Abstract
Objective: The aim of this study was to assess and compare the diagnostic power of B-mode ultrasonography (US), power Doppler US (PD), and ultrasound elastography (USE) in detecting malignant lymph nodes (LNs) during follow-up of patients who were operated on for differentiated thyroid cancer (DTC). Methods: In this prospective study, a total of 103 cervical LNs having suspicious malignant features from 72 patients with DTC were examined using US, PD, and USE. USE scores were classified from 1 to 3 according to the presence of elasticity (1, soft; 2, intermediate; 3, hard). The strain ratios (SRs) of all LNs were calculated according to adjacent muscle tissue. Results: The most-sensitive ultrasonographic features were hilum loss and hypoechogenicity, with 94.4% and 80.6% sensitivity and 93.5% and 84.4% negative predictive value, respectively. The most-specific feature was the presence of cystic component, with 98.5% specificity and 85.7% positive predictive value. Presence of diffuse/ chaotic or irregular vascularity in PD had 47.2% sensitivity and 83.6% specificity in predicting metastasis. In USE, the sensitivity and specificity of score 3 were 56.7% and 74.2%, respectively. The median SR of metastatic LNs was higher than that of benign LNs (median SR [min-max], 3.0 [0.16 and 29] vs. 1.89 [0.26 and 37.9]), but the difference was not significant (P = .07). Multivariate logistic regression analyses revealed 4.9-, 6.6-, and 10-fold increases in metastasis risk for short/long axis ratio ≥0.5, nodal vascularity, and score 3 USE, respectively (P<.05). Conclusion: While USE had higher sensitivity, PD had higher specificity in detecting malignant LNs, but none of these techniques was as sensitive and specific as gray-scale US features.
| Original language | English |
|---|---|
| Pages (from-to) | 1049-1055 |
| Number of pages | 7 |
| Journal | Endocrine Practice |
| Volume | 25 |
| Issue number | 10 |
| DOIs | |
| Publication status | Published - Oct 2019 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
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