Three-Dimensional Characterization of Aortic Root Motion by Vascular Deformation Mapping.

The aorta is in constant motion due to the combination of cyclic loading and unloading with its mechanical coupling to the contractile left ventricle (LV) myocardium. This aortic root motion has been proposed as a marker for aortic disease progression. Aortic root motion extraction techniques have been mostly based on 2D image analysis and have thus lacked a rigorous description of the different components of aortic root motion (e.g., axial versus in-plane). In this study, we utilized a novel technique termed vascular deformation mapping (VDM(D)) to extract 3D aortic root motion from dynamic computed tomography angiography images. Aortic root displacement (axial and in-plane), area ratio and distensibility, axial tilt, aortic rotation, and LV/Ao angles were extracted and compared for four different subject groups: non-aneurysmal, TAA, Marfan, and repair. The repair group showed smaller aortic root displacement, aortic rotation, and distensibility than the other groups. The repair group was also the only group that showed a larger relative in-plane displacement than relative axial displacement. The Marfan group showed the largest heterogeneity in aortic root displacement, distensibility, and age. The non-aneurysmal group showed a negative correlation between age and distensibility, consistent with previous studies. Our results revealed a strong positive correlation between LV/Ao angle and relative axial displacement and a strong negative correlation between LV/Ao angle and relative in-plane displacement. VDM(D)-derived 3D aortic root motion can be used in future studies to define improved boundary conditions for aortic wall stress analysis.

Modeling planar response of vascular tissues using quadratic functions of effective strain.

Simulation-based studies of the cardiovascular structure such as aorta have become increasingly popular for many biomedical problems such as predictions of aneurysm rupture. A critical step in these simulations is the development of constitutive models that accurately describe the tissue's mechanical behavior. In this work, we present a new constitutive model, which explicitly accounts for the gradual recruitment of collagen fibers. The recruitment is considered using an effective stretch, which is a continuum-scale kinematic variable measuring the uncrimped stretch of the tissue in an average sense. The strain energy of a fiber bundle is described by a quadratic function of the effective strain. Constitutive models formulated in this manner are applied to describe the responses of ascending thoracic aortic aneurysm and porcine thoracic aorta tissues. The heterogeneous properties of the ATAA tissue are extracted from bulge inflation test data, and then used in finite element analysis to simulate the inflation test. The descriptive and predictive capabilities are further assessed using planar testing data of porcine thoracic aortic tissues. It is found that the constitutive model can accurately describe the stress-strain relations. In particular, the finite element simulation replicates the displacement, strain, and stress distributions with excellent fidelity.

On strain-based rupture criterion for ascending aortic aneurysm: The role of fiber waviness.

We propose a new approach for constructing strain-based rupture criterion for ascending thoracic aortic aneurysm. The rupture metric is formulated using an effective strain, which is a measure of net strain that the collagen bundles experience after fiber uncrimping. The effective strain is a function of the total strain and the waviness properties of the collagen fibers. In the present work, the waviness properties are obtained from fitting biaxial response data to constitutive models that explicitly consider the collagen waviness and fiber recruitment. Inflation test data from 10 ascending thoracic aortic aneurysm specimens are analyzed. For each specimen, tension-strain data at ∼2300 material points are garnered. The effective strain fields in the configuration immediately before rupture are computed. It is found that the hotspots of the effective strain match the rupture sites very well in all 10 samples. More importantly, the values of effective strain at the hotsopts are closely clustered around 0.1, in contrast to a much wider distribution of the total strain. The study underscores the importance of considering the fiber recruitment in formulating strain-based rupture metric, and suggests that ϵ¯≈0.1, where ϵ¯ is the effective strain metric defined in this work, can be considered as a criterion for assessing the imminent rupture risk of ascending aortic aneurysms. STATEMENT OF SIGNIFICANCE: We advocate to use effective strain in ATAA rupture assessment. The effective strain is a measure of net strain in the collagen network after waviness uncrimping. We analyzed bulge inflation data of ATAA samples. It was found that, while the total strains at rupture varied from sample to sample, the effective strains were closely clustered around 0.1. And the hotspots of effective strain matched the rupture sites well. The work underlines the importance of considering collagen fiber waviness and recruitment when evaluating the rupture risk using strain, and suggests a new direction for developing sharper rupture metrics.

miR-93-5p suppresses ovarian cancer malignancy and negatively regulate CCND2 by binding to its 3'UTR region.

Ovarian cancer is the most fatal gynecological cancer worldwide, yet the fundamental mechanism of malignancy acquisition in ovarian cancer remains unknown. miRNA has been implicated to a variety of diseases, including cancer initiation and progression. Cyclin-D2 (CCND2) is ubiquitously implicated in cancer uncontrol cell proliferation. Bioinformatic research revealed that CCND2 is a candidate gene for miR-93-5p with a binding site in its 3'UTR region in the current study. Using our ovarian cancer sample, we verified that miR-93-5p is negatively correlated with CCND2 mRNA and protein levels. Luciferase report assay revealed miR-93-5p inhibits CCND2 production through binding to the 3'UTR region. The expression of miR-93-5p in ovarian cancer patient samples was then determined, and a survival analysis was performed. Our findings showed that miR-93-5p is downregulated in ovarian cancer and is a favorable predictive factor in ovarian cancer patient. CCK8 assay, wound healing assay and flow cytometry-based cell cycle and apoptotic cell analyses were employed here. We found that miR-93-5p suppresses ovarian cancer cell proliferation and migration while enhances cell death. Our research certified that miR-93-5p reduces ovarian cancer malignancy by targeting CCND2.

Uniaxial properties of ascending aortic aneurysms in light of effective stretch.

A constitutive model that explicitly considers the gradual recruitment of collagen fibers is applied to investigate the uniaxial properties of human ascending aortic aneurysms. The model uses an effective stretch, which is a continuum scale kinematic variable measuring the true stretch of the tissue, to formulate the fiber stress. The constitutive equation contains two shape parameters characterizing the stochastic distribution of fiber waviness, and two elastic parameters accounting for, respectively, the elastic properties of ground substance and the straightened collagen fibers. The model is applied to 156 sets of uniaxial stress-stretch data obtained from 52 aneurysm samples. Major findings include (1) the uniaxial response can be well described by a quadratic strain energy function of the effective strain; (2) the ultimate stretches, when measured in terms of the effective stretch, are closely clustered around 1.1, in contrast to a much wider range in the original stretch; and (3) the ultimate stress correlates positively with the fiber stiffness. The age dependence and directional differences of constitutive parameters are also investigated. Results indicate that only the waviness depends strongly on age; no clear alterations occur in elastic parameters. Further, the fibers are wavier and stiffer in the circumferential direction than in the longitudinal direction. No other parameters exhibit significant direction difference. STATEMENT OF SIGNIFICANCE: We introduced a constitutive model which explicitly accounts for collagen fiber recruitment to investigate the uniaxial properties of human ascending aortic aneurysm tissues. Uniaxial response data from 156 specimens were considered in the study. It was found that the seemingly dissimilar response curves are, in fact, similar if we measure the deformation using an effective stretch which factors out the uncrimping deformation. The rupture stretches in terms of the effective stretch are closely packed around 1.1. And the stress-stretch curves collapse to a canonical curve after a transformation.

Incorporating fiber recruitment in hyperelastic modeling of vascular tissues by means of kinematic average.

We present a framework for considering the gradual recruitment of collagen fibers in hyperelastic constitutive modeling. An effective stretch, which is a response variable representing the true stretch at the tissue-scale, is introduced. Properties of the effective stretch are discussed in detail. The effective stretch and strain invariants derived from it are used in selected hyperelastic constitutive models to describe the tissue response. This construction is investigated in conjunction with Holzapfel-Gasser-Ogden family strain energy functions. The ensuing models are validated against a large body of uniaxial and bi-axial stress-strain response data from human aortic aneurysm tissues. Both the descriptive and the predictive capabilities are examined. The former is evaluated by the quality of constitutive fitting, and the latter is assessed using finite element simulation. The models significantly improve the quality of fitting, and reproduce the experiment displacement, stress, and strain distributions with high fidelity in the finite element simulation.

Estimating aortic thoracic aneurysm rupture risk using tension-strain data in physiological pressure range: an in vitro study.

Previous studies have shown that the rupture properties of an ascending thoracic aortic aneurysm (ATAA) are strongly correlated with the pre-rupture response features. In this work, we present a two-step machine learning method to predict where the rupture is likely to occur in ATAA and what safety reserve the structure may have. The study was carried out using ATAA specimens from 15 patients who underwent surgical intervention. Through inflation test, full-field deformation data and post-rupture images were collected, from which the wall tension and surface strain distributions were computed. The tension-strain data in the pressure range of 9-18 kPa were fitted to a third-order polynomial to characterize the response properties. It is hypothesized that the region where rupture is prone to initiate is associated with a high level of tension buildup. A machine learning method is devised to predict the peak risk region. The predicted regions were found to match the actual rupture sites in 13 samples out of the total 15. In the second step, another machine learning model is utilized to predict the tissue's rupture strength in the peak risk region. Results suggest that the ATAA rupture risk can be reasonably predicted using tension-strain response in the physiological range. This may open a pathway for evaluating the ATAA rupture propensity using information of in vivo response.

Prediction of local strength of ascending thoracic aortic aneurysms.

Knowledges of both local stress and strength are needed for a reliable evaluation of the rupture risk for ascending thoracic aortic aneurysm (ATAA). In this study, machine learning is applied to predict the local strength of ATAA tissues based on tension-strain data collected through in vitro inflation tests on tissue samples. Inputs to machine learning models are tension, strain, slope, and curvature values at two points on the low strain region of the tension-strain curve. The models are trained using data from locations where the tissue ruptured, and subsequently applied to data from intact sites to predict the local rupture strength. The predicted strengths are compared with the known strength at rupture sites as well as the highest tension the tissues experienced at the intact sites. A local rupture index, which is the ratio of the end tension to the predicted rupture strength, is computed. The 'hot spots' of the rupture index are found to match the rupture sites better than those of the peak tension. The study suggests that the strength of ATAA tissue could be reliably predicted from early phase response features defined in this work.

Numerical evaluation of the efficacy of small-caliber colonoscopes in reducing patient pain during a colonoscopy.

Patient pain caused by a colonoscope is one of the main complications in completing a colonoscopy. Currently, randomized controlled trial (RCT) is one of the most used methods to evaluate the efficacy of small-caliber (SC) colonoscopes in reducing patient pain during a colonoscopy, compared with a standard colonoscope (SDC). However, many disturbing factors, including endoscopists' skills, characteristics of patients and new technical features of the colonoscope (passive bending and high force transmission shaft), limit the reliability and generalizability of each finding in current RCTs. This paper focuses on modeling the insertion of colonoscopes within colon models using an explicit finite element method (FEM). Such a numerical model could overcome the limitations in RCTs. At the same time, it is expected to evaluate the efficacy of the small-caliber colonoscopes in reducing patient pain during a colonoscopy, while considering the effects of patient characteristics, including age, region and gender. The simulation results in this work showed that: compared with the SDC, a SC colonoscope may be more helpful in reducing discomfort for older patients, patients with smaller colon diameters and females.