Abstract: There is an ever-increasing burden on imaging departments to deliver high-throughput assessment of medical images.  MRI in particular provides the advantage of full-body coverage and and a variety of quantitative imaging techniques, such as diffusion-weighted MRI, that can offer potent biomarkers for disease response and prognosis; with the advent of accelerated imaging techniques, many quantitative images can now be acquired in a single patient scan.  Increases in computational power and the advent of methodologies such as deep-learning may help to deliver on the promise of truly personalised, image-guided therapies; by helping clinicians to better understand the complexities within multi-parametric MRI it may be possible to derive a non-invasive “digital biopsy” that can be monitored during treatment.  In this presentation, we will review recent developments within the Computational Imaging group at the Institute of Cancer Research and Royal Marsden Hospital, demonstrating how novel algorithms and deep learning can be used to assist in the response assessment of advanced prostate cancer and soft-tissue sarcoma.

Speaker Bio: Dr Matt Blackledge is the team-leader of computational imaging at the ICR, where he has been developing computational techniques in MRI for over a decade.  He is funded by both CRUK and Sarcoma UK to innovate novel approaches to image analysis from MRI and X-ray CT to improve cancer patient outcomes in a variety of disease types.  He is particularly interested in how AI can be used to (i) further accelerate MR-image acquisition, (ii) understand cancer heterogeneity in images, and (iii) probe the link between quantitative imaging biomarkers and their underlying biology.