Role of the Quantitative Imaging Biomarker Alliance in optimizing CT for the evaluation of lung cancer screen-detected nodules

James L. Mulshine, David S. Gierada, Samuel G. Armato, Rick S. Avila, David F. Yankelevitz, Ella A. Kazerooni, Michael F. McNitt-Gray, Andrew J. Buckler, Daniel C. Sullivan

Research output: Contribution to journalArticlepeer-review

20 Scopus citations

Abstract

The Quantitative Imaging Biomarker Alliance (QIBA) is a multidisciplinary consortium sponsored by the RSNA to define processes that enable the implementation and advancement of quantitative imaging methods described in a QIBA profile document that outlines the process to reliably and accurately measure imaging features. A QIBA profile includes factors such as technical (product-specific) standards, user activities, and relationship to a clinically meaningful metric, such as with nodule measurement in the course of CT screening for lung cancer. In this report, the authors describe how the QIBA approach is being applied to the measurement of small pulmonary nodules such as those found during low-dose CT-based lung cancer screening. All sources of variance with imaging measurement were defined for this process. Through a process of experimentation, literature review, and assembly of expert opinion, the strongest evidence was used to define how to best implement each step in the imaging acquisition and evaluation process. This systematic approach to implementing a quantitative imaging biomarker with standardized specifications for image acquisition and postprocessing for a specific quantitative measurement of a pulmonary nodule results in consistent performance characteristics of the measurement (eg, bias and variance). Implementation of the QIBA small nodule profile may allow more efficient and effective clinical management of the diagnostic workup of individuals found to have suspicious pulmonary nodules in the course of lung cancer screening evaluation.

Original languageEnglish
Pages (from-to)390-395
Number of pages6
JournalJournal of the American College of Radiology
Volume12
Issue number4
DOIs
StatePublished - Apr 1 2015

Keywords

  • Low-dose CT scans
  • Lung cancer screening
  • Metrology
  • Pulmonary nodules
  • Quantitative imaging biomarker

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