ICR/RM XNAT Repository

Research powered by XNAT

XNAT is an advanced management system for research images. It uses multiple technologies to provide researchers with the tools they need to process data and view data. The ICR has been at the forefront of developing new capabilities for XNAT, in particular, the ICR-XNAT-OHIF viewer (see Doran et al. Tomography 8.1 (2022). The XNAT Team has the privilege of working with outstanding scientists both locally and internationally, and our tools help them to deliver high-impact clinical studies. This section describes some of the scientific advances we have been part of.

Recent publications for projects supported by XNAT

[1]   Featured publication Simon J Doran, Theo Barfoot, Linda Wedlake, Jessica M Winfield, James Petts, Ben Glocker, Xingfeng Li, Martin Leach, Martin Kaiser, Tara D Barwick, Aristeidis Chaidos,  Laura Satchwell, Neil Soneji, Khalil Elgendy, Alexander Sheeka, Kathryn Wallitt, Dow-Mu Koh, Christina Messiou, Andrea Rockall, Curation of myeloma observational study MALIMAR using XNAT: solving the challenges posed by real-world data, submitted to Insights into Imaging

[2]   Featured publication Amani Arthur; Matthew Orton; Robby Emsley; Sharon Vit; Christian Morland-Kelly; Dirk Strauss; Jason Lunn; Simon Doran; Hafida Lmalem; Axelle Nzokirantevye; Saskia Litiere; Sylvie Bonvalot; Rick Haas; Alessandro Gronchi; Dirk Van Gestel; Anne Ducassou; Chandrajit P Raut; Pierre Meeus; Mateusz Spalek; Matthew Hatton; Khin Thway; Cyril Fisher; Robin Jones; Paul Huang; Christina Messiou. Radiomics in sarcoma of the retroperitoneum (RADSARC-R): A novel externally validated CT-based radiomics model for the prediction of histological subtype and tumor grade Lancet Oncology, 10.1016/S1470-2045 (2023)

[3]   Sam Keaveney, Alina Dragan, Mihaela Rata, Matthew Blackledge, Erica Scurr, Jessica M. Winfield, Joshua Shur, Dow-Mu Koh, Nuria Porta, Antonio Candito, Alexander King, Winston Rennie, Suchi Gaba, Priya Suresh, Paul Malcolm, Amy Davis, Anjumara Nilak, Aarti Shah, Sanjay Gandhi, Mauro Albrizio, Arnold Drury, Guy Pratt, Gordon Cook, Sadie Roberts, Matthew Jenner, Sarah Brown, Martin Kaiser & Christina Messiou, Insights into Imaging 14, 170 (2023)

[4]   Escudero Sanchez L, Buddenkotte T, Al Sa’d M, McCague C, Darcy J, Rundo L, Samoshkin A, Graves MJ, Hollamby V, Browne P, Crispin-Ortuzar M. Integrating Artificial Intelligence Tools in the Clinical Research Setting: The Ovarian Cancer Use Case, Diagnostics 13(17), 2813 (2023)

[5]   Featured publication Matthew R Orton, Evan Hann, Simon J Doran, Scott TC Shepherd, Derfel Ap Dafydd, Charlotte E Spencer, Jose I Lopez, Víctor Artahona, Francesca Castagnoli, Hannah Warren, Joshua Shur, Christina Messiou, James Larkin, Samra Turajlic on behalf of the TRACERx Renal Consortium, Dow-Mu Koh. Interpretability of radiomics models is improved when using feature group selection strategies for predicting molecular and clinical targets in clear-cell renal cell cancer: insights from the TRACERx Renal study, Cancer Imaging 23(1), 76 (2023)

[6]   Featured publication Xiao Fu, Yue Zhao, Jose Lopez, Andrew Rowan, Lewis Au, Annika Fendler, Steve Hazell, Hang Xu, Stuart Horswell, Scott Shepherd, Lavinia Spain, Fiona Byrne, Gordon Stamp, Tim O’Brien, David Nicol, Marcellus Augustine, Ashish Chandra, Sarah Rudman, Antonia Toncheva, Andrew Furness, Lisa Pickering, Matthew Orton, Simon Doran, Dow-Mu Koh, Christina Messiou, Derfel ap Dafydd, Santosh Kumar, James Larkin, Charles Swanton, Erik Sahai, Kevin Litchfield, Samra Turajlic, Paul Bates, Spatial patterns of tumour growth impact clonal diversification: computational modelling and evidence in the TRACERx Renal study, Nature Ecology and Evolution, 6(1), 88–102(2022)

[7]   Featured publication Benjamin Hunter, Mitchell Chen, Prashanthi Ratnakumar, Esubalew Alemu, Andrew Logan, Kristofer Linton-Reid, Daniel Tong, Nishanthi Senthivel, Amyn Bhamani, Susannah Bloch, Samuel V. Kemp, Laura Boddy, Sejal Jain, Shafick Gareeboo, Bhavin Rawal, Simon Doran, Neal Navani, Arjun Nair, Catey Bunce, Stan Kaye, Matthew Blackledge, Eric O. Aboagye, Anand Devaraj, Richard W. Lee, EBioMedicine Dec 1;86:104344 (2022)

[8]   Mihaela Rata, Matthew Blackledge, Erica Scurr, Jessica Winfield, Dow-Mu Koh, Alina Dragan, Antonio Candito, Alexander King, Winston Rennie, Suchi Gaba, Priya Suresh, Paul Malcolm, Amy Davis, Anjumara Nilak, Aarti Shah, Sanjay Gandhi, Mauro Albrizio, Arnold Drury, Sadie Roberts, Matthew Jenner, Sarah Brown, Martin Kaiser and Christina Messiou, Insights into Imaging. 13(1), 1–6 (2022)

[9]   Featured publication Hindocha S, Charlton TG, Linton-Reid K, Hunter B, Chan C, Ahmed M, Greenlay EJ, Orton M, Bunce C, Lunn J, Hindocha S, Charlton TG, Linton-Reid K, Hunter B, Chan C, Ahmed M, Greenlay EJ, Orton M, Bunce C, Lunn J, Doran SJ. Gross tumour volume radiomics for prognostication of recurrence & death following radical radiotherapy for NSCLC. Gross tumour volume radiomics for prognostication of recurrence & death following radical radiotherapy for NSCLC. NPJ Precision Oncology. Oct 27;6(1):1-11 (2022)

[10]   Satchwell L, Wedlake L, Greenlay E, Li X, Messiou C, Glocker B, Barwick T, Barfoot T, Doran S, Leach MO, Koh DM. Development of machine learning support for reading whole body diffusion-weighted MRI (WB-MRI) in myeloma for the detection and quantification of the extent of disease before and after treatment (MALIMAR): protocol for a cross-sectional diagnostic test accuracy study. BMJ Open. Oct 1;12 (2022)

[11]   Francesca Castagnoli, Simon Doran, Jason Lunn, Anna Minchom, Christina Messiou, Dow-Mu Ko, Splenic volume as a predictor of treatment response in patients with non-small cell lung cancer receiving immunotherapy, PLoSOne Jul 7;17(7):e0270950

[12]   Simon J Doran, Mohammad Al Sa’d, James A Petts, James Darcy, Kate Alpert, Woonchan Cho, Lorena Escudero Sanchez, Sachidanand Alle, Ahmed El Harouni, Brad Genereaux, Erik Ziegler, Gordon J Harris, Eric O Aboagye, Evis Sala, Dow-Mu Koh, Dan Marcus, Integrating the OHIF Viewer into XNAT: Achievements, Challenges and Prospects for Quantitative Imaging Studies, Tomography, 8(1), 497–512 (2022)

[13]   Simon J Doran, Santosh Kumar, Matthew Orton, James d’Arcy, Fenna Kwaks, Elizabeth O’Flynn, Zaki Ahmed, Kate Downey, Mitch Dowsett, Nicholas Turner, Christina Messiou, Dow-Mu Koh, “Real-world” radiomics from multi-vendor MRI: an original retrospective study on the prediction of nodal status and disease survival in breast cancer, as an exemplar to promote discussion of the wider issues, Cancer Imaging, 21(1), 1–18 (2021)

[14]   M McAteer, JPB O’Connor, DM Koh, H Leung, S Doran, M Jauregui-Osoro, N Muirhead, C Brew-Graves, E Plummer, E Sala, T Ng, EO Aboagye, G Higgins, S Punwani, Introduction to the National Cancer Imaging Translational Accelerator (NCITA): a UK-wide infrastructure for multicentre clinical translation of cancer imaging biomarkers, British Journal of Cancer 125, 1462–1465 (2021)

[15]   Benjamin W Wormald, Simon Doran, Thomas EJ Ind, James d’Arcy, James Petts, Nandita M de Souza, Radiomic features of cervical cancer on T2- and diffusion- weighted MRI: prognostic value in tumors suitable for trachelectomy, Benjamin Wormald, Gynecologic oncology, 156(1), 107–114 (2020)

[16] James Darcy, Simon J Doran, Matthew Orton, Image processing at scale by containerizing MATLAB, Ch. 18 in Diagnostic Radiology Physics with MATLAB®, Eds. Johan Helmenkamp, Robert Bujila, Gavin Poludniowski, 1st Edition, Taylor & Francis, Boca Raton (2020)