This seminar is being delivered by the Data Science and Machine Learning workstream of the CRUK RadNet Cambridge research programme. The aim of this workstream is to provide computational tools that help across a range of radiotherapy research projects, with a focus on image analysis. In the seminar we will provide updates on three areas of our work:
Hamlet.rt is a multi-centre prospective radiomics study in radiation therapy and was the first project to be awarded a CRUK RadNet collaboration award. Raj Jena will present Hamlet.rt trans, a proposal for a translational biomarker sub-study evaluating the utility of circulating tumour DNA detection and senescence characterisation in patients undergoing radiotherapy.
Registration of images for analysis of radiation dose and tumour recurrence is a core element. We provide tools to perform this analysis at the human and animal model length scale. Hannah Pullen will present an update on how the tools are being used to analyse the data from the practice defining IMPORT studies of partial breast irradiation. Karl Harrison will also discuss how our rich datasets and tooling are being used for a range of undergraduate physics students projects, allowing us to bring new ways of thinking and analysing image data.
Finally Ceilidh Welsh and Gill Barnett will give an update on the tools and techniques we are using novel statistics and machine learning to integrate single nucleotide polymorphism (SNP) data with detailed reports of radiation toxicity. Our aim is to find genetic determinants of radiation toxicity – an area of analysis known as Radiogenomics.
The seminar will take place from 16:00 – 17:00 with drinks from 17:00 – 17:30, if you would like to attend please email Nicky Le Blond to reserve your place on firstname.lastname@example.org.