Skerl, K., Cochran, S. and Evans, A. (2017) First step to facilitate long-term and multi-centre studies of shear wave elastography in solid breast lesions using a computer-assisted algorithm. International Journal of Computer Assisted Radiology and Surgery, 12(9), pp. 1533-1542. (doi: 10.1007/s11548-017-1596-3)
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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 \({E}_{\mathrm{max}}\) and \({E}_{\mathrm{mean}}\) (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.
Item Type: | Articles |
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Additional Information: | This study was part of a PhD studentship funded by SuperSonic Imagine and the Engineering and Physical Science and Research Council (EPSRC) (Grant Number EP/K020439). |
Keywords: | Breast cancer, computer-aided diagnosis, data assessment, diagnosis, shear wave elastography, ultrasound. |
Status: | Published |
Refereed: | Yes |
Glasgow Author(s) Enlighten ID: | Cochran, Professor Sandy |
Authors: | Skerl, K., Cochran, S., and Evans, A. |
College/School: | College of Science and Engineering > School of Engineering > Systems Power and Energy |
Journal Name: | International Journal of Computer Assisted Radiology and Surgery |
Publisher: | Springer |
ISSN: | 1861-6410 |
ISSN (Online): | 1861-6429 |
Published Online: | 06 May 2017 |
Copyright Holders: | Copyright © 2017 The Authors |
First Published: | First published in International Journal of Computer Assisted Radiology and Surgery 12(9): 1533-1542 |
Publisher Policy: | Reproduced under a Creative Commons license |
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