Using an ultrasonography risk stratification system to enhance the thyroid fine needle aspiration performance.

PURPOUSE: The American College of Radiology Thyroid Imaging Reporting and Data System (ACR TI-RADS) is a risk stratification system for thyroid nodules based on their ultrasonography (US) characteristics. Here, we aimed to assess TI-RADS on fine needle aspiration biopsy (FNAB) recommendations and performance in thyroid nodules. METHODS: We performed a retrospective study in a single center. All patients with thyroid nodules who underwent FNAB between 2012 and 2019 were included. TI-RADS data were extracted from medical records. Malignancy rates were defined based on cytological exams. RESULTS: A total of 1,044 nodules (938 patients) were evaluated. TI-RADS classification was as follows: 13 TI-RADS 1, 524 TI-RADS 2, 273 TI-RADS 3, 148 TI-RADS 4, and 85 TI-RADS 5. TI-RADS classification showed a sensitivity of 75% (95 %CI: 63-84.7), a negative predictive value of 97.6% (95 %CI: 96.5-98.5), and accuracy of 73.1% (95 %CI: 70.3-75.8). According to TI-RADS FNAB criteria, only 314 (30%) nodules would have undergone FNAB. Of them, 157 (50%) were classified as benign (Bethesda II), 45 (14.3%) as undetermined (Bethesda III or IV), and 51 (16.2%) as malignant (Bethesda V or VI). Of the remaining 729 nodules that did not meet FNAB criteria, 17 (2.3%) had Bethesda V or VI and underwent surgery. Of them, four (23%) were <1 cm in size (microcarcinomas), and eight (47.0%) remain in follow-up according to the TI-RADS criteria. Seven malignant cases would be missed (0.9%). CONCLUSION: ACR TI-RADS allows a significant decrease in the number of FNAB, increasing its diagnostic accuracy.

Diagnostic performance of the RSNA-proposed classification for COVID-19 pneumonia versus pre-pandemic controls.

OBJECTIVE: To evaluate the diagnostic accuracy of the Radiological Society of North America (RSNA) classification system for coronavirus disease 2019 (COVID-19) pneumonia compared to pre-pandemic chest computed tomography (CT) scan images to mitigate the risk of bias regarding the reference standard. MATERIALS AND METHODS: This was a retrospective, cross-sectional, diagnostic test accuracy study. Chest CT scans, carried out from May 1 to June 30, 2020, and from May 1 to July 17, 2017, were consecutively selected for the COVID-19 (positive reverse transcription-polymerase chain reaction [RT-PCR] for severe acute respiratory syndrome coronavirus 2 result) and control (pre-pandemic) groups, respectively. Four expert thoracic radiologists blindly interpreted each CT scan image. Sensitivity and specificity were calculated. RESULTS: A total of 160 chest CT scan images were included: 79 in the COVID-19 group (56 [43.5-67] years old, 41 men) and 81 in the control group (62 [52-72] years old, 44 men). Typically, an estimated specificity of 98.5% (95% confidence interval [CI] 98.1%-98.4%) was obtained. For the indeterminate classification as a diagnostic threshold, an estimated sensitivity of 88.3% (95% CI 84.7%-91.7%) and a specificity of 79.0% (95% CI 74.5%-83.4%), with an area under the curve of 0.865 (95% CI 0.838-0.895), were obtained. CONCLUSION: The RSNA classification system shows strong diagnostic accuracy for COVID-19 pneumonia, even against pre-pandemic controls. It can be an important aid in clinical decision-making, especially when a typical or indeterminate pattern is found, possibly advising retesting following an initial negative RT-PCR result and streamlining early management and isolation.

Diagnostic performance of the RSNA-proposed classification for COVID-19 pneumonia versus pre-pandemic controls

Abstract Objective To evaluate the diagnostic accuracy of the Radiological Society of North America (RSNA) classification system for coronavirus disease 2019 (COVID-19) pneumonia compared to pre-pandemic chest computed tomography (CT) scan images to mitigate the risk of bias regarding the reference standard. Materials and methods This was a retrospective, cross-sectional, diagnostic test accuracy study. Chest CT scans, carried out from May 1 to June 30, 2020, and from May 1 to July 17, 2017, were consecutively selected for the COVID-19 (positive reverse transcription-polymerase chain reaction [RT-PCR] for severe acute respiratory syndrome coronavirus 2 result) and control (pre-pandemic) groups, respectively. Four expert thoracic radiologists blindly interpreted each CT scan image. Sensitivity and specificity were calculated. Results A total of 160 chest CT scan images were included: 79 in the COVID-19 group (56 [43.5-67] years old, 41 men) and 81 in the control group (62 [52-72] years old, 44 men). Typically, an estimated specificity of 98.5% (95% confidence interval [CI] 98.1%-98.4%) was obtained. For the indeterminate classification as a diagnostic threshold, an estimated sensitivity of 88.3% (95% CI 84.7%-91.7%) and a specificity of 79.0% (95% CI 74.5%-83.4%), with an area under the curve of 0.865 (95% CI 0.838-0.895), were obtained. Conclusion The RSNA classification system shows strong diagnostic accuracy for COVID-19 pneumonia, even against pre-pandemic controls. It can be an important aid in clinical decision-making, especially when a typical or indeterminate pattern is found, possibly advising retesting following an initial negative RT-PCR result and streamlining early management and isolation.