Richard Downe

Standardized evaluation methodology and reference database for evaluating IVUS image segmentation

This paper describes an evaluation framework that allows a standardized and quantitative comparison of IVUS lumen and media segmentation algorithms. This framework has been introduced at the MICCAI 2011 Computing and Visualization for (Intra)Vascular Imaging (CVII) workshop, comparing the results of eight teams that participated. We describe the available data-base comprising of multi-center, multi-vendor and multi-frequency IVUS datasets, their acquisition, the creation of the reference standard and the evaluation measures. The approaches address segmentation of the lumen, the media, or both borders; semi- or fully-automatic operation; and 2-D vs. 3-D methodology. Three performance measures for quantitative analysis have been proposed. The results of the evaluation indicate that segmentation of the vessel lumen and media is possible with an accuracy that is comparable to manual annotation when semi-automatic methods are used, as well as encouraging results can be obtained also in case of fully-automatic segmentation. The analysis performed in this paper also highlights the challenges in IVUS segmentation that remains to be solved.

Simultaneous Registration of Location and Orientation in Intravascular Ultrasound Pullbacks Pairs Via 3D Graph-Based Optimization

A novel method is reported for simultaneous registration of location (axial direction) and orientation (circumferential direction) of two intravascular ultrasound (IVUS) pullbacks of the same vessel taken at different times. Monitoring plaque progression or regression (e.g., during lipid treatment) is of high clinical relevance. Our method uses a 3D graph optimization approach, in which the cost function jointly reflects similarity of plaque morphology and plaque/perivascular image appearance. Graph arcs incorporate prior information about temporal correspondence of the two IVUS sequences and limited angular twisting between consecutive IVUS images. Additionally, our approach automatically identifies starting and ending frame pairs in the two IVUS pullbacks. Validation of our method was performed in 29 pairs of IVUS baseline/follow-up pullback sequences consisting of 8 622 IVUS image frames in total. In comparison to manual registration by three experts, the average location and orientation registration errors ranged from 0.72 mm to 0.79 mm and from 7.3 ° to 9.3 °, respectively, all close to the inter-observer variability with no difference being statistically significant (p = NS). Rotation angles determined by our automated approach and expert observers showed high correlation ( r2 of 0.97 to 0.98) and agreed closely (mutual bias between the automated method and expert observers ranged from -1.57° to 0.15 °). Compared with state-of-the-art approaches, the new method offers lower errors in both location and orientation registration. Our method offers highly automated and accurate IVUS pullback registration and can be employed in IVUS-based studies of coronary disease progression, enabling more focal studies of coronary plaque development and transition of vulnerability.

Joint registration of location and orientation of intravascular ultrasound pullbacks using a 3D graph based method

A novel method for simultaneous registration of location and orientation of baseline and follow-up intravascular ultrasound (IVUS) pullbacks is reported. The main idea is to represent the registration problem as a 3D graph optimization problem (finding a minimum-cost path) solvable by dynamic programming. Thus, global optimality of the resulting location and orientation registration is guaranteed according to the employed cost function and node connections. The cost function integrates information related to vessel/plaque morphology, plaque shape and plaque/perivascular image data. The node connections incorporate the prior information about angular twisting between consecutively co-registered IVUS image pairs. Pilot validation of our method is currently available for four pairs of IVUS pullback sequences consisting of 323 IVUS image frames from four patients. Results showed the average location and orientation registration errors were 0.26 mm and 5.2°, respectively. Compared with our previous results, the new method offers significant alignment improvement (p < 0.001).

IVUS-based assessment of 3D morphology and virtual histology: Prediction of atherosclerotic plaque status and changes

Comprehensive analysis of coronary morphology, plaque composition, hemodynamics, and systemic cardiovascular biomarkers is hypothesized to allow prediction of plaque development. We report the status of a comprehensive project, in which baseline and follow-up intravascular ultrasound imaging of coronary arteries during routine coronary interventions serve as a source of quantitative data for development of a predictive classifier for determining plaque progression over the course of a year from baseline data.

An integrated framework for spatio-temporal registration of intravascular ultrasound pullbacks

Spatio-temporal registration of baseline and follow-up intravascular ultrasound (IVUS) pullbacks is of paramount importance in studying the progression/regression of coronary artery disease. Automating these two tasks has the potential to increase productivity when studying large patient populations. Current automated methods are often designed for only one of the two tasks - spatial or temporal. In this paper, we propose an integrated framework which combines the two tasks and employs side-branches to constrain the IVUS pullback registration tasks. For temporal registration, canonical time warping technique optimizes extracted features and weighs cumulative distances. For spatial registration, the search range of cross-correlation based method is constrained by utilizing the angular differences between side-branches. Pilot validation is currently available for ten pairs of IVUS pullback sub-sequences. Results show average spatial and temporal registration errors of 0.49 mm ± 0.51 mm and 5.56° ± 3.35°, respectively, a notable improvement over our previous approach (p < 0.001) in temporal registration. Our method has the potential to improve spatial and temporal correspondence in studies of atherosclerotic vascular disease development using IVUS.

3D ANGIOGRAPHY/IVUS-VH BASED ANALYSIS OF TEMPORAL CHANGES IN NECROTIC CORE CONTENT AND LUMINAL DISTRIBUTION WITH STATIN TREATMENT

Despite only small changes in total plaque volume, lipid lowering therapy with statin agents (LLT) significantly decreases cardiac events. The precise plaque morphologic changes associated with plaque stabilization are not known. We evaluated temporal patterns of necrotic core (NC) modification via

Three-dimensional and Four-dimensional Cardiopulmonary Image Analysis

Modern medical imaging equipment can provide data that describe the anatomy and function of structures in the body. Image segmentation techniques are needed to take this raw data and identify and delineate the relevant cardiovascular and pulmonary anatomy to put it into a form suitable for 3D and 4D modeling and simulation. These methods must be able to handle large multi-dimensional data sets, possibly limited in resolution, corrupted by noise and motion blur, and sometimes depicting unusual anatomy due to natural shape variation across the population or due to disease processes. This chapter describes modern techniques for robust, automatic image segmentation. Several applications in cardiovascular and pulmonary imaging are presented.