Finite-element simulation of residual stress induced by split-sleeve cold-expansion process of holes

A three-dimensional finite-element simulation was conducted for a split-sleeve cold-expansion process in order to determine the residual stress field around an expanded hole. The commercial FEA software DEFORM-3D\u2122, a Lagrangian implicit code designed for metal forming processes, was used to model the cold-expansion process of a fastener hole. The results show a through-thickness residual stress field in good agreement with the analytical solution developed by Guo. Moreover, the simulation has highlighted the effect of the split sleeve and the plate thickness on the residual stress field. \ua9 2007 Elsevier B.V. All rights reserved

On the left ventricular remodeling of patients with stenotic aortic valve: A statistical shape analysis

The left ventricle (LV) constantly changes its shape and function as a response to patho-logical conditions, and this process is known as remodeling. In the presence of aortic stenosis (AS), the degenerative process is not limited to the aortic valve but also involves the remodeling of LV. Statistical shape analysis (SSA) offers a powerful tool for the visualization and quantification of the geometrical and functional patterns of any anatomic changes. In this paper, a SSA method was devel-oped to determine shape descriptors of the LV under different degrees of AS and thus to shed light on the mechanistic link between shape and function. A total of n = 86 patients underwent computed tomography (CT) for the evaluation of valvulopathy were segmented to obtain the LV surface and then were automatically aligned to a reference template by rigid registrations and transformations. Shape modes of the anatomical LV variation induced by the degree of AS were assessed by principal component analysis (PCA). The first shape mode represented nearly 50% of the total variance of LV shape in our patient population and was mainly associated to a spherical LV geometry. At Pearson’s analysis, the first shape mode was positively correlated to both the end-diastolic volume (p < 0.01, R = 0.814) and end-systolic volume (p < 0.01, and R = 0.922), suggesting LV impairment in patients with severe AS. A predictive model built with PCA-related shape modes achieved better perfor-mance in stratifying the occurrence of adverse events with respect to a baseline model using clinical demographic data as risk predictors. This study demonstrated the potential of SSA approaches to detect the association of complex 3D shape features with functional LV parameters

On the Finite Element Modeling of the Lumbar Spine: A Schematic Review

Finite element modelling of the lumbar spine is a challenging problem. Lower back pain is among the most common pathologies in the global populations, owing to which the patient may need to undergo surgery. The latter may differ in nature and complexity because of spinal disease and patient contraindications (i.e., aging). Today, the understanding of spinal column biomechanics may lead to better comprehension of the disease progression as well as to the development of innovative therapeutic strategies. Better insight into the spine’s biomechanics would certainly guarantee an evolution of current device-based treatments. In this setting, the computational approach appears to be a remarkable tool for simulating physiological and pathological spinal conditions, as well as for various aspects of surgery. Patient-specific computational simulations are constantly evolving, and require a number of validation and verification challenges to be overcome before they can achieve true and accurate results. The aim of the present schematic review is to provide an overview of the evolution and recent advances involved in computational finite element modelling (FEM) of spinal biomechanics and of the fundamental knowledge necessary to develop the best modeling approach in terms of trustworthiness and reliability

Towards data-driven and data-based control of wave energy systems: Classification, overview, and critical assessment

Currently, a significant effort in the world research panorama is focused on finding efficient solutions to a carbon-free energy supply, wave energy being one of the most promising sources of untapped renewable energy. However, wave energy is not currently economic, though control technology has been shown to significantly increase the energy capture capabilities. Usually, the synthesis of a wave energy control strategy requires the adoption of control-oriented models, which are prone to error, particularly arising from unmodelled hydrodynamics, given the complexity of the hydrodynamic interactions between the device and the ocean. In this context, data-driven and data-based control strategies provide a potential solution to some of these issues, using real-time data to gather information about the system dynamics and performance. Thus motivated, this study provides a detailed analysis of different approaches to the exploitation of data in the design of control philosophies for wave energy systems, establishing clear definitions of data-driven and data-based control in this field, together with a classification highlighting the various roles of data in the control synthesis process. In particular, we investigate intrinsic opportunities and limitations behind the use of data in the process of control synthesis, providing a comprehensive review together with critical considerations aimed at directly contributing towards the development of efficient data-driven and data-based control systems for wave energy devices

Atlas-Based Evaluation of Hemodynamic in Ascending Thoracic Aortic Aneurysms

Atlas-based analyses of patients with cardiovascular diseases have recently been explored to understand the mechanistic link between shape and pathophysiology. The construction of probabilistic atlases is based on statistical shape modeling (SSM) to assess key anatomic features for a given patient population. Such an approach is relevant to study the complex nature of the ascending thoracic aortic aneurysm (ATAA) as characterized by different patterns of aortic shapes and valve phenotypes. This study was carried out to develop an SSM of the dilated aorta with both bicuspid aortic valve (BAV) and tricuspid aortic valve (TAV), and then assess the computational hemodynamic of virtual models obtained by the deformation of the mean template for specific shape boundaries (i.e., ±1.5 standard deviation, σ). Simulations demonstrated remarkable changes in the velocity streamlines, blood pressure, and fluid shear stress with the principal shape modes such as the aortic size (Mode 1), vessel tortuosity (Mode 2), and aortic valve morphologies (Mode 3). The atlas-based disease assessment can represent a powerful tool to reveal important insights on ATAA-derived hemodynamic, especially for aneurysms which are considered to have borderline anatomies, and thus challenging decision-making. The utilization of SSMs for creating probabilistic patient cohorts can facilitate the understanding of the heterogenous nature of the dilated ascending aorta

Transcatheter heart valve implantation in bicuspid patients with self-expanding device

Bicuspid aortic valve (BAV) patients are conventionally not treated by transcathether aortic valve implantation (TAVI) because of anatomic constraint with unfavorable outcome. Patient-specific numerical simulation of TAVI in BAV may predict important clinical insights to assess the con-formability of the transcathether heart valves (THV) implanted on the aortic root of members of this challenging patient population. We aimed to develop a computational approach and virtually simulate TAVI in a group of n.6 stenotic BAV patients using the self-expanding Evolut Pro THV. Specif-ically, the structural mechanics were evaluated by a finite-element model to estimate the deformed THV configuration in the oval bicuspid anatomy. Then, a fluid–solid interaction analysis based on the smoothed-particle hydrodynamics (SPH) technique was adopted to quantify the blood-flow patterns as well as the regions at high risk of paravalvular leakage (PVL). Simulations demonstrated a slight asymmetric and elliptical expansion of the THV stent frame in the BAV anatomy. The contact pressure between the luminal aortic root surface and the THV stent frame was determined to quantify the device anchoring force at the level of the aortic annulus and mid-ascending aorta. At late diastole, PVL was found in the gap between the aortic wall and THV stent frame. Though the modeling framework was not validated by clinical data, this study could be considered a further step towards the use of numerical simulations for the assessment of TAVI in BAV, aiming at understanding patients not suitable for device implantation on an anatomic basis

Usefulness of regional right ventricular and right atrial strain for prediction of early and late right ventricular failure following a left ventricular assist device implant: A machine learning approach

Background: Identifying candidates for left ventricular assist device surgery at risk of right ventricular failure remains difficult. The aim was to identify the most accurate predictors of right ventricular failure among clinical, biological, and imaging markers, assessed by agreement of different supervised machine learning algorithms. Methods: Seventy-four patients, referred to HeartWare left ventricular assist device since 2010 in two Italian centers, were recruited. Biomarkers, right ventricular standard, and strain echocardiography, as well as cath-lab measures, were compared among patients who did not develop right ventricular failure (N = 56), those with acute–right ventricular failure (N = 8, 11%) or chronic–right ventricular failure (N = 10, 14%). Logistic regression, penalized logistic regression, linear support vector machines, and naïve Bayes algorithms with leave-one-out validation were used to evaluate the efficiency of any combination of three collected variables in an “all-subsets” approach. Results: Michigan risk score combined with central venous pressure assessed invasively and apical longitudinal systolic strain of the right ventricular–free wall were the most significant predictors of acute–right ventricular failure (maximum receiver operating characteristic–area under the curve = 0.95, 95% confidence interval = 0.91–1.00, by the naïve Bayes), while the right ventricular–free wall systolic strain of the middle segment, right atrial strain (QRS-synced), and tricuspid annular plane systolic excursion were the most significant predictors of Chronic-RVF (receiver operating characteristic–area under the curve = 0.97, 95% confidence interval = 0.91–1.00, according to naïve Bayes). Conclusion: Apical right ventricular strain as well as right atrial strain provides complementary information, both critical to predict acute–right ventricular failure and chronic–right ventricular failure, respectively

On the Material Constitutive Behavior of the Aortic Root in Patients with Transcatheter Aortic Valve Implantation

Background: Transcatheter aortic valve implantation (TAVI) is a minimally invasive procedure used to treat patients with severe aortic valve stenosis. However, there is limited knowledge on the material properties of the aortic root in TAVI patients, and this can impact the credibility of computer simulations. This study aimed to develop a non-invasive inverse approach for estimating reliable material constituents for the aortic root and calcified valve leaflets in patients undergoing TAVI. Methods: The identification of material parameters is based on the simultaneous minimization of two cost functions, which define the difference between model predictions and cardiac-gated CT measurements of the aortic wall and valve orifice area. Validation of the inverse analysis output was performed comparing the numerical predictions with actual CT shapes and post-TAVI measures of implanted device diameter. Results: A good agreement of the peak systolic shape of the aortic wall was found between simulations and imaging, with similarity index in the range in the range of 83.7% to 91.5% for n.20 patients. Not any statistical difference was observed between predictions and CT measures of orifice area for the stenotic aortic valve. After TAVI simulations, the measurements of SAPIEN 3 Ultra (S3) device diameter were in agreement with those from post-TAVI angio-CT imaging. A sensitivity analysis demonstrated a modest impact on the S3 diameters when altering the elastic material property of the aortic wall in the range of inverse analysis solution. Conclusions: Overall, this study demonstrates the feasibility and potential benefits of using non-invasive imaging techniques and computational modeling to estimate material properties in patients undergoing TAVI

Patient-specific analysis of ascending thoracic aortic aneurysm with the living heart human model

In ascending thoracic aortic aneurysms (ATAAs), aneurysm kinematics are driven by ventricular traction occurring every heartbeat, increasing the stress level of dilated aortic wall. Aortic elongation due to heart motion and aortic length are emerging as potential indicators of adverse events in ATAAs; however, simulation of ATAA that takes into account the cardiac mechanics is technically challenging. The objective of this study was to adapt the realistic Living Heart Human Model (LHHM) to the anatomy and physiology of a patient with ATAA to assess the role of cardiac motion on aortic wall stress distribution. Patient-specific segmentation and material parameter estimation were done using preoperative computed tomography angiography (CTA) and ex vivo biaxial testing of the harvested tissue collected during surgery. The lumped-parameter model of systemic circulation implemented in the LHHM was refined using clinical and echocardiographic data. The results showed that the longitudinal stress was highest in the major curvature of the aneurysm, with specific aortic quadrants having stress levels change from tensile to compressive in a transmural direction. This study revealed the key role of heart motion that stretches the aortic root and increases ATAA wall tension. The ATAA LHHM is a realistic cardiovascular platform where patient-specific information can be easily integrated to assess the aneurysm biomechanics and potentially support the clinical management of patients with ATAAs

Staying alive on an active volcano. 80 years population dynamics of Cytisus aeolicus (Fabaceae) from Stromboli (Aeolian Islands, Italy)

Cytisus aeolicus is a narrow endemic species restricted to the Aeolian archipelago (SE Tyrrhenian Sea, Italy) and it is one of the most evolutionarily isolated plants in the Mediterranean flora. Historical and literature data suggest that both metapopulations and isolated individuals of C. aeolicus are gradually shrinking. Field investigations and drone images demonstrate that the C. aeolicus metapopulation from Stromboli experienced a strikingly fast increase during the last decades. As of 2019, more than 7000 ± 3000 mature individuals occur on Stromboli, i.e. 14 to 20 times more than those counted during the last census, 25 years ago. The diachronic analysis of aerial photos concerning last 80 years and the analysis of the growth rings of some selected plants pointed out that the surface occupied, the demographic structure and the distribution pattern of the subpopulations of Stromboli has been highly fluctuating during last decades. Moreover, data issuing from field observations in permanent plots placed in a transect between two isolated mature individuals showed that, under natural conditions, the germination rate of the seedlings of C. aeolicus can be very high and their establishment rate may exceed 40%. By contrast, seedlings mortality is subject to strong annual fluctuations. Additionally, the pollen morphology of the Strombolian metapopulation of this rare and isolated species is studied here for the first time. Contrary to what is stated in recent literature, the C. aeolicus metapopulation from Stromboli is healthy and very dynamic, albeit frequently damaged by the volcanic activity. Regular and repeated field surveys carried out during 3 years (2017–2019) allowed improving our knowledge on the life cycle of C. aeolicus and a new extinction risk assessment of the species, according to IUCN criteria, is presented