1) Understand the opportunities for MR quantitative imaging biomarkers (QIBs) in research and clinical applications.

2) Understand key challenges of MR QIBs and current barriers to implementation.

3) Understand current strategies to address the challenges of MR QIBs based on efforts of national and international agencies and organizations, including the ISMRM, RSNA, NIST, and NCI.

Over the past decade, there has been an increasing focus on quantitative imaging biomarkers (QIBs), which have been defined as “objective characteristics derived from in vivo images as indicators of normal biological processes, pathogenic processes, or response to a therapeutic intervention” [1]. There are many examples of successful QIB implementation and use for research and clinical care in single centers of excellence. Successful implementation of QIBs across systems, centers, and time, however, requires the development and standardization of data acquisition, data analysis, and data display techniques, as well as appropriate reporting structures. As such, successful implementation of QIBs relies on expertise from the fields of medical physics, radiology, statistics, and informatics as well as collaboration from vendors of imaging acquisition, data analysis, and reporting systems. When successfully implemented, QIBs provide image-derived metrics with known bias and variance that can be validated with anatomically and physiologically relevant measures, including treatment response, and the heterogeneity of that response, and outcome. Such non-invasive quantitative measures can then be used confidently and effectively in translational research as well as patient care.

In addition to modality-specific QIB efforts of modality-specific scientific organizations, other national and international agencies and organizations, including the NCI, RSNA, FDA, and NIST, appreciating the tremendous potential of QIBs but also understanding the associated challenges, have become increasingly involved. This presentation will focus on 1) briefly discussing selected MR-based QIBs and illustrating why they are important in research and clinical applications, even though challenging to implement across systems, centers, and time, and 2) providing examples of efforts of national and international organizations, including the ISMRM, RSNA, NCI, and NIST, to address barriers to successful implementation and validation of MR-based QIBs.