Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/75732
Title: Computer-aided assessment of regional vascularity of thyroid nodules for prediction of malignancy
Authors: Baig, FN 
van Lunenburg, JTJ 
Liu, SYW
Yip, SP 
Law, HKW 
Ying, M 
Issue Date: 2017
Publisher: Nature Publishing Group
Source: Scientific reports, 2017, v. 7, 14350 How to cite?
Journal: Scientific reports 
Abstract: Color Doppler vascular index (VI) was assessed alone and in combination with grey-scale ultrasound (GSU) in regionally subdivided thyroid nodules in diagnosing thyroid cancer. Color Doppler sonograms of 111 thyroid nodules were evaluated by a home-developed algorithm that performed "offsetting" (algorithm for changing the area of a region of interest, ROI, without distorting the ROI's contour) and assessed peripheral, central and overall VI of thyroid nodules. Results showed that the optimum offset for dividing peripheral and central regions of nodule was 22%. At the optimum offset, the mean VI of peripheral, central, and overall regions of malignant nodules were significantly higher than those of benign nodules (26.5 +/- 16.2%, 21.7 +/- 19.6%, 23.8 +/- 4.6% v/s 18.2 +/- 16.7%, 11.9 +/- 15.1% and 16.6 +/- 1.8% respectively, P < 0.05). The optimum cut-off of peripheral, central, and overall VI was 19.7%, 9.1% and 20.2% respectively. When compared to GSU alone, combination of VI assessment with GSU evaluation of thyroid nodules increased the diagnostic accuracy from 58.6% to 79.3% (P < 0.05). In conclusion, a novel algorithm for regional subdivision and quantification of thyroid nodular VI in ultrasound images was established, and the optimum offset and cut-off were derived. Assessment of intranodular VI in conjunction with GSU can increase the accuracy in ultrasound diagnosis of thyroid cancer.
URI: http://hdl.handle.net/10397/75732
ISSN: 2045-2322
EISSN: 2045-2322
DOI: 10.1038/s41598-017-14432-7
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