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The purpose of this study was to assess interobserver variability in assigning features in the American College of Radiology Thyroid Imaging Reporting and Data System (ACR TI-RADS) lexicon and in making recommendations for thyroid nodule biopsy.The study cohort comprised 100 nodules in 92 patients who underwent fine-needle aspiration with definitive cytologic results (Bethesda category II or VI) or diagnostic lobectomy between April 2009 and May 2010. Eight board-certified radiologists evaluated the nodules according to the five feature categories that constitute ACR TI-RADS and gave a biopsy recommendation based on their own practice. Variability in feature assignment and biopsy recommendation was assessed with the Fleiss kappa statistic.Agreement in interpretation was fair to moderate for all features except shape (κ = 0.61) and macrocalcifications (κ = 0.73), which had substantial agreement. The features with the poorest agreement were margin and other types of echogenic foci, which had kappa values ranging from 0.25 to 0.39, indicating fair agreement. Interobserver agreement regarding biopsy recommendation was fair (κ = 0.22) based on radiologists' current practice. Applying ACR TI-RADS resulted in moderate agreement (κ = 0.51).Variability in interpreting thyroid nodule sonographic features was highest for margin and all types of echogenic foci, except for macrocalcifications. Because radiologists' interpretations of these features change the level of suspicion of thyroid malignancy, the results of this study suggest a need for further education. Despite the variability in assigning features, adoption of ACR TI-RADS improves agreement for recommending biopsy.

Purpose To compare the biopsy rate and diagnostic accuracy before and after applying the American College of Radiology (ACR) Thyroid Imaging Reporting and Data System (TI-RADS) criteria for thyroid nodule evaluation. Materials and Methods In this retrospective study, eight radiologists with 3-32 years experience in thyroid ultrasonography (US) reviewed US features of 100 thyroid nodules that were cytologically proven, pathologically proven, or both in December 2016. The radiologists evaluated nodule features in five US categories and provided biopsy recommendations based on their own practice patterns without knowledge of ACR TI-RADS criteria. Another three expert radiologists served as the reference standard readers for the imaging findings. ACR TI-RADS criteria were retrospectively applied to the features assigned by the eight radiologists to produce biopsy recommendations. Comparison was made for biopsy rate, sensitivity, specificity, and accuracy. Results Fifteen of the 100 nodules (15%) were malignant. The mean number of nodules recommended for biopsy by the eight radiologists was 80 ± 16 (standard deviation) (range, 38-95 nodules) based on their own practice patterns and 57 ± 11 (range, 37-73 nodules) with retrospective application of ACR TI-RADS criteria. Without ACR TI-RADS criteria, readers had an overall sensitivity, specificity, and accuracy of 95% (95% confidence interval [CI]: 83%, 99%), 20% (95% CI: 16%, 25%), and 28% (95% CI: 21%, 37%), respectively. After applying ACR TI-RADS criteria, overall sensitivity, specificity, and accuracy were 92% (95% CI: 68%, 98%), 44% (95% CI: 33%, 56%), and 52% (95% CI: 40%, 63%), respectively. Although fewer malignancies were recommended for biopsy with ACR TI-RADS criteria, the majority met the criteria for follow-up US, with only three of 120 (2.5%) malignancy encounters requiring no follow-up or biopsy. Expert consensus recommended biopsy in 55 of 100 nodules with ACR TI-RADS criteria. Their sensitivity, specificity, and accuracy were 87% (95% CI: 48%, 98%), 51% (95% CI: 40%, 62%), and 56% (95% CI: 46%, 66%), respectively. Conclusion ACR TI-RADS criteria offer a meaningful reduction in the number of thyroid nodules recommended for biopsy and significantly improve the accuracy of recommendations for nodule management.

Early detection of lung nodules is an important clinical indication for obtaining routine CT studies of the thorax. To date, research has focused on the sensitivity of computer-aided diagnosis (CAD) compared with expert chest radiologists typically using data obtained from single detector CT scanners. The present study focuses on the use of CAD as a second reader supplementing four nonexpert “community level” radiologists using state-of-the-art multidetector high resolution data sets. Evaluations of 18 cases with a total of 87 nodules (average 4.8 per case) were subsequently validated by a panel of two expert dedicated chest radiologists. Only 21% of nodules were identified by all four readers; 17% were identified only by CAD. The mean sensitivity of readers before CAD was 49% while following CAD this improved to 72% (p