Hypothesis and Significance: Specific and consistent fluid dynamic patterns and drag forces magnitude and distribution can be identified in the PLZs of the aortic arch providing valuable insights for proper PLZ and stent-graft selection during TEVAR planning.

Specific Aim: 1) To assess the drag forces acting on different PLZs of the aortic arch by means of Computed Fluid Dynamic (CFD) analysis of preoperative phase contrast-Magnetic Resonance (pc-MRI) and Computed Tomography Angiography (CTA) images. The specific goal is to identify the correlation between different magnitude and direction of migration forces and geometrical patterns of the arch to identify suboptimal landing zones for stent-graft deployment. 2) To develop and perform in-silico simulations of the deployment of different commercially available endografts with patient specific boundary conditions. The exact goal is to assess the impact of the mechanical characteristics of a specific device on the vessel wall by structural finite element analysis (FEA), and on the drag forces in different landing zones by CFD, to identify the more suitable endograft. 3) To assess the drag forces exerted postoperatively on the endograft by means of CFD analysis based on follow-up images (i.e., pc-MRI and CTA). The specific goal is to evaluate the predictive value of the drag forces measured preoperatively in the PLZs, and validate the results from in-silico simulations.

Experimental Design Aim 1: Preoperative medical images acquisition: CTA will be performed using a 16-slice unit (150 mAs, 110 kVp; acquisition thickness 5 mm, pitch 1.5; reconstruction thickness 1.2 mm), before and after intravenous administration of 100 mL of iodinated contrast material. MRI will be performed using a 1.5-T unit with 40-mT/m gradient power (Magneton Sonata Maestro Class, Siemens, Erlangen, Germany) and a four-channel cardio-thoracic coil. ECG-triggered, free-breathing through plane, and in-plane pc-MRI sequences will be performed for phase-velocity mapping of aortic and branches flow with the following technical parameters: TR/TE = 4/3.2 ms, thickness 5 mm, velocity encoding from 150 to 350 ms, and temporal resolution 41 ms.

Medical images processing: Ad hoc processing of preoperative CTAs, based on 3D multiplanar reconstruction, will be performed with 3Mensio Vascular software 8.0® (3Mensio Medical Imaging B.V.), which provides specific functions for automatic measurements. Patients will be stratified according to Aortic Arches Classification (AAC). Radius of curvature, PLZs angulation (tangent angle function) and tortuosity (tortuosity angle function) will be calculated. 3D segmentation of CTA, aimed for in-silico simulation purposes, will be performed by the software Mimics v18.0 (Materialise, Belgium). The 3D model of the aortic lumen in stl format will be used to create CFD suitable computational domain, called mesh by vmtk toolkit (www.vmtk.org). In-silico simulations: State-of-the-art CFD simulations for aortic hemodynamics will be performed by the CFD solver developed by the project EmPaTHIC (Emory Pavia Testing Hemodynamics) that updates LifeV Application Blood Flow through the collaboration among Emory University, Atlanta,Georgia,USA (Prof. A. Veneziani) and University of Pavia (UniPV) (Prof. F. Auricchio). The analysis will run on the cluster available at UniPV Nume-Lab. The project foresees to increase the computational power by adding another node to the available UniPV cluster and also the set-up of a server at Policlinico San Donato (PSD) dedicated to data storage and visualization of the results. Computation of drag forces: The post-processing of the simulations will be performed by python-scripts based on Visualization Toolkit (VTK) libraries and ParaView software (Kitware® Inc., France). Such an analysis aims at computing semi-automatically the aortic centerline, splitting the aortic arch in four regions (i.e., landing zones), and calculating the magnitude and direction of the drag forces in each zone, through the whole cardiac cycle. Preliminary analysis will be performed to assess if the systolic peak is the most relevant time instant for our purposes, in order to possibly reduce the post-processing efforts.

Experimental Design Aim 2: Medical images acquisition: The pre-operative images acquired for Aim 1 will be used. Medical images processing: The 3D models of the aortic lumen derived from the processing performed for Aim 1 will be used. In-silico simulations, Two types of analysis will be performed: 1) Simulation of TEVAR by FEA to predict endograft apposition; 2) CFD analysis to compute post-TEVAR hemodynamics. These simulations will be performed in a serial manner defining a computational framework, which is already developed and tested. FEA of TEVAR: As previously reported by our Group, the geometrical models of the implanted endografts resemble the main features of real endografts samples; mechanical properties are derived from available literature. ABAQUSv16 (Simulia, Dassault Systèmes®, FR) is used as FEA solver. CFD for post- TEVAR hemodynamics: Starting from the configuration of the endograft predicted by the FEA, the computational domain, resembling the aorta with the endovascular implant, is build using image-distance technique. The analysis is then run as described in Aim 1. Computation of drag forces: As described in Aim 1, the developed post-processing tool will be used to compute the magnitude and direction of the drag forces along the arch, and also on the inner surface of the deployed endograft.

Experimental Design Aim 3: Postoperative medical images acquisition: CTA and MRI studies and ad-hoc analysis of the images will be performed at 6-month follow-up in recruited patients as described in Aim 1. In-silico simulations: CFD analyses will be performed as described in Aim 1. Medical images processing: The same approach and the same tools proposed in Aim 1 will be used. Segmentation of post-operative CTA will be performed to reconstruct a 3D model of the aortic lumen and of the struts of the deployed endografts. Computation of drag forces and validation: As in Aim 1, 3D segmentation of post-operative CTA combined with flow data from pc-MRI will be used to run CFD analysis in order to: 1) Assess the predictive value of the drag forces measured preoperatively (Aim 1); 2) Validate the results from in-silico simulations (Aim 2).