Skip to main content

Matthew Marzetti (an associated CDT PhD student)

Research Topic: Novel applications for sarcoma assessment (NASA)

Supervisors: Prof. David Buckley, Prof. Andrew Scarsbrook, Dr Stefan Klein, Dr Martijn Starmans

About Matthew: I graduated from the University of Edinburgh with a bachelor’s degree in computational physics in 2014 and obtained an MSc in Medical Physics from the University of Glasgow in 2015. I went on to achieve registration as a clinical scientist in 2018 while working at NHS Tayside. I joined the Leeds Teaching Hospitals NHS Trust as a clinical scientist in Magnetic Resonance Imaging (MRI) in 2019. During my career I have developed research interests in quantitative MRI. I have recently been awarded an NIHR doctoral fellowship to pursue these interests. My proposed research programme will investigate whether the diagnosis of soft tissue sarcomas can be improved through the use AI and quantitative MRI.

Project Description: Soft tissue sarcomas are a type of cancer that can appear anywhere in the body where there is soft tissue such as muscle or fat. While sarcomas are rare, benign lumps in soft tissue are common and it is currently very difficult to tell the difference between the two using imaging. This means many patients with benign masses are referred for painful biopsies and waiting lists for biopsies are long due to the large diagnostic workload. This research aims to develop an AI algorithm that can differentiate between benign and malignant soft tissue masses using both routine MRI data and advanced quantitative MRI images.