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Centralized Clinical Trial Imaging Data Management: Practical Guidance from a Comprehensive Cancer Center’s Experience

  • Brandon LeeEmail author
  • A. Abbott
  • S. Davidson
  • L. Syrkin
  • G. LeFever
  • A. D. Van den Abbeele
Article
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Abstract

Medical imaging is an integral part of clinical trial research and it must be managed properly to provide accurate data to the sponsor in a timely manner (Clune in Cancer Inform 4:33–56, 2007; Wang et al. in Proc SPIE Int Soc Opt Eng 7967, 2011). Standardized workflows for site qualification, protocol preparation, data storage, retrieval, de-identification, submission, and query resolution are paramount to achieve quality clinical trial data management such as reducing the number of imaging protocol deviations and avoiding delays in data transfer. Centralization of data management and implementation of relational databases and electronic workflows can help maintain consistency and accuracy of imaging data. This technical note aims at sharing the practical implementation of our centralized clinical trial imaging data management processes to avoid the fragmentation of tasks among various disease centers and research staff, and enable us to provide quality, accurate, and timely imaging data to clinical trial sponsors.

Keywords

Clinical trial and imaging data management Relational database Web form Workflow Imaging de-identification Quality improvement 

Notes

Acknowledgments

The authors wish to thank our Radiography and Support Services Supervisor, Anne Commito, and our imaging data associates, Linda Alce, Quinley Miao, and Anika Manigo, for their excellent work in transitioning to the new image transfer workflow and maintaining the current workload. We also thank our imaging technologist teams for their commitment to high-quality scan acquisitions, protocol compliance, and patient care, and our department management and radiologists for their continuous support. We also wish to recognize and thank our CRCs for their invaluable contributions, teamwork, and patient care for patients enrolled in our clinical trials.

Compliance with Ethical Standards

Conflict of Interest

The authors declare that they have no conflict of interest.

References

  1. 1.
    Clunie DA: DICOM structured reporting and cancer clinical trials results. Cancer Inform. 4:33–56, 2007CrossRefGoogle Scholar
  2. 2.
    Wang F, Lee R, Zhang X, Saltz J: Towards building high performance medical image management system for clinical trials. Proc SPIE Int Soc Opt Eng. 7967, 2011Google Scholar
  3. 3.
    Erickson BJ, Pan T, Marcus DS, Group CIIP: Whitepapers on imaging infrastructure for research: Part 1: general workflow considerations. J Digit Imaging. 25:449–453, 2012CrossRefGoogle Scholar
  4. 4.
    Hedges RA, Goodman D, Sachs PB: Electronic workflow for imaging in clinical research. J Digit Imaging 27:457–462, 2014CrossRefGoogle Scholar
  5. 5.
    Reiner B, Siegel E, Carrino JA, McElveny C: SCAR Radiologic Technologist Survey: analysis of technologist workforce and staffing. J Digit Imaging 15:121–131, 2002CrossRefGoogle Scholar
  6. 6.
    Reiner BI, Siegel EL, Carrino JA, Goldburgh MM: SCAR Radiologic Technologist Survey: analysis of the impact of digital technologies on productivity. J Digit Imaging 15:132–140, 2002CrossRefGoogle Scholar
  7. 7.
    Nitrosi A, Borasi G, Nicoli F, Modigliani G, Botti A, Bertolini M, Notari P: A filmless radiology department in a full digital regional hospital: quantitative evaluation of the increased quality and efficiency. J Digit Imaging 20:140–148, 2007CrossRefGoogle Scholar
  8. 8.
    Reiner B, Siegel E, Carrino JA: Workflow optimization: current trends and future directions. J Digit Imaging 15:141–152, 2002CrossRefGoogle Scholar
  9. 9.
    Abbott A, Kuzuhara Y, Syrkin L, Nguyen QD, McCall K, Qin L, Jacene H, Van den Abeele AD: Bridging the gaps to build the future of clinical and pre-clinical imaging research. J Nucl Med 56:2508, 2015Google Scholar
  10. 10.
    NEMA PS3 / ISO 12052, Digital Imaging and Communications in Medicine (DICOM) Standard. Rosslyn, VA, USA: National Electrical Manufacturers Association; (available free at http://medical.nema.org/)
  11. 11.
    PixelMed Publishing™. DicomCleaner™ website. http://www.pixelmed.com/cleaner.html. Accessed 25 May 2018.
  12. 12.
    RSNA MIRC. DicomEditor website. https://mircwiki.rsna.org/index.php?title=DicomEditor. Accessed 25 May 2018.
  13. 13.
    Syrkin L, Vries D, Lefever G, Locascio T, Kuzuhara Y, Van den Abeele AD: Development of a PET/CT database of patient information and scanning parameters. J Nucl Med 48:199P, 2007Google Scholar

Copyright information

© Society for Imaging Informatics in Medicine 2018

Authors and Affiliations

  1. 1.Department of Imaging and Center for Biomedical Imaging in OncologyDana-Farber Cancer InstituteBostonUSA
  2. 2.Department of Information ServicesDana-Farber Cancer InstituteBostonUSA
  3. 3.Department of RadiologyBrigham and Women’s HospitalBostonUSA
  4. 4.Harvard Medical SchoolBostonUSA

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