Objectives: To evaluate whether Superb Micro-Vascular Imaging (SMI; Toshiba Medical Systems Corporation, Tochigi, Japan) is superior to power Doppler flow imaging (PDFI) in depicting thyroid nodular vascularity and to primarily explore the diagnostic performance of vascularity on SMI integrated with grayscale sonographic features for diagnosis of malignant thyroid nodules.
Methods: Ninety-two resident patients with 113 nodules for surgery were included in the study. Thirty-four nodules were benign, and 79 nodules were malignant. Vascularity was classified as none, peripheral, mixed, and intranodular. Grayscale features, including calcifications, echogenicity, margins, shape, and internal components, were evaluated. The distribution of vascular patterns was compared between PDFI and SMI to determine the superior technique for diagnosing malignancy. A multivariate logistic regression analysis was used to evaluate the accuracy of SMI combined with grayscale sonography for thyroid malignancy.
Results: The 92 patients had a male-to-female ratio of 12:11 and a median age of 42 years (range, 20-75 years). Intranodular vascularity on SMI had 91.2% specificity and 75.9% sensitivity, which were superior to PDFI, at 82.3% and 41.8%, respectively (P < .01). We attribute this finding to the fact that peripheral vessels of many nodules on PDFI were actually intense small penetrating vessels around the lesion on SMI. A taller-than-wide shape, microcalcifications, and SMI intranodular vascularity were independent risk factors for thyroid malignancy. The area under the receiver operating characteristic curve for the logistic regression model was 0.92, which was higher than that for a single suspicious sonographic feature (P < .05).
Conclusions: Intranodular vascularity on SMI is useful for determining thyroid carcinoma. Furthermore, a combination of SMI and grayscale features performs better than any single sonographic feature alone.
Keywords: Superb Micro-Vascular Imaging; head and neck ultrasound; sonography; thyroid; vascularity.
© 2017 by the American Institute of Ultrasound in Medicine.