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Updated: Jan 23, 2026

A New Murine Model of Endovascular Aortic Aneurysm Repair
Published on: July 7, 2013
Simulation of Endovascular Aortic Repair Using 3D Printed Abdominal Aortic Aneurysm Model and Fluid Pump
Jussi M Kärkkäinen1, Giuliano Sandri1, Emanuel R Tenorio1
1Mayo Clinic Aortic Center, Advanced Endovascular Aortic Research Program, Division of Vascular and Endovascular Surgery, Mayo Clinic, Rochester, MN, USA.
Background:
Abdominal aortic aneurysm (AAA) models can be manufactured with 3D printing technology. This study describes detailed methodology and validation of endovascular aortic repair (EVAR) simulation using 3D printed AAA model connected to hemodynamic pump.
Method:
The AAA model was printed with Objet500 Connex3 (Stratasys, Eden Prairie, MN) and connected to BDC PD-0500 fluid pump (BDC Laboratories, Wheat Ridge, CO). EVAR procedure metrics were benchmarked in two expert implanters and compared to 20 vascular surgical trainees with different levels of EVAR experience (< 20 or ≥ 20 cases). All simulations were performed using commercially available stent grafts, guidewires, catheters, fluoroscopic guidance and digital subtraction angiography. Studied outcomes included ability to complete the procedure independently, time to deploy aortic component, ability to cannulate contralateral gate and complete the repair, and total fluoroscopy and procedure times.
Results:
A total of 22 EVAR simulation procedures were performed with mean procedure time of 37 ± 12 min. Experienced trainees had significantly lower total procedural time (32 ± 9 vs. 44 ± 6 min, P = 0.003) and fluoroscopic time (13 ± 5 vs. 23 ± 8 min, P = 0.005). All experienced trainees completed the procedure independently in < 45 min, compared to six (46%) of those with less EVAR experience (P = 0.016). Among less experienced trainees, only two (15%) completed the entire procedure independently (P < 0.001). Benchmark implanters performed significantly better than both trainee groups in nearly all EVAR metrics.
Conclusion:
EVAR simulation was feasible and simulated all procedural steps with high fidelity. This model may be applicable for assessment of technical competencies and standard endovascular skill acquisition within vascular surgery training curricula.
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