Co-Clinical Imaging Metadata Information (CIMI) for Cancer Research to Promote Open Science, Standardization, and Reproducibility in Preclinical Imaging

Stephen M Moore¹, James D Quirk¹, Andrew W Lassiter¹, Richard Laforest¹, Gregory D Ayers², Cristian T Badea³, Andriy Y Fedorov⁴, Paul E Kinahan⁵, Matthew Holbrook³, Peder E Z Larson⁶, Renuka Sriram⁶, Thomas L Chenevert⁷, Dariya Malyarenko⁷, John Kurhanewicz⁶, A McGarry Houghton⁸, Brian D Ross⁷, Stephen Pickup⁹, James C Gee⁹, Rong Zhou⁹, Seth T Gammon¹⁰, Henry Charles Manning¹⁰, Raheleh Roudi¹¹, Heike E Daldrup-Link¹¹, Michael T Lewis¹², Daniel L Rubin¹³, Thomas E Yankeelov^{14

15}, Kooresh I Shoghi¹⁶

Affiliations

¹ Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110, USA.
² Department of Biostatistics, Vanderbilt University, Nashville, TN 37235, USA.
³ Quantitative Imaging and Analysis Lab, Department of Radiology, Duke University, Durham, NC 27708, USA.
⁴ Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02115, USA.
⁵ Department of Radiology, University of Washington, Seattle, WA 98195, USA.
⁶ Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA 94143, USA.
⁷ Department of Radiology, University of Michigan Medical School, Ann Arbor, MI 48109, USA.
⁸ Fred Hutchinson Cancer Center, Seattle, WA 98109, USA.
⁹ Department of Radiology, Abramson Cancer Center, University of Pennsylvania, Philadelphia, PA 19104, USA.
¹⁰ Department of Cancer Systems Imaging, Division of Diagnostic Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.
¹¹ Department of Radiology, Stanford University School of Medicine, Stanford, CA 94305, USA.
¹² Dan L Duncan Comprehensive Cancer Center, Departments of Molecular and Cellular Biology and Radiology, Baylor College of Medicine, Houston, TX 77030, USA.
¹³ Departments of Biomedical Data Science, Radiology and Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA.
¹⁴ 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.
¹⁵ Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.
¹⁶ Mallinckrodt Institute of Radiology, Department of Biomedical Engineering, Siteman Cancer Center, Washington University School of Medicine, St. Louis, MO 63110, USA.

PMID: 37218941
PMCID: PMC10204428
DOI: 10.3390/tomography9030081

Co-Clinical Imaging Metadata Information (CIMI) for Cancer Research to Promote Open Science, Standardization, and Reproducibility in Preclinical Imaging

Stephen M Moore et al. Tomography. 2023.

. 2023 May 11;9(3):995-1009.

doi: 10.3390/tomography9030081.

Authors

Affiliations

¹ Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110, USA.
² Department of Biostatistics, Vanderbilt University, Nashville, TN 37235, USA.
³ Quantitative Imaging and Analysis Lab, Department of Radiology, Duke University, Durham, NC 27708, USA.
⁴ Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02115, USA.
⁵ Department of Radiology, University of Washington, Seattle, WA 98195, USA.
⁶ Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA 94143, USA.
⁷ Department of Radiology, University of Michigan Medical School, Ann Arbor, MI 48109, USA.
⁸ Fred Hutchinson Cancer Center, Seattle, WA 98109, USA.
⁹ Department of Radiology, Abramson Cancer Center, University of Pennsylvania, Philadelphia, PA 19104, USA.
¹⁰ Department of Cancer Systems Imaging, Division of Diagnostic Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.
¹¹ Department of Radiology, Stanford University School of Medicine, Stanford, CA 94305, USA.
¹² Dan L Duncan Comprehensive Cancer Center, Departments of Molecular and Cellular Biology and Radiology, Baylor College of Medicine, Houston, TX 77030, USA.
¹³ Departments of Biomedical Data Science, Radiology and Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA.
¹⁴ 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.
¹⁵ Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.
¹⁶ Mallinckrodt Institute of Radiology, Department of Biomedical Engineering, Siteman Cancer Center, Washington University School of Medicine, St. Louis, MO 63110, USA.

PMID: 37218941
PMCID: PMC10204428
DOI: 10.3390/tomography9030081

Abstract

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.

Keywords: Digital Imaging and Communications in Medicine (DICOM); co-clinical imaging; metadata; open science; preclinical imaging; reproducibility; standardization.

PubMed Disclaimer

Conflict of interest statement

M.T.L. is a founder of and limited partner in StemMed Ltd., and a manager in StemMed Holdings, LP, its general partner. He is also a founder of and equity stake holder in Tvardi Therapeutics Inc.

Figures

**Figure 1**
Sample output of DICOM Analysis tool when using the Imaging Common profile.

**Figure 2**
Sample output of the DICOM Analysis tool when using the MR imaging profile. Many elements are omitted from the output for readability.

See this image and copyright information in PMC

References

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Co-Clinical Imaging Metadata Information (CIMI) for Cancer Research to Promote Open Science, Standardization, and Reproducibility in Preclinical Imaging

Affiliations

Co-Clinical Imaging Metadata Information (CIMI) for Cancer Research to Promote Open Science, Standardization, and Reproducibility in Preclinical Imaging

Authors

Affiliations

Abstract

Conflict of interest statement

Figures

References

Publication types

MeSH terms

Grants and funding

LinkOut - more resources

Full Text Sources

Medical

Miscellaneous