Computer-aided assessment of regional vascularity of thyroid nodules for prediction of malignancy

Faisal N. Baig, Jurgen T.J. Van Lunenburg, Shirley Y.W. Liu, Shea Ping Yip, Helen K.W. Law, Tin Cheung Ying

Research output: Journal article publicationJournal articleAcademic researchpeer-review

8 Citations (Scopus)

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.
Original languageEnglish
Article number14350
JournalScientific Reports
Volume7
Issue number1
DOIs
Publication statusPublished - 1 Dec 2017

ASJC Scopus subject areas

  • General

Cite this