Measurement of fibrous cap thickness in atherosclerotic plaques by spatiotemporal analysis of laser speckle images

J Biomed Opt. 2006 Mar-Apr;11(2):021006. doi: 10.1117/1.2186046.


Necrotic-core fibroatheromas (NCFA) with thin, mechanically weak fibrous caps overlying lipid cores comprise the majority of plaques that rupture and cause acute myocardial infarction. Laser speckle imaging (LSI) has been recently demonstrated to enable atherosclerotic plaque characterization with high accuracy. We investigate spatio-temporal analysis of LSI data, in conjunction with diffusion theory and Monte Carlo modeling of light transport, to estimate fibrous cap thickness in NCFAs. Time-varying laser speckle images of 20 NCFAs are selected for analysis. Spatio-temporal intensity fluctuations are analyzed by exponential fitting of the windowed normalized cross-correlation of sequential laser speckle patterns to obtain the speckle decorrelation time constant, tau(rho), as a function of distance rho from the source entry location. The distance, rho', at which tau(rho) dropped to 65% of its maximum value is recorded. Diffusion theory and Monte Carlo models are utilized to estimate the maximum photon penetration depth, zmax(rho'), for a distance equal to rho', measured from LSI. Measurements of zmax(rho') correlate well with histological measurements of fibrous cap thickness (R=0.78, p<0.0001), and paired t-tests show no significant difference between the groups (p=0.4). These results demonstrate that spatio-temporal LSI may allow the estimation of fibrous cap thickness in NCFAs, which is an important predictor of plaque stability.

Publication types

  • Evaluation Study
  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms*
  • Aortic Diseases / pathology*
  • Atherosclerosis / pathology*
  • Cadaver
  • Carotid Stenosis / pathology*
  • Humans
  • Image Enhancement / methods
  • Image Interpretation, Computer-Assisted / methods*
  • Imaging, Three-Dimensional / methods*
  • Lasers*
  • Reproducibility of Results
  • Sensitivity and Specificity