Our research has two foci:
1. Breast Cancer Screening and Diagnosis using Full Field Digital Mammography (FFDM)
2. Dose and Image Quality Optimisation, and Lesion Detection Performance
Some overlap exists between the two foci, with detection performance and dose/image quality optimisation studies occuring in FFDM.
Breast Cancer - Screening & Diagnosis using Full Field Digital Mammography (FFDM)
Theme Lead: Professor Peter Hogg
This has qualitative and quantitative components; however the majority of our research projects are quantitative in nature. Various ways can be used to outline the research we conduct and for the purposes of this paper they are broken down into three categories: technical; practice-based; social.
Our technical research relates to applied physics, engineering and computing and the projects investigate equipment-related matters which are grounded on practical issues which arise in the clinical setting. Examples of this research include: 1. Identification of causation for and minimisation of reasons leading to blurred FFDM images. Blurred FFDM images can lead to false diagnoses and unnecessary repeat examinations. Repeat imaging can heighten client / family anxiety, increase overall breast screening costs and contribute to unnecessary radiation dose. 2. Development of new mathematical models for predicting total lifetime radiation risk from screening mammography. These models are important as they can help clients make informed decisions about whether or not they wish to participate in screening; also they allow for comparisons between country-based screening programmes, intra-country screening regimes and FFDM machines. 3. Identification of FFDM machine inaccuracies which can lead to errors in practice, for instance inaccurate breast cancer risk stratification for future screening and lesion localisation as part of biopsy processes. 4. Analyses of computer screen display capabilities for technical checking and reporting of FFDM images. Our work here has already found that the technical checking monitors located in the clinical rooms might not be of an adequate standard to check images before sending them for reporting.
Our practice-based research mainly relates to improving FFDM image quality and screening client experience during the imaging process. Examples of our research include: 1. identification and minimisation of compression force variability between and within practitioners. We were the first to prove the existence of this, initially focusing our work on a UK population. Since then we have published a major piece of research which assessed the entire screening population of Norway. Impact from this has been high, with an international software company introducing an automated method to assess practitioner variability. This, it is hoped, will allow for easy identification of outliers and the ability to implement solutions on a global scale. 2. Interval cancers are cancers which occur between screening rounds. The way in which they are evaluated within our breast screening service is biased. We are working towards creating a new method to investigate and classify interval cancers. 3. Improving FFDM positioning technique to ensure standardisation, minimise discomfort and improve lesion detection performance. 4. Assessing the impact of visual acuity in breast cancer detection performance with a view to setting standards for eye sight checking (similar to driving a car).
The Word of Mouth Mammogram e-Network (WoMMeN) team met for the final time in December 2017 with retirement of the PI, Dr Leslie Robinson, coinciding with the achievement of the project’s main aim - the creation and evaluation of an online hub to provide information and promote awareness of breast screening mammography. WoMMeN was developed by a high-quality research team of mammography practitioners, multi-disciplinary academics and patients, who through their work have achieved success in establishing a presence in the field of Social Media (SoMe) within breast screening.
Since 2012, the WoMMeN team has achieved the following:
The following publications have also been generated as a direct result of this project:
The following Grant income is associated with this project:
Offshoots from the project, for example the development of a national Social Media education hub, continue and will be led by Dr Cristina Vasilica, one of the WoMMeN project team members from the School of Health and Society. Leslie extends her gratitude and appreciation of all those involved in making the WoMMeN team a success.
1. Digital Mammography: A holistic approach, Hogg P, Kelly J and Mercer C, Springer, 2015, ISBN 978-3-319-04831-4
* Correct as of 01/01/2017
X-ray - Dose and Image Quality Optimisation, and Lesion Detection Performance
Theme Lead: Dr Andrew England
This research relates directly to general radiography imaging practice. We investigate and solve a range of clinically relevant imaging problems that face practitioners on a daily basis. Radiation dose and dose optimisation is a serious concern and can be a limitation when attempting to preserve the diagnostic quality of the image. This research theme covers a large range of imaging modalities and examinations. We use a range of methods within this research theme:
Many aspects of this research have a close relationship with student learning in our BSc Diagnostic Radiography.