A semi-quantitative approach to compare high-sensitivity power doppler sonography and conventional power doppler sonography in the assessment of thyroid vascularity

摘要

Background: Ultrasound is a useful imaging tool in the assessment of thyroid glands, and Doppler ultrasound helps in the evaluation of thyroid vascularity. This study was undertaken to evaluate the difference in the thyroid vascularity demonstrated on the state-of-the-art high-sensitivity power Doppler sonography (HSPDS) and the conventional power Doppler sonography (PDS), and to investigate the feasibility of using a customized algorithm with image-processing software for semi-quantitative assessment of thyroid vascularity. Methods: A total of 25 healthy volunteers were included in the study, and each subject had two thyroid ultrasound examinations with HSPDS and PDS, respectively. High sensitivity and conventional power Doppler sonograms of the thyroid glands were taken and recorded. To evaluate the vascularity of thyroid lobes quantitatively, a customized algorithm using the software Matlab ® was developed and used to analyze the ultrasound images. The vascularity of thyroid lobe (i.e., region of interest, ROI) was expressed as the vascular index (VI), which is the ratio of the number of color pixels to the total number of pixels within the ROI. Results: Results showed that thyroid vascularity was detected in all thyroid lobes on both HSPDS and PDS. The mean VI of the thyroid lobes on HSPDS (right lobe, 0.31±0.08; left lobe, 0.32±0.07) was significantly higher than on PDS (right lobe, 0.18±0.09; left lobe, 0.16±0.08) (p0.05). There was no significant difference in the VI between the right and left thyroid lobes (p0.05). On HSPDS, 96% of the thyroid lobes showed a VI0.5, while 96% of thyroid lobes had a VI0.3 on PDS. Conclusions: HSPDS is more sensitive than PDS in the detection of thyroid vascularity. The developed algorithm can quantify the color pixels on power Doppler sonograms, which is useful for objective assessment of thyroid vascularity.