Vascular Segmentation Algorithms for Generating 3D Atherosclerotic Measurements

Atherosclerosis manifests as plaques within large arteries of the body and remains as a leading cause of mortality and morbidity in the world. Major cardiovascular events may occur in patients without known preexisting symptoms, thus it is important to monitor progression and regression of the plaque burden in the arteries for evaluating patient\u27s response to therapy. In this dissertation, our main focus is quantification of plaque burden from the carotid and femoral arteries, which are major sites for plaque formation, and are straight forward to image noninvasively due to their superficial location. Recently, 3D measurements of plaque burden have shown to be more sensitive to the changes of plaque burden than one-/two-dimensional measurements. However, despite the advancements of 3D noninvasive imaging technology with rapid acquisition capabilities, and the high sensitivity of the 3D plaque measurements of plaque burden, they are still not widely used due to the inordinate amount of time and effort required to delineate artery walls plus plaque boundaries to obtain 3D measurements from the images. Therefore, the objective of this dissertation is developing novel semi-automated segmentation methods to alleviate measurement burden from the observer for segmentation of the outer wall and lumen boundaries from: (1) 3D carotid ultrasound (US) images, (2) 3D carotid black-blood magnetic resonance (MR) images, and (3) 3D femoral black-blood MR images. Segmentation of the carotid lumen and outer wall from 3DUS images is a challenging task due to low image contrast, for which no method has been previously reported. Initially, we developed a 2D slice-wise segmentation algorithm based on the level set method, which was then extended to 3D. The 3D algorithm required fewer user interactions than manual delineation and the 2D method. The algorithm reduced user time by ≈79% (1.72 vs. 8.3 min) compared to manual segmentation for generating 3D-based measurements with high accuracy (Dice similarity coefficient (DSC)\u3e90%). Secondly, we developed a novel 3D multi-region segmentation algorithm, which simultaneously delineates both the carotid lumen and outer wall surfaces from MR images by evolving two coupled surfaces using a convex max-flow-based technique. The algorithm required user interaction only on a single transverse slice of the 3D image for generating 3D surfaces of the lumen and outer wall. The algorithm was parallelized using graphics processing units (GPU) to increase computational speed, thus reducing user time by 93% (0.78 vs. 12 min) compared to manual segmentation. Moreover, the algorithm yielded high accuracy (DSC \u3e 90%) and high precision (intra-observer CV \u3c 5.6% and inter-observer CV \u3c 6.6%). Finally, we developed and validated an algorithm based on convex max-flow formulation to segment the femoral arteries that enforces a tubular shape prior and an inter-surface consistency of the outer wall and lumen to maintain a minimum separation distance between the two surfaces. The algorithm required the observer to choose only about 11 points on its medial axis of the artery to yield the 3D surfaces of the lumen and outer wall, which reduced the operator time by 97% (1.8 vs. 70-80 min) compared to manual segmentation. Furthermore, the proposed algorithm reported DSC greater than 85% and small intra-observer variability (CV ≈ 6.69%). In conclusion, the development of robust semi-automated algorithms for generating 3D measurements of plaque burden may accelerate translation of 3D measurements to clinical trials and subsequently to clinical care

Continuous convex relaxation methodology applied to retroperitoneal tumors

In this paper, two algorithms for the segmentation of tumors in soft tissues are presented and compared. These algorithms are applied to the segmentatiion of retroperitoneal tumors. Method: The algorithms are based on a continuous convex relaxation methodology with the introduction of an accumulated gradient distance (AGD). Algorithm 1 is based on two-label convex relaxation and Algorithm 2 applies multilabel convex relaxation. Results: Algorithms 1 and 2 are tested on a database of 6 CT volumes and their results are compared with the manual segmentation. The multilabel version performs better, achieving a 91% of sensitivity, 100% of specificity, 88% of PPV and 89% of Dice index. Conclusions: To the best of our knowledge, this is the first time that the segmentation of retroperitoneal tumors has been addressed. Two segmentation algorithms have been compared and the multilabel version obtains very good resultsJunta de Andalucía P11-TIC-7727Junta de Andalucía PT13/0006/003

Computer Vision Techniques for Transcatheter Intervention

Minimally invasive transcatheter technologies have demonstrated substantial promise for the diagnosis and treatment of cardiovascular diseases. For example, TAVI is an alternative to AVR for the treatment of severe aortic stenosis and TAFA is widely used for the treatment and cure of atrial fibrillation. In addition, catheter-based IVUS and OCT imaging of coronary arteries provides important information about the coronary lumen, wall and plaque characteristics. Qualitative and quantitative analysis of these cross-sectional image data will be beneficial for the evaluation and treatment of coronary artery diseases such as atherosclerosis. In all the phases (preoperative, intraoperative, and postoperative) during the transcatheter intervention procedure, computer vision techniques (e.g., image segmentation, motion tracking) have been largely applied in the field to accomplish tasks like annulus measurement, valve selection, catheter placement control, and vessel centerline extraction. This provides beneficial guidance for the clinicians in surgical planning, disease diagnosis, and treatment assessment. In this paper, we present a systematical review on these state-of-the-art methods.We aim to give a comprehensive overview for researchers in the area of computer vision on the subject of transcatheter intervention. Research in medical computing is multi-disciplinary due to its nature, and hence it is important to understand the application domain, clinical background, and imaging modality so that methods and quantitative measurements derived from analyzing the imaging data are appropriate and meaningful. We thus provide an overview on background information of transcatheter intervention procedures, as well as a review of the computer vision techniques and methodologies applied in this area

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

Multi-Modality Imaging of Atheromatous Plaques in Peripheral Arterial Disease: Integrating Molecular and Imaging Markers

Peripheral artery disease (PAD) is a common and debilitating condition characterized by the narrowing of the limb arteries, primarily due to atherosclerosis. Non-invasive multi-modality imaging approaches using computed tomography (CT), magnetic resonance imaging (MRI), and nuclear imaging have emerged as valuable tools for assessing PAD atheromatous plaques and vessel walls. This review provides an overview of these different imaging techniques, their advantages, limitations, and recent advancements. In addition, this review highlights the importance of molecular markers, including those related to inflammation, endothelial dysfunction, and oxidative stress, in PAD pathophysiology. The potential of integrating molecular and imaging markers for an improved understanding of PAD is also discussed. Despite the promise of this integrative approach, there remain several challenges, including technical limitations in imaging modalities and the need for novel molecular marker discovery and validation. Addressing these challenges and embracing future directions in the field will be essential for maximizing the potential of molecular and imaging markers for improving PAD patient outcomes

The effect of geometrical configurations on flows in idealised and realistic vascular geometries

This thesis reports the use of computational fluid dynamics (CFD) to investigate geometrical effects on flows in idealised non-branching double curved geometries (Study A) and in realistic distal anastomoses where geometries have been determined in vivo using magnetic resonance imaging (Study B). The purpose of this research is to improve understanding of the effects of geometrical configurations, especially curvature and non-planarity, on steady flow in idealised non-branching double curved geometries typical of arteries such as the aortic arch, the right coronary artery or the femoral arteries and on pulsatile flow in realistic distal anastomosis geometries. It is explained that the further knowledge gained from these idealised geometries can be useful to understand flows in anatomically correct geometries in order to optimise the design of end-to-side bypass graft vessels in clinical surgery. In the Study A, three-dimensional computations of steady flows in planar and non-planar double bends with 8 = 0.25 (curvature ratio) at Reynolds numbers of 125 and 500 were performed using the Navier-Stokes solver called Nektar that is based on spectral/hp element methods. The numerical haemodynamics analysis is presented in terms of the various mechanical factors which primarily involve axial velocity, transverse flows, vorticity, coherent vertical structure and wall shear stress. From these results, we can anticipate the wall shear stress distributions and secondary flow patterns in various double bend geometries with different non-planarity at low Reynolds numbers. Non-planarity plays a significant role on the wall shear stress distribution and the mixing properties of flow in the double bends, both of which are believed to be important factors for the patency of bypass grafts. In the Study B, Three sets of MRI data from patients undergoing tunnelled or superficial femoral bypass surgery were processed to give input velocity waveforms and geometries. From the latter and using the same Navier Stokes solver, detailed patient-specific pulsatile haemodynamics were calculated. Wall shear stress and velocity are influenced by the anatomical geometry, and wall shear stress distributions in pulsatile flow are compared with those in steady flow. The correlation is discussed between the haemodynamics and the remodelling of the vessel following bypass surgery determined in follow-up studies carried out a few months or a few years later. The results suggest that better designs should be possible for bypass grafts and indicate how inflow conditions can affect the flow field. The findings imply that proper anastomotical configurations might, induce haemodynamics environments that may prevent cardiovascular disorders or delay the progression of vascular disease.Open acces

Analysis of Venous Blood Flow and Deformation in the Calf under External Compression

Deep vein thrombosis (DVT) is a common post-operative complication, and a serious threat to the patient’s general recovery. In recent years, there has been increasing awareness of the risk of DVT in healthy individuals after prolonged immobility, such as people taking long-period flights or sitting at a computer. Mechanical methods of DVT prophylaxis, such as compression stockings, have gained widespread acceptance, but the haemodynamic mechanism of their action is still not well understood. In this study, computational modelling approaches based on magnetic resonance (MR) images are used to (i) predict the deformation of calf and deep veins under external compression, (ii) determine blood flow and wall shear stress in the deep veins of the calf, and (iii) quantify the effect of external compression on flow and wall shear stress in the deep veins. As a first step, MR images of the calf obtained with and without external compression were analysed, which indicated different levels of compressibility for different calf muscle compartments. A 2D finite element model (FEM) with specifically tailored boundary conditions for different muscle components was developed to simulate the deformation of the calf under compression. The calf tissues were described by a linear elastic model. The simulation results showed a good qualitative agreement with the measurements in terms of deep vein deformation, but the area reduction predicted by the FEM was much larger than that obtained from the MR images. In an attempt to improve the 2D FEM, a hyperelastic material model was employed and a finite element based non-rigid registration algorithm was developed to calculate the bulk modulus of the calf tissues. Using subject-specific bulk modulus derived with this method together with a hyperelastic material model, the numerical results showed better quantitative agreement with MR measured deformations of deep veins and calf tissues. In order to understand the effect of external compression on flow in the deep veins, MR imaging and real-time flow mapping were performed on 10 healthy volunteers before and after compression. Computational fluid dynamics was then employed to calculate the haemodynamic wall shear stress (WSS), based on the measured changes in vessel geometry and flow waveforms. The overall results indicated that application of the compression stocking led to a reduction in both blood flow rate and cross sectional area of the peroneal veins in the calf, which resulted in an increase in WSS, but the individual effects were highly variable. Finally, a 3D fluid-structure interactions (FSI) model was developed for a segment of the calf with realistic geometry for the calf muscle and bones but idealised geometry for the deep vein. The hyperelastic material properties evaluated previously were employed to describe the solid behaviours. Some predictive ability of the FSI model was demonstrated, but further improvement and validation are still needed