Vascular remodeling after endovascular treatment: quantitative analysis of medical images with a focus on aorta

In the last years, the convergence of advanced imaging techniques and endovascular procedures has revolutionized the practice of vascular surgery. However, regardless the anatomical district, several complications still occur after endovascular treatment and the impact of endovascular repair on vessel morphology remains unclear. Starting from this background, the aim of this thesis is to ll the gaps in the eld of vessel remodeling after endovascular procedure. Main focus of the work will be the repair of the aorta and, in particular thoracic and thoracoabdominal treatments. Furthermore an investigation of the impact of endovascular repair on femoro-popliteal arterial segment will be reported in the present work. Analyses of medical images will been conducted to extract anatomical geometric features and to compare the changes in morphology before treatment and during follow-up. After illustrating in detail the aims and the outline of the dissertation in Chapter 1, Chapter 2 will concern the anatomy and the physiology of the aorta along with the main aortic pathologies and the related surgical treatments. Subsequently, an overview of the medical image techniques for segmentation and vessel geometric quantication will be provided. Chapter 3 will introduce the concept of remodeling of the aorta after endovascular procedure. In particular, two types of aortic remodeling will be considered. On one side remodeling can be seen as the shrinkage of the aneurysmal sac or false lumen thrombosis. On the other side, aortic remodeling could be seen as the changes in the aortic morphology following endograft placement which could lead to complications. Chapter 4 will illustrate a study regarding the analysis of medical images to measure the geometrical changes in the pathological aorta during follow-up in patients with thoracoabdominal aortic aneurysms treated with endovascular procedure using a novel uncovered device, the Cardiatis Multilayer Flow Modulator. Chapter 5 will focus on the geometrical remodeling of the aortic arch and descending aorta in patients who underwent hybrid arch treatment to treat thoracic aneurysms. The goal of the work is to develop a pipeline for the processing of pre-operative and post-operative Computed Tomography images in order to detect the changes in the aortic arch physiological curvature due to endograft insertion. Chapter 6 will focuse on the use of 3D printing technology as valuable tool to support patient's follow-up. In particular, we report a case of a patient originally treated with endovascular procedure for type B aortic dissection and which experimented several complications during follow-up. 3D printing technology is used to show the remodeling of the aortic vasculature during time. Chapter 7 will concern patient-specic nite element simulations of aortic endovascular procedure. In particular, starting from a clinical case where complication developed during followup, the predictive value of computational simulations will be shown. Chapter 8 will illustrate a study concerning the evaluation of morphological changes of the femoro-popliteal arterial segment due to limb exion in patients undergoing endovascular treatment of popliteal artery aneurysms

Optimization of CT scanning protocol of Type B aortic dissection follow-up through 3D printed model

This research aims to develop and evaluate a human tissue-like material 3D printed model used as a phantom in determining optimized scanning parameters to reduce the radiation dose for Type B aortic dissection patients after thoracic endovascular aortic repair. The results show that radiation risk for follow-up Type B aortic dissection patients can be potentially reduced. Further, the value of using 3D printed model in studying CT scanning protocols was further validated

Multi-stage learning for segmentation of aortic dissections using a prior aortic anatomy simplification

Aortic dissection (AD) is a life-threatening cardiovascular disease with a high mortality rate. The accurate and generalized 3-D reconstruction of AD from CT-angiography can effectively assist clinical procedures and surgery plans, however, is clinically unavaliable due to the lacking of efficient tools. In this study, we presented a novel multi-stage segmentation framework for type B AD to extract true lumen (TL), false lumen (FL) and all branches (BR) as different classes. Two cascaded neural networks were used to segment the aortic trunk and branches and to separate the dual lumen, respectively. An aortic straightening method was designed based on the prior vascular anatomy of AD, simplifying the curved aortic shape before the second network. The straightening-based method achieved the mean Dice scores of 0.96, 0.95 and 0.89 for TL, FL, and BR on a multi-center dataset involving 120 patients, outperforming the end-to-end multi-class methods and the multi-stage methods without straightening on the dual-lumen segmentation, even using different network architectures. Both the global volumetric features of the aorta and the local characteristics of the primary tear could be better identified and quantified based on the straightening. Comparing to previous deep learning methods dealing with AD segmentations, the proposed framework presented advantages in segmentation accuracy

Modeling of Intraluminal Surfaces of Thoracic Aortas

Vascular diseases are getting more and more common as a result of modern-day lifestyle and the fact that the population is getting older. One of the newest treatments for vascular diseases such as aneurysms and dissections is endovascular repair with endografting. This treatment uses a fabric covered metallic structure that is implanted using a minimally invasive approach to serve as an artificial vessel in a damaged region. To ensure that the interventions are successful, the endograft must be placed in the correct location, and be designed to sustain the hostile biological, chemical, and mechanical conditions in the body for many years.To accurately describe the complex mechanical conditions of the intraluminal surfaces of diseased blood vessels inside the body, this thesis presented a segmentation and quantification methodology for a natural and intuitive vessel surface description. The thesis also included some important clinical applications, all based on non-invasive temporal imaging. The results emphasized the need for explicit surface curvature quantification, as compared to relying solely on centerline curvature and estimation methods. Methods for preoperative prediction of endograft malapposition severity based on geometric analysis of thoracic aortic surfaces were introduced. Finally, a multiaxial dynamic analysis of cardiac induced thoracic aortic surface deformation showed how a thoracic endovascular aortic repair is a↵ecting the deformations of the thoracic aorta.Thus, the work presented in this thesis contributes by giving surgeons a tool to use in their treatment planning to minimize complications. Moreover, this method provides more nuanced boundary conditions so that endograft manufacturers can improve their designs to improve the quality of life for the treated patients

Geometric Modeling of Thoracic Aortic Surface Morphology - Implications for Pathophysiology and Clinical Interventions

Vascular disease risk factors such as hypertension, hyperlipidemia and old age are all\ua0results of modern-day lifestyle, and these diseases are getting more and more common. One\ua0treatment option for vascular diseases such as aneurysms and dissections is endovascular\ua0aortic repair introduced in the early 1990s. This treatment uses tubular fabric covered\ua0metallic structures (endografts) that are implanted using a minimally invasive approach\ua0and placed to serve as an articial vessel in a damaged portion of the vasculature. To ensure\ua0that the interventions are successful, the endograft must be placed in the correct location,\ua0and designed to sustain the hostile biological, chemical, and mechanical conditions in the\ua0body for many years. This is an interaction that goes both ways, and keeping in mind\ua0that the endograft is a foreign object placed in the sensitive vascular system, it is also\ua0important that it does not disrupt the native conditions more than necessary.This thesis presents a segmentation and quantication methodology to accurately\ua0describe the complex morphology and motion of diseased blood vessels in vivo through a\ua0natural and intuitive description of their luminal surfaces. After methodology validation,\ua0a series of important clinical applications are performed, all based on non-invasive imaging.\ua0Firstly, it is shown that explicit surface curvature quantication is necessary when\ua0compared to relying solely on centerline curvature and estimation methods. Secondly, it is\ua0shown that endograft malapposition severity can be predicted from preoperative geometric\ua0analysis of thoracic aortic surfaces. Thirdly, a multiaxial dynamics analysis of cardiac\ua0induced thoracic aortic surface motion shows how thoracic endovascular aortic repair\ua0affects the deformations of the dierent portions of the thoracic aorta. Fourthly, the helical\ua0propagation pattern of type B aortic dissection is determined, and two distinct modes of\ua0chirality are revealed, i.e., achiral and right-handed chiral groups. Finally, the effects of\ua0thoracic endovascular aortic repair on helical and cross-sectional morphology of type B\ua0dissections are investigated revealing how acuity and chirality affects the alteration due to\ua0intraluminal lining with endografts. Thus, the work presented in this thesis contributes\ua0by adding knowledge about pathology and pathophysiology through better geometric\ua0description of surface conditions of diseased thoracic aortas. This gives clinicians insights\ua0to use in their treatment planning and provides more nuanced boundary conditions for\ua0endograft manufacturers. Comprehensive knowledge about diseases, better treatment\ua0planning, and better devices are all crucial in order to improve the outcomes of performed\ua0interventions and ultimately the quality of life for the treated patients

Automatic Aorta Segmentation with Heavily Augmented, High-Resolution 3-D ResUNet: Contribution to the SEG.A Challenge

Automatic aorta segmentation from 3-D medical volumes is an important yet difficult task. Several factors make the problem challenging, e.g. the possibility of aortic dissection or the difficulty with segmenting and annotating the small branches. This work presents a contribution by the MedGIFT team to the SEG.A challenge organized during the MICCAI 2023 conference. We propose a fully automated algorithm based on deep encoder-decoder architecture. The main assumption behind our work is that data preprocessing and augmentation are much more important than the deep architecture, especially in low data regimes. Therefore, the solution is based on a variant of traditional convolutional U-Net. The proposed solution achieved a Dice score above 0.9 for all testing cases with the highest stability among all participants. The method scored 1st, 4th, and 3rd in terms of the clinical evaluation, quantitative results, and volumetric meshing quality, respectively. We freely release the source code, pretrained model, and provide access to the algorithm on the Grand-Challenge platform.Comment: MICCAI 2023 - SEG.A Challenge Contributio

Multiaxial pulsatile dynamics of the thoracic aorta and impact of thoracic endovascular repair

Purpose: The thoracic aorta is a highly mobile organ whose dynamics are altered by thoracic endovascular aorta repair (TEVAR). The aim of this study was to quantify cardiac pulsatility-induced multi-axial deformation of the thoracic aorta before and after descending aortic TEVAR. Methods: Eleven TEVAR patients (8 males and 3 females, age 57–89) underwent retrospective cardiac-gated CT angiography before and after TEVAR. 3D geometric models of the thoracic aorta were constructed, and lumen centerlines, inner and outer surface curves, and cross-sections were extracted to measure aortic arclength, centerline, inner surface, and outer surface longitudinal curvatures, as well as cross-sectional effective diameter and eccentricity for the ascending and stented aortic portions. Results: From pre- to post-TEVAR, arclength deformation was increased at the ascending aorta from 5.9 \ub1 3.1 % to 8.8 \ub1 4.4 % (P < 0.05), and decreased at the stented aorta from 7.5 \ub1 5.1 % to 2.7 \ub1 2.5 % (P < 0.05). Longitudinal curvature and diametric deformations were reduced at the stented aorta. Centerline curvature, inner surface curvature, and cross-sectional eccentricity deformations were increased at the distal ascending aorta. Conclusions: Deformations were reduced in the stented thoracic aorta after TEVAR, but increased in the ascending aorta near the aortic arch, possibly as a compensatory mechanism to maintain overall thoracic compliance in the presence of reduced deformation in the stiffened stented aorta