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.

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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
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article

A nomogram based on clinical and ultrasound features to identify sub-1 cm benign and malignant thyroid lesions

Yu-xia Zhai, Jia-fan Li, Huanbin Lin, Jiajia Wang et al.
Clinical Hemorheology and Microcirculation
Thyroid Cancer Diagnosis and Treatment
article

A nomogram based on clinical and ultrasound features to identify sub-1 cm benign and malignant thyroid lesions

Yu-xia Zhai, Jia-fan Li, Huanbin Lin, Jiajia Wang, Zhe Chen, Ruo-ting Zheng
article en

Abstract

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.

Clinical Hemorheology and MicrocirculationVol. 89(4)
Shantou University (CN), Cancer Hospital of Shantou University Medical College (CN), Second Affiliated Hospital of Shantou University Medical College (CN)
Good health and well-being
Openalex Percentile: Top 93%
Thyroid Cancer Diagnosis and Treatment
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A nomogram based on clinical and ultrasound features to identify sub-1 cm benign and malignant thyroid lesions — Yu-xia Zhai, Jia-fan Li, et al. · Clinical Hemorheology and Microcirculation (2025) | TGRS Research Map | TGRS