Using the American College of Radiology Thyroid Imaging Reporting and Data System at the Point of Care: Sonographer Performance and Interobserver Variability.

Published

Journal Article

The purpose of this study was to assess inter-observer variability and performance when sonographers assign features to thyroid nodules on ultrasound using the American College of Radiology (ACR) Thyroid Imaging Reporting and Data System (TI-RADS). Fifteen sonographers retrospectively evaluated 100 thyroid nodules and assigned features to each nodule according to ACR TI-RADS lexicon. Ratings were compared with one another and to a gold standard using Fleiss' and Cohen's kappa statistics, respectively. Sonographers were also asked subjective questions regarding their comfort level assessing each feature, and opinions were compared with performance using a mixed effects model. Sonographers demonstrated only slight agreement for margin (κ = 0.18, 95% confidence interval [CI]: 0.16-0.20) and large comet tail artifact (κ = 0.08, 95% CI: 0.06-0.10) but better performance for macrocalcification (κ = 0.41, 95% CI: 0.39-0.43) and no echogenic foci (κ = 0.52, 95% CI: 0.50-0.54). Sonographer comfort level with different feature assignments did not statistically correlate with performance for a given feature. In conclusion, sonographers using ACR TI-RADS to assign thyroid nodule features on ultrasound demonstrate a range of agreement across features, with margin and large comet tail artifact showing the most variability. These results highlight potential areas of focus for sonographer education efforts as ACR TI-RADS continues to be implemented in radiology departments.

Full Text

Duke Authors

Cited Authors

  • Wildman-Tobriner, B; Ahmed, S; Erkanli, A; Mazurowski, MA; Hoang, JK

Published Date

  • August 2020

Published In

Volume / Issue

  • 46 / 8

Start / End Page

  • 1928 - 1933

PubMed ID

  • 32507343

Pubmed Central ID

  • 32507343

Electronic International Standard Serial Number (EISSN)

  • 1879-291X

Digital Object Identifier (DOI)

  • 10.1016/j.ultrasmedbio.2020.04.019

Language

  • eng

Conference Location

  • England