{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,29]],"date-time":"2026-08-29T12:08:26Z","timestamp":1788005306331,"version":"build-2784847793"},"reference-count":21,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2025,8,29]],"date-time":"2025-08-29T00:00:00Z","timestamp":1756425600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Endocrinol."],"abstract":"<jats:sec><jats:title>Purpose<\/jats:title><jats:p>To assess the clinical utility of ultrasound grayscale ratio (UGSR) in distinguishing between benign and malignant thyroid nodules.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>We conducted a retrospective analysis of patients diagnosed with thyroid nodules between January 2017 and December 2021. Malignancy and benignity were determined based on histopathology (biopsy or surgery) as the reference standard. Conventional ultrasonography (US) was performed to measure the maximum diameter of each nodule and assess positive features of the Chinese Thyroid Imaging Reporting and Data System (C-TIRADS). UGSR was calculated as the ratio of nodule grayscale value to surrounding thyroid parenchyma grayscale value, quantified using ImageJ software. Two experienced radiologists used ImageJ software for UGSR measurements. Logistic regression analysis examined the association between UGSR and thyroid malignancy. A receiver operating characteristic (ROC) curve analysis was conducted, and the area under the curve (AUC) was calculated to assess UGSR\u2019s effectiveness in distinguishing between benign and malignant thyroid nodules. The UGSR cut-off value was established through ROC curve analysis.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>A total of 125 nodules (78 benign, 47 malignant) were evaluated. Significant differences were observed between benign and malignant nodules in maximum diameter (<jats:italic>p<\/jats:italic> = 0.042), UGSR (<jats:italic>p<\/jats:italic> &amp;lt; 0.001), and C-TIRADS features (<jats:italic>p<\/jats:italic> &amp;lt; 0.001), supporting UGSR\u2019s diagnostic utility. However, no significant intergroup differences were observed in gender or age distribution (<jats:italic>p<\/jats:italic>&amp;gt;0.05 for both). Multivariable logistic regression analysis identified UGSR, irregular margins, taller-than-wide orientation, and microcalcifications as independent predictive factors for differentiating malignant from benign thyroid nodules (all <jats:italic>p<\/jats:italic>&amp;lt;0.05). The diagnostic performance evaluation demonstrated that UGSR achieved an AUC of 0.852 (95% CI: 0.792 - 0.912), with a sensitivity of 63.83% and specificity of 92.31%. UGSR showed significantly superior diagnostic accuracy compared to markedly hypoechogenicity (<jats:italic>p<\/jats:italic>&amp;lt;0.05).<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>UGSR demonstrated high specificity (92.31%) and reliability in differentiating malignant from benign thyroid nodules, suggesting its potential as a quantitative adjunct to ultrasound diagnosis, though sensitivity (63.83%) warrants combination with other features.<\/jats:p><\/jats:sec>","DOI":"10.3389\/fendo.2025.1665113","type":"journal-article","created":{"date-parts":[[2025,8,29]],"date-time":"2025-08-29T04:10:36Z","timestamp":1756440636000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":3,"title":["The predictive value of the ultrasound grayscale ratio for identifying malignant thyroid nodules"],"prefix":"10.3389","volume":"16","author":[{"given":"Kaimei","family":"Lian","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Teng","family":"Lin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2025,8,29]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","DOI":"10.21037\/qims-21-501","article-title":"Dual-source dual-energy computed tomography-derived quantitative parameters combined with machine learning for the differential diagnosis of benign and Malignant thyroid nodules","volume":"12","author":"Jiang","year":"2022","journal-title":"Quant Imaging Med Surg"},{"key":"B2","doi-asserted-by":"publisher","DOI":"10.1002\/jcla.23458","article-title":"Comparison of the clinical validity of droplet digital PCR to ARMS-PCR for BRAF V600E mutation detection in thyroid nodules","volume":"34","author":"Li","year":"2020","journal-title":"J Clin Lab Anal"},{"key":"B3","doi-asserted-by":"publisher","first-page":"298","DOI":"10.14366\/usg.21097","article-title":"Using ultrasonographic features to predict the outcomes of patients with small papillary thyroid carcinomas: a retrospective study implementing the 2015 ATA patterns and ACR TI-RADS categories","volume":"41","author":"Min","year":"2022","journal-title":"Ultrasonography"},{"key":"B4","doi-asserted-by":"publisher","DOI":"10.3233\/CH-201021","article-title":"Comparison of ACR TI-RADS, Kwak TI-RADS, ATA guidelines and KTA\/KSThR guidelines in combination with SWE in the diagnosis of thyroid nodules","volume":"78","author":"Zhang","year":"2021","journal-title":"Clin Hemorheol Microcirc"},{"key":"B5","doi-asserted-by":"publisher","DOI":"10.3389\/fonc.2021.662273","article-title":"Contrast-enhanced ultrasound in the differential diagnosis and risk stratification of ACR TI-RADS category 4 and 5 thyroid nodules with non-hypovascular","volume":"11","author":"Wang","year":"2021","journal-title":"Front Oncol"},{"key":"B6","doi-asserted-by":"publisher","DOI":"10.1007\/s11154-020-09592-3","article-title":"The ultrasound risk stratification systems for thyroid nodule have been evaluated against papillary carcinoma. 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