## 1 Introduction  
The challenges associated with diagnosing and treating vascular disease are many and diverse. The complexity of and variation in each patient's anatomy and morphology, the tortuosity of access vessels, and hostile environments (such as thrombus and calcification deposition in blood vessels) make intervention multifaceted and risky. The current practice of endovascular aortic repair (EVAR) relies on two-dimensional (2D) and three-dimensional (3D) CT imaging visualisations, and these meet most of the current requirements for the planning of EVAR. However, they do not provide a realistic 3D representation of the relationship between complex vascular diseases and anatomical structures [1]. The implementation of 3D printing technology to produce patient-specific or personalised models has the potential to overcome the limitations of the currently used 2D and 3D visualisations, owing to its superiority in producing realistic 3D models of anatomical structures in relation to pathology. It is purported that clinician skills can be optimised when 3D-printed models are introduced for training and procedural simulation [2]. Three-dimensional-printed cardiac models have been produced for teaching anaesthetic residents and fellows anatomy and pathology and for planning surgical interventions [3], while 3D-printed personalised vascular models (3 DPPVMs) have been utilised for the pre-surgical planning and simulation of EVAR [4; 5; 6; 7]. Previous studies have demonstrated the utility and clinical value of 3 DPPVMs in vascular conditions, including aneurysm, dissection, extremity vascular disease, and other arterial diseases [2; 3; 4; 5; 8; 9; 10; 11; 12; 13]. In a recent systematic and meta-analysis, [PERSON] et al. analysed 107 studies with regard to the use of 3D-printed models in patient education, simulation, training, and procedural planning for cardiovascular interventions [14]. Most of the 3D-printed models were used in congenital heart disease (38 studies), left atrial appendage occlusion (11 studies), and aortic disease (10 studies). Of these 10 studies, the use of 3D-printed models was found to change the decision making in 20% of cases in patients with aortic aneurysm when compared to reviewing standard CT images [15]; reduce the fluoroscopy and intervention times (by 30% and 29%, respectively); and reduce the contrast medium (by 25%) in the training of residents in EVAR [16]. The current evidence confirms the accuracy, reliability, and potential clinical value of 3D-printed models in aortic and other vascular diseases, although further evidence is needed to support broader applications of 3D-printed vascular models. There is a paradigm shift in surgical training, as it is moving from traditional methods to simulation-based approaches, with the aim of developing more effective learning environments. With the advancement of the materials used in 3D printing, it is possible to produce models with \"tissue-mimicking properties\" [17], which further enhances the applications of 3D printing technology in the cardiovascular field. [PERSON] et al. [4] developed a personalised 3D-printed aortic dissection model and tested different materials. Their results showed that Agilus A30 had a tensile strength similar to normal human aortic tissue, with similar CT attenuation on both non-contrast and contrast-enhanced CT scans of aortic dissection. This prompted us to use this material to produce 3 DPPVMs in our study, as we aimed to produce realistic vascular models for education and simulation purposes. Our study aimed to address the research gap by including common vascular diseases, such as aortic, carotid, coronary, and renal arterial diseases, with the development of corresponding 3D-printed models, as most previous studies are based on either isolated case reports or case series or a particular anatomical vascular region [14].