Background: Carotid artery stenting (CAS) could lead to a modification of the carotid bifurcation geometry with possible clinical implications. This study aimed to clarify the geometrical impact of three carotid stents with different designs on the carotid bifurcation and its clinical consequences. Methods: This was a retrospective single-center study. We included all patients who underwent CAS in a 3-year period. Anatomical changes of the carotid bifurcation were evaluated by reviewing angiographic images. The population was divided into three groups based on the stent implanted: Group 1 (Carotid Wallstent), Group 2 (Roadsaver), and Group 3 (C-Guard). Results: A total of 226 patients were included. The mean age was 77.0 ± 7.4 years and 72.5% (164/226) were male. Three different stents were implanted into three groups: Group 1 (n = 131/226, 58%), Group 2 (n = 57/226, 25.2%), and Group 3 (n = 38/226, 16.8%). The mean pre-stent implantation CCA-ICA angle of the entire population was 155 ± 14.9°, and the post-CAS angle was 167.7 ± 8.7° (p = 0.0001). In every subgroup, the difference was statistically different, with the biggest difference registered in Group 2 (−16.1 ± 13.2°). Regarding stent oversizing, there was a significant relationship between CCA oversizing and CCA-ICA angle modification (p = 0.006). During follow-up, a total of 14 (6.2%) restenoses were registered. The mean CCA-ICA angle modification in the restenosis group was −9.5 ± 14.4° vs. −12.8 ± 11.9° in the no-restenosis group with no significant statistical differences were outlined (p = 0.3). Conclusions: Compared to the Carotid Wallstent and C-Guard, the Roadsaver stent appears to have a lower adaptability to the carotid vascular territory, resulting in a higher CCA-ICA angle modification after implantation, with no impact on the stent restenosis rate.

Background: Acute infrainguinal bypass graft occlusion is a critical vascular emergency that threatens limb viability and challenges both surgical and endovascular management. Despite progress in revascularization strategies, outcomes remain suboptimal, and consensus on the optimal treatment approach is lacking. Methods: This narrative review summarizes current evidence on the epidemiology, etiology, diagnosis, and treatment of acute infrainguinal graft occlusion. Particular attention is given to the evolving role of catheter-directed thrombolysis and mechanical thrombectomy, as well as to prevention strategies based on structured surveillance and medical optimization. Results: Infrainguinal bypass failure is influenced by technical, anatomical, and systemic factors, with distinct mechanisms affecting vein and prosthetic grafts. While surgical thrombectomy remains a viable option in selected cases, endovascular techniques have gained prominence due to their minimally invasive nature and promising short-term outcomes. Prevention of occlusion through duplex surveillance and best medical therapy is crucial to preserving graft patency and reducing major amputation risk. Conclusions: Management of acute graft occlusion requires timely diagnosis and a tailored, multidisciplinary approach. Although endovascular therapies have expanded treatment options, further prospective studies are needed to define optimal strategies and improve long-term outcomes in this high-risk population.

Computed tomography angiography (CTA) is the reference imaging modality for diagnosis, endovascular planning, and surveillance of abdominal aortic aneurysms (AAAs), but conventional assessment remains time-consuming, operator-dependent, and limited by complex anatomy. This narrative review examines the role of artificial intelligence (AI) in three-dimensional aortic CTA segmentation for AAA management. The narrative synthesis drew on literature identified through PubMed/MEDLINE, Scopus and the Cochrane Library, with the original search covering January 2000 to July 2026. Ten primary studies from the existing bibliography were characterized in a study-level table, and reported Dice coefficients were displayed for nine studies. Current evidence indicates that AI-based segmentation, particularly using convolutional neural networks, U-Net-derived models, and nnU-Net frameworks, can improve the speed and reproducibility of aortic lumen, wall, thrombus, branch vessel, endograft, and aneurysm sac delineation. These techniques may support more accurate morphometric measurements, device sizing, procedural planning, quantitative surveillance, and the development of advanced imaging biomarkers. However, available studies remain heterogeneous in datasets, anatomical evaluation, imaging protocols, validation strategies, and reported performance metrics, limiting direct comparison and clinical generalizability. AI-assisted 3D segmentation represents a promising tool for transforming CTA from descriptive imaging into quantitative decision support, but robust multicenter validation, workflow integration, and expert supervision remain essential before widespread clinical adoption.