{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,5]],"date-time":"2026-08-05T02:36:24Z","timestamp":1785897384260,"version":"3.56.0"},"reference-count":21,"publisher":"Springer Science and Business Media LLC","issue":"2","license":[{"start":{"date-parts":[[2025,7,3]],"date-time":"2025-07-03T00:00:00Z","timestamp":1751500800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2025,7,3]],"date-time":"2025-07-03T00:00:00Z","timestamp":1751500800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/501100004000","name":"Guangzhou Municipal Science and Technology Program key projects","doi-asserted-by":"publisher","award":["2024A04J3554"],"award-info":[{"award-number":["2024A04J3554"]}],"id":[{"id":"10.13039\/501100004000","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Digit Imaging. Inform. med."],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Machine learning is now extensively implemented in medical imaging for preoperative risk stratification and post-therapeutic outcome assessment, enhancing clinical decision-making. Numerous studies have focused on predicting whether thyroid nodules are benign or malignant using a nodule-based approach, which is time-consuming, inefficient, and overlooks the impact of the peritumoral region. To evaluate the effectiveness of using the whole-thyroid as the region of interest in differentiating between benign and malignant thyroid nodules, exploring the potential application value of the entire thyroid. This study enrolled 1121 patients with thyroid nodules between February 2017 and May 2023. All participants underwent contrast-enhanced CT scans prior to surgical intervention. Radiomics features were extracted from arterial phase images, and feature dimensionality reduction was performed using the Least Absolute Shrinkage and Selection Operator (LASSO) algorithm. Four machine learning models were trained on the selected features within the training cohort and subsequently evaluated on the independent validation cohort. The diagnostic performance of whole-thyroid versus nodule-based radiomics models was compared through receiver operating characteristic (ROC) curve analysis and area under the curve (AUC) metrics. The nodule-based logistic regression model achieved an AUC of 0.81 in the validation set, with sensitivity, specificity, and accuracy of 78.6%, 69.4%, and 75.6%, respectively. The whole-thyroid-based random forest model attained an AUC of 0.80, with sensitivity, specificity, and accuracy of 90.0%, 51.9.%, and 80.1%, respectively. The AUC advantage ratios on the LR, DT, RF, and SVM models are approximately\u2009\u2212\u20092.47%, 0.00%,\u2009\u2212\u20094.76%, and\u2009\u2212\u20094.94%, respectively. The Delong test showed no significant differences among the four machine learning models regarding the region of interest defined by either the thyroid primary lesion or the whole thyroid. There was no significant difference in distinguishing between benign and malignant thyroid nodules using either a nodule-based or whole-thyroid-based strategy for ROI outlining. We hypothesize that the whole-thyroid approach provides enhanced diagnostic capability for detecting\u00a0papillary thyroid carcinomas (PTCs) with ill-defined margins.<\/jats:p>","DOI":"10.1007\/s10278-025-01584-6","type":"journal-article","created":{"date-parts":[[2025,7,3]],"date-time":"2025-07-03T12:28:42Z","timestamp":1751545722000},"page":"1265-1273","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Can Whole-Thyroid-Based CT Radiomics Model Achieve the Performance of Lesion-Based Model in Predicting the Thyroid Nodules Malignancy? \u2014 A Comparative Study"],"prefix":"10.1007","volume":"39","author":[{"given":"Wenxia","family":"Yuan","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiayang","family":"Wu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wenfeng","family":"Mai","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hengguo","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2112-2870","authenticated-orcid":false,"given":"Zhenyu","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,7,3]]},"reference":[{"issue":"1","key":"1584_CR1","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1089\/thy.2015.0020","volume":"26","author":"BR Haugen","year":"2016","unstructured":"Haugen BR, Alexander EK, Bible KC, et al. 2015 American Thyroid Association Management Guidelines for Adult Patients with Thyroid Nodules and Differentiated Thyroid Cancer: The American Thyroid Association Guidelines Task Force on Thyroid Nodules and Differentiated Thyroid Cancer. Thyroid 26(1):1-133,2016.","journal-title":"Thyroid"},{"key":"1584_CR2","doi-asserted-by":"crossref","unstructured":"Salvatore Vaccarella PD, Silvia Franceschi MD, Freddie Bray PD, Christopher P. Wild PD, Martyn Plummer PDaLDM, Ph.D. Worldwide Thyroid-Cancer Epidemic? The Increasing Impact of Overdiagnosis. N Engl J Med 375(7):614\u2013617,2016.","DOI":"10.1056\/NEJMp1604412"},{"issue":"6","key":"1584_CR3","first-page":"373","volume":"63","author":"DF Schneider","year":"2013","unstructured":"Schneider DF, Chen H. New developments in the diagnosis and treatment of thyroid cancer. CA Cancer J Clin 63(6):373-394,2013.","journal-title":"CA Cancer J Clin"},{"key":"1584_CR4","first-page":"1","volume":"2021","author":"H Liu","year":"2021","unstructured":"Liu H, Jin J, Chen Q, Li Z, Falhammar H. A Single-Center Retrospective Study of the Impact of Thyroid Cancer on the Malignant Risk of Contralateral TI-RADS 3 and 4 Nodules. Int J Endocrinol 2021:1-8,2021.","journal-title":"Int J Endocrinol"},{"issue":"1","key":"1584_CR5","doi-asserted-by":"publisher","first-page":"185","DOI":"10.1148\/radiol.2018172572","volume":"287","author":"JK Hoang","year":"2018","unstructured":"Hoang JK, Middleton WD, Farjat AE, et al. Reduction in Thyroid Nodule Biopsies and Improved Accuracy with American College of Radiology Thyroid Imaging Reporting and Data System. Radiology 287(1):185-193,2018.","journal-title":"Radiology"},{"issue":"1","key":"1584_CR6","first-page":"7","volume":"72","author":"RL Siegel","year":"2022","unstructured":"Siegel RL, Miller KD, Fuchs HE, Jemal A. Cancer statistics, 2022. CA Cancer J Clin 72(1):7-33,2022.","journal-title":"CA Cancer J Clin"},{"key":"1584_CR7","doi-asserted-by":"crossref","unstructured":"Lin S, Gao M, Yang Z, et al. CT-Based Radiomics Models for Differentiation of Benign and Malignant Thyroid Nodules: A Multicenter Development and Validation Study. 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Intranodular and perinodular ultrasound radiomics distinguishes benign and malignant thyroid nodules: a multicenter study. Gland Surgery 13(12):2359-2371,2024.","journal-title":"Gland Surgery"},{"issue":"11","key":"1584_CR18","doi-asserted-by":"publisher","first-page":"1942","DOI":"10.21037\/gs-24-247","volume":"13","author":"W Zhan","year":"2024","unstructured":"Zhan W, Cai X, Qi H, et al. Intratumoral and peritumoral radiomics based on ultrasound for the differentiation of follicular thyroid neoplasm. Gland Surgery 13(11):1942-1953,2024.","journal-title":"Gland Surgery"},{"key":"1584_CR19","doi-asserted-by":"crossref","unstructured":"Liu C, Xiao C, Chen J, et al. Risk factor analysis for predicting cervical lymph node metastasis in papillary thyroid carcinoma: a study of 966 patients. BMC Cancer 19(1),2019.","DOI":"10.1186\/s12885-019-5835-6"},{"issue":"227","key":"1584_CR20","first-page":"357","volume":"39","author":"J Berkson","year":"1944","unstructured":"Berkson J. Application of the Logistic Function to Bio-Assay. Journal of the American Statistical Association 39(227):357-365,1944.","journal-title":"Journal of the American Statistical Association"},{"key":"1584_CR21","doi-asserted-by":"crossref","unstructured":"Peng W, Liu C, Xia S, et al. Thyroid nodule recognition in computed tomography using first order statistics. Biomed Eng Online 16(1),2017.","DOI":"10.1186\/s12938-017-0367-2"}],"container-title":["Journal of Imaging Informatics in Medicine"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10278-025-01584-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10278-025-01584-6","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10278-025-01584-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,22]],"date-time":"2026-04-22T16:22:49Z","timestamp":1776874969000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10278-025-01584-6"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,7,3]]},"references-count":21,"journal-issue":{"issue":"2","published-online":{"date-parts":[[2026,4]]}},"alternative-id":["1584"],"URL":"https:\/\/doi.org\/10.1007\/s10278-025-01584-6","relation":{},"ISSN":["2948-2933"],"issn-type":[{"value":"2948-2933","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,7,3]]},"assertion":[{"value":"20 February 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"29 May 2025","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"9 June 2025","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"3 July 2025","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"This is an observational, retrospective study and received approval from the institutional review board of the First affiliated Hospital of Jinan University (KY-2023\u2013327), which exempted the need for informed consent given the retrospective design of the study.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics Approval and Consent to Participate"}},{"value":"Not applicable.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Clinical Trial Registration"}},{"value":"Not applicable.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Permission to Reproduce Material from Other Sources"}},{"value":"The authors declare no competing interests.","order":5,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of Interest"}}]}}