Biomechanical properties of 3D printable material usable for synthetic personalized healthy human aorta.

With the development of three-dimensional (3D) printing, 3D-printed products have been widely used in medical fields, such as plastic surgery, orthopedics, dentistry, etc. In cardiovascular research, 3D-printed models are becoming more realistic in shape. However, from a biomechanical point of view, only a few studies have explored printable materials that can represent the properties of the human aorta. This study focuses on 3D-printed materials that might simulate the stiffness of human aortic tissue. First, the biomechanical properties of a healthy human aorta were defined and used as reference. The main objective of this study was to identify 3D printable materials that possess similar properties to the human aorta. Three synthetic materials, NinjaFlex (Fenner Inc., Manheim, USA), FilasticTM (Filastic Inc., Jardim Paulistano, Brazil), and RGD450+TangoPlus (Stratasys Ltd.©, Rehovot, Israel), were printed in different thicknesses. Uniaxial and biaxial tensile tests were performed to compute several biomechanical properties, such as thickness, stress, strain, and stiffness. We found that with the mixed material RGD450+TangoPlus, it was possible to achieve a similar stiffness to healthy human aorta. Moreover, the 50-shore-hardness RGD450+TangoPlus had similar thickness and stiffness to the human aorta.

Use of Numerical Simulation to Predict Iliac Complications During Placement of An Aortic Stent Graft.

BACKGROUND: During endovascular aneurysm repair (EVAR), complex iliac anatomy is a source of complications such as unintentional coverage of the hypogastric artery. The aim of our study was to evaluate ability to predict coverage of the hypogastric artery using a biomechanical model simulating arterial deformations caused by the delivery system. METHODS: The biomechanical model of deformation has been validated by many publications. The simulations were performed on 38 patients included retrospectively, for a total of 75 iliac arteries used for the study. On the basis of objective measurements, two groups were formed: one with "complex" iliac anatomy (n = 38 iliac arteries) and the other with "simple" iliac anatomy (n = 37 iliac arteries). The simulation enabled measurement of the lengths of the aorta and the iliac arteries once deformed by the device. Coverage of the hypogastric artery was predicted if the deformed renal/iliac bifurcation length (Lpre) was less than the length of the implanted device (Lstent-measured on the postoperative computed tomography [CT]) and nondeformed Lpre was greater than Lstent. RESULTS: Nine (12%) internal iliac arteries were covered unintentionally. Of the coverage attributed to perioperative deformations, 1 case (1.3%) occurred with simple anatomy and 6 (8.0%) with complex anatomy (P = 0.25). All cases of unintentional coverage were predicted by the simulation. The simulation predicted hypogastric coverage in 35 cases (46.7%). There were therefore 26 (34.6%) false positives. The simulation had a sensitivity of 100% and a specificity of 60.6%. On multivariate analysis, the factors significantly predictive of coverage were the iliac tortuosity index (P = 0.02) and the predicted margin between the termination of the graft limb and the origin of the hypogastric artery in nondeformed (P = 0.009) and deformed (P = 0.001) anatomy. CONCLUSIONS: Numerical simulation is a sensitive tool for predicting the risk of hypogastric coverage during EVAR and allows more precise preoperative sizing. Its specificity is liable to be improved by using a larger cohort.

Identification of Parameters Influencing the Vascular Structure Displacement in Fusion Imaging during Endovascular Aneurysm Repair.

PURPOSE: To quantify the displacement of the vascular structures after insertion of stiff devices during endovascular aneurysm repair (EVAR) of abdominal aortic aneurysm and to identify potential parameters influencing this displacement. MATERIALS AND METHODS: A total of 50 patients from a single center undergoing EVAR were prospectively enrolled between January 2016 and December 2017. Fusion imaging was employed using the EndoNaut (Therenva, Rennnes, France) station through a 3-dimensional (3D)/2-dimensional (2D) technology synchronizing the 3D computed tomography scan to the live intraoperative fluoroscopy. The accuracy of the fusion roadmap was evaluated before deployment by conventional digital subtraction angiogram on a single plane (with different C-arm incidences). RESULTS: The mean displacement error of the ostium of the lowest renal artery was 4.1 ± 2.4 mm (range, 0-11.7 mm), with a left/right displacement of 1.6 ± 1.7 mm (range, 0-6.9 mm) and a craniocaudal displacement of 3.5 ± 2.4 mm (range, 0-11.3 mm). The correction required for the ostium of the lower renal artery was mostly cranial and to the left. Multiple linear regression analysis revealed only the sharpest angle between the aneurysm neck and sac as the factor influencing the accuracy of fusion imaging. All other parameters did not show any correlation. CONCLUSIONS: This study identified the sources of fusion error after insertion of rigid material during EVAR. As the sharpest angulation between aneurysm neck and sac increases, the overall accuracy of the fusion might be affected.