{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,21]],"date-time":"2026-08-21T10:25:28Z","timestamp":1787307928847,"version":"build-2736575974"},"reference-count":35,"publisher":"Oxford University Press (OUP)","issue":"1211","license":[{"start":{"date-parts":[[2026,3,16]],"date-time":"2026-03-16T00:00:00Z","timestamp":1773619200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/pages\/standard-publication-reuse-rights"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,8,21]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Purpose<\/jats:title>\n                    <jats:p>This study aimed to develop a comprehensive predictive model that integrates clinical factors, conventional ultrasound (US) features, and ultrasound viscosity imaging metrics to improve diagnostic accuracy in thyroid nodules and to explore the role of viscosity metrics in differentiating benign and malignant thyroid nodules.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>A total of 215 patients with thyroid nodules were included in the study, with 70% in the training set and 30% in the testing set. Univariate and multivariate logistic regression were employed to identify key predictors, resulting in the development of three models. Three models were developed: ModA (clinical factors), ModB (clinical factors and conventional US features), and ModC (clinical factors, conventional US features, and US viscosity imaging). The diagnostic efficacy of the models was evaluated and compared using receiver operating characteristic curves.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Multivariate analysis revealed that factors, such as echogenicity, viscosity minimum (Vmin), and viscosity mean (Vmean), were significant risk factors for distinguishing between benign and malignant thyroid nodules. In the testing set, ModA demonstrated an Area Under the Curve (AUC) of 0.777, ModB exhibited an improvement to 0.922, and ModC demonstrated an AUC of 0.945. The findings indicate that ModC exhibits superior predictive accuracy for differentiating between benign and malignant thyroid nodules.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>The integration of US viscosity imaging with clinical factors and conventional US features can enhance the predictive performance of differentiation in thyroid nodules, offering a reliable clinical tool to support early and accurate diagnosis of thyroid nodules.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Research Questions<\/jats:title>\n                  <\/jats:sec>","DOI":"10.1093\/postmj\/qgaf224","type":"journal-article","created":{"date-parts":[[2025,12,2]],"date-time":"2025-12-02T13:00:07Z","timestamp":1764680407000},"page":"817-825","source":"Crossref","is-referenced-by-count":0,"title":["A comprehensive predictive model study: ultrasound viscosity imaging in thyroid nodules"],"prefix":"10.1093","volume":"102","author":[{"ORCID":"https:\/\/orcid.org\/0009-0000-7216-8011","authenticated-orcid":false,"given":"Xiaohan","family":"Zou","sequence":"first","affiliation":[{"name":"Department of Ultrasound, The Second Clinical Medical College, Jinan University (Shenzhen People's Hospital) , No. 1017 Dongmen North Road, Luohu District, Shenzhen, Guangdong 518020, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sijie","family":"Mo","sequence":"additional","affiliation":[{"name":"Department of Ultrasound, The Second Clinical Medical College, Jinan University (Shenzhen People's Hospital) , No. 1017 Dongmen North Road, Luohu District, Shenzhen, Guangdong 518020, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shuzhen","family":"Tang","sequence":"additional","affiliation":[{"name":"Department of Ultrasound, The Second Clinical Medical College, Jinan University (Shenzhen People's Hospital) , No. 1017 Dongmen North Road, Luohu District, Shenzhen, Guangdong 518020, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mengna","family":"Shao","sequence":"additional","affiliation":[{"name":"Department of Ultrasound, The Second Clinical Medical College, Jinan University (Shenzhen People's Hospital) , No. 1017 Dongmen North Road, Luohu District, Shenzhen, Guangdong 518020, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jing","family":"Chen","sequence":"additional","affiliation":[{"name":"Department of Ultrasound, The Second Clinical Medical College, Jinan University (Shenzhen People's Hospital) , No. 1017 Dongmen North Road, Luohu District, Shenzhen, Guangdong 518020, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fengling","family":"Chen","sequence":"additional","affiliation":[{"name":"Department of Ultrasound Medicine, Beihai No. 2 People's Hospital , No. 116, Xinshiji Avenue, Beihai City 536000, Guangxi Zhuang Autonomous Region ,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lin","family":"Zhou","sequence":"additional","affiliation":[{"name":"Department of Ultrasound Medicine, Beihai No. 2 People's Hospital , No. 116, Xinshiji Avenue, Beihai City 536000, Guangxi Zhuang Autonomous Region ,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7579-6969","authenticated-orcid":false,"given":"Zhibin","family":"Huang","sequence":"additional","affiliation":[{"name":"Department of Ultrasound, The Second Clinical Medical College, Jinan University (Shenzhen People's Hospital) , No. 1017 Dongmen North Road, Luohu District, Shenzhen, Guangdong 518020, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fajin","family":"Dong","sequence":"additional","affiliation":[{"name":"Department of Ultrasound, The Second Clinical Medical College, Jinan University (Shenzhen People's Hospital) , No. 1017 Dongmen North Road, Luohu District, Shenzhen, Guangdong 518020, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2026,3,16]]},"reference":[{"key":"2026082105420093500_ref1","doi-asserted-by":"publisher","first-page":"2347","DOI":"10.1056\/NEJMcp1415786","article-title":"Clinical practice. 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