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Updated: Jan 8, 2026

Author Spotlight: Integrating Ultrasound Imaging with Biochemical Markers for Thyroid Disease Diagnosis
Published on: February 9, 2024
Qualitative and Quantitative Prediction of Central Cervical Lymph Node Metastases by Utilizing Contrast-enhanced
1Department of Ultrasound, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, PR China.
Abstract:
The aim of this study was to explore the qualitative and quantitative characteristics of PTC on contrast-enhanced ultrasound (CEUS) in predicting central cervical lymph node metastases (CLNM). This prospective study analyzed a dataset of grayscale US and CEUS images in 201 nodules with biopsy-confirmed PTC. Seven grayscale US features and five qualitative CEUS parameters were employed to develop the approaches. Four quantitative CEUS parameters of the time-intensity curve were obtained and compared between PTC and adjacent thyroid tissue (ATT), as well as within different PTC groups. The diagnostic performance of an equation with quantitative CEUS parameters were compared with grayscale US features and qualitative CEUS for predicting central CLNM. The patients were divided into three groups based on their final pathological results: 28 patients in the macro-metastases group, 95 patients in micro-metastasis group, 78 patients confirmed to have no metastases. Independent predictive grayscale US and qualitative CEUS features included size, capsule contact and heterogeneity on CEUS. In quantitative CEUS parameters, there were significant differences in peak intensity (PI) between PTC and ATT in all three groups (p < 0.05). Significant differences in PI were also observed among three groups (p < 0.05). A PI ratio of PTC and ATT greater than or equal to 1 was found to be a more sensitive index for predicting central CLNM. The quantitative CEUS-assisted US equation demonstrated the best diagnostic performance. A grayscale US and CEUS equation with PI ratio based on quantitative CEUS was developed for predicting occult central CLNM and it is considered highly valuable in the clinical management of PTC.

