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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±1.09 mm -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.

Validation of parameter estimation methods for determining optical properties of atherosclerotic tissues in intravascular OCT