Multiparametric Attenuation and Backscatter Images for Characterization of Carotid Plaque

Author:

Bridal S. Lori1,Beyssen Bernard2,FoRNÈs Paul3,Julia Pierre4,Berger Geneviève1

Affiliation:

1. Laboratoire d'Imagerie Paramétrique UMR 7623 CNRS — Université Paris VI 15, rue de l'Ecole de Médecine 75270 Paris Cedex 06, France

2. Radiologie Cardiovasculaire Assistance Publique-Hôpitaux de Paris

3. Laboratoire d'Anatomie Pathologique Hôpital Broussais 96, rue Didot 75014 Paris, France

4. Service de Chirurgie Cardiovasculaire Hôpital Broussais 96, rue Didot 75014 Paris, France

Abstract

The goal of this study was to develop methods for quantitative ultrasound imagery suitable for noninvasive assessment of carotid plaque composition prior to the selection of the technique for revascularization. Using two broadband transducers (5–12 MHz and 12–28 MHz), backscattered radio frequency signals were acquired from entire lengths of 15 carotid endarterectomy specimens. Spectral analysis methods with correction for system response and beam diffraction were applied to radio frequency signals from local volumes of plaque having a 2 mm slice thickness, 1 mm width and axial depth of 480 μm and 240 μm at 10 MHz and 20 MHz, respectively. From these spectra, local values of four ultrasound parameters (integrated backscatter, frequency dependence of backscatter, integrated attenuation and slope of attenuation) were estimated and used to construct quantitative images. To combine information from these different parameter images, a two-step approach was followed. First, in 59 independent quantitative images of highly stenotic plaque, the average parameter values in a central five-by-three pixel region were correlated with plaque composition as assessed by histology to investigate the relationship between parameter values, frequency bandwidth and plaque composition. Discriminant analysis of parameter values vs. plaque composition was made to find a set of predictive equations to classify sets of measurements. Correct classification was obtained for 100% of calcified, 75% of intraplaque hemorrhage and 71 % of lipidic plaques of the input data set. Second, each set of pixels from different parameter images was classified using the predictive equations, and a single, local tissue composition image was constructed. Examples of tissue composition images are presented in comparison with corresponding histologic sections. Both agreement and disagreement between image pairs are discussed.

Publisher

SAGE Publications

Subject

Radiology, Nuclear Medicine and imaging,Radiological and Ultrasound Technology

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