Breast cancer is the most common cancer in women worldwide. In 2009, a novel imaging modality called Shear Wave Elastography (SWE), an ultrasound technique visualising the elasticity of tissue, was introduced to the field of clinical breast imaging. Because malignant tissues are generally stiffer than benign tissues, SWE supports the differentiation of benign / malignant solid breast lesions. However, no standard has yet been defined for the application and the evaluation of results. Furthermore, image evaluation has to be carried out directly from the ultrasound system, complicating long-term and multi-centre studies. This PhD thesis investigated the influences from the imaging process and image evaluation on SWE measurements. Various parameters were appraised with regard to their diagnostic performance, in order to define the best clinical standard. To define more complex image analysis, taking the parameters investigated into account, algorithms were devised to enable automatic assessment of B-mode and SWE images. In this work, influences from the imaging process and image evaluation on the SWE measurements were demonstrated. The influences investigated included: the impact from the region of interest and the imaging plane used; the individual variation in breast composition; the number of images considered and the pressure applied during imaging. The algorithms described within this work achieved a diagnostic accuracy similar to that of manual assessment by a radiology expert. This thesis demonstrated influences from the imaging process and image evaluation on the SWE measurements obtained. Taking these influences into consideration would complicate the clinical application of SWE imaging. However, automatic image evaluation as presented here would overcome this issue. Using the guidelines defined in this PhD thesis also allows for comparison of results taken from different imaging sites.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:716219 |
| Date | January 2016 |
| Creators | Skerl, Katrin |
| Contributors | Evans, Andrew |
| Publisher | University of Dundee |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | https://discovery.dundee.ac.uk/en/studentTheses/5ee2b3ed-89aa-4874-830a-ec9be233aae4 |
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