Abdominal Aortic Aneurysm Clinical Issues

Model:Abdominal Aortic Aneurysm(Silicone model) (FBD015)

Abdominal aortic aneurysm is defined as an aortic diameter greater than 3 cm. Predisposing factors include advanced age, family history, past or current smoking, hypercholesterolemia, and hypertension; diabetes mellitus is associated with a decreased risk. The major risk is the risk of death from rupture and hemorrhage. Therefore, the goal of treatment is to repair the aneurysm before rupture. Although several factors influence the timing and type of repair, the most important predictor of rupture is the diameter of the aneurysm, with the larger the aneurysm, the greater the risk. Treatment of abdominal aortic aneurysms recommends repair for men with aneurysms 5.5 cm or greater in maximum diameter and for women with aneurysms 5.0 cm or greater in maximum diameter.

The results of randomized controlled trials have shown that endovascular aortic aneurysm repair (EVAR) is associated with a lower risk of perioperative complications and mortality than open surgical repair. The early advantage of EVAR over open surgery lasts an average of 2 to 3 years from the date of the procedure. There is no long-term advantage in survival. Although EVAR is associated with a higher risk of reintervention, most such interventions involve minor endovascular procedures. Open repair is associated with a higher risk of reintervention over the patient's lifetime than laparotomy. Long-term imaging surveillance with duplex ultrasound or computed tomography angiography is recommended for patients undergoing EVAR.

The model is a typical giant fusiform abdominal aneurysm, three times larger than a healthy abdominal aorta. The model belongs to the infrarenal type of abdominal aortic aneurysm, which accounts for more than 90% of the total cases. The left iliac artery is also enlarged due to the aneurysm, and this structure has an incidence of 10-20% in the abdominal aortic aneurysm patient population.The model is 3D printed from angiography and CT data for testing, training, and demonstration.