Affiliation:
1. Department of Ultrasound, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
Abstract
Objective: The objective of this study was to establish a multimodality ultrasound prediction model based on conventional ultrasound (Con-US), shear wave elastography (SWE), and strain elastography (SE) and contrast-enhanced ultrasound (CEUS) and to explore their diagnostic values for thyroid nodules ≤ 10 mm. Methods: This retrospective study included 198 thyroid nodules (maximum diameter≤10 mm) in 198 thyroid surgery patients who were examined preoperatively with above-mentioned methods. The pathological findings of the thyroid nodules were used as the gold standard, and there were 72 benign nodules and 126 malignant nodules. The multimodal ultrasound prediction models were developed by logistic regression analysis based on the ultrasound image appearances. The diagnostic efficacy of these prediction models was then compared and internally cross-validated in a fivefold manner. Results: The specific features on CEUS (enhancement boundary, enhancement direction and decreased nodule area) and the parenchyma-to-nodule strain ratio (PNSR) on SE and SWE ratio were included in the prediction model. The Model one combining American College of Radiology Thyroid Imaging Reporting and Data Systems (ACR TI-RADS) score with PNSR and SWE ratio had the highest sensitivity (92.8%), while the Model three combining TI-RADS score with PNSR, SWE ratio and specific CEUS indicators had the highest specificity, accuracy, and AUC (90.2%,91.4%, and 0.958, respectively). Conclusion: The multimodality ultrasound predictive models effectively improved the differential diagnosis of thyroid nodules smaller than 10 mm. Advances in knowledge: For the differential diagnosis of thyroid nodules ≤ 10 mm, both ultrasound elastography and CEUS could be effective complements to ACR TI-RADS.
Publisher
Oxford University Press (OUP)
Subject
Radiology, Nuclear Medicine and imaging,General Medicine
Cited by
2 articles.
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