Co-Clinical Imaging Metadata Information (CIMI) for Cancer Research to Promote Open Science, Standardization, and Reproducibility in Preclinical Imaging
Stephen M. Moore,
James D. Quirk,
Andrew W. Lassiter,
Richard Laforest,
Gregory D. Ayers,
Cristian T. Badea,
Andriy Y. Fedorov,
Paul E. Kinahan,
Matthew Holbrook,
Peder E. Z. Larson,
Renuka Sriram,
Thomas L. Chenevert,
Dariya Malyarenko,
John Kurhanewicz,
A. McGarry Houghton,
Brian D. Ross,
Stephen Pickup,
James C. Gee,
Rong Zhou,
Seth T. Gammon,
Henry Charles Manning,
Raheleh Roudi,
Heike E. Daldrup-Link,
Michael T. Lewis,
Daniel L. Rubin,
Thomas E. Yankeelov,
Kooresh I. Shoghi
Affiliations
Stephen M. Moore
Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110, USA
James D. Quirk
Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110, USA
Andrew W. Lassiter
Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110, USA
Richard Laforest
Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110, USA
Gregory D. Ayers
Department of Biostatistics, Vanderbilt University, Nashville, TN 37235, USA
Cristian T. Badea
Quantitative Imaging and Analysis Lab, Department of Radiology, Duke University, Durham, NC 27708, USA
Andriy Y. Fedorov
Brigham and Women’s Hospital and Harvard Medical School, Boston, MA 02115, USA
Paul E. Kinahan
Department of Radiology, University of Washington, Seattle, WA 98195, USA
Matthew Holbrook
Quantitative Imaging and Analysis Lab, Department of Radiology, Duke University, Durham, NC 27708, USA
Peder E. Z. Larson
Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA 94143, USA
Renuka Sriram
Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA 94143, USA
Thomas L. Chenevert
Department of Radiology, University of Michigan Medical School, Ann Arbor, MI 48109, USA
Dariya Malyarenko
Department of Radiology, University of Michigan Medical School, Ann Arbor, MI 48109, USA
John Kurhanewicz
Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA 94143, USA
A. McGarry Houghton
Fred Hutchinson Cancer Center, Seattle, WA 98109, USA
Brian D. Ross
Department of Radiology, University of Michigan Medical School, Ann Arbor, MI 48109, USA
Stephen Pickup
Department of Radiology, Abramson Cancer Center, University of Pennsylvania, Philadelphia, PA 19104, USA
James C. Gee
Department of Radiology, Abramson Cancer Center, University of Pennsylvania, Philadelphia, PA 19104, USA
Rong Zhou
Department of Radiology, Abramson Cancer Center, University of Pennsylvania, Philadelphia, PA 19104, USA
Seth T. Gammon
Department of Cancer Systems Imaging, Division of Diagnostic Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
Henry Charles Manning
Department of Cancer Systems Imaging, Division of Diagnostic Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
Raheleh Roudi
Department of Radiology, Stanford University School of Medicine, Stanford, CA 94305, USA
Heike E. Daldrup-Link
Department of Radiology, Stanford University School of Medicine, Stanford, CA 94305, USA
Michael T. Lewis
Dan L Duncan Comprehensive Cancer Center, Departments of Molecular and Cellular Biology and Radiology, Baylor College of Medicine, Houston, TX 77030, USA
Daniel L. Rubin
Departments of Biomedical Data Science, Radiology and Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA
Thomas E. Yankeelov
Departments of Biomedical Engineering, Diagnostic Medicine and Oncology, Oden Institute for Computational and Engineering Sciences, Livestrong Cancer Institutes, The University of Texas at Austin, Austin, TX 78712, USA
Kooresh I. Shoghi
Mallinckrodt Institute of Radiology, Department of Biomedical Engineering, Siteman Cancer Center, Washington University School of Medicine, St. Louis, MO 63110, USA
Preclinical imaging is a critical component in translational research with significant complexities in workflow and site differences in deployment. Importantly, the National Cancer Institute’s (NCI) precision medicine initiative emphasizes the use of translational co-clinical oncology models to address the biological and molecular bases of cancer prevention and treatment. The use of oncology models, such as patient-derived tumor xenografts (PDX) and genetically engineered mouse models (GEMMs), has ushered in an era of co-clinical trials by which preclinical studies can inform clinical trials and protocols, thus bridging the translational divide in cancer research. Similarly, preclinical imaging fills a translational gap as an enabling technology for translational imaging research. Unlike clinical imaging, where equipment manufacturers strive to meet standards in practice at clinical sites, standards are neither fully developed nor implemented in preclinical imaging. This fundamentally limits the collection and reporting of metadata to qualify preclinical imaging studies, thereby hindering open science and impacting the reproducibility of co-clinical imaging research. To begin to address these issues, the NCI co-clinical imaging research program (CIRP) conducted a survey to identify metadata requirements for reproducible quantitative co-clinical imaging. The enclosed consensus-based report summarizes co-clinical imaging metadata information (CIMI) to support quantitative co-clinical imaging research with broad implications for capturing co-clinical data, enabling interoperability and data sharing, as well as potentially leading to updates to the preclinical Digital Imaging and Communications in Medicine (DICOM) standard.
