Gaetano Burriesci

The impact of recovered atrial dynamics on pre-existing thrombi within the left atrial appendage (LAA) remains a poorly understood phenomenon, despite its potential clinical implications during spontaneous or induced restoration of sinus rhythm (SR) in patients with atrial fibrillation (AF). While computational studies have investigated thrombus formation during AF, none have examined the fate of established thrombi following SR restoration. This work addresses that gap by modelling thrombus formation and embolisation in the LAA under AF and after the return to normal rhythm. A meshless particle-based thrombus model was employed to simulate the formation of clots in a patient specific LAA, under AF conditions, and then analyse haemodynamic changes and thrombus behaviour under persistent AF and recovered SR. Results show that SR restoration profoundly modifies thrombus growth and erosion compared with AF. The resumption of atrial contractility increases local shear strain rate, especially in the proximity of anatomical features such as knees and trabeculae, driving progressive thrombi erosion and detachment from secondary lobes. These processes are amplified during the atrial systolic phase, when mechanical forces promote thrombus detachment. Conversely, if AF persists, the associated reduction in blood wash-out and shear stresses promote thrombus growth. Clots located in regions of higher stagnation remain stable under both restored SR and persistent AF. By providing the first direct computational comparison of thrombus behaviour in AF and after SR restoration, this work offers novel insights with potential to inform personalised therapeutic strategies.

The morphological analysis of the left atrial appendage is crucial to ensure that the most appropriate treatment is selected for patients suffering from atrial fibrillation. However, the process is susceptible to three sources of subjectivity: identification of the region that separates the left atrial appendage from the left atrium, computation of the appendage features, and morphological classification. We developed an automated method for detecting the left atrial appendage from 3D reconstruction from clinical images, overcoming the need for human intervention. Our method operates on a triangulated surface mesh containing both the left atrium and the left atrial appendage. The method exploits skeletonisation, distance analysis, affinity evaluation, and plane identification techniques for accurate appendage detection. Furthermore, it computes the left atrial appendage size and performs network analysis of the appendage skeleton to characterize the auricula using specific metrics. In addition, we introduced a metric-based classification approach, wherein clusters are formed based on the extracted features. This approach allows for more objective and data-driven classification, enhancing the accuracy and reliability of the morphological analysis. By integrating these advancements, our method represents a significant step towards reducing subjectivity in the analysis of the left atrial appendage, thus facilitating more consistent and standardized investigations of its morphologies and therapeutic selection.

Fluid–structure interaction (FSI) is crucial in the numerical simulation of cardiovascular phenomena, where pulsatile blood flow dynamically interacts with highly deformable tissues. High-fidelity FSI approaches have become essential to enhance the understanding of potentially lethal pathologies, assisting diagnosis and development of novel therapeutic solutions. This work presents and experimentally validates a new, totally meshless FSI approach, specifically designed for cardiovascular applications. The method is based on the Lagrangian smoothed particle hydrodynamics (SPH), employing a unified physics to represent both blood and deformable walls, avoiding FSI interfaces. A key advantage of this method lies in its ability to overcome the SPH complex issue in contour management, a common challenge that typically increases the complexity of this methodology in FSI applications. Deformable walls are immersed in the fluid domain, and a buffer region of fluid is defined to handle the structural deformation. For validation, a new FSI benchmark is proposed and analyzed with the particle image velocimetry technique. Tailored to entail the typical complexities of relevant cardiovascular situations, the benchmark involves pulsatile flow interacting with a chamber with deformable curved walls, moving through both filling and emptying phases. Despite its simplified geometry, designed to allow a reliable experimental validation, the structure experiences a field of three-dimensional strains and large volume variations, thereby replicating complexities often associated with more intricate models. Numerical and experimental results show good agreement in terms of fluid velocity field and structural deformation, establishing the proposed totally meshless FSI approach as a reliable tool for complex cardiovascular modeling.

Current commercial midsoles provide a fixed level of cushioning and elasticity regardless of gait phase or loading rate. We report a novel “artificial muscle” midsole composite that dynamically tunes its compressive stiffness and relaxation behavior by embedding nickel–titanium (Nitinol) shape‐memory alloy (SMA) wires into multilayer silicone substrates (Shore A12, A20, A30) using two hand‐knitting patterns (A and C). Specimens (undeformed height = 30 mm; frontal area = 61,213.856 mm ² or 612.139 cm ² ) were tested on a 50 kN Instron 5969 under displacement control. For compression (stress–strain) testing, each sample was ramped from an initial grip separation of 30 mm to a 12.5 mm gap (≈58.33% nominal compressive strain) at 200 mm/min (≈0.111 s ⁻¹ strain rate). At each voltage state (0 V ⟶ 14 V for Pattern A; 0 V ⟶ 10 V for Pattern C), four loading–unloading cycles were conducted at 60 mm/min (≈0.033 s ⁻¹ strain rate). For stress‐relaxation (creep) testing, specimens were ramped from 30 mm to a 12.5 mm gap (≈58.33% strain) at 60 mm/min (≈0.033 s ⁻¹ ) and then held at constant displacement for 120 s under three voltage levels (Pattern A: 0 V, 14 V, 19 V; Pattern C: 0 V, 8 V, 14 V). Under these protocols, silicone A30 with Pattern C consistently exhibited the largest actuation‐induced contraction (Δ = 27.79% in compression; Δ = 36.54% in creep/relax), while MANOVA and t ‐test results confirmed that substrate hardness, actuation state, and knitting pattern each significantly modulated compressive stress (all p < 0.001). These findings demonstrate that our SMA‐enabled midsole can switch between soft and stiff modes—across ≈58.3% strain at strain rates up to ≈0.111 s ⁻¹ —offering a tunable, durable, and cost‐effective solution for adaptive footwear.