An artificial intelligence based abdominal aortic aneurysm prognosis classifier to predict patient outcomes.

Abdominal aortic aneurysms (AAA) have been rigorously investigated to understand when their clinically-estimated risk of rupture-an event that is the 13th leading cause of death in the US-exceeds the risk associated with repair. Yet the current clinical guideline remains a one-size-fits-all "maximum diameter criterion" whereby AAA exceeding a threshold diameter is thought to make the risk of rupture high enough to warrant intervention. However, between 7 and 23.4% of smaller-sized AAA have been reported to rupture with diameters below the threshold. In this study, we train and assess machine learning models using clinical, biomechanical, and morphological indices from 381 patients to develop an aneurysm prognosis classifier to predict one of three outcomes for a given AAA patient: their AAA will remain stable, their AAA will require repair based as currently indicated from the maximum diameter criterion, or their AAA will rupture. This study represents the largest cohort of AAA patients that utilizes the first available medical image and clinical data to classify patient outcomes. The APC model therefore represents a potential clinical tool to striate specific patient outcomes using machine learning models and patient-specific image-based (biomechanical and morphological) and clinical data as input. Such a tool could greatly assist clinicians in their management decisions for patients with AAA.

A Comparative Study of Machine Learning and Algorithmic Approaches to Automatically Identify the Yield Point in Normal and Aneurysmal Human Aortic Tissues.

The stress-strain curve of biological soft tissues helps characterize their mechanical behavior. The yield point on this curve is when a specimen breaches its elastic range due to irreversible microstructural damage. The yield point is easily found using the offset yield method in traditional engineering materials. However, correctly identifying the yield point in soft tissues can be subjective due to its nonlinear material behavior. The typical method for yield point identification is visual inspection, which is investigator-dependent and does not lend itself to automation of the analysis pipeline. An automated algorithm to identify the yield point objectively assesses soft tissues' biomechanical properties. This study aimed to analyze data from uniaxial extension testing on biological soft tissue specimens and create a machine learning (ML) model to determine a tissue sample's yield point. We present a trained machine learning model from 279 uniaxial extension curves from testing aneurysmal/nonaneurysmal and longitudinal/circumferential oriented tissue specimens that multiple experts labeled through an adjudication process. The ML model showed a median error of 5% in its estimated yield stress compared to the expert picks. The study found that an ML model could accurately identify the yield point (as defined) in various aortic tissues. Future studies will be performed to validate this approach by visually inspecting when damage occurs and adjusting the model using the ML-based approach.

The regulatory environment for artificial intelligence-enabled devices in the United States.

The regulatory environment in the United States has not kept pace with the rapidly developing market for artificial intelligence (AI)-enabled devices. The number of AI-enabled devices has increased year after year. All of these devices are registered or cleared by the US Food and Drug Administration through exempt or 510(k) premarket notification pathways, and the majority are related to the radiology or cardiovascular spaces. US Food and Drug Administration guidance has not yet addressed the unique challenges of AI-enabled devices, including development, comprehensibility, and continuously learning models. The liability aspects of AI-enabled devices deployed into use by clinicians in practice have yet to be addressed. Future guidance from government regulatory sources will be necessary as the field moves forward.

Mechanical and matrix effects of short and long-duration exposure to beta-aminopropionitrile in elastase-induced model abdominal aortic aneurysm in mice.

Objective: Evaluate the mechanical and matrix effects on abdominal aortic aneurysms (AAA) during the initial aortic dilation and after prolonged exposure to beta-aminopropionitrile (BAPN) in a topical elastase AAA model. Methods: Abdominal aortae of C57/BL6 mice were exposed to topical elastase with or without BAPN in the drinking water starting 4 days before elastase exposure. For the standard AAA model, animals were harvested at 2 weeks after active elastase (STD2) or heat-inactivated elastase (SHAM2). For the enhanced elastase model, BAPN treatment continued for either 4 days (ENH2b) or until harvest (ENH2) at 2 weeks; BAPN was continued until harvest at 8 weeks in one group (ENH8). Each group underwent assessment of aortic diameter, mechanical testing (tangent modulus and ultimate tensile strength [UTS]), and quantification of insoluble elastin and bulk collagen in both the elastase exposed aorta as well as the descending thoracic aorta. Results: BAPN treatment did not increase aortic dilation compared with the standard model after 2 weeks (ENH2, 1.65 ± 0.23 mm; ENH2b, 1.49 ± 0.39 mm; STD2, 1.67 ± 0.29 mm; and SHAM2, 0.73 ± 0.10 mm), but did result in increased dilation after 8 weeks (4.3 ± 2.0 mm; P = .005). After 2 weeks, compared with the standard model, continuous therapy with BAPN did not have an effect on UTS (24.84 ± 7.62 N/cm2; 18.05 ± 4.95 N/cm2), tangent modulus (32.60 ± 9.83 N/cm2; 26.13 ± 9.10 N/cm2), elastin (7.41 ± 2.43%; 7.37 ± 4.00%), or collagen (4.25 ± 0.79%; 5.86 ± 1.19%) content. The brief treatment, EHN2b, resulted in increased aortic collagen content compared with STD2 (7.55 ± 2.48%; P = .006) and an increase in UTS compared with ENH2 (35.18 ± 18.60 N/cm2; P = .03). The ENH8 group had the lowest tangent modulus (3.71 ± 3.10 N/cm2; P = .005) compared with all aortas harvested at 2 weeks and a lower UTS (2.18 ± 2.18 N/cm2) compared with both the STD2 (24.84 ± 7.62 N/cm2; P = .008) and ENH2b (35.18 ± 18.60 N/cm2; P = .001) groups. No differences in the mechanical properties or matrix protein concentrations were associated with abdominal elastase exposure or BAPN treatment for the thoracic aorta. The tangent modulus was higher in the STD2 group (32.60 ± 9.83 N/cm2; P = .0456) vs the SHAM2 group (17.99 ± 5.76 N/cm2), and the UTS was lower in the ENH2 group (18.05 ± 4.95 N/cm2; P = .0292) compared with the ENH2b group (35.18 ± 18.60 N/cm2). The ENH8 group had the lowest tangent modulus (3.71 ± 3.10 N/cm2; P = .005) compared with all aortas harvested at 2 weeks and a lower UTS (2.18 ± 2.18 N/cm2) compared with both the STD2 (24.84 ± 7.62 N/cm2; P = .008) and ENH2b (35.18 ± 18.60 N/cm2; P = .001) groups. Abdominal aortic elastin in the STD2 group (7.41 ± 2.43%; P = .035) was lower compared with the SHAM2 group (15.29 ± 7.66%). Aortic collagen was lower in the STD2 group (4.25 ± 0.79%; P = .007) compared with the SHAM2 group (12.44 ± 6.02%) and higher for the ENH2b (7.55 ± 2.48%; P = .006) compared with the STD2 group. Conclusions: Enhancing an elastase AAA model with BAPN does not affect the initial (2-week) dilation phase substantially, either mechanically or by altering the matrix content. Late mechanical and matrix effects of prolonged BAPN treatment are limited to the elastase-exposed segment of the aorta. Clinical Relevance: This paper explores the use of short- and long-term exposure to beta-aminopropionitrile to create an enhanced topical elastase abdominal aortic aneurysm model in mice. Readouts of aneurysm severity included loss of mechanical stability and vascular extracellular matrix composition reminiscent of what is seen in the course of human disease. Additionally, we show that the thoracic aorta, unlike the findings below the renal arteries, is not damaged in our animal model.

Dynamical modeling reveals RNA decay mediates the effect of matrix stiffness on aged muscle stem cell fate.

Loss of muscle stem cell (MuSC) self-renewal with aging reflects a combination of influences from the intracellular (e.g., post-transcriptional modifications) and extracellular (e.g., matrix stiffness) environment. Whereas conventional single cell analyses have revealed valuable insights into factors contributing to impaired self-renewal with age, most are limited by static measurements that fail to capture nonlinear dynamics. Using bioengineered matrices mimicking the stiffness of young and old muscle, we showed that while young MuSCs were unaffected by aged matrices, old MuSCs were phenotypically rejuvenated by young matrices. Dynamical modeling of RNA velocity vector fields in silico revealed that soft matrices promoted a self-renewing state in old MuSCs by attenuating RNA decay. Vector field perturbations demonstrated that the effects of matrix stiffness on MuSC self-renewal could be circumvented by fine-tuning the expression of the RNA decay machinery. These results demonstrate that post-transcriptional dynamics dictate the negative effect of aged matrices on MuSC self-renewal.

An Objective and Repeatable Sac Isolation Technique for Comparing Biomechanical Metrics in Abdominal Aortic Aneurysms.

(1) Abdominal aortic aneurysm (AAA) biomechanics-based metrics often reported may be over/under-estimated by including non-aneurysmal regions in the analyses, which is typical, rather than isolating the dilated sac region. We demonstrate the utility of a novel sac-isolation algorithm by comparing peak/mean wall stress (PWS, MWS), with/without sac isolation, for AAA that were categorized as stable or unstable in 245 patient CT image sets. (2) 245 patient computed tomography images were collected, segmented, meshed, and had subsequent finite element analysis performed in preparation of our novel sac isolation technique. Sac isolation was initiated by rotating 3D surfaces incrementally, extracting 2D projections, curve fitting a Fourier series, and taking the local extrema as superior/inferior boundaries for the aneurysmal sac. The PWS/MWS were compared pairwise using the entire aneurysm and the isolated sac alone. (3) MWS, not PWS, was significantly different between the sac alone and the entire aneurysm. We found no statistically significant difference in wall stress measures between stable (n = 222) and unstable (n = 23) groups using the entire aneurysm. However, using sac-isolation, PWS (24.6 ± 7.06 vs. 20.5 ± 8.04 N/cm2; p = 0.003) and MWS (12.0 ± 3.63 vs. 10.5 ± 4.11 N/cm2; p = 0.022) were both significantly higher in unstable vs. stable groups. (4) Our results suggest that evaluating only the AAA sac can influence wall stress metrics and may reveal differences in stable and unstable groups of aneurysms that may not otherwise be detected when the entire aneurysm is used.

The predictive capability of aortic stiffness index for aortic dissection among dilated ascending aortas.

OBJECTIVE: We created a finite element model to predict the probability of dissection based on imaging-derived aortic stiffness and investigated the link between stiffness and wall tensile stress using our model. METHODS: Transthoracic echocardiogram measurements were used to calculate aortic diameter change over the cardiac cycle. Aortic stiffness index was subsequently calculated based on diameter change and blood pressure. A series of logistic models were developed to predict the binary outcome of aortic dissection using 1 or more series of predictor parameters such as aortic stiffness index or patient characteristics. Finite element analysis was performed on a subset of diameter-matched patients exhibiting patient-specific material properties. RESULTS: Transthoracic echocardiogram scans of patients with type A aortic dissection (n = 22) exhibited elevated baseline aortic stiffness index when compared with aneurysmal patients' scans with tricuspid aortic valve (n = 83, P < .001) and bicuspid aortic valve (n = 80, P < .001). Aortic stiffness index proved an excellent discriminator for a future dissection event (area under the curve, 0.9337, odds ratio, 2.896). From the parametric finite element study, we found a correlation between peak longitudinal wall tensile stress and stiffness index (ρ = .6268, P < .001, n = 28 pooled). CONCLUSIONS: Noninvasive transthoracic echocardiogram-derived aortic stiffness measurements may serve as an impactful metric toward predicting aortic dissection or quantifying dissection risk. A correlation between longitudinal stress and stiffness establishes an evidence-based link between a noninvasive stiffness parameter and stress state of the aorta with clinically apparent dissection events.

Multimodal Structural Analysis of the Human Aorta: From Valve to Bifurcation.

OBJECTIVE: The aims of the present study were to assess the relative proportion of collagen and elastin in the arterial wall and to evaluate the collagen microstructure from the aortic root to the external iliac artery. METHODS: Arterial wall tissue samples sampled during post-mortem examination from 16 sites in 14 individuals without aneurysm disease were fixed and stained for collagen and elastin. Stained sections were imaged and analysed to calculate collagen and elastin content as a percentage of overall tissue area. Scanning electron microscopy was used to quantify the collagen microstructure at six specific arterial regions. RESULTS: From the aortic root to the level of the suprarenal aorta, the percentages (area fractions) of collagen (ascending, descending, and suprarenal aorta respectively with 95% confidence interval [CI] 37.5%, 31.7 - 43.2; 38.9%, 33.1 - 44.7; 44.8%, 37.4 - 52.1) and elastin (43.0%, 37.3 - 48.8; 40.3%, 34.8 - 46.1; 32.4%, 25.2 - 39.6) in the aortic wall were similar. From the suprarenal aorta to the internal iliac arteries, the percentage of collagen increased (abdominal aorta, common and internal iliac arteries and external iliac artery respectively with 95% CI 50.6%, 42.7 - 58.7; 51.2%, 45.5 - 56.9; 49.2%, 42.0 - 56.4) reaching a double percentage for elastin (23.6%, 15.7 - 31.6; 20.8%, 15.1 - 26.5; 22.2%, 14.9 - 29.5). Mean collagen fibre diameter (MFD) and average segment length (ASL) were significantly larger in the external iliac artery (MFD 6.03, 95% CI 5.95 - 6.11; ASL 22.21, 95% CI 20.80 - 23.61) than in the ascending aorta (MFD 5.81, 5.72 - 5.89; ASL 19.47, 18.07 - 20.88) and the abdominal aorta (MFD 5.92, 5.84 - 6.00; ASL 21.10, 19.69 - 22.50). CONCLUSION: In subjects lacking aneurysmal disease, the aorta and iliac arteries are not structurally uniform along their length. There is an increase in collagen percentage and decrease in elastin percentage progressing distally along the aorta. Mean collagen fibre diameter and average segment length are larger in the external iliac artery, compared with the ascending and the abdominal aorta.

Artificial intelligence framework to predict wall stress in abdominal aortic aneurysm.

Abdominal aortic aneurysms (AAA) have been rigorously investigated to understand when their risk of rupture - which is the 13th leading cause of death in the US - exceeds the risks associated with repair. Clinical intervention occurs when an aneurysm diameter exceeds 5.5 cm, but this "one-size fits all" criterion is insufficient, as it has been reported thatup to a quarter of AAA smaller than 5.5 cm do rupture. Therefore, there is a need for a more reliable, patient-specific, clinical tool to aide in the management of AAA. Biomechanical assessment of AAA is thought to provide critical physical insights to rupture risk, but clinical translataion of biomechanics-based tools has been limited due to the expertise, time, and computational requirements. It was estimated that through 2015, only 348 individual AAA cases have had biomechanical stress analysis performed, suggesting a deficient sample size to make such analysis relevant in the clinic. Artificial intelligence (AI) algorithms offer the potential to increase the throughput of AAA biomechanical analyses by reducing the overall time required to assess the wall stresses in these complex structures using traditional methods. This can be achieved by automatically segmenting regions of interest from medical images and using machine learning models to predict wall stresses of AAA. In this study, we present an automated AI-based methodology to predict the biomechanical wall stresses for individual AAA. The predictions using this approach were completed in a significantly less amount of time compared to a more traditional approach (~4 hours vs 20 seconds).

CCL2 loaded microparticles promote acute patency in silk-based vascular grafts implanted in rat aortae.

Cardiovascular disease is the leading cause of death worldwide, often associated with coronary artery occlusion. A common intervention for arterial blockage utilizes a vascular graft to bypass the diseased artery and restore downstream blood flow; however, current clinical options exhibit high long-term failure rates. Our goal was to develop an off-the-shelf tissue-engineered vascular graft capable of delivering a biological payload based on the monocyte recruitment factor C-C motif chemokine ligand 2 (CCL2) to induce remodeling. Bi-layered silk scaffolds consisting of an inner porous and outer electrospun layer were fabricated using a custom blend of Antherea Assama and Bombyx Mori silk (lyogel). Lyogel silk scaffolds alone (LG), and lyogel silk scaffolds containing microparticles (LGMP) were tested. The microparticles (MPs) were loaded with either CCL2 (LGMP+) or water (LGMP-). Scaffolds were implanted as abdominal aortic interposition grafts in Lewis rats for 1 and 8 weeks. 1-week implants exhibited patency rates of 50% (7/14), 100% (10/10), and 100% (5/5) in the LGMP-, LGMP+, and LG groups, respectively. The significantly higher patency rate for the LGMP+ group compared to the LGMP- group (p = 0.0188) suggests that CCL2 can prevent acute occlusion. Immunostaining of the explants revealed a significantly higher density of macrophages (CD68+ cells) within the outer vs. inner layer of LGMP- and LGMP+ constructs but not in LG constructs. After 8 weeks, there were no significant differences in patency rates between groups. All patent scaffolds at 8 weeks showed signs of remodeling; however, stenosis was observed within the majority of explants. This study demonstrated the successful fabrication of a custom blended silk scaffold functionalized with cell-mimicking microparticles to facilitate controlled delivery of a biological payload improving their in vivo performance. STATEMENT OF SIGNIFICANCE: This study outlines the development of a custom blended silk-based tissue-engineered vascular graft (TEVG) for use in arterial bypass or replacement surgery. A custom mixture of silk was formulated to improve biocompatibility and cellular binding to the tubular scaffold. Many current approaches to TEVGs include cells that encourage graft cellularization and remodeling; however, our technology incorporates a microparticle based delivery platform capable of delivering bioactive molecules that can mimic the function of seeded cells. In this study, we load the TEVGs with microparticles containing a monocyte attractant and demonstrate improved performance in terms of unobstructed blood flow versus blank microparticles. The acellular nature of this technology potentially reduces risk, increases reproducibility, and results in a more cost-effective graft when compared to cell-based options.

Extracellular Vesicles Derived from Primary Adipose Stromal Cells Induce Elastin and Collagen Deposition by Smooth Muscle Cells within 3D Fibrin Gel Culture.

Macromolecular components of the vascular extracellular matrix (ECM), particularly elastic fibers and collagen fibers, are critical for the proper physiological function of arteries. When the unique biomechanical combination of these fibers is disrupted, or in the ultimate extreme where fibers are completely lost, arterial disease can emerge. Bioengineers in the realms of vascular tissue engineering and regenerative medicine must therefore ideally consider how to create tissue engineered vascular grafts containing the right balance of these fibers and how to develop regenerative treatments for situations such as an aneurysm where fibers have been lost. Previous work has demonstrated that the primary cells responsible for vascular ECM production during development, arterial smooth muscle cells (SMCs), can be induced to make new elastic fibers when exposed to secreted factors from adipose-derived stromal cells. To further dissect how this signal is transmitted, in this study, the factors were partitioned into extracellular vesicle (EV)-rich and EV-depleted fractions as well as unseparated controls. EVs were validated using electron microscopy, dynamic light scattering, and protein quantification before testing for biological effects on SMCs. In 2D culture, EVs promoted SMC proliferation and migration. After 30 days of 3D fibrin construct culture, EVs promoted SMC transcription of the elastic microfibril gene FBN1 as well as SMC deposition of insoluble elastin and collagen. Uniaxial biomechanical properties of strand fibrin constructs were no different after 30 days of EV treatment versus controls. In summary, it is apparent that some of the positive effects of adipose-derived stromal cells on SMC elastogenesis are mediated by EVs, indicating a potential use for these EVs in a regenerative therapy to restore the biomechanical function of vascular ECM in arterial disease.

Mechanical, compositional and morphological characterisation of the human male urethra for the development of a biomimetic tissue engineered urethral scaffold.

This study addresses a crucial gap in the literature by characterising the relationship between urethral tissue mechanics, composition and gross structure. We then utilise these data to develop a biomimetic urethral scaffold with physical properties that more accurately mimic the native tissue than existing gold standard scaffolds; small intestinal submucosa (SIS) and urinary bladder matrix (UBM). Nine human urethra samples were mechanically characterised using pressure-diameter and uniaxial extension testing. The composition and gross structure of the tissue was determined using immunohistological staining. A pressure stiffening response is observed during the application of intraluminal pressure. The elastic and viscous tissue responses to extension are free of regional or directional variance. The elastin and collagen content of the tissue correlates significantly with tissue mechanics. Building on these data, a biomimetic urethral scaffold was fabricated from collagen and elastin in a ratio that mimics the composition of the native tissue. The resultant scaffold is comprised of a dense inner layer and a porous outer layer that structurally mimic the submucosa and corpus spongiosum layers of the native tissue, respectively. The porous outer layer facilitated more uniform cell infiltration relative to SIS and UBM when implanted subcutaneously (p < 0.05). The mechanical properties of the biomimetic scaffold better mimic the native tissue compared to SIS and UBM. The tissue characterisation data presented herein paves the way for the development of biomimetic urethral grafts, and the novel scaffold we develop demonstrates positive findings that warrant further in vivo evaluation.

Development of a Semi-Automated, Bulk Seeding Device for Large Animal Model Implantation of Tissue Engineered Vascular Grafts.

Vascular tissue engineering is a field of regenerative medicine that restores tissue function to defective sections of the vascular network by bypass or replacement with a tubular, engineered graft. The tissue engineered vascular graft (TEVG) is comprised of a biodegradable scaffold, often combined with cells to prevent acute thrombosis and initiate scaffold remodeling. Cells are most effectively incorporated into scaffolds using bulk seeding techniques. While our group has been successful in uniform, rapid, bulk cell seeding of scaffolds for TEVG testing in small animals using our well-validated rotational vacuum technology, this approach was not directly translatable to large scaffolds, such as those required for large animal testing or human implants. The objective of this study was to develop and validate a semi-automated cell seeding device that allows for uniform, rapid, bulk seeding of large scaffolds for the fabrication of TEVGs appropriately sized for testing in large animals and eventual translation to humans. Validation of our device revealed successful seeding of cells throughout the length of our tubular scaffolds with homogenous longitudinal and circumferential cell distribution. To demonstrate the utility of this device, we implanted a cell seeded scaffold as a carotid interposition graft in a sheep model for 10 weeks. Graft remodeling was demonstrated upon explant analysis using histological staining and mechanical characterization. We conclude from this work that our semi-automated, rotational vacuum seeding device can successfully seed porous tubular scaffolds suitable for implantation in large animals and provides a platform that can be readily adapted for eventual human use.

Ex-vivo quantification of ovine pia arachnoid complex biomechanical properties under uniaxial tension.

BACKGROUND: The pia arachnoid complex (PAC) is a cerebrospinal fluid-filled tissue conglomerate that surrounds the brain and spinal cord. Pia mater adheres directly to the surface of the brain while the arachnoid mater adheres to the deep surface of the dura mater. Collagen fibers, known as subarachnoid trabeculae (SAT) fibers, and microvascular structure lie intermediately to the pia and arachnoid meninges. Due to its structural role, alterations to the biomechanical properties of the PAC may change surface stress loading in traumatic brain injury (TBI) caused by sub-concussive hits. The aim of this study was to quantify the mechanical and morphological properties of ovine PAC. METHODS: Ovine brain samples (n = 10) were removed from the skull and tissue was harvested within 30 min post-mortem. To access the PAC, ovine skulls were split medially from the occipital region down the nasal bone on the superior and inferior aspects of the skull. A template was used to remove arachnoid samples from the left and right sides of the frontal and occipital regions of the brain. 10 ex-vivo samples were tested with uniaxial tension at 2 mm s-1, average strain rate of 0.59 s-1, until failure at < 5 h post extraction. The force and displacement data were acquired at 100 Hz. PAC tissue collagen fiber microstructure was characterized using second-harmonic generation (SHG) imaging on a subset of n = 4 stained tissue samples. To differentiate transverse blood vessels from SAT by visualization of cell nuclei and endothelial cells, samples were stained with DAPI and anti-von Willebrand Factor, respectively. The Mooney-Rivlin model for average stress-strain curve fit was used to model PAC material properties. RESULTS: The elastic modulus, ultimate stress, and ultimate strain were found to be 7.7 ± 3.0, 2.7 ± 0.76 MPa, and 0.60 ± 0.13, respectively. No statistical significance was found across brain dissection locations in terms of biomechanical properties. SHG images were post-processed to obtain average SAT fiber intersection density, concentration, porosity, tortuosity, segment length, orientation, radial counts, and diameter as 0.23, 26.14, 73.86%, 1.07 ± 0.28, 17.33 ± 15.25 µm, 84.66 ± 49.18°, 8.15%, 3.46 ± 1.62 µm, respectively. CONCLUSION: For the sizes, strain, and strain rates tested, our results suggest that ovine PAC mechanical behavior is isotropic, and that the Mooney-Rivlin model is an appropriate curve-fitting constitutive equation for obtaining material parameters of PAC tissues.

Computational modeling of the strength of the ascending thoracic aortic media tissue under physiologic biaxial loading conditions.

Type A Aortic Dissection (TAAD) is a life-threatening condition involving delamination of ascending aortic media layers. While current clinical guidelines recommend surgical intervention for aneurysm diameter > 5.5 cm, high incidence of TAAD in patients below this diameter threshold indicates the pressing need for improved evidence-based risk prediction metrics. Construction of such metrics will require the knowledge of the biomechanical failure properties of the aortic wall tissue under biaxial loading conditions. We utilized a fiber-level finite element based structural model of the aortic tissue to quantify the relationship between aortic tissue strength and physiologically relevant biaxial stress state for nonaneurysmal and aneurysmal patient cohorts with tricuspid aortic valve phenotype. We found that the model predicted strength of the aortic tissue under physiologic biaxial loading conditions depends on the stress biaxiality ratio, defined by the ratio of the longitudinal and circumferential components of the tissue stress. We determined that predicted biaxial tissue strength is statistically similar to its uniaxial circumferential strength below biaxiality ratios of 0.68 and 0.69 for nonaneurysmal and aneurysmal cohorts, respectively. Beyond this biaxiality ratio, predicted biaxial strength for both cohorts reduced drastically to a magnitude statistically similar to its longitudinal strength. We identified fiber-level failure mechanisms operative under biaxial stress state governing aforementioned tissue failure behavior. These findings are an important first step towards the development of mechanism-based TAAD risk assessment metrics for early identification of high-risk patients.

Extracellular Vesicles Enhance the Remodeling of Cell-Free Silk Vascular Scaffolds in Rat Aortae.

Vascular tissue engineering is aimed at developing regenerative vascular grafts to restore tissue function by bypassing or replacing defective arterial segments with tubular biodegradable scaffolds. Scaffolds are often combined with stem or progenitor cells to prevent acute thrombosis and initiate scaffold remodeling. However, there are limitations to cell-based technologies regarding safety and clinical translation. Extracellular vesicles (EVs) are nanosized particles released by most cell types, including stem and progenitor cells, that serve to transmit protein and RNA cargo to target cells throughout the body. EVs have been shown to replicate the therapeutic effect of their parent cells; therefore, EVs derived from stem or progenitor cells may serve as a more translatable, cell-free, therapeutic base for vascular scaffolds. Our study aims to determine if EV incorporation provides a positive effect on graft patency and remodeling in vivo. We first assessed the effect of human adipose-derived mesenchymal stem cell (hADMSC) EVs on vascular cells using in vitro bioassays. We then developed an EV-functionalized vascular graft by vacuum-seeding EVs into porous silk-based tubular scaffolds. These constructs were implanted as aortic interposition grafts in Lewis rats, and their remodeling capacity was compared to that observed for hADMSC-seeded and blank (non-seeded) controls. The EV group demonstrated improved patency (100%) compared to the hADMSC (56%) and blank controls (82%) following eight weeks in vivo. The EV group also produced significantly more elastin (126.46%) and collagen (44.59%) compared to the blank group, while the hADMSC group failed to produce significantly more elastin (57.64%) or collagen (11.21%) compared to the blank group. Qualitative staining of the explanted neo-tissue revealed improved endothelium formation, increased smooth muscle cell infiltration, and reduced macrophage numbers in the EV group compared to the controls, which aids in explaining this group's favorable pre-clinical outcomes.

Bioresorbable silk grafts for small diameter vascular tissue engineering applications: In vitro and in vivo functional analysis.

The success of tissue-engineered vascular graft (TEVG) predominantly relies on the selection of a suitable biomaterial and graft design. Natural biopolymer silk has shown great promise for various tissue-engineering applications. This study is the first to investigate Indian endemic non-mulberry silk (Antheraea assama-AA) - which inherits naturally superior mechanical and biological traits (e.g., RGD motifs) compared to Bombyx mori-BM silk, for TEVG applications. We designed bi-layered biomimetic small diameter AA-BM silk TEVGs adopting a new fabrication methodology. The inner layer showed ideally sized (~40 µm) pores with interconnectivity to allow cellular infiltration, and an outer dense electrospun layer that confers mechanical resilience. Biodegradation of silk TEVGs into amino acids as resorbable byproducts corroborates their in vivo remodeling ability. Following our previous reports, we surgically implanted human adipose tissue-derived stromal vascular fraction (SVF) seeded silk TEVGs in Lewis rats as abdominal aortic interposition grafts for 8 weeks. Adequate suture retention strength (0.45 ± 0.1 N) without any blood seepage post-implantation substantiate the grafts' viability. AA silk-based TEVGs showed superior animal survival and graft patency compared to BM silk TEVGs. Histological analysis revealed neo-tissue formation, host cell infiltration and graft remodeling in terms of extracellular matrix turnover. Altogether, this study demonstrates promising aspects of AA silk TEVGs for vascular tissue engineering applications. STATEMENT OF SIGNIFICANCE: Clinical 'off the shelf' implementation of tissue-engineered vascular grafts (TEVGs) remains a challenge. Achieving optimal blood vessel regeneration requires the use of bioresorbable materials having suitable degradation rates while producing minimal or no toxic byproducts. Host cell recruitment and preventing acute thrombosis are other pre-requisites for successful graft remodeling. In this study, for the first time we explored the use of naturally derived Indian endemic non-mulberry Antheraea assama silk in combination with Bombyx mori silk for TEVG applications by adopting a new biomimetic approach. Our bi-layered silk TEVGs were optimally porous, mechanically resilient and biodegradable. In vivo implantation in rat aorta showed long-term patency and graft remodeling by host cell infiltration and extracellular matrix deposition corroborating their clinical feasibility.

Cerebral Aneurysm Wall Stress After Coiling Depends on Morphology and Coil Packing Density.

Endovascular coil embolization is now widely used to treat cerebral aneurysms (CA) as an alternative to surgical clipping. It involves filling the aneurysmal sac with metallic coils to reduce flow, induce clotting, and promote the formation of a coil/thrombus mass which protects the aneurysm wall from hemodynamic forces and prevents rupture. However, a significant number of aneurysms are incompletely coiled leading to aneurysm regrowth and/or recanalization. Computational models of aneurysm coiling may provide important new insights into the effects of intrasaccular coil and thrombus on aneurysm wall stresses. Porcine blood and platinum coils were used to construct an in vitro coil thrombus mass (CTM) for mechanical testing. A uniaxial compression test was performed with whole blood clots and CTM, with coil packing densities (CPDs) of 10%, 20%, and 30% to obtain compressive stress/strain responses. A fourth-order polynomial mechanical response function was fit to the experimentally obtained stress/strain responses for each CPD in order to represent their mechanical properties for computational simulations. Patient-specific three-dimensional (3D) geometries of three aneurysms with simple geometry and four with complex geometry were reconstructed from digital subtraction angiography (DSA) images. The CPDs were digitally inserted in the aneurysm geometries and finite element modeling was used to determine transmural peak/mean wall stress (MWS) with and without coil packing. Reproducible stress/strain curves were obtained from compression testing of CTM and the polynomial mechanical response function was found to approximate the experimental stress/strain relationship obtained from mechanical testing to a high degree. An exponential increase in the CTM stiffness was observed with increasing CPD. Elevated wall stresses were found throughout the aneurysm dome, neck, and parent artery in simulations of the CAs with no filling. Complete, 100% filling of the aneurysms with whole blood clot and CPDs of 10%, 20%, and 30% significantly reduced MWS in simple and complex geometry aneurysms. Sequential increases in CPD resulted in significantly greater increases in MWS in simple but not complex geometry aneurysms. This study utilizes finite element analysis to demonstrate the reduction of transmural wall stress following coil embolization in patient-specific computational models of CAs. Our results provide a quantitative measure of the degree to which CPD impacts wall stress and suggest that complex aneurysmal geometries may be more resistant to coil embolization treatment. The computational modeling employed in this study serves as a first step in developing a tool to evaluate the patient-specific efficacy of coil embolization in treating CAs.

Functional Vascular Tissue Engineering Inspired by Matricellular Proteins.

Modern regenerative medicine, and tissue engineering specifically, has benefited from a greater appreciation of the native extracellular matrix (ECM). Fibronectin, collagen, and elastin have entered the tissue engineer's toolkit; however, as fully decellularized biomaterials have come to the forefront in vascular engineering it has become apparent that the ECM is comprised of more than just fibronectin, collagen, and elastin, and that cell-instructive molecules known as matricellular proteins are critical for desired outcomes. In brief, matricellular proteins are ECM constituents that contrast with the canonical structural proteins of the ECM in that their primary role is to interact with the cell. Of late, matricellular genes have been linked to diseases including connective tissue disorders, cardiovascular disease, and cancer. Despite the range of biological activities, this class of biomolecules has not been actively used in the field of regenerative medicine. The intent of this review is to bring matricellular proteins into wider use in the context of vascular tissue engineering. Matricellular proteins orchestrate the formation of new collagen and elastin fibers that have proper mechanical properties-these will be essential components for a fully biological small diameter tissue engineered vascular graft (TEVG). Matricellular proteins also regulate the initiation of thrombosis via fibrin deposition and platelet activation, and the clearance of thrombus when it is no longer needed-proper regulation of thrombosis will be critical for maintaining patency of a TEVG after implantation. Matricellular proteins regulate the adhesion, migration, and proliferation of endothelial cells-all are biological functions that will be critical for formation of a thrombus-resistant endothelium within a TEVG. Lastly, matricellular proteins regulate the adhesion, migration, proliferation, and activation of smooth muscle cells-proper control of these biological activities will be critical for a TEVG that recellularizes and resists neointimal formation/stenosis. We review all of these functions for matricellular proteins here, in addition to reviewing the few studies that have been performed at the intersection of matricellular protein biology and vascular tissue engineering.