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Circulation. 2005 Aug 9;112(6):885-92. Epub 2005 Aug 1.

Characterization of atherosclerotic plaques by laser speckle imaging.

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Department of Dermatology, Harvard Medical School, Wellman Center for Photomedicine, Massachusetts General Hospital, 40 Blossom St, BAR 718, Boston, MA 02114, USA.



A method capable of determining atherosclerotic plaque composition and measuring plaque viscoelasticity can provide valuable insight into intrinsic features associated with plaque rupture and can enable the identification of high-risk lesions. In this article, we describe a new optical technique, laser speckle imaging (LSI), that measures an index of plaque viscoelasticity. We evaluate the potential of LSI for characterizing atherosclerotic plaque.


Time-varying helium-neon laser speckle images were acquired from 118 aortic plaque specimens from 14 human cadavers under static and deforming conditions (0 to 200 microm/s). Temporal fluctuations in the speckle patterns were quantified by exponential fitting of the normalized cross-correlation of sequential frames in each image series of speckle patterns to obtain the exponential decay time constant, tau. The decorrelation time constants of thin-cap fibroatheromas (TCFA) (tau=47.5+/-19.2 ms) were significantly lower than those of other atherosclerotic lesions (P<0.001), and the sensitivity and specificity of the LSI technique for identifying TCFAs were >90%. Speckle decorrelation time constants demonstrated strong correlation with histological measurements of plaque collagen (R=0.73, P<0.0001), fibrous cap thickness (R=0.87, P<0.0001), and necrotic core area (R=-0.81, P<0.0001). Under deforming conditions (10 to 200 microm/s), tau correlated well with cap thickness in necrotic core fibroatheromas (P>0.05).


The measurement of speckle decorrelation time constant from laser speckle images provides an index of plaque viscoelasticity and facilitates the characterization of plaque type. Our results demonstrate that LSI is a highly sensitive technique for characterizing plaque and identifying thin-cap fibroatheromas.

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