Validation of ACR TI ‐ RADS for Predicting Cytological Outcomes in Thyroid Nodules: A Large FNA Cohort Study

ABSTRACT Purpose To evaluate the diagnostic performance of ACR TI‐RADS for predicting malignant cytology in thyroid nodules undergoing fine‐needle aspiration (FNA) in a large tertiary centre. Methods A retrospective analysis was performed of 3368 thyroid nodules undergoing ultrasound‐guided FNA. Nodules were classified according to ACR TI‐RADS (TR1–TR5). Cytological outcomes were recorded using the Bethesda System. Malignant cytology was defined as Bethesda V–VI and Bethesda IV–VI was evaluated as a secondary composite cytological outcome. The distribution of cytology across TI‐RADS categories was assessed, and malignancy rates were calculated. Diagnostic performance was evaluated using TR4–TR5 as a positive threshold. Results Nodules were classified as TR1 (1.4%), TR2 (5.3%), TR3 (23.7%), TR4 (51.0%) and TR5 (18.7%). Malignant cytology increased across categories from 0.0% in TR1 to 6.5% in TR5, while Bethesda IV–VI cytology increased from 0.0% to 12.6%. Among TR3–TR5 nodules, 81.0% met the corresponding ACR size threshold for FNA; malignant cytology occurred in 2.6% meeting the threshold and 1.7% below threshold ( p = 0.24). TI‐RADS category was significantly associated with cytological outcome ( p < 0.001). Using TR4–TR5 as a threshold, sensitivity was 88.2% and negative predictive value 99.1%. Conclusion ACR TI‐RADS demonstrates a clear association with cytology outcomes, with increasing malignancy risk across categories. In this large FNA‐based cohort, TI‐RADS showed excellent negative predictive value, supporting its role in ultrasound‐based risk stratification and optimisation of FNA decision‐making.

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Journal
Journal of Medical Imaging and Radiation Oncology
Published
2026-10-07
DOI
https://doi.org/10.1111/1754-9485.70207
Primary Topic
Thyroid Cancer Diagnosis and Treatment
Type
article
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article

Validation of ACR TI ‐ RADS for Predicting Cytological Outcomes in Thyroid Nodules: A Large FNA Cohort Study

Ilona Lavender, Dee Nandurkar
Journal of Medical Imaging and Radiation Oncology
Thyroid Cancer Diagnosis and Treatment
article

Validation of ACR TI ‐ RADS for Predicting Cytological Outcomes in Thyroid Nodules: A Large FNA Cohort Study

Ilona Lavender, Dee Nandurkar
article en

Abstract

ABSTRACT Purpose To evaluate the diagnostic performance of ACR TI‐RADS for predicting malignant cytology in thyroid nodules undergoing fine‐needle aspiration (FNA) in a large tertiary centre. Methods A retrospective analysis was performed of 3368 thyroid nodules undergoing ultrasound‐guided FNA. Nodules were classified according to ACR TI‐RADS (TR1–TR5). Cytological outcomes were recorded using the Bethesda System. Malignant cytology was defined as Bethesda V–VI and Bethesda IV–VI was evaluated as a secondary composite cytological outcome. The distribution of cytology across TI‐RADS categories was assessed, and malignancy rates were calculated. Diagnostic performance was evaluated using TR4–TR5 as a positive threshold. Results Nodules were classified as TR1 (1.4%), TR2 (5.3%), TR3 (23.7%), TR4 (51.0%) and TR5 (18.7%). Malignant cytology increased across categories from 0.0% in TR1 to 6.5% in TR5, while Bethesda IV–VI cytology increased from 0.0% to 12.6%. Among TR3–TR5 nodules, 81.0% met the corresponding ACR size threshold for FNA; malignant cytology occurred in 2.6% meeting the threshold and 1.7% below threshold ( p = 0.24). TI‐RADS category was significantly associated with cytological outcome ( p < 0.001). Using TR4–TR5 as a threshold, sensitivity was 88.2% and negative predictive value 99.1%. Conclusion ACR TI‐RADS demonstrates a clear association with cytology outcomes, with increasing malignancy risk across categories. In this large FNA‐based cohort, TI‐RADS showed excellent negative predictive value, supporting its role in ultrasound‐based risk stratification and optimisation of FNA decision‐making.

Journal of Medical Imaging and Radiation Oncology
Monash Health (AU), Monash University (AU)
Openalex Percentile: Top 11%
Thyroid Cancer Diagnosis and Treatment
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