ISSN: 1899-0967
Polish Journal of Radiology
Established by prof. Zygmunt Grudziński in 1926 Sun
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2019
vol. 84
 
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Head and neck radiology
abstract:
Original paper

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

Seyed Babak Moosavi Toomatari
1
,
Afshin Mohammadi
2
,
Nariman Sepehrvand
3
,
Seyed Ehsan Moosavi Toomatari
4
,
Mohammad Ghasemi-Rad
5
,
Saber Zafar Shamspour
6
,
Seyfollah Rezayi
7
,
Mohammadreza Toubaei
1
,
Zahra Karimi Sarabi
8

1.
Department of Surgery, Zanjan University of Medical Sciences, Zanjan, Iran
2.
Department of Radiology, Urmia University of Medical Sciences, Urmia, Iran
3.
Department of Medicine, University of Alberta, Edmonton, Alberta, Canada
4.
Department of General Surgery, Tabriz University of Medical Sciences, Tabriz, Iran
5.
Department of Radiology, Baylor College of Medicine, Houston, Texas, USA
6.
Department of Neurosurgery, Shiraz University of Medical Sciences, Shiraz, Iran
7.
Department of Surgery, Urmia University of Medical Sciences, Urmia, Iran
8.
Department of Anaesthesiology, Urmia University of Medical Sciences, Urmia, Iran
© Pol J Radiol 2019; 84: e517-e521
Online publish date: 2019/12/06
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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.

keywords:

ultrasonography, thyroid nodule, colour mapping, malignancy

 
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