Combining radiomics with ultrasound-based risk stratification systems for thyroid nodules: an approach for improving per
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Combining radiomics with ultrasound-based risk stratification systems for thyroid nodules: an approach for improving performance Vivian Y. Park 1 & Eunjung Lee 2 & Hye Sun Lee 3 & Hye Jung Kim 4 & Jiyoung Yoon 1 & Jinwoo Son 1 & Kijun Song 5 & Hee Jung Moon 1 & Jung Hyun Yoon 1 & Ga Ram Kim 1 & Jin Young Kwak 1 Received: 9 June 2020 / Revised: 30 August 2020 / Accepted: 1 October 2020 # European Society of Radiology 2020
Abstract Objectives To develop a radiomics score using ultrasound images to predict thyroid malignancy and to investigate its potential as a complementary tool to improve the performance of risk stratification systems. Methods We retrospectively included consecutive patients who underwent fine-needle aspiration (FNA) for thyroid nodules that were cytopathologically diagnosed as benign or malignant. Nodules were randomly assigned to a training and test set (8:2 ratio). A radiomics score was developed from the training set, and cutoff values based on the maximum Youden index (Rad_maxY) and for 5%, 10%, and 20% predicted malignancy risk (Rad_5%, Rad_10%, Rad_20%, respectively) were applied to the test set. The performances of the American College of Radiology (ACR) and the American Thyroid Association (ATA) guidelines were compared with the combined performances of the guidelines and radiomics score with interpretations from expert and nonexpert readers. Results A total of 1624 thyroid nodules from 1609 patients (mean age, 50.1 years [range, 18–90 years]) were included. The radiomics score yielded an AUC of 0.85 (95% CI: 0.83, 0.87) in the training set and 0.75 (95% CI: 0.69, 0.81) in the test set (Rad_maxY). When the radiomics score was combined with the ACR or ATA guidelines (Rad_5%), all readers showed increased specificity, accuracy, and PPV and decreased unnecessary FNA rates (all p < .05), with no difference in sensitivity (p > .05). Conclusion Radiomics help predict thyroid malignancy and improve specificity, accuracy, PPV, and unnecessary FNA rate while maintaining the sensitivity of the ACR and ATA guidelines for both expert and nonexpert readers. Key Points • The radiomics score yielded an AUC of 0.85 and 0.75 in the training and test set, respectively. • For all readers, combining a 5% predicted malignancy risk cutoff for the radiomics score with the ACR and ATA guidelines significantly increased specificity, accuracy, and PPV and decreased unnecessary FNA rates, with no decrease in sensitivity. • Radiomics can help predict malignancy in thyroid nodules in combination with risk stratification systems, by improving specificity, accuracy, and PPV and unnecessary FNA rates while maintaining sensitivity for both expert and nonexpert readers. Keywords Thyroid nodule . Ultrasonography . Risk assessment . Thyroid neoplasms
Electronic supplementary material The online version of this article (https://doi.org/10.1007/s00330-020-07365-9) contains supplementary material, which is available to authorized users. * Jin Young Kwak [email protected] 1
Department of Radiology, Severance Hospital
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