Search Results (47)

Background/Objectives: This study compared the hemodynamic performance of fenestrated (FEVAR), branched (BEVAR), and chimney endovascular aortic aneurysm repair (chEVAR) in patients with complex aortic aneurysms. Methods: The pre- (native) and post-endovascular repair (endograft-defined) blood lumen was reconstructed from computed tomography angiographies of nine (9) elective patients treated with FEVAR (n = 3), BEVAR (n = 3), and chEVAR (n = 3). Computational fluid dynamics (CFD) simulations obtained blood flow properties. Velocity magnitude, wall shear stress (WSS), time-averaged wall shear stress (TAWSS), oscillatory shear index (OSI), relative residence time (RRT), and local normalized helicity (LNH) were computed at peak systole and mid-diastole. The hemodynamic data were statistically analyzed to evaluate correlations between FEVAR, BEVAR, and chEVAR, focusing on targeted visceral arteries. Results: Only slight differences were observed regarding RRT, OSI, and TAWSS between FEVAR and BEVAR, whereas the chEVAR group demonstrated a marked deviation from both. In FEVAR, the postoperative helical flow structures appeared more compact, while in BEVAR they were more developed and exhibited a more rotational configuration. The LNH of the visceral vessel patterns exhibited similar qualitative features across groups. Regarding TAWSS, higher values were found in BEVAR, whereas chEVAR showed the lowest. Conclusions: FEVAR, BEVAR, and chEVAR improved postoperative blood flow characteristics toward near-physiological conditions, reducing undesired flow patterns and recirculation zones. FEVAR showed more stable visceral flow, and BEVAR demonstrated higher flow rates and fewer recirculation zones, while chEVAR exhibited more streamlined visceral artery flow with reduced regurgitation at bridging stent entries. Despite variations, all approaches effectively preserved visceral artery perfusion. Full article

Background: Simulation-based training may offer a useful approach to support skill acquisition in neurointerventional stroke treatment without exposing patients to procedural risks. As the global demand for thrombectomy rises, training strategies that ensure procedural competence while addressing workforce constraints are increasingly important. With this pilot study, we aim to generate a hypothesis as to whether additional exposure of trainees to mechanical thrombectomy could benefit from simulator training on top of the standard training carried out on flow models. This study was designed as an exploratory pilot investigation and was not able to provide inferential or confirmatory statistical conclusions. Methods: Six novice participants (advanced clinical-year medical students with completed anatomical and preclinical training, but without previous exposure to catheter-based interventions) performed two neurointerventional tasks, vascular access and mechanical thrombectomy (MTE), on flow models. After a baseline assessment, three participants received standard model-based training (control group), and three received additional simulator training using a high-fidelity angiography simulator (Mentice VIST G5). Performance was reassessed after four weeks using technical and clinical surrogate metrics, which were ranked and descriptively analyzed. Results: No relevant differences were observed between groups for the vascular access task. In contrast, the simulator group demonstrated a trend toward improved performance in the MTE task, with greater gains in efficiency, autonomy, and procedural safety. Conclusions: Our findings indicate a possible benefit of even brief simulator exposure for skill acquisition for complex endovascular procedures such as MTE. While conventional training may suffice for basic skills, simulation may be particularly helpful in supporting learning in more advanced tasks. Full article

Background: Mock circulatory loops (MCLs) are benchtop experimental platforms that reproduce key features of the human cardiovascular system, providing a safe, controlled, and reproducible environment for haemodynamic investigation. This scoping review aims to systematically map the current landscape of MCLs used for aortic simulation and identify major areas of application. Methods: A systematic search of PubMed, Scopus, and Web of Science identified original studies employing MCLs for aortic simulation. Eligible studies were categorized into predefined themes: (I) (bio)mechanical aortic characterization, (II) hemodynamics, (III) device testing, (IV) diagnostics, and (V) training. Data on MCL configurations, aortic models, and study objectives were synthesized narratively. Results: Eighty-four studies met the inclusion criteria. Twenty-five investigated aortic biomechanics, 23 hemodynamics, 22 device or product testing, 13 validated diagnostic imaging techniques, and one training application. Models included porcine (n = 22), human cadaveric (n = 7), canine (n = 1), ovine (n = 1), bovine (n = 1), and 3D-printed or molded aortic phantoms (n = 55). MCLs were employed to study parameters such as aortic stiffness, flow dynamics, dissection propagation, endoleaks, imaging accuracy, and device performance. Conclusions: This review provides a comprehensive overview of MCL applications in aortic research. MCLs represent a versatile pre-clinical platform for studying aortic pathophysiology and testing endovascular therapies under controlled conditions. Standardized reporting frameworks are now required to improve reproducibility and accelerate translation to patient-specific planning. Full article

Background/Objectives: Endovascular aneurysm repair (EVAR) is the standard treatment for abdominal aortic aneurysms, but the risk of endoleak compromises its effectiveness. Type IA endoleak, stemming from an inadequate proximal seal, is the most critical complication associated with the highest risk of rupture. Current preoperative planning relies on static anatomical measurements from computed tomography angiography that fail to predict seal failure due to dynamic biomechanical forces. This study aimed to retrospectively validate the predictive accuracy of a novel physics-informed digital twin and artificial intelligence (AI) model for predicting type IA endoleak risk compared to conventional static planning methods. Methods: This was a retrospective, single-center proof-of-concept validation study involving 15 patients who underwent elective EVAR (5 with confirmed type IA endoleak and 10 without type IA endoleak). A patient-specific digital twin was created for each case to simulate stent-graft deployment and capture the dynamic biomechanical interaction with the aortic wall. A logistic regression AI model processed over 16,000 biomechanical measurements to generate a single, objective metric of the endoleak risk index (ERI). The predictive performance of the ERI (using a cutoff of 0.80) was assessed and compared against a 1:3 propensity score-matched conventional control group (n = 45) who received traditional anatomical-based planning. Results: The mean ERI was significantly higher in the endoleak-positive group (0.85 ± 0.10) compared to the endoleak-negative group (0.39 ± 0.11) (p = 0.011). The digital twin/AI model demonstrated superior predictive capability, achieving an overall accuracy of 80% (95% CI: 51.9–95.7) and an area under the curve (AUC) of 0.85 (95% CI: 0.58–0.99). Crucially, the model achieved a sensitivity of 100% and a negative predictive value (NPV) of 100%, correctly identifying all high-risk cases and ruling out endoleak in all low-risk cases. In stark contrast, the matched conventional planning group achieved an overall accuracy of only 51.1% and an AUC of 0.54. Conclusion: This physics-informed digital twin and AI framework successfully validated its capability to accurately and objectively predict the risk of type IA endoleak following EVAR. The derived ERI offers a significant quantitative advantage over traditional static anatomical measurements, establishing it as a highly reliable safety tool (100% NPV) for ruling out endoleak risk. This technology represents a critical advancement toward personalized EVAR planning, enabling surgeons to proactively identify high-risk anatomies and adjust treatment strategies to minimize post-procedural complications. Further large-scale, multicenter prospective trials are necessary to confirm these findings and support clinical adoption. Full article

Background: Animal models are essential for translating diagnostic and therapeutic strategies into clinical practice and offer valuable insights into the pathophysiology of diseases such as aortic dissection. This study presents a novel acute in vivo large animal model of Stanford type A aortic dissection, combining open surgical access with endovascular techniques to leverage the advantages of both. The model aims to reproducibly simulate acute dissections in swine, providing a standardized platform for evaluating diagnostics, disease mechanisms, and treatment strategies. Methods: Six pigs underwent a standardized protocol to induce aortic dissection. Arterial pressure was monitored via femoral and carotid catheterization. A conventional sternotomy was performed, followed by tangential cross-clamping of the ascending aorta and a controlled incision proximal to the brachiocephalic trunk. The intima and the media were separated using a guidewire and catheter-based technique to create a false lumen. A re-entry tear was also established to allow for controlled intraluminal access. Animals were monitored for 12 h post-intervention, with serial blood sampling. At the end of the experiment, the animals were euthanized and the aortas harvested for macroscopic and histological analysis. Results: In all 6 animals, the placement of arterial catheters in femoral and carotid arteries, as well as the sternotomy, was established without any complications. The dissection model was successfully created in 5 out of 6 animals by clinical signs such as adventitial hematoma, macroscopic wall separation and/or decreased femoral blood pressure. One animal experienced complete aortic perforation. Five animals completed the full observation period of 12 h. Conclusion: A standardized, reproducible, and robust large animal model of acute Stanford type A aortic dissection using a hybrid approach was developed. This model closely simulates the clinical and pathological features of human aortic dissection, making it a valuable tool for preclinical research in diagnostics, pathophysiology, and treatment development. Full article

Background/Objectives: The aberrant subclavian artery (ASA) represents the most common congenital anomaly of the aortic arch, and is frequently associated with a Kommerell diverticulum, an aneurysmal dilation at the anomalous vessel origin. This condition carries a significant risk of rupture and dissection, and growing evidence indicates that local hemodynamic alterations may contribute to its development and progression. Computational Fluid Dynamics (CFD) provides a valuable non-invasive modality to assess biomechanical stresses and elucidate the pathophysiological mechanisms underlying these vascular abnormalities. Methods: In this study, twelve thoracic CT angiography scans were analyzed: six from patients with ASA and six from individuals with normal aortic anatomy. CFD simulations were performed using OpenFOAM, with standardized boundary conditions applied across all cases to isolate the influence of anatomical differences in flow behavior. Four key hemodynamic metrics were evaluated—Wall Shear Stress (WSS), Oscillatory Shear Index (OSI), Drag Forces (DF), and Turbulent Viscosity Ratio (TVR). The aortic arch was subdivided into Ishimaru zones 0–3, with an adapted definition accounting for ASA anatomy. For each region, time- and space-averaged quantities were computed to characterize mean values and oscillatory behavior. Conclusions: The findings demonstrate that patients with ASA exhibit markedly altered hemodynamics in zones 1–3 compared to controls, with consistently elevated WSS, OSI, DF, and TVR. The most pronounced abnormalities occurred in zones 2–3 near the origin of the aberrant vessel, where disturbed flow patterns and off-axis mechanical forces were observed. These features may promote chronic wall stress, endothelial dysfunction, and localized aneurysmal degeneration. Notably, two patients (M1 and M6) displayed particularly elevated drag forces and TVR in the distal arch, correlating with the presence of a distal aneurysm and right-sided arch configuration, respectively. Overall, this work supports the hypothesis that aberrant hemodynamics contribute to Kommerell diverticulum formation and progression, and highlights the CFD’s feasibility for clarifying disease mechanisms, characterizing flow patterns, and informing endovascular planning by identifying hemodynamically favorable landing zones. Full article

Three-dimensional printing has emerged as a promising technology in endovascular surgery for the production of patient-specific stent-grafts. Thermoplastic polyurethane (TPU) is widely used for this purpose due to its favourable biocompatibility, hemocompatibility, and mechanical properties. However, its long-term stability under physiological conditions remains uncertain. This study evaluates the ageing behaviour of 3D-printed TPU stent-grafts under accelerated oxidative conditions (20% H₂O₂–0.1 M CoCl₂) over three months, corresponding to approximately 45 months in vivo, and during three months in hydrolytic (0.1 M NaOH) conditions. Mechanical, physicochemical, thermal, and surface properties were periodically analysed. Differential scanning calorimetry revealed a decrease in crystallisation enthalpy of 41% and a reduction in melting enthalpy of 29% after hydrolytic ageing, whereas no decrease was observed after oxidative ageing. Despite these chemical changes, size exclusion chromatography indicated minimal chain scission. However, spectroscopy and microscopy showed minor chain scission and additive migration (antioxidant and lubricant). Nevertheless, tensile testing highlighted that mechanical performance remained within clinically acceptable ranges. These findings demonstrate that 3D-printed TPU vascular implants retain essential properties under prolonged simulated ageing, supporting their safety and durability for vascular applications. Full article

An abdominal aortic aneurysm (AAA) poses a significant risk of arterial wall rupture, which critically endangers the patient’s life. To address this condition, an endovascular aneurysm repair (EVAR) is required, involving the insertion and expansion of a stent-graft within the aorta, to support and isolate the weakened vessel wall. In this context, this article aims to approach the problem from a mechanical perspective and to simulate the expansion and deployment procedure realistically, utilizing the Finite Element Analysis (FEA). The process initiates with the computation evaluation of the aortic structure in order to identify critical regions of stress and strain in an aneurysmatic aortic region. Then, a customized 3D-designed stent graft model was developed for the aorta and positioned properly. Applying all the necessary boundary conditions, a complex nonlinear FEA was conducted until the stent-graft expanded radially, reaching a final diameter 25% larger than the aorta’s vessel wall while withstanding mean stress and strain values close to 400 MPa and 1.5%, respectively. Finally, the mechanical behavior of the stent-graft and its interaction with the internal aortic wall, during the expansion process, was evaluated, and the extracted results were analyzed. Full article

Intracranial aneurysms are a serious cerebrovascular condition with a risk of subarachnoid hemorrhage due to rupture, leading to high mortality and morbidity. Flow Diverter Stents (FDSs) have become an important endovascular treatment option for unruptured large or wide-neck aneurysms. Hemodynamic factors significantly influence treatment outcomes in aneurysms treated with FDSs, and Computational Fluid Dynamics (CFD) has been widely used to evaluate post-deployment flow characteristics. However, conventional wire-resolved CFD methods require extremely fine meshes to reconstruct individual FDS wires, resulting in prohibitively high computational costs. This severely limits their feasibility for use in clinical treatment planning, where fast and robust simulations are essential. To address this limitation, we developed a computationally efficient CFD method that incorporates a porous media model accounting for local variations in wire density after FDS deployment. Based on Virtual Stent Simulation, the FDS region was defined as a hollow cylindrical domain with spatially varying resistance derived from cell-specific wire density. We validated the proposed method using 15 clinical cases, demonstrating close agreement with conventional wire-resolved CFD results. Relative errors in key hemodynamic parameters, including velocity, shear rate, inflow rate, and turnover time, were within 5%, with correlation coefficients exceeding 0.98. The number of grid elements, the data size, and total analysis time were reduced by over 90%. The method also allowed comparison between Total-Filling (OKM Grade A) and Occlusion (Grade D) cases, and evaluation of different FDS sizing, positioning, and coil-assisted strategies. The proposed method enables practical and efficient CFD analysis following FDS treatment and supports hemodynamics-based treatment planning of aneurysms. Full article

Background: The rapid shift from open to endovascular techniques in vascular surgery has significantly decreased trainee exposure to high-stakes open procedures. Simulation-based training, especially that incorporating virtual reality (VR) and artificial intelligence (AI), provides a promising way to bridge this skill gap. Objective: This narrative review aims to assess the current evidence on the integration of extended reality (XR) and AI into vascular surgeon training, focusing on technical skill development, performance evaluation, and educational results. Methods: We reviewed the literature on AI- and XR-enhanced surgical education across various specialties, focusing on validated cognitive learning theories, simulation methods, and procedure-specific training. This review covered studies on general, neurosurgical, orthopedic, and vascular procedures, along with recent systematic reviews and consensus statements. Results: VR-based training speeds up skill learning, reduces procedural mistakes, and enhances both technical and non-technical skills. AI-powered platforms provide real-time feedback, performance benchmarking, and objective skill evaluations. In vascular surgery, high-fidelity simulations have proven effective for training in carotid artery stenting, EVAR, rAAA management, and peripheral interventions. Patient-specific rehearsal, haptic feedback, and mixed-reality tools further improve realism and readiness. However, challenges like cost, data security, algorithmic bias, and the absence of long-term outcome data remain. Conclusions: XR and AI technologies are transforming vascular surgical education by providing scalable, evidence-based alternatives to traditional training methods. Future integration into curricula should focus on ethical use, thorough validation, and alignment with cognitive learning frameworks. A structured approach that combines VR, simulation, cadaver labs, and supervised practice may be the safest and most effective way to train the next generation of vascular surgeons. Full article

Cardiovascular diseases require fast and precise treatment, often involving angiography for diagnosis and intervention. However, training in angiographic procedures often entails exposure to ionizing radiation, which carries inherent risks. To reduce this exposure and enhance training realism, we developed AngioSim—a novel augmented-reality angiography simulation system combined with a vascular silicone simulator. This study evaluates the realism, effectiveness, and potential benefits of AngioSim for neurointerventional training. AngioSim was tested during neurointerventional training sessions with 24 physicians at RWTH Aachen University Hospital. Participants completed a questionnaire assessing realism, usefulness, and preferences compared to other simulators using a Likert scale. Responses were converted to binary categories and McNemar tests were applied for paired comparisons. A total of 92% of physicians rated guidewire and catheter visibility during fluoroscopy as sufficient, while 86% found RM and DSA simulations realistic. AngioSim was preferred over camera-based silicone simulators by 93%, and 96% of physicians rated it necessary for training—significantly more than other simulators (p < 0.05). These results demonstrate the high acceptance and perceived realism of the system and suggest that AngioSim offers advantages over existing training methods. AngioSim offers a realistic, cost-effective, and radiation-free training solution while maintaining the benefits of silicone models. It showed high utility for training purposes, making it a promising addition to neurointerventional programs. Full article

Background: CT image guidance and navigation, although routinely used in complex endovascular procedures, is an unexplored territory in evolving vascular robotic procedures. In robotic surgery, it promises the better localization of vasculature, the optimization of port placement, less inadvertent tissue damage, and increased patient safety during the dissection of retroperitoneal structures. However, unknown tissue displacement resulting from induced pneumoperitoneum and positional changes compared to the preoperative CT scan can pose significant limitations to the reliability of image guidance. We aimed to study the displacement of retroperitoneal organs and vasculature due to factors such as increased intra-abdominal pressure (IAP) due to CO₂ insufflation and patient positioning (PP) using intraoperative CT imaging in a cadaveric model. Methods: A thawed, fresh-frozen human cadaveric model was positioned according to simulated procedural workflows. Intra-arterial, contrast-enhanced CT scans were performed after the insertion of four laparoscopic ports in the abdomen. CT scans were performed with 0–5–15–25 mmHg IAPs in supine, left lateral decubitus, right lateral decubitus, Trendelenburg, and reverse Trendelenburg positions. Euclidean distances between fixed anatomical bony and retroperitoneal vascular landmarks were measured and compared across different CT scans. Results: Comparing the effects of various IAPs to the baseline (zero IAP) in the same PP, an average displacement for retroperitoneal vascular landmarks ranged from 0.6 to 3.0 mm (SD 1.0–2.8 mm). When changing the PPs while maintaining the same IAP, the average displacement of the retroperitoneal vasculature ranged from 2.0 to 15.0 mm (SD 1.7–7.2 mm). Conclusions: Our preliminary imaging findings from a single cadaveric model suggest minimal (~3 mm maximum) target vasculature displacement in the retroperitoneum due to elevated IAP in supine position and higher displacement due to changes in patient positioning. Similar imaging studies are needed to quantify procedural workflow-specific and anatomy-specific deformation, which would be invaluable in developing and validating advanced tissue deformation models, facilitating the routine applicability and usefulness of CT image guidance for target delineation during robotic vascular procedures. Full article

This study aimed to assess the clinical value of three-dimensional printed personalised vascular models (3DPPVMs) in assisting with the pre-operative planning and simulation of endovascular interventions. CT angiographic images of four cases, namely, abdominal aorta aneurysm (AAA), carotid artery stenosis, coronary artery stenosis, and renal artery stenosis, were selected, and 3DPPVMs were obtained. A total of 21 clinicians specialising in interventional radiology and vascular surgery were invited to participate in the study, comprising 6 radiologists and 15 vascular surgeons. Of these, 66.7% had not used a 3DPPVM prior to their participation. Considering all areas of experience and all four models, it was observed that 75% of the participants gave a ranking of 7 or above out of 10 with regard to the recommendation of the use of the 3DPPVMs. The mean scores of the participants’ ranking of the models ranged from 3.2 to 4.3 out of 5. The AAA model was ranked the highest for realism (4.10 ± 0.89, p = 0.002), the planning of interventions and simulations (3.90 ± 1.12 and 4.05 ± 0.95), the development of haptic skills (3.56 ± 0.98), reducing the procedure time (3.47 ± 1.12), and clarifying the pathology to patients (4.33 ± 0.69, p all >0.05), indicating consistency amongst the participants. The carotid artery model was ranked the highest for accurately displaying anatomical structures (4.3 ± 0.73). All the 3DPPVMs enhanced the understanding of the disease demonstrated, with rankings between 3.8 and 3.95. All the models aided in elucidating the intervention procedure required and in the planning of vascular interventions, with rankings of 3.5 and 3.9. The highest rankings were given by qualified clinicians with 8 or more years of experience. This study shows the potential value of using 3D-printed vascular models in education for clinicians and patients, as well as for clinical training and the pre-surgical simulation of endovascular stent-grafting procedures. Full article

Pathophysiological conditions in arteries, such as stenosis or aneurysms, have a great impact on blood flow dynamics enforcing the numerical study of such pathologies. Computational fluid dynamics (CFD) could provide the means for the calculation and interpretation of pressure and velocity fields, wall stresses, and important biomedical factors in such pathologies. Additionally, most of these pathological conditions are connected with geometric vessel changes. In this study, the numerical solution of the 2D flow in a branching artery and a multiscale model of 3D flow are presented utilizing CFD. In the 3D case, a multiscale approach (3D and 0D–1D) is pursued, in which a dynamically altered velocity parabolic profile is applied at the inlet of the geometry. The obtained waveforms are derived from a 0D–1D mathematical model of the entire arterial tree. The geometries of interest are patient-specific 3D reconstructed abdominal aortic aneurysms after fenestrated (FEVAR) and branched endovascular aneurysm repair (BEVAR). Critical hemodynamic parameters such as velocity, wall shear stress, time averaged wall shear stress, and local normalized helicity are presented, evaluated, and compared. Full article

Background/Objectives: Intracranial arteriovenous malformations (AVMs) exhibit a complex vasculature characterized by a locally occurring tangled nidus connecting the arterial and venous system bypassing the capillary network. Clinically available imaging modalities may not give sufficient spatial or temporal resolution. Adequate 3D models of large vascular areas and a detailed blood flow analysis of the nidus including the surrounding vessels are not available yet. Methods: Three representative AVM cases containing multimodal image data (3D rotational angiography, magnetic resonance angiography, magnetic resonance venography, and phase-contrast quantitative magnetic resonance imaging) are investigated. Image segmentation results in partial 3D models of the different vascular segments, which are merged into large-scale neurovascular models. Subsequently, image-based blood flow simulations are conducted based on the segmented models using patient-specific flow measurements as boundary conditions. Results: The segmentation results provide comprehensive 3D models of the overall arteriovenous morphology including realistic nidus vessels. The qualitative results of the hemodynamic simulations show realistic flow behavior in the complex vasculature. Feeding arteries exhibit increased wall shear stress (WSS) and higher flow velocities in two cases compared to contralateral vessels. In addition, feeding arteries are exposed to higher overall WSS with increased value variation between individual vessels (20.1 Pa ± 17.3 Pa) compared to the draining veins having a 62% lower WSS (8.9 Pa ± 5.9 Pa). Blood flow distribution is dragged towards the dominating circulation side feeding the nidus for all the cases quantified by the volume flow direction changes in the posterior communicating arteries. Conclusions: This multimodal study demonstrates the feasibility of the presented workflow to acquire detailed blood flow predictions in large-scale AVM models based on complex image data. The hemodynamic models serve as a base for endovascular treatment modeling influencing flow patterns in distally located vasculatures. Full article