Evaluation of underlying lymphocytic thyroiditis with histogram analysis using grayscale ultrasound images

Ga Ram Kim, Eun Kyung Kim, Soo Jin Kim, Eun Ju Ha, Jaeheung Yoo, Hye Sun Lee, Jung Hwa Hong, Jung Hyun Yoon, Hee Jung Moon, Jin Young Kwak

Research output: Contribution to journalArticlepeer-review

8 Citations (Scopus)

Abstract

Objectives-The purpose of this study was to evaluate diagnostic performance of histogram analysis using grayscale ultrasound (US) images in the diagnosis of lymphocytic thyroiditis. Methods-Three radiologists reviewed a total of 505 US images and classified the images according to the presence/existence of lymphocytic thyroiditis. After 2 months, each reviewer repeated the process with the same 505 images in a randomly mixed order. The intraobserver and interobserver variability was analyzed with a generalized κ value. Four histogram parameters (mean value, standard deviation, skewness, and kurtosis) were obtained, and an index was calculated from principal component analysis. Diagnostic performances were compared. Results-Of 505 patients, 125 (24.8%) had lymphocytic thyroiditis, and 380 (75.2%) had normal thyroid parenchyma on pathologic analysis. The κ value for intraobserver variance ranged from -0.002 to 0.781, and the overall κ values for interobserver variance were 0.570 and 0.214 in the first and second tests, respectively. The sensitivity, specificity, accuracy, positive predictive value, and negative predictive value for the 3 reviewers versus the principal component analysis index were 28.0% to 83.2%, 43.7% to 82.6%, 53.5% to 79.0%, 24.6% to 56.2%, and 75.2% to 88.9% versus 58.4%, 72.4%, 68.9%, 41.0%, and 84.1%. Conclusions-Histogram analysis of grayscale US images provided confirmable and quantitative information about lymphocytic thyroiditis and was comparable with performers' assessments in diagnostic performance.

Original languageEnglish
Pages (from-to)519-526
Number of pages8
JournalJournal of Ultrasound in Medicine
Volume35
Issue number3
DOIs
Publication statusPublished - 2016 Mar 1

All Science Journal Classification (ASJC) codes

  • Radiological and Ultrasound Technology
  • Radiology Nuclear Medicine and imaging

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