Skip to main content

Co-Clinical Imaging Resource Program (CIRP): Bridging the Translational Divide to Advance Precision Medicine.

Publication ,  Journal Article
Shoghi, KI; Badea, CT; Blocker, SJ; Chenevert, TL; Laforest, R; Lewis, MT; Luker, GD; Manning, HC; Marcus, DS; Mowery, YM; Pickup, S; Ross, BD ...
Published in: Tomography
September 2020

The National Institutes of Health's (National Cancer Institute) precision medicine initiative emphasizes the biological and molecular bases for cancer prevention and treatment. Importantly, it addresses the need for consistency in preclinical and clinical research. To overcome the translational gap in cancer treatment and prevention, the cancer research community has been transitioning toward using animal models that more fatefully recapitulate human tumor biology. There is a growing need to develop best practices in translational research, including imaging research, to better inform therapeutic choices and decision-making. Therefore, the National Cancer Institute has recently launched the Co-Clinical Imaging Research Resource Program (CIRP). Its overarching mission is to advance the practice of precision medicine by establishing consensus-based best practices for co-clinical imaging research by developing optimized state-of-the-art translational quantitative imaging methodologies to enable disease detection, risk stratification, and assessment/prediction of response to therapy. In this communication, we discuss our involvement in the CIRP, detailing key considerations including animal model selection, co-clinical study design, need for standardization of co-clinical instruments, and harmonization of preclinical and clinical quantitative imaging pipelines. An underlying emphasis in the program is to develop best practices toward reproducible, repeatable, and precise quantitative imaging biomarkers for use in translational cancer imaging and therapy. We will conclude with our thoughts on informatics needs to enable collaborative and open science research to advance precision medicine.

Duke Scholars

Altmetric Attention Stats
Dimensions Citation Stats

Published In

Tomography

DOI

EISSN

2379-139X

Publication Date

September 2020

Volume

6

Issue

3

Start / End Page

273 / 287

Location

Switzerland

Related Subject Headings

  • United States
  • Translational Research, Biomedical
  • Proteomics
  • Precision Medicine
  • Neoplasms
  • Humans
  • Diagnostic Imaging
  • Animals
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Shoghi, K. I., Badea, C. T., Blocker, S. J., Chenevert, T. L., Laforest, R., Lewis, M. T., … Zhou, R. (2020). Co-Clinical Imaging Resource Program (CIRP): Bridging the Translational Divide to Advance Precision Medicine. Tomography, 6(3), 273–287. https://doi.org/10.18383/j.tom.2020.00023
Shoghi, Kooresh I., Cristian T. Badea, Stephanie J. Blocker, Thomas L. Chenevert, Richard Laforest, Michael T. Lewis, Gary D. Luker, et al. “Co-Clinical Imaging Resource Program (CIRP): Bridging the Translational Divide to Advance Precision Medicine.Tomography 6, no. 3 (September 2020): 273–87. https://doi.org/10.18383/j.tom.2020.00023.
Shoghi KI, Badea CT, Blocker SJ, Chenevert TL, Laforest R, Lewis MT, et al. Co-Clinical Imaging Resource Program (CIRP): Bridging the Translational Divide to Advance Precision Medicine. Tomography. 2020 Sep;6(3):273–87.
Shoghi, Kooresh I., et al. “Co-Clinical Imaging Resource Program (CIRP): Bridging the Translational Divide to Advance Precision Medicine.Tomography, vol. 6, no. 3, Sept. 2020, pp. 273–87. Pubmed, doi:10.18383/j.tom.2020.00023.
Shoghi KI, Badea CT, Blocker SJ, Chenevert TL, Laforest R, Lewis MT, Luker GD, Manning HC, Marcus DS, Mowery YM, Pickup S, Richmond A, Ross BD, Vilgelm AE, Yankeelov TE, Zhou R. Co-Clinical Imaging Resource Program (CIRP): Bridging the Translational Divide to Advance Precision Medicine. Tomography. 2020 Sep;6(3):273–287.

Published In

Tomography

DOI

EISSN

2379-139X

Publication Date

September 2020

Volume

6

Issue

3

Start / End Page

273 / 287

Location

Switzerland

Related Subject Headings

  • United States
  • Translational Research, Biomedical
  • Proteomics
  • Precision Medicine
  • Neoplasms
  • Humans
  • Diagnostic Imaging
  • Animals