Mireille Garreau

Three-dimensional reconstruction of the coronary arteries usinga priori knowledge

A method for 3D reconstruction of the coronary arteries from two radiographic images is presented. A novel technique for matching image structures is the main contribution of the work. After a comprehensive study of the knowledge required to approach this problem, an automatic method, which includes both numeric and symbolic procedures to solve geometric ambiguities, is developed. In the proposed method, all possible (virtual) reconstructions are first obtained. Their validity is evaluated by means of a priori knowledge about the 3D object and its projections. From the set of chosen possible solutions, the most likely solution is selected. The method is tested using real images and is implemented in a platform that allows further clinical validation.

Evaluation of a 3D segmentation software for the coronary characterization in multi-slice computed tomography

A new generation of sub-second multi-slices computed tomography (MSCT) scanners, which allow a complete coronary coverage, is becoming widely available. Nevertheless, they need to be associated with 3D processing tools to quantify the coronary diseases. This study proposes to evaluate a new 3D moment-based method for the extraction of the coronary network and the calcification localization in MSCT. We called on two medical experts respectively in coronarography and radiology to carry out this evaluation. It was based on a comparison between extracted vessels and original scan data with objective and subjective criteria. This preliminary study has been performed on a set of six data sets, which included pathological patterns such as dense and scattered calcifications. These results confirm the good performances of the method with high scores of sensitivity and constitute a first step toward the detection of coronary networks in MSCT data.

Coronary characterization in multi-slice computed tomography

We present a 3D extraction method of coronaries in MSCT, which aims at refining the delineating of the vascular inner wall and the calcified contours for quantification purposes. The proposed approach makes use of a two-step process: the first one performs a vessel central axis tracking by applying a semi-automatic 3D geometrical moment-based method. A refinement is then performed, based on a level set approach, to improve the detection accuracy of both contours and calcifications. The level sets were applied first in 2-D space, independently on each slice, then in 3-D to perform the extraction directly in the volume. A comparison between the 2-D and 3-D procedures is provided in term of quality of delineation.

Transvenous path finding in cardiac resynchronization therapy

Cardiovascular diseases are a major health concern all over the world and, especially, heart failure has gained more importance in the recent years. Improving diagnosis and therapy is therefore critical and among the several resources at our disposal, implantable devices is expected to have a better rate of success. This paper is focused on two topics: (i) our views of the main challenges to face in order to reach these objectives and (ii) a specific target regarding the pose of leads for multisite pacemakers by means of virtual endoscopy pre-operative planning and path finding throughout the coronary venous tree.

A surface-volume matching process using a markov random field model for cardiac motion extraction in MSCT imaging

Multislice Computed Tomography (MSCT) scanners offers new perspectives for cardiac kinetics evaluation with 3D time image sequences of high contrast and spatio-temporal resolutions. A new method is proposed for cardiac motion extraction in Multislice CT. Based on a 3D surface-volume matching process, it provides the detection of the heart left cavities along the acquired sequence and the estimation of their 3D surface velocity fields. A 3D segmentation step and surface reconstruction process are first applied on only one image of the sequence to obtain a 3D mesh representation for one t time. A Markov Random Field model is defined to find best correspondences between 3D mesh nodes at t time and voxels in the next volume at t + 1 time. A simulated annealing is used to perform a global optimization of the correspondences. First results obtained on simulated and real data show the good behaviour of this method.

Cardiac Motion Extraction Using 3D Surface Matching in Multislice Computed Tomography

A new generation of Multislice Computed Tomography (MSCT) scanners, which allows a complete heart coverage and offers new perspectives for cardiac kinetic evaluation, is becoming widely available. A new method has been developed for the left ventricle motion analysis from dynamic MSCT images. It is based on a 3D surface matching process applied to left cavity volumes. It provides 3D velocity fields which can express contraction or expansion movements. First results obtained on real data show that MSCT imaging could be of great clinical interest for cardiac applications.

Cardiac motion extraction in multislice computed tomography by using a 3D hierarchical surface matching process

Retrospective data reconstruction provided in multislice computed tomography (MSCT) scanners offers new perspectives for cardiac kinetics evaluation with volume sequences of high spatial and temporal resolutions. A new method is proposed for cardiac motion extraction in MSCT. It is based on a 3D surface matching process associated to a hierarchical description of shapes. It provides 3D velocity fields associated to the left ventricle inner surface, which can be used for global and local motion quantification. 3D segmentation and surface reconstruction processes are first applied on each volume to obtain one mesh representation for each time. A hierarchical surface matching scheme is then performed: mesh nodes are selected as entities and matched according to a local energy. A simulated annealing is used to perform a global optimisation of the correspondences. First results obtained on simulated and real data show the good behavior of this method.

Understanding coronary artery movement: a knowledge-based approach

The aim of this paper is to describe a knowledge-based system that interprets three-dimensional (3D) coronary artery movement, using data from digital subtraction angiography image sequences. Dynamic information obtained from artery centerline 3D reconstruction and optical flow estimation, is classified according to experimental evidence indicating that artery displacements are quasi-homogeneous by a segment analysis. Characteristic motion features like displacement direction, perpendicular/radial components, rotation direction, curvature and torsion are qualitatively described from an image sequence using symbolic labels. These facts are then related and interpreted using anatomical-functional knowledge provided by a specialist, as well as spatial and temporal knowledge, applying spatio-temporal reasoning schemes. Facts, knowledge and reasoning rules are stated in a declarative form. Detailed examples of local and global interpretation results, using a real reconstructed angiographic biplane image sequence are presented in order to illustrate how our system suitably interprets coronary artery dynamic behavior.

Clinical contributions of 64-slice computed tomography in the evaluation of cardiomyopathy of unknown origin

BACKGROUNDnMeta-analyses have confirmed the high performance of multislice computed tomography (MSCT) in coronary stenosis detection. Recent reports have described the study of left ventricular anatomy and function and coronary venous anatomy with MSCT.nnnAIMSnWe sought to compare, in patients with cardiomyopathy of unknown origin, the performance of MSCT versus angiography for significant coronary artery disease detection and versus transthoracic echocardiography (TTE) for left ventricular anatomy and function evaluation, and to assess its ability to characterize coronary venous anatomy.nnnMETHODSnFifty-nine patients with cardiomyopathy (left ventricular ejection fraction [LVEF] less than or equal to 40%) of unknown origin, in sinus rhythm, underwent MSCT, TTE and coronary angiography.nnnRESULTSnTwenty-four (3%) of 724 analysable coronary segments (97%) and 12 (20%) patients had significant coronary artery disease. MSCT sensitivity, specificity, and positive and negative predictive values for coronary artery disease detection were 87.5%, 98.5%, 67.7% and 99.6% in the per-segment assessment and 100%, 91%, 75% and 100% in the per-patient evaluation, respectively. Statistical analyses showed good agreement between MSCT and TTE in LVEF measurement (33+/-10% vs 32+/-11%, p=0.4, mean difference=0.7%, limits of agreement+/-13.6%) and a small LVED diameter overestimation (65.0+/-9.3mm vs 63.6+/-9.4mm, p=0.03). MSCT allowed detection of the posterolateral vein in 86% of cases.nnnCONCLUSIONSnIn selected patients presenting with idiopathic cardiomyopathy, MSCT is accurate for coronary artery disease detection and is a useful coronary venous imaging tool. MSCT studies of left ventricular function and morphology were mostly concordant with TTE measurements.

Towards dynamic cardiac scenes interpretation based on spatial-temporal knowledge

Cardiac motion analysis enables to identify pathologies related to myocardial anomalies or coronary arteries circulation deficiencies. Conventionally, bi-dimensional (2D) left ventricle contour images have been extensively used, to perform quantitative measurements and qualitative evaluations of the cardiac function. Nevertheless, there are other cardiac anatomical structures, the coronary arteries, imaged on routine procedures, upon which complementary motion interpretation can be conducted. This paper presents an experimental methodology to perform dynamic cardiac scenes interpretation, studying three-dimensional (3D) coronary arteries spatial-temporal behavior. Being an alternative way to approach computer assisted cardiac motion interpretation, it reveals a wide range of rarely explored spatial-temporal situations and proposes how to address them. Considering the challenges to achieve dynamic scene interpretation, it is explained how spatial and temporal knowledge, are connected to specialist knowledge and measured parameters, to obtain a dynamic scene interpretation. Global and local motion features are modeled according to cardiac motion and geometrical knowledge, before its transformation into symbols. Anatomical knowledge and spatial-temporal knowledge are applied, along with spatial-temporal reasoning schemes, to access symbols meaning. Experimental results obtained using real data are presented. Complexity of interpretation envisioning is discussed, taking the given results as an example.