Abstract
PurposeTo develop and validate a nomogram combining radiomics of B-mode ultrasound (BMUS) images and the American College of Radiology (ACR) Thyroid Imaging Reporting and Data System (TI-RADS) for predicting malignant thyroid nodules and improving the performance of the guideline.MethodA total of 451 thyroid nodules referred for surgery and proven pathologically at an academic referral center from January 2019 to September 2020 were retrospectively collected and randomly assigned to training and validation cohorts (7:3 ratio). A nomogram was developed through combining the BMUS radiomics score (Rad-Score) with ACR TI-RADS score (ACR-Score) in the training cohort; the performance of the nomogram was assessed with respect to discrimination, calibration, and clinical application in the validation and entire cohorts.ResultsThe ACR-Rad nomogram showed good calibration and yielded an AUC of 0.877 (95% CI 0.836–0.919) in the training cohort and 0.864 (95% CI 0.799–0.931) in the validation cohort, which were significantly better than the ACR-Score model (p < 0.001 and 0.031, respectively). The significantly improved AUC, net reclassification index (NRI), and integrated discriminatory improvement (IDI) of the nomogram were found for both senior and junior radiologists (all p < 0.001). Decision curve analysis indicated that the nomogram was clinically useful. When cutoff values for 50% predicted malignancy risk (ACR-Rad_50%) were applied, the nomogram showed increased specificity, accuracy and positive predictive value (PPV), and decreased unnecessary fine-needle aspiration (FNA) rates in comparison to ACR TI-RADS.ConclusionThe ACR-Rad nomogram has favorable value in predicting malignant thyroid nodules and improving performance of the ACR TI-RADS for senior and junior radiologists.
Highlights
With the increasing number of imaging-detected thyroid nodules, overdiagnosis and overtreatment are major clinical challenges in the management of these nodules; an accurate and practical risk stratification tool is necessary [1]
Exclusion criteria are as follows: 1) the pathological result of the nodule was ambiguous, 2) interventional procedures such as fine-needle aspiration (FNA) and radiofrequency ablation were performed before B-mode ultrasound (BMUS), and 3) the BMUS image of the target nodule was unclear
There was no significant difference between the training and validation cohorts for clinicopathological and BMUS characteristics
Summary
With the increasing number of imaging-detected thyroid nodules, overdiagnosis and overtreatment are major clinical challenges in the management of these nodules; an accurate and practical risk stratification tool is necessary [1]. Previous studies have compared different guidelines to find a management guideline that is most beneficial to patients and demonstrated that the 2017 American College of Radiology (ACR) Thyroid Imaging Reporting and Data System (TIRADS) showed accurate diagnostic performance and meaningful reduction in the number of thyroid nodules recommended for biopsy [6,7,8]. Radiomics features are usually analyzed from a single-section image of the target nodule; radiomics alone might lose some important BMUS information, which makes it impossible to significantly improve the performance of risk stratification systems for all radiologists with different proficiency levels [15]
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