Dr Matthew Grech-Sollars - CMIC/WEISS Joint Seminar Series
07 December 2022, 1:00 pm–2:00 pm
Dr Matthew Grech-Sollars- a talk as part of CMIC/WEISS Joint Seminar Series
UCL Centre for Medical Image Computing and Wellcome/EPSRC Centre for Interventional and Surgical Sciences
Speaker: Dr Matthew Grech-Sollars
Title: Challenges of Clinical Translation in Brain Tumour Imaging
The implementation of advanced imaging techniques in a clinical environment is challenging. In this talk I will introduce brain tumours and present some of the challenges around clinical translation through single-centre and multi-centre clinical studies, and cover both established and newer imaging techniques. Topics covered will include MR Fingerprinting, DTI, PET / MR, and AI in digital pathology.
Dr Matthew Grech-Sollars is an Associate Professor in Quantitative Neuroradiology at University College London and a Clinical Scientist (MRI Physics) at the National Hospital for Neurology and Neurosurgery, University College London Hospitals NHS Foundation Trust. Matthew graduated in Electrical Engineering from the University of Malta in 2005 and after working in industry, he pursued an MSc in Biomedical Engineering with Medical Physics at Imperial College London in 2008-2009. He received his PhD in Medical Physics from University College London in 2014. Matthew then joined Imperial College London as an MRI Physicist, while training as a Clinical Scientist at Imperial College Healthcare NHS Trust. In 2017, he was awarded an Imperial College Research Fellowship, which he carried out until 2021. Prior to joining UCL, Matthew was Principal MRI Physicist at Royal Surrey NHS Foundation Trust. He has a key interest in developing MRI tools for use within a clinical environment, with a particular focus on quantitative MR and neuro-oncology. Matthew has extensive experience of working on multi-centre trials and the implementation of advanced imaging techniques in a clinical environment; including diffusion MR, perfusion MR and MR spectroscopy, as well as experience in PET-MR and AI based techniques.