Augmented vessels for quantitative analysis of vascular abnormalities and endovascular treatment planning

Abstract

Abstract-Endovascular treatment plays an important role in the minimally invasive treatment of patients with vascular diseases, a major cause of morbidity and mortality worldwide. Given a segmentation of an angiography, quantitative analysis of abnormal structures can aid radiologists in choosing appropriate treatments and apparatuses. However, effective quantitation is only attainable if the abnormalities are identified from the vasculature. To achieve this, a novel method is developed, which works on the simpler shape of normal vessels to identify different vascular abnormalities (viz. stenotic atherosclerotic plaque, and saccular and fusiform aneurysmal lumens) in an indirect fashion, instead of directly manipulating the complex-shaped abnormalities. The proposed method has been tested on three synthetic and 17 clinical data sets. Comparisons with two related works are also conducted. Experimental results show that our method can produce satisfactory identification of the abnormalities and approximations of the ideal post-treatment vessel lumens. In addition, it can help increase the repeatability of the measurement of clinical parameters significantly.

3-D Quantitative Vascular Shape Analysis for Arterial Bifurcations via Dynamic Tube Fitting

“…We firstly compare the proposed image-driven energy functional with its volume domain counterparts, i.e., Wong and Chung's method [8] and the model proposed by Kang et al [9], to show the benefits offered by the proposed energy formulation. The comparison was carried out using synthetic 3D vascular images, which allow testing these energy metrics on various types of vessel segments with known optimal solutions (i.e., ground truth data).…”

“…Such methods allow the local deformation of a curve (surface) in terms of image features, while maintaining global smoothness, usually constrained by inherent physical characteristics, such as elasticity and stiffness. Wong and Chung [8] proposed a deformable tube model based method to recover the healthy shape of abnormal vessels in 3D angiography images. In their method, the original shape of a diseased vessel segment is reconstructed by registering a circular cross sectional tube to the vessel boundaries in the normal regions.…”

“…Firstly, it works directly on the mesh domain, which alleviates the requirement for image upsampling. Secondly, contrary to conventional circular cross sectional tube models [8][9][10], which use linear interpolation to determine the width along the tube, the proposed method estimates the tubular cross sections based on partial information of the vessel surface to be fitted. Specifically, the cross sections of the tube are adaptively estimated by finding the best fitting ellipse to the intersection points (obtained by slicing the vessel surface using a cutting plane which is perpendicular to the centreline points) belonging to the desired constituent branch of the bifurcation.…”

Principal Curves for Lumen Center Extraction and Flow Channel Width Estimation in 3-D Arterial Networks: Theory, Algorithm, and Validation

“…14(e) for the model] illustrates that our model can bypass the pathological structure and provide a good estimation of the postembolization vessel lumen. Such a pathology-free lumen plays an important role in studying the geometry of the attached aneurysmal sac, particularly the aneurysmal neck [34]. This disease-free lumen approximation is not possible if the circular cross-sectional assumption is relaxed in our framework.…”

Coronary Vein Extraction in MSCT Volumes Using Minimum Cost Path and Geometrical Moments

“…If we consider the extraction scheme, three main families are reported in the literature: regiongrowing-based approaches [9], active contour family [10], [11] and centerline extraction methods. The latter gathers direct centerline tracking [12], [13], model-based [14] and minimum cost path techniques [15], [16], [17], [18]. The performances of these methods vary according to multiple factors: the presence of severe pathologies (acute stenosis, large aneurysm), local complexity of vascular networks (complicated branching situations) and the surrounding tissue environment.…”