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

Author:

Raunig David L1,McShane Lisa M2,Pennello Gene3,Gatsonis Constantine4,Carson Paul L5,Voyvodic James T6,Wahl Richard L7,Kurland Brenda F8,Schwarz Adam J9,Gönen Mithat10,Zahlmann Gudrun11,Kondratovich Marina V3,O’Donnell Kevin12,Petrick Nicholas3,Cole Patricia E13,Garra Brian3,Sullivan Daniel C14,

Affiliation:

1. ICON Medical Imaging, Warrington, USA

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.

Publisher

SAGE Publications

Subject

Health Information Management,Statistics and Probability,Epidemiology

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