Statistical Issues in Testing Conformance with the Quantitative Imaging Biomarker Alliance (QIBA) Profile Claims

Acad Radiol. 2016 Apr;23(4):496-506. doi: 10.1016/j.acra.2015.12.020. Epub 2016 Feb 18.


A major initiative of the Quantitative Imaging Biomarker Alliance is to develop standards-based documents called "Profiles," which describe one or more technical performance claims for a given imaging modality. The term "actor" denotes any entity (device, software, or person) whose performance must meet certain specifications for the claim to be met. The objective of this paper is to present the statistical issues in testing actors' conformance with the specifications. In particular, we present the general rationale and interpretation of the claims, the minimum requirements for testing whether an actor achieves the performance requirements, the study designs used for testing conformity, and the statistical analysis plan. We use three examples to illustrate the process: apparent diffusion coefficient in solid tumors measured by MRI, change in Perc 15 as a biomarker for the progression of emphysema, and percent change in solid tumor volume by computed tomography as a biomarker for lung cancer progression.

Keywords: QIBA; bias; linearity; precision; quantitative imaging biomarker; repeatability; total deviation index.

Publication types

  • Research Support, N.I.H., Extramural
  • Review

MeSH terms

  • Biomarkers
  • Diagnostic Imaging / statistics & numerical data*
  • Emphysema / diagnosis
  • Humans
  • Lung Neoplasms / diagnostic imaging
  • Magnetic Resonance Imaging / statistics & numerical data
  • Research Design / statistics & numerical data*
  • Tomography, X-Ray Computed / statistics & numerical data


  • Biomarkers