| Literature DB >> 29606785 |
Ronny Shalev1, Madhusudhana Gargesha1, David Prabhu1, Kentaro Tanaka2, Andrew M Rollins1, Marco Costa2, Hiram G Bezerra2, Guy Lamouche3, David L Wilson1,4.
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.Entities:
Keywords: OCT; Optical Coherence Tomography; iOCT; intravascular imaging; optical parameters
Year: 2014 PMID: 29606785 PMCID: PMC5873319 DOI: 10.1117/12.2043654
Source DB: PubMed Journal: Proc SPIE Int Soc Opt Eng ISSN: 0277-786X