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.
Highlights
Thyroid cancer accounts for about 3.8% of all malignant cases[1]
Results of some studies suggested that color Doppler ultrasound is useful in differentiation between benign and malignant thyroid nodules[15,16,17], whilst others suggested that Doppler ultrasound has limited value in prediction of thyroid malignancy[18,19,20,21,22,23]
The thyroid nodule with confirmed cytological/histological result was included in the study
Summary
Thyroid cancer accounts for about 3.8% of all malignant cases[1]. Among endocrine malignancies, thyroid cancer ranks the highest in the incidence. Grey-scale ultrasound (GSU) is commonly used to assess thyroid nodules and various GSU features for identifying malignant nodules have been reported such as microcalcification, hypoechogenicity, absent halo sign, solid internal structure, and irregular margins[4,5,6,7] Assessment of these features is subjective and qualitative which is vulnerable to inter and intra-observer variability. Results of some studies suggested that color Doppler ultrasound is useful in differentiation between benign and malignant thyroid nodules[15,16,17], whilst others suggested that Doppler ultrasound has limited value in prediction of thyroid malignancy[18,19,20,21,22,23] These controversial findings are probably due to the fact that assessment of thyroid nodular vascularity was performed subjectively rather than using an objective and quantitative approach in previous studies. The study aimed to evaluate the diagnostic accuracy of this computer-aided detection (CAD) of regional vascularity in distinguishing benign and malignant thyroid nodules, and to assess the added value of this CAD approach on GSU assessment of thyroid nodules
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