Diego Gallo

Keratoconus is a progressive corneal ectatic disorder characterized by stromal thinning and biomechanical weakening of the cornea, leading to progressive corneal protrusion and visual impairment. Therapeutic strategies have evolved from visual correction toward approaches specifically targeting the biomechanical instability underlying disease progression. This review provides a biomechanical perspective on current and emerging strategies for the biomechanical stabilization of the keratoconic cornea. Conservative treatments based on contact lenses remain essential for visual rehabilitation but do not modify the underlying ectatic process. Corneal collagen crosslinking represents the reference treatment for progressive keratoconus, as it increases stromal stiffness through the formation of additional covalent bonds. However, its efficacy depends on treatment protocol, epithelial status, corneal thickness, and disease stage. Corneal implants, i.e., synthetic intracorneal ring segments and corneal allogenic intrastromal ring segments, provide stretch-induced geometric improvement of the corneal shape and, consequently, of visual acuity, although predictability remains limited. Combined approaches, such as ring implantation followed by cross-linking, aim to integrate corneal reshaping with intrinsic stromal reinforcement. Emerging approaches, including cell-based therapies, and implantation of stromal lenticule or tissue-engineered scaffolds, suggest a future shift toward a multimodal therapeutic strategy integrating biomechanical stabilization, restoration of stromal structure, and biological regeneration. Advancing keratoconus management will require objective biomechanical assessment and predictive modeling tools to guide individualized treatment planning and improve outcome predictability. Ultimately, future management should increasingly incorporate a biomechanical perspective, with interventions designed to modify the mechanical behavior of the ectatic cornea, arrest progression, and restore functional corneal integrity.

The role of local hemodynamics on atherosclerosis at the carotid bifurcation has been the subject of study by computational fluid-dynamics (CFD) simulations for over three decades. Nevertheless, questions still swirl about the inherent rigid-wall assumption, especially with the introduction of increasingly predictive—but also increasingly intricate—hemodynamic parameters. Two-way-coupled fluid–structure interaction (FSI) simulations were performed on a cohort of 10 carotid bifurcations with ostensibly normal lumen geometries, along with CFD simulations assuming rigid arterial walls. In FSI simulations, carotid wall mechanical properties were assumed to be anisotropic via a fiber-reinforced hyperelastic material model, also accounting for prestress and external tissue support. Three-element Windkessel models were used to impose pressure conditions consistent with patient-specific measured inflow rates and outflow divisions. Maximum cross-sectional area changes over the cardiac cycle were generally less than 21%. Qualitatively, only small-to-moderate differences were observed between FSI and CFD simulations in terms of wall shear stress (WSS) and intravascular flow patterns. Quantitatively, median differences in the surface areas exposed to low time-averaged WSS (TAWSS), high oscillatory shear index (OSI) and topological shear variation index (TSVI) were 4.1%, 1.4%, and 2.3%, respectively, and co-localized satisfactorily (median similarity index: 0.83, 0.79, and 0.68, respectively). CFD simulations assuming arterial rigid walls are generally sufficient to adequately capture hemodynamic features of biological/clinical relevance, even for sensitive quantities like TSVI. However, the benefits of FSI for computation of structural quantities and the ability to explore the synergistic relationship between these quantities and hemodynamic stresses on the endothelium should not be overlooked.

Aortic aneurysms (AAs), both abdominal and thoracic, remain one of the most lethal cardiovascular diseases, with increasing prevalence and incidence, especially in sporadic forms, in our populations, primarily represented by elderly individuals. The high mortality risk is primarily due to delayed management, although their management has shown progress, particularly regarding imaging techniques that facilitate diagnosis and otherwise complex surgical procedures. This is due to the clinical decision-making approach, which, unfortunately, is still based, according to guidelines, on the maximum aortic diameter. The maximum aortic diameter, as repeatedly emphasized, fails to capture the biological and biomechanical complexity of these pathological conditions, which are influenced, among other things, by highly individual factors (genetics, gender, lifestyle, etc.). Thanks to the advent of network medicine and omics sciences, diverse and complex clinical, imaging, and biomarker datasets are available. Artificial intelligence (AI) could process this data to facilitate the complex management of aneurysms and accurately predict risk. AI could prove an excellent tool for aneurysm management, improving risk prediction and radically transforming the way we understand, monitor, and manage aneurysm patients, despite some limitations, as well as improving its therapeutic applications towards personalized strategies. This narrative review provides an overview of these aspects based on current evidence.

Background: Aortic stiffness (AoS) is an established predictor of cardiovascular morbidity and mortality. Endovascular aneurysm repair (EVAR) introduces a rigid stent-graft into the aorta, potentially increasing AoS and impairing subendocardial perfusion. This prospective study aimed to evaluate changes in AoS and myocardial perfusion following EVAR, measured by carotid-to-femoral pulse wave velocity (cf-PWV) and the Subendocardial Viability Ratio (SEVR), and examined the influence of graft length on post-operative cf-PWV and SEVR. Methods: From October 2023 to April 2025, 38 patients undergoing elective EVAR were prospectively enrolled. Cf-PWV and the SEVR were measured ® device. Descriptive statistics were used to summarize baseline characteristics. Data were assessed for normality with the Shapiro–Wilk test; non-normally distributed variables were analysed using the Wilcoxon signed-rank test and presented as median [interquartile range, IQR], while normally distributed variables were analysed using paired t-tests and presented as mean ± standard deviation (SD). Linear regression was applied to evaluate associations between graft length and postoperative changes in cf-PWV and SEVR. Results: Cf-PWV increased significantly after EVAR, with a median within-patient change of 1.0 m/s [IQR 3.1] (p < 0.001), corresponding to a 10.6% increase. The SEVR decreased significantly by 15.1% (p = 0.006). Graft length correlated positively with cf-PWV change, with a 0.2% increase in cf-PWV per millimetre of graft length (r = 0.41; p = 0.029), but not with SEVR (r = 0.058, p = 0.763). Conclusions: EVAR was associated with increased AoS and reduced subendocardial perfusion, with greater stiffness changes observed in patients receiving longer grafts. These preliminary findings highlight important haemodynamic consequences of EVAR and may inform patient selection, postoperative management, and the development of future stent-graft designs to mitigate long-term cardiovascular risk.

This study reports the first biomedical application of event-based imaging velocimetry (EBIV) and demonstrates its feasibility for investigating cardiac hemodynamics. Experiments were conducted in a left-heart pulse duplicator to characterize intraventricular fluid mechanics with a transcatheter mitral valve. EBIV and conventional particle image velocimetry (PIV) measurements were acquired synchronously under two distinct flow regimes. The aim was to assess whether EBIV—a neuromorphic, event-driven imaging technology—can provide flow measurements comparable to those obtained with PIV, which serves as the reference technique for the in vitro assessment of prosthetic heart valves hydrodynamics. The results show that EBIV accurately reproduces valve-related hemodynamic features, including phase-averaged velocity fields, vortex structures, circulation, Lagrangian trajectories, and pulsatile kinetic energy, while producing markedly compact datasets and benefiting from an extended dynamic range. A modal analysis based on proper orthogonal decomposition further confirms a strong agreement between EBIV and PIV, revealing nearly identical dominant spatial modes. These findings establish EBIV as a promising, data-efficient, and real-time capable alternative for the quantitative characterization of cardiac flows. This first biomedical application underscores EBIV's potential for device assessment, intraventricular flow analysis, and broader application in experimental cardiovascular research.

Aortic aneurysms (AAs), both abdominal and thoracic, remain one of the most fatal cardiovascular emergencies, with a growing prevalence and incidence, especially for sporadic forms in our populations, which are primarily comprised of elderly individuals. A high mortality risk also appears to be linked to managerial delays, despite advances in imaging techniques that facilitate the difficult diagnosis, and in surgical procedures. This is the result of the clinical decision-making approach, which is unfortunately still based, as per guidelines, on the maximum aortic diameter. This parameter, as suggested, fails to capture the biological and biomechanical complexity underlying these pathological conditions, which are influenced, among other things, by entirely individual factors (genetics, gender, lifestyle, etc.). With the emergence of network medicine and omics sciences, diverse and complex sets of clinical, imaging, and biomarker data are now available. These could be precisely processed by artificial intelligence (AI), enabling accurate prediction of AA risk and facilitating its complex management. Therefore, AI could represent an excellent tool for AAs, showing the potential not only to refine AA risk prediction but also to radically transform the way we understand, monitor, and manage AA patients, despite some limitations. These aspects are the subject of this review, as are their therapeutic applications.

Aortic mechanical heart valves (MHVs) have been implanted for decades to treat aortic valve disease and remain a viable option when valve durability is prioritized. However, the non-physiological hemodynamics induced by MHVs may lead to adverse clinical outcomes. Fluid-structure interaction (FSI) simulations enable the analysis of the biomechanical interaction between MHVs and blood flow. This study presents a strongly coupled, boundary-fitted FSI framework for aortic MHVs, used to assess the impact of MHV design and aortic curvature on hemodynamics. Nine simulation scenarios were investigated, considering three commercially available MHVs and three idealized aortic geometries (one straight and two curved models). Overall, the framework proved to provide results for flow-rate waveforms, velocity fields, and leaflet kinematics aligning well with previous experimental and computational studies. The framework highlighted that: (i) MHV design influences velocity fields and large-scale vorticity transport in the aorta, with systolic differences among the three devices of up to 41% and 133% in average swirling strength and stretching, respectively; (ii) the straight aortic model underestimates systolic swirling strength (up to 56%) and stretching (up to 91%) compared to curved models. This FSI framework can support MHV development by analyzing different device designs and anatomical scenarios.

Coronary bifurcation lesions present complex challenges in interventional cardiology, necessitating effective stenting techniques to achieve optimal results. This literature review comprehensively examines the application of computational and bench testing methods in coronary bifurcation stenting, offering insights into procedural aspects, stent design considerations, and patient‐specific characteristics. Structural mechanics finite element analysis, computational fluid dynamics, and multi‐objective optimization are valuable tools for evaluating stenting strategies, including provisional side branch stenting and two‐stenting techniques. We highlight the impact of procedural factors, such as balloon positioning and rewiring techniques, and stent design features on the outcome of percutaneous coronary interventions with stents. We discuss the importance of patient‐specific characteristics in deployment strategies, such as bifurcation angle and plaque properties. This understanding informs present and future research and clinical practice on bifurcation stenting. Computational simulations are a continuously maturing advance that has significantly enhanced stenting devices and techniques for coronary bifurcation lesions over the years. However, the accurate account of patient‐specific vessel and lesion characteristics, both in terms of anatomical and accurate physiological behavior, and their large variation between patients, remains a significant challenge in the field. In this context, advancements in multi‐objective optimization offer significant opportunities for refining stent design and procedural practices.

Deciphering the complex interactions at the blood vessel–wall interface remains a key challenge in hemodynamics research. Wall shear stress (WSS) is recognized as a signature for near-wall velocity dynamics, while vorticity represents a fundamental structure of fluid motion. In this work, we revise and extend a recently proposed unifying theoretical approach that sought to connect the topological features of surface vorticity (SV) and WSS [Mazzi, Gallo, Calò, Steinman, and Morbiducci, “Linking wall shear stress and vorticity topologies: Toward a unified theory of cardiovascular flow disturbances,” Phys. Fluids 36(6), 61905 (2024)], the latter recently gaining momentum as a predictor of vascular disease. By revising a partially erroneous interpretation of the link between WSS and SV fixed points (focal points on the luminal surface where these fields vanish), we demonstrate here that every WSS fixed point is also a SV fixed point, and vice versa, though their nature and stability may differ. Building upon the previous study, we establish a robust theoretical classification of the possible combinations of WSS and SV fixed points, based on their nature and stability, and mechanistically connect them to near-wall fluid structures. These structures can further be distinguished by the presence or absence of vorticity diffusion flux normal to the wall, depending on local vorticity kinematics. High-resolution computational fluid dynamics simulations on intracranial aneurysm models validate these theoretical insights. This unifying framework offers a clear taxonomy describing the mechanistic relationship between near-wall flow disturbances and intravascular hemodynamics, providing a deeper understanding of how local shear forces are influenced by near-wall fluid structures, while also paving the way for a clearer interpretation of the role of near-wall hemodynamics in vascular pathophysiology.

Background: Coronary microvascular dysfunction has been associated with adverse cardiovascular events following acute myocardial infarction. This study evaluates the role of the angiography‐derived index of microcirculatory resistance (angio‐IMR) in predicting myocardial damage in patients with ST‐segment–elevation myocardial infarction undergoing primary percutaneous coronary intervention (PCI). Methods and Results: In this post hoc analysis of the CLEVER‐ACS (Controlled‐Level Everolimus in Acute Coronary Syndromes) trial, the associations between post‐PCI angio‐IMR of infarct‐related coronary arteries (IRAs) and infarct size, microvascular obstruction, and left ventricular ejection fraction at 30 days as assessed by cardiac magnetic resonance were investigated. High post‐PCI angio‐IMR was defined as ≥40 mm Hg*s . In non‐IRAs, angio‐IMR was measured before IRA‐PCI. A total of 52 IRAs and 94 non‐IRAs of 52 patients were analyzed. Post‐PCI angio‐IMR was 41.5 (interquartile range [IQR], 28.5–55.7) mm Hg*s in IRAs and pre‐PCI angio‐IMR was 43.7 (IQR, 31.7–54.0) mm Hg*s in non‐IRAs ( P =0.70). Patients with high post‐PCI angio‐IMR (52%) exhibited a larger myocardial infarct size (36.0 [IQR, 23.0–52.5] g versus 14.5 [IQR, 6.50–26.5] g, P P =0.002) at 30 days as compared with those with low post‐PCI angio‐IMR values. Post‐PCI angio‐IMR positively correlated with myocardial infarct size (r=0.45, P =0.001) and extent of microvascular obstruction (r=0.40, P =0.004) at 30 days. Post‐PCI angio‐IMR predicted myocardial infarct size (area under the curve, 0.78 [IQR, 0.65–0.92]; P =0.001) and extent of microvascular obstruction (area under the curve, 0.74 [IQR, 0.60–0.89]; P =0.009) at 30 days. Conclusions: In patients with ST‐segment–elevation myocardial infarction, post‐PCI angio‐IMR was identified as independent predictor of myocardial infarct size and extent of microvascular obstruction. Registration: URL: https:// clinicaltrials.gov ; Unique Identifier: NCT01529554.