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Abstract #0242

A Repository-Integrated Quantitative Imaging Data Analysis Pipeline for Enabling Multi-Centre Clinical Biomarker Studies

Jonathan R Birchall1, Michael Berks2, Sam Keaveney3,4, Andrew Gill1, Edith Gallagher5, Julia E Markus6, Simon Doran3,4, Ross Little2, Michael Dubec2,7, James P B O'Connor2,4,8, and Penny L Hubbard Cristinacce2
1Department of Radiology, University of Cambridge, Cambridge, United Kingdom, 2Department of Health Sciences, University of Manchester, Manchester, United Kingdom, 3Royal Marsden NHS Foundation Trust, Sutton, United Kingdom, 4Department of Radiotherapy and Imaging, Institute for Cancer Research, London, United Kingdom, 5Department of Oncology, University of Oxford, Oxford, United Kingdom, 6Department of Medicine, University College London, London, United Kingdom, 7Christie Medical Physics and Engineering, The Christie NHS Foundation Trust, Manchester, United Kingdom, 8Department of Radiology, The Christie NHS Foundation Trust, Manchester, United Kingdom

Synopsis

Keywords: Software Tools, Data Processing, Data Analysis

Motivation: Robust evaluation of novel quantitative imaging biomarkers in multi-centre imaging trials requires harmonised workflow for storage, quality control and analysis of imaging data to facilitate clinical translation.

Goal(s): To establish a standardised, repository-integrated framework for quantitative MR data analysis to aid reproducibility.

Approach: A software container for quantitative MR data analysis was created using Docker, integrated with the XNAT imaging repository and demonstrated using example data.

Results: Repository-integrated software was used to generate quantitative maps of T1, ADC and hypoxia, as well as DCE and IVIM modelling parameters in primary and nodal tumours from a patient with head-and-neck cancer.

Impact: Quantitative MR biomarker translation can be accelerated by standardisation of analysis protocols across multi-centre trials. Integration of containerised, user-configurable data analysis software within imaging repositories will improve repeatability and lower the barrier for entry to clinical trial involvement.

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