Micromechanical and Ultrastructural Properties of Abdominal Aortic Aneurysms

Abdominal aortic aneurysms are a common condition of uncertain pathogenesis that can rupture if left untreated. Current recommended thresholds for planned repair are empirical and based entirely on diameter. It has been observed that some aneurysms rupture before reaching the threshold for repair whilst other larger aneurysms do not rupture. It is likely that geometry is not the only factor influencing rupture risk. Biomechanical indices aiming to improve and personalise rupture risk prediction require, amongst other things, knowledge of the material properties of the tissue and realistic constitutive models. These depend on the composition and organisation of the vessel wall which has been shown to undergo drastic changes with aneurysmal degeneration, with loss of elastin, smooth muscle cells, and an accumulation of isotropically arranged collagen. Most aneurysms are lined with intraluminal thrombus, which has an uncertain effect on the underlying vessel wall, with some authors demonstrating a reduction in wall stress and others a reduction in wall strength. The majority of studies investigating biomechanical properties of ex vivo abdominal aortic aneurysm tissues have used low-resolution techniques, such as tensile testing, able to measure the global material properties at the macroscale. High-resolution engineering techniques such as nanoindentation and atomic force microscopy have been modified for use in soft biological tissues and applied to vascular tissues with promising results. These techniques have the potential to advance the understanding and improve the management of abdominal aortic aneurysmal disease.

3D Printing in Modern Cardiology

BACKGROUND

3D printing represents an emerging technology in the field of cardiovascular medicine. 3D printing can help to perform a better analysis of complex anatomies to optimize intervention planning.

METHODS

A systematic review was performed to illustrate the 3D printing technology and to describe the workflow to obtain 3D printed models from patient-specific images. Examples from our laboratory of the benefit of 3D printing in planning interventions were also reported.

RESULTS

3D printing technique is reliable when applied to high-quality 3D image data (CTA, CMR, 3D echography), but it still needs the involvement of expert operators for image segmentation and mesh refinement. 3D printed models could be useful in interventional planning, although prospective studies with comprehensive and clinically meaningful endpoints are required to demonstrate the clinical utility.

CONCLUSION

3D printing can be used to improve anatomy understanding and surgical planning.

Modeling biomechanical interaction between soft tissue and soft robotic instruments: importance of constitutive anisotropic hyperelastic formulations

Cardiovascular diseases are the leading cause of death in the western countries. Robotic surgery recently emerged as a confirmed strategy in the cardiovascular field, especially thanks to the improvement of soft robotics. These techniques have demonstrated their potential in terms of speed of execution and precision. In this context, a deeper knowledge of the material properties of the blood vessels is required, especially for computational soft robotics applications. A constitutive model including the contribution of the collagen fibers families is needed to take hyperelasticity and anisotropy into account. For this purpose, four different models are presented: two fiber families with dispersion (2FFD), two fiber families without dispersion (2FF), four fiber families with dispersion (4FFD), and four fiber families without dispersion (4FF). A set of experimental biaxial data obtained from ex-vivo specimens was used to assess the model performances. Two fitting procedures were imposed: a procedure with no weighting of scores and a procedure with a weight set to enhance the model performances in the contact range. A finite element simulation of a contact procedure was developed to evaluate the effect on the contact pressures and forces according to the different model implementations. In particular, a minimally invasive aortic valve positioning process through a previously designed soft robot was simulated. The results confirmed the overall fitting procedure. The adoption of the weighting process for the fitting was successful, as it permitted an accurate prediction in the region of interest through models with less parameters.