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Updated: Jan 25, 2026

A Swin Transformer-Based Model for Thyroid Nodule Detection in Ultrasound Images
Published on: April 21, 2023
Ultrasound Microvascular Blood Flow Evaluation: A New Tool for the Management of Thyroid Nodule?
Carlo Cappelli1, Ilenia Pirola1, Elena Gandossi1
1Department of Clinical and Experimental Sciences, SSD Medicina ad indirizzo Endocrino-metabolico, University of Brescia, ASST Spedali Civili di Brescia, 25123 Brescia, Italy.
Background:
Toshiba Medical System has developed a new Doppler technique [Superb Microvascular Imaging (SMI)] that has improved microvascular flow imaging. SMI depicts perinodular and intranodular thyroid microvascular flow in higher detail compared to standard colour Doppler (CD) and power Doppler (PD) imaging.
Objective:
Assess the nodular microvascular architecture by SMI compared to CD and PD features in a series of thyroid nodules submitted to fine needle aspiration cytology, in order to evaluate the potential of SMI in detecting thyroid cancer.
Materials And Methods:
From April 2016 to July 2017, 254 patients with thyroid nodules, evaluated as at high risk for malignancy in agreement with AACE/ACE/AME guidelines, were submitted to cytology. All nodules were previously submitted to ultrasound grayscale, CD, PD, and SMI evaluation. Benign and malignant nodules were stratified in accordance to the number of vessels visualised by SMI: score 1 with a maximum of two blood vessels and score 2 with three or more vessels.
Results:
Score 1 was found in 59.6% of benign nodules and in 17.9% of malignant nodules, whereas score 2 was found in 40.4% and in 82.1%, respectively (sensitivity 81.7%; specificity 60.5%, p < 0.001). Variables significantly associated with malignancy in the univariate analysis were gender (OR, 0.18; 95% CI, 0.08-0.37; p < 0.001), vascularity (OR, 1.91; 95% CI, 1.65-3.89; p < 0.001), and SMI (OR, 6.72; 95% CI, 3.89-11.59; p < 0.001); multivariate logistic model confirmed SMI score 2 as an independent risk factor for malignancy (OR, 6.99; 95% CI, 3.46-12.09; p < 0.001).
Conclusions:
This prospective pilot study showed that SMI can depict intranodular flow in higher detail compared to CDI and PDI, thus improving thyroid cancer detection.
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