Original contributionAssessing spectral algorithms to predict atherosclerotic plaque composition with normalized and raw intravascular ultrasound data
Section snippets
Introduction and literature
Angiography, the traditional method for assessing atherosclerosis, has significant limitations. It allows evaluation of the geometry of the unobstructed part of the lumen only; it cannot provide information on the structure of the arterial wall, which is essential to estimating the extent of atherosclerosis. Intravascular ultrasound (IVUS) is becoming accepted as an imaging modality that allows precise cross-sectional assessment of the coronary anatomy in vivo Gussenhoven et al 1989b, Potkin et
Specimens and preparation
A total of 32 human hearts were obtained at autopsy, from subjects between the ages of 40 and 70 years. The left anterior descending (LAD) coronary artery was dissected from the ostium to the apex, including approximately 40 mm of surrounding fat and myocardial tissue. Inclusion of surrounding tissue ensured the maintenance of proper vessel support and reduced artefactual US reflections from the tissue-air interface. The LAD was harvested because it most often contains significant disease and
One-way ANOVA
The one-way ANOVA tested for significance of separation of the four plaque types. Due to the presence of calcium in both the calcified and the calcified-necrotic regions, there was no significant difference in mean values of the spectral parameters of these two plaque components. Hence, these two were combined as one atherosclerotic component for the ANOVA analysis. The number of ROIs from this category was 60 (23 calcium + 37 calcified-necrosis).
The unnormalized data were analyzed with 14
Discussion
This study aimed at assessing two factors that may have a significant effect on the analysis of IVUS RF spectral signature, and employing a novel approach to achieve accurate IVUS-histology correlation. These factors were: 1. analysis of normalized and un-normalized spectra; and 2. performance of three PSD algorithms toward classification of atherosclerotic tissue with IVUS.
The one-way ANOVA results among the three spectral algorithms were similar for both the unnormalized and normalized
Summary
This study aimed at comparing the ability of different spectral estimators for characterizing atherosclerosis with IVUS backscatter, by constructing classification trees. The approach employed various spectral parameters at the same time to provide the classification. These parameters were calculated with different spectral estimators in an attempt to achieve high spectral resolution. Results demonstrated that WPSD and CPSD performed equally well. The best accuracies for classification of
Acknowledgements
This project was funded in part by a Biomedical Engineering Grant awarded by the Whitaker Foundation (97 to 0332; D. G. Vince, Principal Investigator). The authors thank Jon Klingensmith for use of the IVUS image reconstruction software. Azita Tajaddini helped with data collection, and Dominik Meier was an invaluable source of help with histology image registration and morphing. The authors thank Christine Kassuba for editorial assistance.
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