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Quantitative imaging biomarkers: a review of statistical methods for technical performance assessment.

Publication ,  Journal Article
Raunig, DL; McShane, LM; Pennello, G; Gatsonis, C; Carson, PL; Voyvodic, JT; Wahl, RL; Kurland, BF; Schwarz, AJ; Gönen, M; Zahlmann, G ...
Published in: Stat Methods Med Res
February 2015

Technological developments and greater rigor in the quantitative measurement of biological features in medical images have given rise to an increased interest in using quantitative imaging biomarkers to measure changes in these features. Critical to the performance of a quantitative imaging biomarker in preclinical or clinical settings are three primary metrology areas of interest: measurement linearity and bias, repeatability, and the ability to consistently reproduce equivalent results when conditions change, as would be expected in any clinical trial. Unfortunately, performance studies to date differ greatly in designs, analysis method, and metrics used to assess a quantitative imaging biomarker for clinical use. It is therefore difficult or not possible to integrate results from different studies or to use reported results to design studies. The Radiological Society of North America and the Quantitative Imaging Biomarker Alliance with technical, radiological, and statistical experts developed a set of technical performance analysis methods, metrics, and study designs that provide terminology, metrics, and methods consistent with widely accepted metrological standards. This document provides a consistent framework for the conduct and evaluation of quantitative imaging biomarker performance studies so that results from multiple studies can be compared, contrasted, or combined.

Duke Scholars

Published In

Stat Methods Med Res

DOI

EISSN

1477-0334

Publication Date

February 2015

Volume

24

Issue

1

Start / End Page

27 / 67

Location

England

Related Subject Headings

  • Terminology as Topic
  • Statistics as Topic
  • Statistics & Probability
  • Research Design
  • Reproducibility of Results
  • Humans
  • Diagnostic Imaging
  • Clinical Trials as Topic
  • Biomarkers
  • Bias
 

Citation

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Raunig, D. L., McShane, L. M., Pennello, G., Gatsonis, C., Carson, P. L., Voyvodic, J. T., … QIBA Technical Performance Working Group, . (2015). Quantitative imaging biomarkers: a review of statistical methods for technical performance assessment. Stat Methods Med Res, 24(1), 27–67. https://doi.org/10.1177/0962280214537344
Raunig, David L., Lisa M. McShane, Gene Pennello, Constantine Gatsonis, Paul L. Carson, James T. Voyvodic, Richard L. Wahl, et al. “Quantitative imaging biomarkers: a review of statistical methods for technical performance assessment.Stat Methods Med Res 24, no. 1 (February 2015): 27–67. https://doi.org/10.1177/0962280214537344.
Raunig DL, McShane LM, Pennello G, Gatsonis C, Carson PL, Voyvodic JT, et al. Quantitative imaging biomarkers: a review of statistical methods for technical performance assessment. Stat Methods Med Res. 2015 Feb;24(1):27–67.
Raunig, David L., et al. “Quantitative imaging biomarkers: a review of statistical methods for technical performance assessment.Stat Methods Med Res, vol. 24, no. 1, Feb. 2015, pp. 27–67. Pubmed, doi:10.1177/0962280214537344.
Raunig DL, McShane LM, Pennello G, Gatsonis C, Carson PL, Voyvodic JT, Wahl RL, Kurland BF, Schwarz AJ, Gönen M, Zahlmann G, Kondratovich MV, O’Donnell K, Petrick N, Cole PE, Garra B, Sullivan DC, QIBA Technical Performance Working Group. Quantitative imaging biomarkers: a review of statistical methods for technical performance assessment. Stat Methods Med Res. 2015 Feb;24(1):27–67.
Journal cover image

Published In

Stat Methods Med Res

DOI

EISSN

1477-0334

Publication Date

February 2015

Volume

24

Issue

1

Start / End Page

27 / 67

Location

England

Related Subject Headings

  • Terminology as Topic
  • Statistics as Topic
  • Statistics & Probability
  • Research Design
  • Reproducibility of Results
  • Humans
  • Diagnostic Imaging
  • Clinical Trials as Topic
  • Biomarkers
  • Bias