Share Email Print
cover

Proceedings Paper

Validation of parameter estimation methods for determining optical properties of atherosclerotic tissues in intravascular OCT
Author(s): Ronny Shalev; Madhusudhana Gargesha; David Prabhu; Kentaro Tanaka; Andrew M. Rollins; Marco Costa; Hiram G. Bezerra; Guy Lamouche; David L. Wilson
Format Member Price Non-Member Price
PDF $14.40 $18.00

Paper Abstract

In this paper we present a new process for assessing optical properties of tissues from 3D pullbacks, the standard clinical acquisition method for iOCT data. Our method analyzes a volume of interest (VOI) consisting of about 100 A-lines spread across the angle of rotation (θ) and along the artery, z. The new 3D method uses catheter correction, baseline removal, speckle noise reduction, alignment of A-line sequences, and robust estimation. We compare results to those from a more standard, “gold standard” stationary acquisition where many image frames are averaged to reduce noise. To do these studies in a controlled fashion, we use a realistic optical artery phantom containing of multiple “tissue types.” Precision and accuracy for 3D pullback analysis are reported.

Our results indicate that when implementing the process on a stationary acquisition dataset, the uncertainty improves at each stage while the uncertainty is reduced. When comparing stationary acquisition dataset to pullback dataset, the values were as follows: calcium: 3.8±1.09mm-1 in stationary and 3.9±1.2 mm-1 in a pullback; lipid: 11.025±0.417 mm-1 in stationary and 11.27±0.25 mm-1 in pullback; fibrous: 6.08±1.337 mm-1 in stationary and 5.58±2.0 mm-1. These results indicates that the process presented in this paper introduce minimal bias and only a small change in uncertainty when comparing a stationary and pullback dataset, thus paves the way to a highly accurate clinical plaque type discrimination, enabling automatic classification.

Paper Details

Date Published: 11 March 2014
PDF: 8 pages
Proc. SPIE 9037, Medical Imaging 2014: Image Perception, Observer Performance, and Technology Assessment, 90371D (11 March 2014); doi: 10.1117/12.2043654
Show Author Affiliations
Ronny Shalev, Case Western Reserve Univ. (United States)
Madhusudhana Gargesha, Case Western Reserve Univ. (United States)
David Prabhu, Case Western Reserve Univ. (United States)
Kentaro Tanaka, Univ. Hospitals Case Medical Ctr. (United States)
Andrew M. Rollins, Case Western Reserve Univ. (United States)
Marco Costa, Univ. Hospitals Case Medical Ctr. (United States)
Hiram G. Bezerra, Univ. Hospitals Case Medical Ctr. (United States)
Guy Lamouche, National Research Council (Canada)
David L. Wilson, Case Western Reserve Univ. (United States)


Published in SPIE Proceedings Vol. 9037:
Medical Imaging 2014: Image Perception, Observer Performance, and Technology Assessment
Claudia R. Mello-Thoms; Matthew A. Kupinski, Editor(s)

© SPIE. Terms of Use
Back to Top