Background: Arteriovenous fistula (AVF) is the preferred vascular access (VA) for hemodialysis, but it is still affected by high non-maturation and early failure rates due to stenosis development. Increasing evidence suggests that the presence of turbulent-like flow may play a key role, therefore, to stabilize the flow in the venous segment, an external support device (VasQ TM ) has been designed. The aim of this study was to provide preliminary evidence of VasQ TM impact on AVF hemodynamics as compared to AVFs created with conventional surgery. Methods: In this pilot single-center prospective randomized study six patients were enrolled, three in the VasQ group and three in the control group. Contrast-free magnetic resonance imaging (MRI) scans were acquired at 3 days, 3 months and 1 year after AVF surgery and were used to generate 3D patient-specific models. Computational fluid dynamic (CFD) simulations were performed using pimpleFoam, imposing patient-specific flow waveforms derived from ultrasound (US) examinations at the inlet of the proximal and distal artery, and a traction-free condition at the venous outflow. Morphologic and hemodynamic changes occurring over time were compared between VasQ and control AVFs. Results: Our MRI protocol provided high-quality images suitable for reliable segmentation and reconstruction of patient-specific 3D models of AVFs at all three timepoints in four out of six patients. The VasQ TM device maintained the angle between the artery and the vein almost unchanged over time, with a more stable flow in the AVFs supported by the device. In contrast, one of the AVFs of the control group evolved to an extreme dilatation of the vein and highly disturbed flow, while the other developed a stenosis in the juxta-anastomotic region. Conclusions: This study demonstrated the feasibility of characterizing the morphological and hemodynamic changes occurring over time in AVFs created using the VasQ TM device and provided preliminary evidence of the potential hemodynamic benefits of its use. Keywords Arteriovenous fistula , computational fluid dynamics , disturbed flow , external support device , longitudinal changes

Mechanical forces related to blood pressure and flow patterns play a crucial role in vascular homeostasis. Perturbations in vascular stresses and strain resulting from changes in hemodynamic may occur in pathological conditions, leading to vascular dysfunction as well as in vascular prosthesis, arteriovenous shunt for hemodialysis and in mechanical circulation support. Turbulent-like blood flows can induce high-frequency vibrations of the vessel wall, and this stimulus has recently gained attention as potential contributors to vascular pathologies, such as development of intimal hyperplasia in arteriovenous fistula for hemodialysis. However, the biological response of vascular cells to this stimulus remains incompletely understood. This review provides an analysis of the existing literature concerning the impact of high-frequency stimuli on vascular cell morphology, function, and gene expression. Morphological and functional investigations reveal that vascular cells stimulated at frequencies higher than the normal heart rate exhibit alterations in cell shape, alignment, and proliferation, potentially leading to vessel remodeling. Furthermore, vibrations modulate endothelial and smooth muscle cells gene expression, affecting pathways related to inflammation, oxidative stress, and muscle hypertrophy. Understanding the effects of high-frequency vibrations on vascular cells is essential for unraveling the mechanisms underlying vascular diseases and identifying potential therapeutic targets. Nevertheless, there are still gaps in our understanding of the molecular pathways governing these cellular responses. Further research is necessary to elucidate these mechanisms and their therapeutic implications for vascular diseases.

AbstractApproximately 3% of the population is estimated to have cerebral aneurysms, which are the leading cause of subarachnoid haemorrhage. Convincing evidences suggest that wall shear stresses (WSS) play a role in vessel remodeling and in the development of vascular diseases. SinceWSS cannot be directly measured, researchers have resorted to using medical images available in routine clinical practice to simulate computational fluid dynamics (CFD) and investigate patient-specific vascular conditions. They retrospectively analyse the correlation between WSS and disease outcomes to find potential clinical tools for future use. However, most of these models are based on assumptions that introduce variability and error. In this work we investigated the effects of a non-Newtonian viscosity model and inflow uncertainty on the prediction of commonly computed hemodynamic metrics. Our results show a substantial influence of the non-Newtonian model and blood flow rate on CFD outcomes, highlighting the need of incorporating non-Newtonian rheology and patient-specific blood flow measurements in CFD simulations.

INTRODUCTION:The COVID-19 pandemic has affected millions worldwide, causing mortality and multi-organ morbidity. Neurological complications have been recognized. This study aimed to assess brain structural, microstructural, and connectivity alterations in patients with COVID-19-related olfactory or cognitive impairment using post-acute (time from onset: 264[208-313] days) multi-directional diffusion-weighted MRI (DW-MRI). METHODS:The study included 16 COVID-19 patients with cognitive impairment (COVID-CM), 35 COVID-19 patients with olfactory disorder (COVID-OD), and 14 controls. A state-of-the-art processing pipeline was developed for DW-MRI pre-processing, mean diffusivity and fractional anisotropy computation, fiber density and cross-section analysis, and tractography of white-matter bundles. Brain parcellation required for probing network connectivity, region-specific microstructure and volume, and cortical thickness was based on T1-weighted scans and anatomical atlases. RESULTS:Compared to controls, COVID-CM patients showed overall gray matter atrophy (age and sex corrected p = 0.004), and both COVID-19 patient groups showed regional atrophy and cortical thinning. Both groups presented an increase in gray matter mean diffusivity (corrected p = 0.001), decrease in white matter fiber density and cross-section (corrected p < 0.05), , and COVID-CM patients also displayed an overall increased diffusivity (p = 0.022) and decreased anisotropy (corrected p = 0.038) in white matter. Graph-based analysis revealed reduced network modularity, with an extensive pattern of connectivity increase, in conjunction with a localized reduction in a few connections, mainly located in the left hemisphere. The left cingulate, anterior cingulate, and insula were primarily involved. CONCLUSION:Expanding upon previous findings, this study further investigated significant alterations in brain morphology, microstructure, and connectivity in COVID-19 patients with olfactory or cognitive disfunction. These findings suggest underlying neurodegeneration, neuroinflammation, and concomitant compensatory mechanisms. Future longitudinal studies are required to monitor the alterations over time and assess their transient or permanent nature.

Despite significant computational and experimental efforts and progress made over the past few decades, the mechanobiological mechanism underlying vascular stenosis formation in arteriovenous fistulae (AVF) for hemodialysis remains mostly unknown.To investigate potential mechanisms, we presented the case of a 72-years old end-stage kidney disease patient who experienced the failure of a distal radio-cephalic AVF 1.5 years post-surgery due to stenosis formation. High-fidelity patient-specific fluid-structure interaction simulations were performed at 5 consecutive time points to assess the evolution of hemodynamics and vascular wall mechanical stresses.The results revealed that flow instabilities induced elevated vibration amplitudes and high-pass strain in the initial segment of the cephalic vein, corresponding with the region where stenosis subsequently manifested in this patient. These vibrations reached their maximum value just before the formation of stenosis. This suggests that high-frequency vascular wall vibrations and strain may be overlooked mechanobiological stimuli that directly influence vascular cells, potentially contributing to adverse vascular remodeling, and warrants further investigation.If confirmed in larger cohorts, our findings could potentially pave the way for a rapid, non-invasive, and cost-effective method for monitoring AVF evolution through the quantification of mechanical vibration amplitudes and frequencies.

Arteriovenous fistula (AVF), the preferred vascular access for hemodialysis, is associated with high failure rate. The aim of this study was to investigate the potential of AVF sound auscultation in providing quantitative information on AVF hemodynamic conditions. This single-center prospective study involved six patients with native radio-cephalic AVFs who underwent multiple follow-up visits. Doppler Ultrasound blood flow volume (BFV) assessment and electronic stethoscope-based sound recordings were performed during each visit, whereas MRIs were acquired 3 days, 3 weeks and 1 year after surgery. Computational fluid dynamic (CFD) simulations were performed on patient-specific MRI-derived geometrical models. Higher values of median peak amplitudes ratios (high-low peak ratio-HLPR) were found to be associated with complex blood flow and velocity streamlines recirculation at systolic peak, and corresponding extended regions of high oscillatory shear index (OSI). On the contrary, lower values of HLPR were associated with laminar flow pattern and low values of OSI. Significant differences were observed in HLPR between subgroups with extended or limited areas with OSI > 0.1 (0.67 vs 0.31, respectively). Significant relationships were found between AVF sound intensity and brachial BFV (slope = 0.103, p < 0.01) as well as between longitudinal changes in brachial BFV and HLPR (slope = − 0.001, p < 0.01). Our results show that AVF sound can be exploited to extract fundamental information on AVF hemodynamic conditions, providing indication of the presence of complex hemodynamic and adequate BFV to perform hemodialysis. Sound analysis has therefore the potential to improve clinical AVF surveillance and to ameliorate outcome.

BACKGROUND:The number of patients treated with hemodialysis (HD) in Europe is more than half a million and this number increases annually. The arteriovenous fistula (AVF) is the vascular access (VA) of first choice, but the clinical outcome is still poor. A consistent number of AVFs fails to reach the desired blood flow rate for HD treatment, while some have too high flow and risk for cardiac complications. Despite the skill of the surgeons and the possibility to use Ultrasound investigation for mapping arm vasculature, it is still not possible to predict the blood flow volume that will be obtained after AVF maturation.METHODS:We evaluated the potential of using a computational model (AVF.SIM) to predict the blood flow volume that will be achieved after AVF maturation, within a multicenter international clinical investigation aimed at assessing AVF.SIM predictive power. The study population included 231 patients, with data on AVF maturation in 124 patients, and on long-term primary patency in 180 patients.RESULTS:At 1 year of follow-up, about 60% of AVFs were still patent, with comparable primary patency in proximal and distal anastomosis. The correlation between predicted and measured blood flow volume in the brachial artery at 40 days after surgery was statistically significant, with an overall correlation coefficient of 0.58 (p < 0.001). The percent difference between measured and predicted brachial blood flow 40 days after surgery was less than 30% in 72% of patients investigated.CONCLUSIONS:The results indicate that the use of the AVF.SIM system allowed to predict with a good accuracy the blood flow volume achievable after VA maturation, for a given location and type of anastomosis. This information may help in AVF surgical planning, reducing the AVFs with too low or too high blood flow, thus improving AVF patency rate and clinical outcome of renal replacement therapy.

Background: Arteriovenous fistula (AVF) is the preferred vascular access (VA) for hemodialysis, but it is associated with high non-maturation and failure rates. Predicting patient-specific AVF maturation and postoperative changes in blood flow volumes (BFVs) and vessel diameters is of fundamental importance to support the choice of optimal AVF location and improve VA survival. The goal of this study was to employ machine learning (ML) in order to give physicians a fast and easy-to-use tool that provides accurate patient-specific predictions, useful to make AVF surgical planning decisions. Methods: We applied a set of ML approaches on a dataset of 156 patients. Both parametric and non-parametric ML approaches, taking preoperative data as input, were exploited to predict maturation, postoperative BFVs, and diameters. The best approach associated with lowest cross-validation errors between predictions and real measurements was then chosen to provide estimates and quantify prediction errors. Results: The k-NN was the best approach to predict brachial BFV, AVF maturation, and other VA variables, and it was also associated with the least computational effort. With this approach, the confusion matrices proved the high accuracy of the prediction for AVF maturation (96.8%) and the low absolute error distribution for the continuous BFV and diameter variables. Conclusions: Our data-based approach provided accurate patient-specific predictions for different AVF configurations, requiring short computational time as compared to a physical model we previously developed. By supporting VA surgical planning, this fast computing approach could allow AVF surgical planning and help reducing the rate of non-maturation, which might ultimately have a broad impact on the management of hemodialysis patients.

It has been largely documented that local hemodynamic conditions, characterized by low and oscillating wall shear stresses, play a key role in the initiation and progression of vascular atherosclerotic lesions. Thus, investigation of the flow field in the carotid bifurcation can lead to early identification of vulnerable plaques. In this scenario, the development of novel non-invasive imaging tools that can be used in routine clinical practice to identify disturbed and recirculating blood flow becomes crucial. In this context, Vector Flow Imaging is becoming a relevant tool as it provides an angle independent assessment of blood flow velocity and multidimensional flow vector visualization. The purpose of the present study was to validate, in several locations of the carotid bifurcation, the high-frame rate vector flow imaging (HiFR-VFI) technique by comparing with computational fluid dynamic simulations (CFD).In all eight carotid bifurcations, HiFR-VFI accurately detected regions of laminar flow as well as recirculation and unsteady flow areas. An accurate and statistically significant agreement was observed between velocity vectors obtained by HiFR-VFI and those computed by CFD, both for vector magnitude (R = 0.85) and direction (R = 0.74).Our study demonstrated that HiFR-VFI is a valid technique for rapid and advanced visual representation of velocity field in large arteries. Thus, it has a great potential in research-based clinical practice for the identification of flow recirculation, low and oscillating velocity gradients near vessel wall. The use of HiFR-VFI may provide a great improvement in the investigation of the role of local hemodynamics in vascular pathologies, as well in the assessment of the effect of pharmacological treatments.

BACKGROUND:Arteriovenous fistula (AVF) is the preferred vascular access (VA) for hemodialysis, but it is still affected by high non-maturation and early failure rates due to stenosis development. Increasing evidence suggests that the presence of turbulent-like flow may play a key role, therefore, to stabilize the flow in the venous segment, an external support device (VasQTM) has been designed. The aim of this study was to provide preliminary evidence of VasQTM impact on AVF hemodynamics as compared to AVFs created with conventional surgery. METHODS:In this pilot single-center prospective randomized study six patients were enrolled, three in the VasQ group and three in the control group. Contrast-free magnetic resonance imaging (MRI) scans were acquired at 3 days, 3 months and 1 year after AVF surgery and were used to generate 3D patient-specific models. Computational fluid dynamic (CFD) simulations were performed using pimpleFoam, imposing patient-specific flow waveforms derived from ultrasound (US) examinations at the inlet of the proximal and distal artery, and a traction-free condition at the venous outflow. Morphologic and hemodynamic changes occurring over time were compared between VasQ and control AVFs. RESULTS:Our MRI protocol provided high-quality images suitable for reliable segmentation and reconstruction of patient-specific 3D models of AVFs at all three timepoints in four out of six patients. The VasQTM device maintained the angle between the artery and the vein almost unchanged over time, with a more stable flow in the AVFs supported by the device. In contrast, one of the AVFs of the control group evolved to an extreme dilatation of the vein and highly disturbed flow, while the other developed a stenosis in the juxta-anastomotic region. CONCLUSIONS:This study demonstrated the feasibility of characterizing the morphological and hemodynamic changes occurring over time in AVFs created using the VasQTM device and provided preliminary evidence of the potential hemodynamic benefits of its use.

The dataset contains two folders: 1) Imaging, and 2) Post-processing, each containing data from individual patients (C1, C2, V1, and V2). In details: - the Imaging folder contains MRI DICOM data at different time points (3 days, 3 weeks, and 1 year) and US data used as boundary conditions for CFD simulations - the Post-processing folder contains .vtp files of both morphology (CSA.vtp) and hemodynamics (hemo.vtp) at different time points