Objectives—A high proportion of cytologically indeterminate, Afirma Gene Expression Classifier “suspicious” thyroid nodules are benign. The Thyroid Imaging Reporting and Data System (TIRADS), was proposed by the American College of Radiology in 2017 to help classify thyroid nodules based on ultrasound characteristics in a standardized fashion to guide management. We aim to determine the interobserver variability of TIRADS classification among cytologically indeterminate and Afirma suspicious nodules. Methods—We retrospectively queried cytopathology archives for thyroid fine-needle aspiration specimens obtained between February 2012 and September 2016 with associated (1) indeterminate diagnosis, (2) ultrasound imaging at our institution, (3) Afirma suspicious result, and (4) surgery at our institution. We compared the TIRADS variability of the 3 blinded radiologists using intraclass correlation coefficients. Results—Our cohort consisted of 127 nodules. Intraclass correlation coefficients can be interpreted as follows: less than 0.4, poor; 0.4 to 0.59, fair; 0.6 to 0.74, good; 0.75 to 1.00, excellent. The intraclass correlation coefficients of the raw TIRADS score and category variability was 0.561 (95% confidence interval [CI]: 0.464–0.651) or fair and 0.547 (95% CI, 0.449–0.640) or fair, respectively. When analyzing composition, echogenicity, shape, margin, and echogenic foci, the ICCs were 0.552 (95% CI, 0.454–0.643), fair; 0.533 (95% CI, 0.432–0.627), fair; 0.359 (95% CI, 0.248–0.469), poor; 0.192 (95% CI, 0.084–0.308), poor; and 0.549 (95% CI, 0.451– 0.641), fair, respectively. Conclusions—Our results show that among the subset of cytologically indeterminate and Afirma suspicious nodules, TIRADS interobserver variability was fair. Shape and margin criteria were the biggest sources of disagreement. Large prospective studies are needed to evaluate the interobserver variability of TIRADS in this subset of thyroid nodules.
- Endocrine surgery
- Indeterminate nodules
- Interobserver variability
ASJC Scopus subject areas
- Radiological and Ultrasound Technology
- Radiology Nuclear Medicine and imaging