Aboagye, EO

Brew-Graves, C

Doran, S

Higgins, G

Jauregui-Osoro, M

Koh, D-M

Leung, H

McAteer, M

Muirhead, N

Ng, T

O'Connor, JPB

Plummer, E

Punwani, S

Sala, E

Duric, Martina

O'Connor, James PB

Koh, Dow-Mu

Leung, Hing

Doran, Simon

Jauregui-Osoro, Maite

Muirhead, Nicola

Brew-Graves, Chris

Plummer, Elizabeth

Sala, Evis

Ng, Tony

Aboagye, Eric O

Higgins, Geoffrey

Punwani, Shonit

Oxford University Research Archive

COMMENT OPENIntroduction to the National Cancer Imaging TranslationalAccelerator (NCITA): a UK-wide infrastructure for multicentreclinical translation of cancer imaging biomarkersM. A. McAteer 1✉, J. P. B. O’Connor2,3, D. M. Koh3, H. Y. Leung 4, S. J. Doran3, M. Jauregui-Osoro5, N. Muirhead6, C. Brew-Graves6,E. R. Plummer7, E. Sala 8, T. Ng9,10, E. O. Aboagye5, G. S. Higgins1 and S. Punwani6© The Author(s) 2021The National Cancer Imaging Translational Accelerator (NCITA) is creating a UK national coordinated infrastructure for acceleratedtranslation of imaging biomarkers for clinical use. Through the development of standardised protocols, data integration tools andongoing training programmes, NCITA provides a unique scalable infrastructure for imaging biomarker qualification usingmulticentre clinical studies.British Journal of Cancer (2021) 125:1462–1465; https://doi.org/10.1038/s41416-021-01497-5Imaging biomarkers have potential to provide objective, minimallyinvasive tools for the diagnosis and therapeutic management oftumours, including quantitative assessment of tissue microstruc-ture, metabolism and function. However, clinical imaging withinhealthcare systems remains largely limited to assessment ofanatomical changes in tumour size, with a few notable exceptionssuch as assessment of tumour metabolism using positronemission tomography (PET) with 2-deoxy-2-[fluorine-18]fluoro-D-glucose integrated with computed tomography ([18F]FDG PET-CT)[1, 2]. This gap between translatable imaging biomarker researchand clinical application reflects the challenges in crossing two key‘translational gaps’ [3, 4]; namely translation of promisingcandidates into fully validated and standardised products andthe provision of robust evidence to support their implementationand adoption into clinical practice [5]. For complex multicentreimaging biomarker studies, differences in imaging sequences fordifferent scanners, field strengths and vendors and inter- andintra-observer variability in image acquisition and analysis posesignificant challenges for standardisation. Here, we outline a newcoordinated infrastructure designed to accelerate the clinicaltranslation of robust and reproducible imaging biomarkers totransform cancer diagnosis and improve healthcare outcomes forpatients.The National Cancer Imaging Translational Accelerator (NCITA)is a clinical imaging research consortium, which is creating thenecessary integrated infrastructure to accelerate robust qualifica-tion of cancer imaging biomarkers for clinical use, as proposed inthe Imaging Biomarker Roadmap for Cancer Studies [5]. Estab-lished in 2019, through Cancer Research UK (CRUK) Acceleratoraward funding, NCITA builds on previous Cancer Imaging CentresInitiatives (2008–2018), funded by CRUK and the Engineering andPhysical Sciences Research Council (EPSRC), which were pivotal indriving innovation in biomarker research using novel imagingtechniques [6–11]. NCITA brings together nine UK centres ofexcellence for medical imaging, namely, University CollegeLondon, The University of Manchester, University of Oxford, King’sCollege London, The Institute of Cancer Research (ICR), ImperialCollege London, University of Cambridge, University of Glasgowand Newcastle University (Supplementary 1). This multi-institutional collaborative network includes medical imagingexperts, clinical oncologists, physicists and research scientistswho are developing standardised imaging biomarker qualificationpipelines to accelerate the development of qualified imagingbiomarkers using multicentre studies.The NCITA infrastructure includes three cross-institutional units(imaging clinical trials unit (CTU), quality assurance/quality control(QA/QC) and repository units) and three activity groups (engage-ment, training and contracts management), which together withthe Governance Group, work in synergy to facilitate cross-sectortranslational imaging biomarker research. The goals of NCITA areto establish standardised protocols and locked-down quality-assured processes for imaging biomarker qualification and afederated research data repository for secure data storage andsharing between study sites. The repository incorporates auto-mated QA and post-hoc computational image analysis usingcontainerised workflows, novel machine learning and artificialintelligence (AI) tools (Fig. 1). To improve study efficiencies, NCITAis developing unified contracts, policies and standard operatingprocedures that transcend individual institutions. Throughengagement with key imaging stakeholders, NCITA will developReceived: 11 March 2021 Accepted: 9 July 2021Published online: 27 July 20211Department of Oncology, University of Oxford, Oxford, UK. 2Division of Cancer Sciences, The University of Manchester, Manchester, UK. 3Division of Radiotherapy and Imaging,The Institute of Cancer Research and Royal Marsden Hospital, London, UK. 4Beatson Institute for Cancer Research, University of Glasgow, Glasgow, UK. 5Department of Surgeryand Cancer, Imperial College London, London, UK. 6Centre for Medical Imaging, University College London, London, UK. 7Northern Institute for Cancer Care, Freeman Hospitaland Newcastle University, Newcastle upon Tyne, UK. 8Department of Radiology, University of Cambridge and CRUK Cambridge Centre, Cambridge, UK. 9UCL Cancer Institute,University College London, London, UK. 10School of Cancer and Pharmaceutical Sciences, King’s College London, London, UK. ✉email: martina.mcateer@oncology.ox.ac.ukwww.nature.com/bjc British Journal of CancerPublished on Behalf of CRUKconsensus guidelines for robust qualification of imaging biomar-kers to instill reliability in the development pathway andaccelerate clinical adoption. NCITA also organises ongoing work-shops, events and online training materials to ensure that thevaluable skills and expertise of the NCITA workforce aresustainable and scalable.NCITA supports a portfolio of Exemplar studies, selected todemonstrate the effectiveness of the infrastructure in acceleratingqualification and translation of these promising imaging biomar-kers (Supplemental Table). NCITA infrastructure support is alsoaccessible to external clinical researchers from academia andindustry through NCITA’s study adoption process. Internationalpartners are also eligible to apply. For example, NCITA providesrepository support for CRUK International Alliance for Cancer EarlyDetection (ACED), which includes partners at Stanford Universityand Oregon Health and Science University, USA. Researchers areencouraged to contact NCITA early during study development byemail (ncita.general@ucl.ac.uk) or via the website (ncita.org.uk/contact), preferably prior to applying for grant funding. Whilecancer imaging studies are a key focus, clinical research studies inother disease areas involving AI algorithm development, trainingand validation will be considered, especially if these studies arethought to benefit AI algorithm development for future earlycancer detection studies. Study applications are reviewed by theprogramme and unit managers and the governance group toassess the quality of the study proposal, funding plans and status(Supplementary 2). Where studies are successfully adopted, arepresentative from the new institution or company will beencouraged to join the relevant NCITA management, trial steeringcommittee or consensus group to facilitate knowledge transferand potential growth of the required infrastructure.Early phase observational and validation-based studies as well aslater phase interventional and therapeutic studies are supported bythe NCITA CTU using a range of imaging technologies, includingwhole-body MRI, hyperpolarised 13C MRI, multi-parametric MRI,oxygen-enhanced MRI, PET, PET-MRI and PET-CT. The NCITA CTUcomplements local study infrastructure and provides an adaptablegovernance framework that can be tailored to the study develop-ment phase. This bespoke service provides excellent value formoney and aids smoother funding applications and approvals. Thisis especially important for observational imaging studies, which areoften deprioritised when competing for limited National Institute forHealth Research (NIHR) infrastructure support, in favour of interven-tional cancer studies.The QA/QC Unit supports study setup, technical and biologicalvalidation, protocol development and staged lockdown ofstandardised image acquisition, processing and analysis meth-odologies. Efficient management of site equipment, processdocumentation, workflows, audits, training and continuous qualityimprovements across study sites is facilitated by a centralisedquality management system. The QA/QC Unit is also establishing anational MRI Core Lab, to support site evaluation, site qualificationand performance monitoring for MRI multicentre studies (Supple-mentary 3). This will help to elevate the quality of MRI biomarkersand improve translation efficiency. For NCITA PET imaging studies,NCITA will liaise closely with the UK PET Core Lab at St Thomas’Hospital London to ensure the studies are performed to agreedstandards.The Repository Unit is developing a sustainable, cross-institutional federated repository structure for secure data storage,integration, analysis and sharing. The repository is based on aneXtensible Neuroimaging Archive Toolkit (XNAT) prototype,originally built and hosted by the ICR [12] under the aegis ofICR’s CRUK-EPSRC Cancer Imaging Centre, and related work at theCRUK Cambridge Institute. The repository supports short- or long-term secure data archival, and encompasses the full range of datamaturity including initial data acquisition, through various levels ofdata curation, to controlled release of deidentified data as acommunity resource. For example, the NCITA repository alreadycontains a large COVID database including the UK National Covid-19 Chest Imaging Database (NCCID). The repository will beinteroperable with and receive data directly from the NationalHealth Service (NHS), including NHS Digital’s Trusted ResearchEnvironment services.DICOM dataThe vision: easy access to all forms of imagingnon-DICOMdataQueryVisualiseProvenanceProcessFig. 1 High-level schematic overview of the NCITA Image Repository Unit. Clinical study data from both DICOM and non-DICOM modalitiesare curated securely, enabling users to perform both automated data quality assurance (thus improving data harmonisation) and bespokeanalysis using containerised workflows, including novel AI tools. Processing outputs will be stored back in the repository with completeprovenance. Cohort-building tools, which may use natural language processing or content-based image retrieval, together with enhancedvisualisation, will allow clinicians and scientists to participate in virtual tumour boards, to enable collaborative knowledge sharing andcommunication for improving clinical interpretation of complex imaging biomarker readouts.M.A. McAteer et al.1463British Journal of Cancer (2021) 125:1462 – 14651234567890();,:NCITA’s data sharing solutions are based on the FAIR principles[13], that data are findable, accessible, interoperable and reusable.For NCITA’s adopted studies, streamlined data access procedureswill enable data sharing, including an approach to the relevantEthics and Trial Steering Committees. For non-NCITA sites, dataaccess will involve an application process and will be regulated byaudited procedures. Open-access data resources will also bedeveloped for the imaging research community worldwide.The Repository and QA/QC Units are developing quality-assuredpipelines for imaging biomarker qualification from source imagedata. Recent work includes implementation of the VERDICTtechnique [14], radiomics pipelines in line with InternationalBiomarker Standardisation Initiative guidelines [15] and a pluginto enable automatic assessment of incoming imaging datasets todetermine compliance with study protocols. The Repository Unit isalso developing AI-assisted image annotation for radiologists,linking of curated imaging datasets to publications and genera-tion of datasets for AI development. The Repository Unit is alsoengaged in the release lifecycle of XNAT and is the integrator ofthe Open Health Imaging Foundation (OHIF) viewer into XNAT[16], which provides a flexible framework for building web-basedimaging applications to support clinical imaging research.A key goal for NCITA is to generate consensus on how theimaging biomarker development pathway can be improved toachieve more efficient translation of quality-assured imagingbiomarkers into clinical practice. The NCITA Engagement Groupare engaging with key imaging stakeholders, to facilitate theestablishment of a consensus group to agree and publishrecommendations for accelerating robust qualification and adop-tion of imaging biomarkers for clinical use. The EngagementGroup also facilitates clinical researchers from academia andindustry to access the NCITA infrastructure and works closely withCRUK’s Commercial Partnerships team to ensure translationalsupport for new discoveries arising from exemplar projects andother projects supported by CRUK. Other engagement activitiesinclude dissemination of news, events and information throughthe NCITA website (https://www.ncita.org.uk), social mediaaccounts (NCITA Imaging (@imaging_cancer)|Twitter and Linke-dIn), press releases and publications.During the 5-year CRUK Accelerator Award, NCITA will haveestablished the necessary integrated infrastructure to facilitateaccelerated translation of imaging biomarkers for clinical applica-tion. To ensure continued growth and sustainability, NCITA willlink with NHS initiatives including the NIHR Biomedical ResearchCouncil/Clinical Research Network and NIHR Imaging Group, aswell as funding bodies, charities and industrial partnerships. Thesustainability of NCITA will have significant benefits in streamlin-ing future clinical imaging studies and providing ongoing trainingof a new generation of highly skilled medical imaging researchersto accelerate personalised and precision medicine for cancer care.DATA AVAILABILITYNot applicable.REFERENCES1. Boellaard R, Delgado-Bolton R, Oyen WJ, Giammarile F, Tatsch K, Eschner W, et al.FDG PET/CT: EANM procedure guidelines for tumour imaging: version 2.0. Eur JNucl Med Mol Imaging. 2015;42:328–54.2. Fletcher JW, Djulbegovic B, Soares HP, Siegel BA, Lowe VJ, Lyman GH, et al.Recommendations on the use of 18F-FDG PET in oncology. J Nucl Med.2008;49:480–508.3. Black N. The Cooksey review of UK health research funding. BMJ.2006;333:1231–2.4. Sung NS, Crowley WF Jr, Genel M, Salber P, Sandy L, Sherwood LM, et al. Centralchallenges facing the national clinical research enterprise. JAMA.2003;289:1278–87.5. O’Connor JP, Aboagye EO, Adams JE, Aerts HJ, Barrington SF, Beer AJ, et al.Imaging biomarker roadmap for cancer studies. Nat Rev Clin Oncol.2017;14:169–86.6. Sharma R, Aboagye E. Development of radiotracers for oncology-the interfacewith pharmacology. Br J Pharmacol. 2011;163:1565–85.7. Scarsbrook AF, Bottomley D, Teoh EJ, Bradley KM, Payne H, Afaq A, et al. Effect of(18)F-fluciclovine positron emission tomography on the management of patientswith recurrence of prostate cancer: results from the FALCON trial. Int J RadiatOncol Biol Phys. 2020;107:316–24.8. Arulappu A, Battle M, Eisenblaetter M, McRobbie G, Khan I, Monypenny J, et al. c-Met PET imaging detects early-stage locoregional recurrence of basal-like breastcancer. J Nucl Med. 2016;57:765–70.9. Diocou S, Volpe A, Jauregui-Osoro M, Boudjemeline M, Chuamsaamarkkee K, Man F,et al. [(18)F]tetrafluoroborate-PET/CT enables sensitive tumor and metastasis in vivoimaging in a sodium iodide symporter-expressing tumor model. Sci Rep. 2017;7:946.10. Eisenblaetter M, Flores-Borja F, Lee JJ, Wefers C, Smith H, Hueting R, et al.Visualization of tumor-immune interaction—-target-specific imaging of S100A8/A9 reveals pre-metastatic niche establishment. Theranostics. 2017;7:2392–401.11. Salem A, Little RA, Latif A, Featherstone AK, Babur M, Peset I, et al. Oxygen-enhanced MRI is feasible, repeatable, and detects radiotherapy-induced changein hypoxia in xenograft models and in patients with non-small cell lung cancer.Clin Cancer Res. 2019;25:3818–29.12. Doran SJ, d’Arcy J, Collins DJ, Andriantsimiavona R, Orton M, Koh DM, et al.Informatics in radiology: development of a research PACS for analysis of func-tional imaging data in clinical research and clinical trials. Radiographics.2012;32:2135–50.13. Wilkinson MD, Dumontier M, Aalbersberg IJ, Appleton G, Axton M, Baak A, et al.The FAIR Guiding Principles for scientific data management and stewardship. SciData. 2016;3:160018.14. Bonet-Carne E, Johnston E, Daducci A, Jacobs JG, Freeman A, Atkinson D, et al.VERDICT-AMICO: Ultrafast fitting algorithm for non-invasive prostate micro-structure characterization. NMR Biomed. 2019;32:e4019.15. Zwanenburg A, Vallieres M, Abdalah MA, Aerts H, Andrearczyk V, Apte A, et al.The image biomarker standardization initiative: standardized quantitativeradiomics for high-throughput image-based phenotyping. Radiology.2020;295:328–38.16. Ziegler E, Urban T, Brown D, Petts J, Pieper SD, Lewis R, et al. Open healthimaging foundation viewer: an extensible open-source framework for buildingweb-based imaging applications to support cancer research. JCO Clin CancerInform. 2020;4:336–45.ACKNOWLEDGEMENTSNoneAUTHOR CONTRIBUTIONSMAM drafted the manuscript and all authors contributed to the drafting or revising ofthe manuscript and approved the final version.FUNDINGNCITA is funded by a Cancer Research UK Accelerator Award (C42780/A27066(University College London; PI Professor Shonit Punwani); C34326/A28684 (University ofOxford; PI Professor Geoff Higgins); C1922/A28683 (University of Manchester; PIProfessor James O’Connor); C22479/A28667 (University of Cambridge; PI Professor EvisSala); C2536/A28680 (Imperial College London; PI Professor Eric Aboagye); C7273/A28677 (Institute of Cancer Research, London; PI Professor Dow Mu Koh); C1519/A28682(King’s College London; PI Professor Tony Ng). The Panorama Trial (NCITA Exemplarstudy) received support from the Cancer Research UK KCL-UCL Comprehensive CancerImaging Centre (C1519/A16463 (2013-18) C1519/A10331 (2008-13)).ETHICS APPROVAL AND CONSENT TO PARTICIPATENot applicable.CONSENT FOR PUBLICATIONNot applicable.COMPETING INTERESTSThe authors declare no competing interests.M.A. McAteer et al.1464British Journal of Cancer (2021) 125:1462 – 1465ADDITIONAL INFORMATIONSupplementary information The online version contains supplementary materialavailable at https://doi.org/10.1038/s41416-021-01497-5.Correspondence and requests for materials should be addressed to M.A.M.Reprints and permission information is available at http://www.nature.com/reprintsPublisher’s note Springer Nature remains neutral with regard to jurisdictional claimsin published maps and institutional affiliations.Open Access This article is licensed under a Creative CommonsAttribution 4.0 International License, which permits use, sharing,adaptation, distribution and reproduction in anymedium or format, as long as you giveappropriate credit to the original author(s) and the source, provide a link to the CreativeCommons license, and indicate if changes were made. The images or other third partymaterial in this article are included in the article’s Creative Commons license, unlessindicated otherwise in a credit line to the material. If material is not included in thearticle’s Creative Commons license and your intended use is not permitted by statutoryregulation or exceeds the permitted use, you will need to obtain permission directlyfrom the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.© The Author(s) 2021M.A. McAteer et al.1465British Journal of Cancer (2021) 125:1462 – 1465

English

Introduction to the National Cancer Imaging Translational Accelerator (NCITA): a UK-wide infrastructure for multicentre clinical translation of cancer imaging biomarkers

Introduction to the National Cancer Imaging Translational Accelerator (NCITA): a UK-wide infrastructure for multicentre clinical translation of cancer imaging biomarkers

Abstract

Similar works

Full text

Available Versions

Oxford University Research Archive