Determination of lymph node metastasis using quantitative ultrasound elastography of papillary thyroid carcinoma nodule: a systematic review and meta-analysis

papillary thyroid carcinoma (PTC) as the most common thyroid tumor, tends to invade adjacent organs, especially lymphatic system. This study aimed to evaluate the discrimination performance of ultrasound elastography (USE) in assessing PTC nodule for determination of cervical lymph node metastasis (CLNM)...

Abstract
Background and purpose
papillary thyroid carcinoma (PTC) as the most common thyroid tumor, tends to invade adjacent organs, especially lymphatic system. This study aimed to evaluate the discrimination performance of ultrasound elastography (USE) in assessing PTC nodule for determination of cervical lymph node metastasis (CLNM).
Methods
The protocol was pre-registered at (https://osf.io/r5tc8). Using PubMed, Web of Science, Embase, and Cochrane Library, studies published up to March 10, 2025, were identified. Data extraction was conducted independently, and a random-effects bivariate model was applied to estimate pooled differentiation accuracy estimates.
Results
Twenty-one studies were included involving 7559 patients; 2790 (36%) were positive for CLNM, while 4769 (63%) were negative. The pooled Emean values for positive and negative CLNM were 51.2k Pa (95% CI: 42.6 to 59.7) and 44.8 kPa (95% CI: 35.2 to 54.4), respectively. It represents an absolute increase of 6.14 kPa (95% CI: 2.70 to 9.59) in the metastatic group compared to the benign group. Additionally, the pooled Emax value for positive and negative CLNM were 87.9 kPa (95% CI: 49.5 to 126.4) and 68.7 kPa (95% CI: 44.2 to 93.1), respectively. This corresponds to an absolute increase of + 19.57 kPa (95% CI: 2.96 to 36.18) in the metastatic group, representing a more dramatic elevation compared to Emean values. The thyroid nodule Emax and Emean were significantly higher for positive CLNM of + 27.5% (95% CI: 10.5–44.5%) and + 12.9% (95% CI: 5.1–20.7%) respectively. Combining USE with conventional ultrasound improved differentiation accuracy, achieving a sensitivity of 80% (95% CI: 62–90%), specificity of 79% (95% CI: 70–85%), and an AUC of 0.85 (95% CI: 0.81 to 0.88).
Conclusion
USE parameters demonstrated potential as a discrimination tool for the preoperative assessment of CLNM, particularly when combined with conventional ultrasound, which enhances its performance.

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Ardakani AA

He received his Ph.D. in Medical Physics in 2018 from the Iran University of Medical Sciences (IUMS), specializing in medical imaging and using artificial intelligence in radiological diagnosis. His research interests focus on the physics of medical imaging systems, quantitative analysis of medical images, and applying artificial intelligence in diagnostic radiology procedures. He is an assistant professor of Medical Physics at Shahid Beheshti University of Medical Sciences.

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