A novel computerised quantification of thyroid vascularity in the differentiation of malignant and benign thyroid nodules

  • Toomatari S
  • Mohammadi A
  • Sepehrvand N
  • et al.
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Abstract

Purpose: Only five percent of thyroid nodules are malignant. It is important to find reliable and at the same time non-invasive methods to identify high-risk nodules. The aim of this study was to determine the diagnostic validity of a morphologic feature-oriented approach of ultrasound study for the identification of malignant thyroid nodules. Material and methods: Seventy-one thyroid nodules in 71 consecutive patients were evaluated with both ultrasonography (US) and US-assisted fine needle aspiration biopsy (FNAB). Thyroid grey-scale and power Doppler US were performed, and a Windows-based software was designed to process power Doppler US (PDUS) images that were recorded directly by the US device. We provided a histogram graph of coloured pixels and calculated the Malignancy Index to identify the probability of malignancy for each thyroid nodule. Results: Thirty-six nodules (50.7%) were determined to be malignant in FNAB. Area under the receiver operating curve was 0.91 (95% CI: 0.85-0.98) for PDUS-based malignancy index in differentiating malignant thyroid nodules from benign ones. The best cut-off point for malignancy index was determined to be 0.092, with a sensitivity of 86.1% and specificity of 80% in identifying malignant nodules. Conclusions: This PDUS-driven malignancy index using a contour-finding algorithm approach could accurately and reliably differentiate malignant and benign thyroid nodules. As a pre-FNAB assessment, the malignancy index may be able to reduce the number of patients with nodular thyroid disease undergoing this invasive procedure.

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APA

Toomatari, S. B. M., Mohammadi, A., Sepehrvand, N., Toomatari, S. E. M., Ghasemi-Rad, M., Shamspour, S. Z., … Sarabi, Z. K. (2019). A novel computerised quantification of thyroid vascularity in the differentiation of malignant and benign thyroid nodules. Polish Journal of Radiology, 84, 517–521. https://doi.org/10.5114/pjr.2019.91208

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