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

Authors :
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
Source :
Tomography, Vol 9, Iss 3, Pp 995-1009 (2023)
Publication Year :
2023
Publisher :
MDPI AG, 2023.

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.

Details

Language :
English
ISSN :
2379139X and 23791381
Volume :
9
Issue :
3
Database :
Directory of Open Access Journals
Journal :
Tomography
Publication Type :
Academic Journal
Accession number :
edsdoj.03b45b43e1546d4a22efc4f2e820217
Document Type :
article
Full Text :
https://doi.org/10.3390/tomography9030081