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Ultrasound Strain Elastography for Breast Lesions: Computer-Aided Evaluation With Quantifiable Elastographic

Yang Xiao1, Jie Zeng2, Xue Zhang1

  • 1Paul C. Lauterbur Research Center for Biomedical Imaging, Institute of Biomedical and Health Engineering, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.

Journal of Ultrasound in Medicine : Official Journal of the American Institute of Ultrasound in Medicine
|March 16, 2017
PubMed
Summary

Quantifiable ultrasound strain elastography (SE) features improve breast lesion differentiation. This method offers higher specificity and diagnostic performance compared to conventional B-mode ultrasound for characterizing breast masses.

Keywords:
breastcomputer-aidedquantifiable elastographic featuresultrasound real-time strain elastograhpy

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Area of Science:

  • Medical Imaging
  • Diagnostic Ultrasound
  • Breast Imaging

Background:

  • Distinguishing benign from malignant breast lesions is crucial for patient management.
  • Conventional B-mode ultrasound has limitations in characterizing breast lesions accurately.

Purpose of the Study:

  • To develop and evaluate quantifiable elastographic features using ultrasound real-time strain elastography (SE).
  • To assess the efficacy of these SE features in differentiating between benign and malignant breast lesions.

Main Methods:

  • 226 breast lesions (81 malignant, 145 benign) were analyzed using SE and B-mode ultrasound.
  • A computer-aided tool calculated four elastographic features: elasticity score, stiffness degree, lesion-to-fat strain ratio, and elastography-to-B-mode lesion area ratio.
  • Diagnostic performance was evaluated using sensitivity, specificity, and ROC curve analysis.

Main Results:

  • Quantifiable SE features were significantly higher for malignant lesions (P < .001).
  • Individual SE features significantly improved specificity compared to B-mode ultrasound (P < .001).
  • A logistic regression model combining SE features significantly enhanced diagnostic performance, increasing specificity to 95.2% and AUC to 0.988.

Conclusions:

  • Computer-aided SE provides valuable elasticity information for breast lesion characterization.
  • Quantifiable SE features demonstrate superior diagnostic performance over conventional B-mode ultrasound for breast lesion differentiation.