A nomogram based on clinical and ultrasound features to identify sub-1 cm benign and malignant thyroid lesions
BackgroundA non-invasive and reliable method is essential for diagnosing sub-1 cm thyroid lesions.ObjectiveWe have developed a nomogram that integrates ultrasound features and clinical risk factors to effectively diagnosed sub-1 cm thyroid lesions.MethodsOur study included 406 patients with sub-1 cm thyroid lesions. We collected their demographic data and ultrasound characteristics of the thyroid, followed by conducting univariate and multivariate analyses to identify the risk factors. Subsequently, we developed a nomogram for predicting sub-1 cm thyroid lesions, comparing its diagnostic performance with that of American College of Radiology TIRADS (ACR TI-RADS) and Chinese Thyroid Imaging Reporting and Data Systems (C TI-RADS).ResultsSix variables, including female gender, capsular invasion, solid composition, aspect ratio >1, irregular margin and microcalcification, were identified as potential predictors and used to develop a predictive nomogram. Receiver operating characteristic curves were constructed and compared with ACR TI-RADS and C TI-RADS classifications. The area under the curve of the nomogram was found to be at 0.85, while the AUC of ACR TI-RADS classification and C TI-RADS classification were at 0.771 and 0 .736 respectively.ConclusionsBy utilizing this user-friendly nomogram, the likelihood of sub-1 cm malignancy in thyroid lesions can be objectively quantified.
Authors
- Yu-xia Zhai
- Jia-fan Li
- Huanbin Lin
- Jiajia Wang (ORCID: https://orcid.org/0000-0003-4506-5417)
- Zhe Chen (ORCID: https://orcid.org/0000-0003-1283-0266)
- Ruo-ting Zheng
Institutions
- Shantou University (CN)
- Cancer Hospital of Shantou University Medical College (CN)
- Second Affiliated Hospital of Shantou University Medical College (CN)
Publication Details
- Journal
- Clinical Hemorheology and Microcirculation
- Published
- 2025-03-19
- DOI
- https://doi.org/10.1177/13860291251324565
- Primary Topic
- Thyroid Cancer Diagnosis and Treatment
- Type
- article
- Field-Weighted Citation Impact
- 0.00