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SINAPSE experts from around Scotland have developed ten online modules designed to explain medical imaging. They are freely available and are intended for non-specialists.

Edinburgh Imaging Academy at the University of Edinburgh offers the following online programmes through a virtual learning environment:

Neuroimaging for Research MSc/Dip/Cert

Imaging MSc/Dip/Cert

PET-MR Principles & Applications Cert

Applied Medical Image Analysis Cert

Online Short Courses

PhD opportunity at Strathclyde: Micro-scale tissue characterisation to help detect and diagnose cancer using ultrasound

Micro-scale assessment of tissue biomechanics for non-invasive cancer staging

Ultrasound elastography is an imaging method that can detect large-scale changes in tissue stiffness to be presented as a colour map or stiffness estimate. However, the physical property that is measured to make the estimate varies with the clinical ultrasound system used, preventing comparisons between machines or over time. The sensitivity with which features can be distinguished by size or stiffness are also limited so elastography is commonly used to establish that further investigation and biopsy are needed.

Tumour tissue is stiff because it is dense, with lots of multiplying cells, a higher density of extracellular matrix fibres, chaotic network of blood vessels and poor lymphatic drainage. But the cells themselves need to be very elastic to escape the tumour, they also spread more quickly when confined. Cells also modify their surroundings so local stiffness increases. These cellular level insights suggest that non-invasive microscale tissue characterisation will reveal new information that could be used in diagnosis and treatment planning.

Advances in high resolution ultrasound hardware and programmable array systems now allow us to probe tissue at the micro-scale. In this project the student will develop micro-scale tissue characterisation by combining elastography with information extracted from the sound signals that are scattered by these tiny tissue volumes. When this data is mapped and compared to pathology we expect distinct patterns to emerge based on disease stage and aggression. This information can be used to help detect and diagnose cancer without the need for biopsy.

For details of this project with Dr Helen Mulvana at the University of Strathclyde, go to

The deadline for application is 5 May 2020