Mechanical Engineering


Saffari wins new grant to research prostate cancer detection

11 December 2022

Professor Nader Saffari has been awarded a £1.13 million grant from the EPSRC to develop a new concept and device for the detection of prostate cancer.

a portrait of Professor Nader Saffari

Professor Nader Saffari has been awarded a £1.13 million grant from the EPSRC to develop a new concept and device for the detection of prostate cancer. This project will be a collaboration with Dr Antonio Gomez (Mech. Eng.), Prof Andreas Demosthenous of UCL Electrical and Electronic Engineering, Dr Marta Betcke of UCL Computer Science, Prof Mark Emberton Dean of UCL Faculty of Medical Sciences and colleagues from the University of Granada in Spain.

Prostate Cancer (PCa) is the most common cancer in men in the UK. It is also the second cause of cancer death after lung cancer. It represents around 13% of all cases of cancer and accounts for 7% of all UK cancer deaths.

Current research is investigating whether modern imaging techniques can identify the site of the tumour. There are two main streams that are showing promising preliminary results: Magnetic Resonance Imaging (MRI) and Elastography techniques. MRI is showing promising results, particularly when using a multi-parametric approach (mpMRI), but its high cost and limited availability hold back its wider use, particularly in resource-poor parts of the world.

In welcoming the new funding, Professor Saffari wrote,

“The aim of this study is to develop a system and prove the feasibility of using a Transurethral-Shear Wave Elastography (TU-SWE) approach for diagnosis and ablation monitoring of PCa. The team have demonstrated the proof-of-concept for the method using a scaled version of a novel disposable probe and the image reconstruction software.

a diagram of a device inserted into a human prostate
The end point of this project will see the production of a TU-SWE medical prototype probe with its electronic control system following the same fabrication processes established for the proof-of-concept laboratory prototype. Improvement of the software for image reconstruction will include extending the model of wave propagation to realistic 3D geometries and using machine learning to enhance the image resolution with data from a parallel clinical study.”


This diagnostic and treatment monitoring tool will thus lead to earlier detection of prostate cancers and more efficacious and therefore cost-effective cancer treatments, saving the NHS time, resources and money.