Back to Search
Start Over
Quantitative analysis of vascularity for thyroid nodules on ultrasound using superb microvascular imaging: Can nodular vascularity differentiate between malignant and benign thyroid nodules?
- Source :
-
Medicine [Medicine (Baltimore)] 2022 Feb 04; Vol. 101 (5), pp. e28725. - Publication Year :
- 2022
-
Abstract
- Abstract: This study aimed to investigate the utility of adding superb microvascular imaging (SMI) to B-mode ultrasound (US) for distinguishing between benign and malignant thyroid nodules and evaluate the usefulness of SMI quantification of nodular vascularity for diagnosing thyroid cancer.The malignancy likelihood was scored for 3 datasets before versus after additional color Doppler imaging or SMI using 4-scale visual analysis (i.e., B-mode US alone, B-mode US + color Doppler image, and B-mode US + SMI). Further, the SMI pixel count was measured in the region of interest, including the whole nodule, on the longitudinal view. It was compared between benign and malignant nodules and analyzed according to the US patterns of thyroid nodules based on the Korean thyroid imaging reporting and data system. We calculated the area under the receiver operating characteristic curve values, sensitivities, and specificities.There was no significant difference in the area under the receiver operating characteristic curve values among B-mode, B-mode + color Doppler, and B-mode + SMI. However, the SMI pixel count was significantly higher in malignant thyroid nodules than in benign ones. The optimal cut-off value for the SMI pixel count for predicting malignant thyroid nodules obtained using a receiver operating characteristic curve was 17 (40.54% in sensitivity, 91.3% in specificity). Analysis based on the US pattern of thyroid nodules revealed significant differences in the nodules with low-to-intermediate suspicious US features between malignant and benign nodules.Quantification analysis of vascularity using SMI can differentiate malignant thyroid nodules from benign ones.<br />Competing Interests: The authors have no conflicts of interests to disclose.<br /> (Copyright © 2022 the Author(s). Published by Wolters Kluwer Health, Inc.)
Details
- Language :
- English
- ISSN :
- 1536-5964
- Volume :
- 101
- Issue :
- 5
- Database :
- MEDLINE
- Journal :
- Medicine
- Publication Type :
- Academic Journal
- Accession number :
- 35119020
- Full Text :
- https://doi.org/10.1097/MD.0000000000028725