Reducing the Number of Unnecessary Thyroid Nodule Biopsies With the American College of Radiology (ACR) Thyroid Imaging Reporting and Data System (TI-RADS)
Bibliographic record
Abstract
Introduction Thyroid nodules are exceedingly common, occurring in up to 76% of adults. Less than 10% are palpable, and the majority are detected incidentally with an estimated prevalence of 68%, 25%, and 18% using ultrasound (US), CT, and MRI, respectively. The rising use of imaging over the last four decades has led to a significant increase in nodule detection or 'over-identification,' fine-needle aspiration (FNA), a higher reported incidence of thyroid cancer, and thyroidectomy. The purpose of this study is to provide a descriptive experience with thyroid nodule FNAs one year prior and one year after the implementation of the American College of Radiology (ACR) Thyroid Imaging Reporting and Data System (TI-RADS) at a prototypical community hospital. Methods A total of 104 patients with 114 thyroid nodules underwent US-guided FNA at Bluewater Health from January 1, 2018, to March 31, 2020, with available cytological results (The Bethesda System). The study population was divided into two cohorts (January 1, 2018, to December 31, 2018 - 'local best practice cohort', and March 1, 2019, to March 31, 2020 - 'ACR TI-RADS cohort') based on the implementation of the ACR TI-RADS guidelines in March 2019. Results The local best practice cohort (January 1, 2018, to December 31, 2018) comprised 57 thyroid nodules in 52 patients (mean age 66 ± 12; 40 Women). The ACR TI-RADS cohort (March 1, 2019, to March 31, 2020) comprised 57 thyroid nodules in 52 patients (mean age 61 ± 16; 41 Women). There were no statistical differences with respect to age, gender, or thyroid nodule location. Our results show a dramatic decrease in the number of unnecessary FNAs if ACR TI-RADS was implemented from January to December 2018. Thirty (52.6%) of the previously sampled thyroid nodules using the local best practice guidelines would have been followed as per ACR TI-RADS. Conclusion ACR TI-RADS is a reliable classification system in routine practice that significantly reduces the number of unnecessary thyroid FNAs with higher specificity compared to local best practice guidelines.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".