AUTHOR=Wang Bin , Cao Qing , Cui Xin-Wu , Dietrich Christoph F. , Yi Ai-jiao 

TITLE=A model based on clinical data and multi-modal ultrasound for predicting cervical lymph node metastasis in patients with thyroid papillary carcinoma

JOURNAL=Frontiers in Endocrinology

VOLUME=Volume 13 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/endocrinology/articles/10.3389/fendo.2022.1063998

DOI=10.3389/fendo.2022.1063998

ISSN=1664-2392

ABSTRACT=Objective: To explore the diagnostic performance based on clinical characteristics, conventional ultrasound, Angio PLUS (AP), shear wave elastography (SWE) and contrast-enhanced ultrasound (CEUS) for preoperative evaluation of cervical lymph node metastasis (CLNM) in papillary thyroid carcinoma (PTC) patients, find a reliable predictive model for evaluating CLNM.
Materials and Methods: A total of 206 patients with 206 thyroid nodules were enrolled. AP, SWE and CEUS were performed for all nodules. Univariate analysis and multivariate logistic regression analysis were performed to ascertain the independent risk factors. The sensitivity, specificity and the area under the curve (AUC) of independent risk factors and the diagnostic model were compared.
Results: Sex, age, nodules size, multifocality, contact extent with adjacent thyroid capsule, Emax and capsule integrity at CEUS were independent risk predictors for cervical lymph node metastasis of PTC. A predictive model was established based on the multivariate logistic regression: Logit (P) =−2.382+1.452×Sex−1.064×Age +1.338×Size+1.663×multifocality+1.606×contact extent with adjacent thyroid capsule+1.717×Emax+1.409×capsule integrity at CEUS. The AUC of the predictive model was 0.887 (95% CI: 0.841-0.933), significantly higher than using independent risk predictors alone
Conclusion: Our study found presence of male, age <45 years, size ≥ 10mm, multifocality, contact extent with adjacent thyroid capsule >25%, Emax ≥ 48.4 and interrupted capsule at CEUS were independent risk predictors for CLNM in PTC patients. We developed a diagnostic model for predicting CLNM, which could be a potentially simple, useful and accurate method for clinicians, it might be beneficial to surgical decision making, patients management, and improve prognosis.