InSilc: 3D Reconstruction and plaque characterization tool.

Coronary artery disease (CAD) is the leading cause of mortality in Europe and worldwide. Atherosclerosis is the most common pathologic process that is highly related with CAD, while the implantation of drug-eluting Bioresorbable Vascular Scaffolds (BVS) is the most promising procedure for treating patients with CAD. InSilc is an textbfin silico clinical trial (ISCT) platform for the development and assessment of drugeluting BVS. The InSilc platform provides insight in the performance of drug-eluting BVS in their short term and medium/long term through the Mechanical Modelling Module, the Deployment Module, the Fluid Dynamics Module, the Myocardial Perfusion Module, the Drug-delivery Module and the Degradation Module. In order for the aforementioned modules to be developed, the utilization of the reconstructed patient specific arterial segment and the BVS design are required, which is achieved through the 3D reconstruction and plaque characterization tool.In this study, the overall architecture of the InSilc platform is presented with special emphasis on the 3D reconstruction and plaque characterization tool. The tool will be able to implement different medical image processing workflows. The workflows will require minimum user intervention in order to be used in large scale clinical trials.

Three-dimensional reconstruction of coronary arteries and plaque morphology using CT angiography - comparison and registration using IVUS.

The aim of this study is to present a new method for three-dimensional (3D) reconstruction of coronary arteries and plaque morphology using Computed Tomography (CT) Angiography. The method is summarized in three steps. In the first step, image filters are applied to CT images and an initial estimation of the vessel borders is extracted. In the second step, the 3D centerline is extracted using the center of gravity of each rough artery border. Finally in the third step, the borders and the plaque are detected and placed onto the 3D centerline constructing a 3D surface. By using as gold standard the results of a recently presented Intravascular Ultrasound (IVUS) plaque characterization method, high correlation is observed for calcium objects detected by CT and IVUS. The correlation coefficients for objects' volume, surface area, length and angle are r=0.51, r=0.89, r=0.96 and r=0.93, respectively.

Effect of modeling parameters on the frequency response of the middle ear by means of finite element analysis.

A 3D finite element model of the human middle ear was developed for the investigation of the modeling parameters' effect on the frequency response. In this study, we incorporated realistic reconstructed geometries from microCT imaging data. The geometric representation of the stapedial annular ligament provided additional damping and the Rayleigh parameter ß was adjusted to lower values in comparison to previous computational studies. The maximum displacement of the stapes footplate, equal to 0.168 µm, was observed at a frequency of 1050 Hz. The computational results were validated with experimental measurements. Good agreement is observed between our results and the experimental data and other finite element studies.

Modeling of blood flow through sutured micro-vascular anastomoses.

Microanastomosis is a surgical procedure used to reconnect two blood vessels using sutures. The optimal microanastomosis may be predicted by assessing the factors that influence this invasive procedure. Blood flow and hemodynamics following microanastomosis are important factors for the successful longevity of this operation. How is the blood flow affected by the presence of sutures? Computational Fluid Dynamics (CFD) is a powerful tool that permits the estimation of specific quantities, such as fluid stresses, that are hardly measurable in vivo. In this study, we propose a methodology which evaluates the alterations in the hemodynamic status due to microanastomosis. A CFD model of a reconstructed artery has been developed, based on anatomical information provided by intravascular ultrasound and angiography, and was used to simulate blood flow after microanastomosis. The 3D reconstructed arterial segments are modeled as non-compliant 1.24 - 1.47 mm diameter ducts, with approximately 0.1 mm arterial thickness. The blood flow is considered laminar and the no-slip condition is imposed on the boundary wall, which is assumed to be rigid. In analyzing the results, the distribution of the wall shear stress (WSS) is presented in the region of interest, near the sutures. The results indicate that high values of WSS appear in the vicinity of sutures. Such regions may promote thrombus formation and subsequently anastomotic failure, therefore their meticulous study is of high importance.

Computerized methodology for micro-CT and histological data inflation using an IVUS based translation map.

A framework for the inflation of micro-CT and histology data using intravascular ultrasound (IVUS) images, is presented. The proposed methodology consists of three steps. In the first step the micro-CT/histological images are manually co-registered with IVUS by experts using fiducial points as landmarks. In the second step the lumen of both the micro-CT/histological images and IVUS images are automatically segmented. Finally, in the third step the micro-CT/histological images are inflated by applying a transformation method on each image. The transformation method is based on the IVUS and micro-CT/histological contour difference. In order to validate the proposed image inflation methodology, plaque areas in the inflated micro-CT and histological images are compared with the ones in the IVUS images. The proposed methodology for inflating micro-CT/histological images increases the sensitivity of plaque area matching between the inflated and the IVUS images (7% and 22% in histological and micro-CT images, respectively).

Methodology for micro-CT data inflation using intravascular ultrasound images.

In this paper, a framework for the inflation of micro-CT data using intravascular ultrasound (IVUS) images, is presented. The proposed methodology consists of four steps. In the first step a centerline is extracted from the micro-CT images. In the second step the micro CT images are segmented automatically using the k-means algorithm. In the third step IVUS- micro-CT images are co-registered based on fiducial markers selected manually by the experts. Finally, the images are inflated by applying a transformation method on each image. The transformation method is based on the IVUS and micro-CT contour difference. The proposed methodology for inflating micro-CT images could increase the reliability of correct plaque labeling process as well to enhance the accuracy of the produced training dataset from the micro-CT images.

Fully automated calcium detection using optical coherence tomography.

Optical Coherence Tomography (OCT) is a new invasive technology for performing high-resolution cross-sectional imaging of the coronary arteries. In OCT images only Calcified plaque (CA) components can be accurately depicted as light penetrates hard tissue. In this work we present an automated method for detecting CA in OCT images. The method is fully automated as no user intervention is needed and includes three steps. In the first step the region between the lumen and the maximum penetration depth of OCT from the lumen border is determined. In the second step the region is classified into 3 clusters using the K-means algorithm. CA is identified using the results of k-means. The method was validated using experts' annotations on 27 images. The sensitivity of the method is 83% with Positive predictive value (PVV) 74 %.