in aortic wall composition and mechanical properties.

RESULTS

Findings revealed strong correlations between local decreases in elastic energy storage and increases in circumferential material stiffness with increasing proximal aortic diameter and especially mural defect size. Mural defects tended to exhibit a pronounced biomechanical dysfunction that is driven by an altered organization of collagen and elastic fibers.

CONCLUSIONS

While aneurysmal dilatation is often observed within particular segments of the aorta, dissection and rupture initiate as highly localized mechanical failures. We show that wall composition and material properties are compromised in regions of local mural defects, which further increases the dilatation and overall structural vulnerability of the wall. Identification of therapies focused on promoting robust collagen accumulation may protect the wall from these vulnerabilities and limit the incidence of dissection and rupture.

Simulating progressive intramural damage leading to aortic dissection using DeepONet: an operator-regression neural network

Aortic dissection progresses mainly via delamination of the medial layer of the wall. Notwithstanding the complexity of this process, insight has been gleaned by studying in vitro and in silico the progression of dissection driven by quasi-static pressurization of the intramural space by fluid injection, which demonstrates that the differential propensity of dissection along the aorta can be affected by spatial distributions of structurally significant interlamellar struts that connect adjacent elastic lamellae. In particular, diverse histological microstructures may lead to differential mechanical behaviour during dissection, including the pressure-volume relationship of the injected fluid and the displacement field between adjacent lamellae. In this study, we develop a data-driven surrogate model of the delamination process for differential strut distributions using DeepONet, a new operator-regression neural network. This surrogate model is trained to predict the pressure-volume curve of the injected fluid and the damage progression within the wall given a spatial distribution of struts, with in silico data generated using a phase-field finite-element model. The results show that DeepONet can provide accurate predictions for diverse strut distributions, indicating that this composite branch-trunk neural network can effectively extract the underlying functional relationship between distinctive microstructures and their mechanical properties. More broadly, DeepONet can facilitate surrogate model-based analyses to quantify biological variability, improve inverse design and predict mechanical properties based on multi-modality experimental data.