First step to facilitate long term and multi centre studies of shear wave elastography in solid breast lesions using a computer assisted algorithm

Katrin Skerl (Lead / Corresponding author), Sandy Cochran, Andrew Evans

    Research output: Contribution to journalArticle

    2 Citations (Scopus)
    194 Downloads (Pure)

    Abstract

    Purpose: Shear wave elastography (SWE) visualises the elasticity of tissue. As malignant tissue is generally stiffer than benign tissue, SWE is helpful to diagnose solid breast lesions. Until now, quantitative measurements of elasticity parameters have been possible only, while the images were still saved on the ultrasound imaging device. This work aims to overcome this issue and introduces an algorithm allowing fast offline evaluation of SWE images.
    Methods: The algorithm was applied to a commercial phantom comprising three lesions of various elasticities and 207 in vivo solid breast lesions. All images were saved in DICOM, JPG and QDE (quantitative data export; for research only) format and evaluated according to our clinical routine using a computer-aided diagnosis algorithm. The results were compared to the manual evaluation (experienced radiologist and trained engineer) regarding their numerical discrepancies and their diagnostic performance using ROC and ICC analysis.
    Results: ICCs of the elasticity parameters in all formats were nearly perfect (0.861–0.990). AUC for all formats was nearly identical for Emax
    and Emean (0.863–0.888). The diagnostic performance of SD using DICOM or JPG estimations was lower than the manual or QDE estimation (AUC 0.673 vs. 0.844).
    Conclusions: The algorithm introduced in this study is suitable for the estimation of the elasticity parameters offline from the ultrasound system to include images taken at different times and sites. This facilitates the performance of long-term and multi-centre studies.
    Original languageEnglish
    Pages (from-to)1533-1542
    Number of pages10
    JournalInternational Journal of Computer Assisted Radiology and Surgery
    Volume12
    Issue number9
    Early online date6 May 2017
    DOIs
    Publication statusPublished - Sep 2017

    Keywords

    • Computer-aided diagnosis
    • Breast cancer
    • Shear wave elastography
    • Ultrasound
    • Data assessment
    • Diagnosis

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