Skip to main content
Journal cover image

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

Publication ,  Journal Article
Mulshine, JL; Gierada, DS; Armato, SG; Avila, RS; Yankelevitz, DF; Kazerooni, EA; McNitt-Gray, MF; Buckler, AJ; Sullivan, DC
Published in: J Am Coll Radiol
April 2015

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.

Duke Scholars

Published In

J Am Coll Radiol

DOI

EISSN

1558-349X

Publication Date

April 2015

Volume

12

Issue

4

Start / End Page

390 / 395

Location

United States

Related Subject Headings

  • Tomography, X-Ray Computed
  • Solitary Pulmonary Nodule
  • Sensitivity and Specificity
  • Reproducibility of Results
  • Radiographic Image Interpretation, Computer-Assisted
  • Radiographic Image Enhancement
  • Nuclear Medicine & Medical Imaging
  • Lung Neoplasms
  • Humans
  • Early Detection of Cancer
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Mulshine, J. L., Gierada, D. S., Armato, S. G., Avila, R. S., Yankelevitz, D. F., Kazerooni, E. A., … Sullivan, D. C. (2015). Role of the Quantitative Imaging Biomarker Alliance in optimizing CT for the evaluation of lung cancer screen-detected nodules. J Am Coll Radiol, 12(4), 390–395. https://doi.org/10.1016/j.jacr.2014.12.003
Mulshine, James L., David S. Gierada, Samuel G. Armato, Rick S. Avila, David F. Yankelevitz, Ella A. Kazerooni, Michael F. McNitt-Gray, Andrew J. Buckler, and Daniel C. Sullivan. “Role of the Quantitative Imaging Biomarker Alliance in optimizing CT for the evaluation of lung cancer screen-detected nodules.J Am Coll Radiol 12, no. 4 (April 2015): 390–95. https://doi.org/10.1016/j.jacr.2014.12.003.
Mulshine JL, Gierada DS, Armato SG, Avila RS, Yankelevitz DF, Kazerooni EA, et al. Role of the Quantitative Imaging Biomarker Alliance in optimizing CT for the evaluation of lung cancer screen-detected nodules. J Am Coll Radiol. 2015 Apr;12(4):390–5.
Mulshine, James L., et al. “Role of the Quantitative Imaging Biomarker Alliance in optimizing CT for the evaluation of lung cancer screen-detected nodules.J Am Coll Radiol, vol. 12, no. 4, Apr. 2015, pp. 390–95. Pubmed, doi:10.1016/j.jacr.2014.12.003.
Mulshine JL, Gierada DS, Armato SG, Avila RS, Yankelevitz DF, Kazerooni EA, McNitt-Gray MF, Buckler AJ, Sullivan DC. Role of the Quantitative Imaging Biomarker Alliance in optimizing CT for the evaluation of lung cancer screen-detected nodules. J Am Coll Radiol. 2015 Apr;12(4):390–395.
Journal cover image

Published In

J Am Coll Radiol

DOI

EISSN

1558-349X

Publication Date

April 2015

Volume

12

Issue

4

Start / End Page

390 / 395

Location

United States

Related Subject Headings

  • Tomography, X-Ray Computed
  • Solitary Pulmonary Nodule
  • Sensitivity and Specificity
  • Reproducibility of Results
  • Radiographic Image Interpretation, Computer-Assisted
  • Radiographic Image Enhancement
  • Nuclear Medicine & Medical Imaging
  • Lung Neoplasms
  • Humans
  • Early Detection of Cancer