David Geoffrey Vince

Segmentation of three-dimensional intravascular ultrasound images using spectral analysis and a dual active surface model

Intravascular ultrasound (IVUS) imaging provides detailed assessment of the coronary anatomy and can be used as at quantitative tool for tracking the progression of atherosclerotic disease. The geometric information also provides evaluation of positive remodeling, a phenomenon linked to the likelihood of plaque rupture. To provide this valuable information, luminal and medial-adventitial borders must be identified in the sequence of IVUS images, a problem traditionally approached using gray-scale intensity based algorithms. However, by acquiring the radiofrequency (RF) IVUS data, the frequency information that is typically ignored can be used to improve segmentation algorithms.

Classification of atherosclerotic plaque composition by spectral analysis of intravascular ultrasound data

Knowledge of atherosclerotic plaque composition in vivo would be a tremendous aid towards selection of appropriate clinical intervention and timely detection of unstable atheroma. Spectral analysis of backscattered intravascular ultrasound (IVUS) data has demonstrated ability to characterize plaque. Spectral parameters such as slope, midband fit and y-intercept are indicative of scatterer size, concentration and acoustic impedance. In this study, we compared the ability of spectral parameters computed via the Welch power spectrum (PSD) and autoregressive (AR) models to classify plaque composition. Data was collected in vitro from 32 left anterior descending coronary arteries, with 30 MHz non-focused IVUS transducers in saline at physiologic pressure. Regions of interest (ROI), selected from histology, comprised 64 collagen-rich, 24 fibro-lipidic, 23 calcified and 37 calcified-necrotic regions. A novel quantitative method was used for IVUS data correlation with corresponding histology sections. Periodograms of IVUS samples, identified for each ROI, were used to calculate various spectral parameters (such as the midband fit, slope, y-intercept, and maximum power). Statistical classification trees (CT) were computed with 75% of the data for plaque characterization. The remaining data were utilized to assess the accuracy of the CTs. The overall accuracies with the Welch PSD and AR model (order 14) were 85.6% and 81.1% on the training data, 64.9% and 37.8% on the test data, respectively. These numbers were improved to 91.9% and 89.2% on training data, 73% and 59.5% on test data, when the calcified and calcified-necrotic regions were combined for analysis. Further analysis with AR model order number and level of zero padding increased the overall accuracy, with individual sensitivities to collagen of 91.7%, calcium of 88.9%, and fibro-lipid of 83.3%. Most of the CTs mis-classified few fibro-lipidic regions as collagen, which is histologically acceptable.

Volumetric coronary plaque composition using intravascular ultrasound: three-dimensional segmentation and spectral analysis

Intravascular ultrasound provides precise tomographic assessment of coronary artery disease, allowing unique potential for analysis of both plaque geometry and composition, two critical factors related to the likelihood of plaque rupture. A novel three-dimensional segmentation technique and spectral analysis are used to create a unique tool for volumetric assessment of plaque composition. The semi-automated 3D segmentation technique was used to identify luminal and medial-adventitial borders in ECG-gated images created from radiofrequency (RF) IVUS data acquired during automated pullbacks in patients. Spectral analysis was applied to the RF data within the segmented plaque. Color-coded pseudo-histology images were created from these plaque component predictions using statistical classification trees. Quantitative analysis and visualization techniques were used to assess volumetric plaque composition and provide a unique tool for evaluation of plaque vulnerability.

Quantification of coronary arterial plaque volume using 3D reconstructions formed by fusing intravascular ultrasound and biplane angiography

This paper, through plaque quantification, demonstrates the use of three-dimensional (3D) reconstructions of coronary arteries to assess compensatory enlargement. The lumen and medial-adventitial border are segmented from intravascular ultrasound (IVUS) images using a novel 3D method called active surfaces and the segmented data is used to calculate the cross-sectional area of the lumen and vessel, respectively. The area of plaque for each slice is the difference of the two. Information about the distance between path points, located using a calibrated biplane angiography system, is used for the calculation of plaque volume. This quantification system can be used to track the progression or regression of atherosclerosis and is currently being used to document compensatory enlargement, a physiological phenomenon in which the overall vessel cross-sectional area increases with an increase in plaque area with little or no decrease in luminal cross-sectional area. Four ex-vivo cases have been quantified, all demonstrating this remodeling mechanism, shown by strong positive correlation between plaque area and vessel area over the reconstructed length of the vessel (R equals 0.98, R equals 0.93, R equals 0.98, R equals 0.68).

Respiratory motion correction for geometrically correct three-dimensional reconstructions of coronary arteries

By fusing intravascular ultrasound (IVUS) with biplane angiography, geometrically correct three-dimensional (3D) reconstructions of coronary arteries can be produced. Spatio-temporal localization of the IVUS transducer is challenging due to cardiac and respiratory motion. Since cardiac motion can be eliminated via ECG-gating, the aim of this project was to develop a scheme for respiratory motion correction of the 3D transducer path. A model-based technique was used to eliminate respiratory motion in transducer paths reconstructed from biplane angiography in three pullbacks. Although biplane angiography is the current standard, alternate technology for spatio-temporal localization, will potentially allow inexpensive, real-time 3D reconstruction with no ionizing radiation. The model-based respiratory motion correction has the potential to aid in real-time clinical 3D reconstruction of coronary artery anatomy.