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Stat Methods Med Res. 2015 Feb;24(1):27-67. doi: 10.1177/0962280214537344. Epub 2014 Jun 11.

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

Author information

1
ICON Medical Imaging, Warrington, USA David.Raunig@iconplc.com.
2
National Cancer Institute, Bethesda, USA.
3
Food and Drug Administration/CDRH, Silver Spring, USA.
4
Brown University, Providence, USA.
5
University of Michigan Health System, Ann Arbor, USA.
6
Duke University BIAC, Durham, USA.
7
Johns Hopkins Medical Institute, Baltimore, MD, USA.
8
University of Pittsburgh, Pittsburg, USA.
9
Eli Lilly and Co, Indianapolis, USA.
10
Memorial Sloan Kettering Cancer Center, New York, USA.
11
Hoffman-La Roche Ltd., Basel, CH.
12
Toshiba Medical Research Institute, Vernon Hills, USA.
13
Takaeda, Deerfield, USA.
14
Duke University School of Medicine, Durham, USA.

Abstract

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.

KEYWORDS:

agreement; bias; imaging biomarkers; linearity; precision; quantitative imaging; reliability; repeatability; reproducibility

PMID:
24919831
DOI:
10.1177/0962280214537344
[Indexed for MEDLINE]
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