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Quantitative analysis of vascularity for thyroid nodules on ultrasound using superb microvascular imaging: Can nodular vascularity differentiate between malignant and benign thyroid nodules?

Min Ji HongHye Shin AhnSu Min HaHyun Jeong ParkJiyun Oh
Published in: Medicine (2022)
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.
Keyphrases
  • high resolution
  • magnetic resonance imaging
  • emergency department
  • blood flow
  • peripheral blood
  • computed tomography
  • deep learning
  • mass spectrometry
  • photodynamic therapy
  • fluorescence imaging
  • ultrasound guided