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Carotid plaque typing by multiple-parameter ultrasonic tissue characterization

T Noritomi1, B Sigel, V Swami

  • 1Department of Surgery Allegheny University of the Health Sciences, MCP-Hahnemann School of Medicine, Philadelphia, PA 19129, USA.

Ultrasound in Medicine & Biology
|January 1, 1997
PubMed
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Ultrasonic tissue characterization effectively distinguishes advanced carotid plaque components. This method aids in identifying high-risk thrombi, potentially preventing embolic neurologic ischemic events.

Area of Science:

  • Medical Imaging
  • Biomedical Engineering
  • Cardiovascular Research

Background:

  • Advanced carotid plaques pose a risk for embolic neurologic ischemic events.
  • Accurate characterization of plaque components is crucial for risk assessment.

Purpose of the Study:

  • To evaluate ultrasonic tissue characterization (UTC) for distinguishing fibrous, lipid, and thrombus components in advanced carotid plaques.
  • To assess the efficacy of spectral analysis parameters in plaque classification.

Main Methods:

  • In vitro spectral analysis of echo signals from human carotid endarterectomy specimens.
  • Calculation of slope, intercept, and total power from calibrated power spectrum.
  • Histological identification of plaque constituents.
  • Discriminant function analysis for classification efficacy evaluation.

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Main Results:

  • Slope and intercept parameters alone achieved 92.5% (fibrous), 57.6% (lipid), and 72.4% (thrombus) correct classification.
  • Combining slope, intercept, and total power improved classification to 93.0% (fibrous), 69.7% (lipid), and 81.0% (thrombus).
  • Overall correct classification increased from 84.5% to 88.0% with the three-parameter model.

Conclusions:

  • Ultrasonic tissue characterization, using spectral analysis of backscattered echo signals, can effectively differentiate advanced carotid plaque components.
  • The inclusion of total power alongside slope and intercept enhances classification accuracy, particularly for lipid and thrombus.
  • This technique shows promise for identifying high-risk plaque, specifically thrombi, potentially leading to improved stroke prevention strategies.