{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,17]],"date-time":"2026-04-17T14:17:38Z","timestamp":1776435458729,"version":"3.51.2"},"reference-count":29,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2024,11,15]],"date-time":"2024-11-15T00:00:00Z","timestamp":1731628800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2024,11,15]],"date-time":"2024-11-15T00:00:00Z","timestamp":1731628800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/501100005047","name":"Liaoning Natural Science Foundation","doi-asserted-by":"crossref","award":["No. 2022-YGJC-52"],"award-info":[{"award-number":["No. 2022-YGJC-52"]}],"id":[{"id":"10.13039\/501100005047","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Cancer Imaging"],"abstract":"<jats:title>Abstract<\/jats:title><jats:sec>\n                <jats:title>Objective<\/jats:title>\n                <jats:p>The aim of this study was to establish an ensemble learning model based on clinicopathological parameter and ultrasound radomics for assessing the risk of lateral cervical lymph node with short diameter less than 8\u00a0mm (small lymph nodes were used instead) metastasis in patients with papillary thyroid cancer (PTC), thereby guiding the selection of surgical methods.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Methods<\/jats:title>\n                <jats:p>This retrospective analysis was conducted on 454 patients diagnosed with papillary thyroid carcinoma who underwent total thyroidectomy and lateral neck lymph node dissection or lymph node intraoperative frozen section biopsy at the First Hospital of China Medical University between January 2015 and April 2022. In a ratio of 8:2, 362(80%) patients were assigned to the training set and 92(20%) patients were assigned to the test set. Clinical pathological features and radomics features related to ultrasound imaging were extracted, followed by feature selection using recursive feature elimination (RFE). Based on distinct feature sets, we constructed ensemble learning models comprising random forest (RF), extreme gradient boosting (XGBoost), categorical boosting (CatBoost), gradient boosting decision tree (GBDT), and light gradient boosting machine (Lightgbm) to develop clinical models, radiomics models, and clinical-radiomic models. Through the comparison of performance metrics such as area under curve (AUC), accuracy (ACC), specificity (SPE), precision (PRE), recall rate, F1 score, mean squared error (MSE) etc., we identified the optimal model and visualized its results using shapley additive exPlanations (SHAP).<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Results<\/jats:title>\n                <jats:p>In this study, a total of 454 patients were included, among whom 342 PTC patients had small lymph node metastasis in the lateral neck region, while 112 did not have any metastasis. A total of 1035 features were initially considered for inclusion in this study, which were then narrowed down to 10 clinical features, 8 radiomics features, and 17 combined clinical-omics features. Based on these three feature sets, a total of fifteen ensemble learning models were established. In the test set, RF model in the clinical model is outperforms other models (AUC\u2009=\u20090.72, F1\u2009=\u20090.75, Jaccard\u2009=\u20090.60 and Recall\u2009=\u20090.84), while CatBoost model in the radiomics model is superior to other models (AUC\u2009=\u20090.91, BA\u2009=\u20090.83 and SPE\u2009=\u20090.76). Among the clinical-radiomic models, Catboost exhibits optimal performance (AUC\u2009=\u20090.93, ACC\u2009=\u20090.88, BA\u2009=\u20090.87, F1\u2009=\u20090.91, SPE\u2009=\u20090.83, PRE\u2009=\u20090.88, Jaccard\u2009=\u20090.83 and Recall\u2009=\u20090.92). Using the SHAP algorithm to visualize the operation process of the clinical-omics CatBoost model, we found that clinical omics features such as central lymph node metastasis (CLNM), Origin_Shape_Sphericity (o_shap_sphericity), LoG-sigma3_first order_ Skewness (log-3_fo_skewness), wavelet-HH_first order_Skewness (w-HH_fo_skewness) and wavelet-HH_first order_Skewness (sqr_gldm_DNUN) had the greatest impact on predicting the presence of lateral cervical small lymph node metastasis in PTC patients.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Conclusions<\/jats:title>\n                <jats:p>(1) In this study, among the ensemble learning models established based on clinicopathological features and radiomics features for predicting PTC lateral small lymph node metastasis, the clinical-radiomic CatBoost model has the best performance. (2) SHAP can visualize how the clinical and radiomics features affect the results and realize the interpretation of the model. (3) The combined CatBoost model can improve the diagnostic accuracy of suspicious lymph nodes with short diameter\u2009&lt;\u20098\u00a0mm that are difficult to obtain accurate puncture results. The combined application of radiomics features is more accurate and reasonable than the prediction of clinical data alone, which helps to accurately evaluate the surgical scope and provide support for individual clinical decision making.<\/jats:p>\n              <\/jats:sec>","DOI":"10.1186\/s40644-024-00803-7","type":"journal-article","created":{"date-parts":[[2024,11,15]],"date-time":"2024-11-15T08:21:27Z","timestamp":1731658887000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Prediction of lateral lymph node metastasis with short diameter less than 8\u00a0mm in papillary thyroid carcinoma based on radiomics"],"prefix":"10.1186","volume":"24","author":[{"given":"Yan","family":"Wang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shuangqingyue","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Minghui","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Gaosen","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhiguang","family":"Chen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xuemei","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ziyi","family":"Yang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zijun","family":"Yu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"He","family":"Ma","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhihong","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Liang","family":"Sang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,11,15]]},"reference":[{"key":"803_CR1","doi-asserted-by":"publisher","first-page":"560","DOI":"10.1089\/thy.2021.0662","volume":"32","author":"UC Megwalu","year":"2022","unstructured":"Megwalu UC, Moon PK. Thyroid Cancer Incidence and Mortality trends in the United States: 2000\u20132018. Thyroid. 2022;32:560\u201370. https:\/\/doi.org\/10.1089\/thy.2021.0662","journal-title":"Thyroid"},{"key":"803_CR2","doi-asserted-by":"publisher","first-page":"94","DOI":"10.1016\/j.ijsu.2017.12.029","volume":"50","author":"YK So","year":"2018","unstructured":"So YK, Kim MJ, Kim S, Son YI. Lateral lymph node metastasis in papillary thyroid carcinoma: a systematic review and meta-analysis for prevalence, risk factors, and location. Int J Surg. 2018;50:94\u2013103. https:\/\/doi.org\/10.1016\/j.ijsu.2017.12.029","journal-title":"Int J Surg"},{"key":"803_CR3","doi-asserted-by":"publisher","first-page":"1019037","DOI":"10.3389\/fendo.2022.1019037","volume":"13","author":"SW Lai","year":"2022","unstructured":"Lai SW, et al. Machine learning-based dynamic prediction of lateral lymph node metastasis in patients with papillary thyroid cancer. Front Endocrinol (Lausanne). 2022;13:1019037. https:\/\/doi.org\/10.3389\/fendo.2022.1019037","journal-title":"Front Endocrinol (Lausanne)"},{"key":"803_CR4","doi-asserted-by":"publisher","unstructured":"Hu D, et al. Risk factors of lateral lymph node metastasis in cN0 papillary thyroid carcinoma. World J Surg Oncol. 2018;16. https:\/\/doi.org\/10.1186\/s12957-018-1336-3","DOI":"10.1186\/s12957-018-1336-3"},{"key":"803_CR5","doi-asserted-by":"publisher","first-page":"157","DOI":"10.1634\/theoncologist.2012-0240","volume":"18","author":"DF Schneider","year":"2013","unstructured":"Schneider DF, Mazeh H, Chen H, Sippel RS. Lymph node ratio predicts recurrence in papillary thyroid cancer. Oncologist. 2013;18:157\u201362. https:\/\/doi.org\/10.1634\/theoncologist.2012-0240","journal-title":"Oncologist"},{"key":"803_CR6","doi-asserted-by":"publisher","first-page":"815207","DOI":"10.3389\/fendo.2021.815207","volume":"12","author":"L Gao","year":"2021","unstructured":"Gao L, et al. Large-volume lateral lymph Node Metastasis predicts worse prognosis in papillary thyroid carcinoma patients with N1b. Front Endocrinol (Lausanne). 2021;12:815207. https:\/\/doi.org\/10.3389\/fendo.2021.815207","journal-title":"Front Endocrinol (Lausanne)"},{"issue":"4","key":"803_CR7","doi-asserted-by":"publisher","first-page":"284","DOI":"10.37015\/AUDT.2020.200001","volume":"4","author":"K Huang","year":"2020","unstructured":"Huang K, Ji-Bin, Liu. Application of Ultrasonography in the diagnosis and management of papillary thyroid microcarcinoma. Adv Ultrasound Diagnosis Therapy. 2020;4(4):284\u201390. https:\/\/doi.org\/10.37015\/AUDT.2020.200001","journal-title":"Adv Ultrasound Diagnosis Therapy"},{"key":"803_CR8","doi-asserted-by":"publisher","first-page":"191","DOI":"10.1016\/j.ejso.2012.07.119","volume":"39","author":"DW Lee","year":"2013","unstructured":"Lee DW, et al. Roles of ultrasonography and computed tomography in the surgical management of cervical lymph node metastases in papillary thyroid carcinoma. Eur J Surg Oncol. 2013;39:191\u20136. https:\/\/doi.org\/10.1016\/j.ejso.2012.07.119","journal-title":"Eur J Surg Oncol"},{"key":"803_CR9","doi-asserted-by":"publisher","first-page":"e0227315","DOI":"10.1371\/journal.pone.0227315","volume":"15","author":"VY Park","year":"2020","unstructured":"Park VY, et al. Radiomics signature for prediction of lateral lymph node metastasis in conventional papillary thyroid carcinoma. PLoS ONE. 2020;15:e0227315. https:\/\/doi.org\/10.1371\/journal.pone.0227315","journal-title":"PLoS ONE"},{"issue":"Suppl 1","key":"803_CR10","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1111\/cen.12515","volume":"81","author":"P Perros","year":"2014","unstructured":"Perros P, et al. Guidelines for the management of thyroid cancer. Clin Endocrinol (Oxf). 2014;81(Suppl 1):1\u2013122. https:\/\/doi.org\/10.1111\/cen.12515","journal-title":"Clin Endocrinol (Oxf)"},{"key":"803_CR11","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1089\/thy.2015.0020","volume":"26","author":"BR Haugen","year":"2015","unstructured":"Haugen BR, et al. 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. 2015;26:1\u2013133. https:\/\/doi.org\/10.1089\/thy.2015.0020. (2016).","journal-title":"Thyroid"},{"key":"803_CR12","doi-asserted-by":"publisher","unstructured":"Leenhardt L et al. 2013 European thyroid association guidelines for cervical ultrasound scan and ultrasound-guided techniques in the postoperative management of patients with thyroid cancer. Eur Thyroid J 2, 147\u2013159, https:\/\/doi.org\/10.1159\/000354537 (2013).","DOI":"10.1159\/000354537"},{"key":"803_CR13","doi-asserted-by":"publisher","first-page":"642142","DOI":"10.3389\/fonc.2021.642142","volume":"11","author":"S Xia","year":"2021","unstructured":"Xia S, Chen Y, Zhan W, Zhou W. Ultrasound-guided fine-needle aspiration Versus Fine-Needle Capillary Sampling in evaluation of Lymph Node metastasis of thyroid Cancer. Front Oncol. 2021;11:642142. https:\/\/doi.org\/10.3389\/fonc.2021.642142","journal-title":"Front Oncol"},{"key":"803_CR14","doi-asserted-by":"publisher","unstructured":"Agyekum EA, et al. Evaluation of Cervical Lymph Node Metastasis in papillary thyroid carcinoma using clinical-Ultrasound Radiomic Machine Learning-based model. Cancers (Basel). 2022;14. https:\/\/doi.org\/10.3390\/cancers14215266","DOI":"10.3390\/cancers14215266"},{"key":"803_CR15","doi-asserted-by":"publisher","first-page":"e14546","DOI":"10.7717\/peerj.14546","volume":"11","author":"H Zhu","year":"2023","unstructured":"Zhu H, et al. Models of ultrasonic radiomics and clinical characters for lymph node metastasis assessment in thyroid cancer: a retrospective study. PeerJ. 2023;11:e14546. https:\/\/doi.org\/10.7717\/peerj.14546","journal-title":"PeerJ"},{"key":"803_CR16","doi-asserted-by":"publisher","first-page":"e221465","DOI":"10.1148\/radiol.221465","volume":"307","author":"L Xiao","year":"2023","unstructured":"Xiao L, et al. Contrast-enhanced US with Perfluorobutane to diagnose small lateral cervical lymph node metastases of papillary thyroid carcinoma. Radiology. 2023;307:e221465. https:\/\/doi.org\/10.1148\/radiol.221465","journal-title":"Radiology"},{"key":"803_CR17","doi-asserted-by":"publisher","first-page":"640565","DOI":"10.3389\/fendo.2021.640565","volume":"12","author":"Y Huang","year":"2021","unstructured":"Huang Y, Yin Y, Zhou W. Risk factors for central and lateral lymph node metastases in patients with papillary thyroid Micro-carcinoma: retrospective analysis on 484 cases. Front Endocrinol (Lausanne). 2021;12:640565. https:\/\/doi.org\/10.3389\/fendo.2021.640565","journal-title":"Front Endocrinol (Lausanne)"},{"key":"803_CR18","doi-asserted-by":"publisher","first-page":"20670","DOI":"10.1002\/cam4.6567","volume":"12","author":"L Shao","year":"2023","unstructured":"Shao L, Wang Z, Dong W, Sun W, Zhang H. Risk factors associated with preferential lateral lymph node metastasis in papillary thyroid carcinoma. Cancer Med. 2023;12:20670\u20136. https:\/\/doi.org\/10.1002\/cam4.6567","journal-title":"Cancer Med"},{"key":"803_CR19","doi-asserted-by":"publisher","first-page":"ARTN","DOI":"10.3389\/fendo.2023.1151505","volume":"14","author":"M Zhao","year":"2023","unstructured":"Zhao M, et al. Predicting skip metastasis in lateral lymph nodes of papillary thyroid carcinoma based on clinical and ultrasound features. Front Endocrinol. 2023;14:ARTN. https:\/\/doi.org\/10.3389\/fendo.2023.1151505","journal-title":"Front Endocrinol"},{"key":"803_CR20","doi-asserted-by":"publisher","first-page":"944569","DOI":"10.3389\/fonc.2022.944569","volume":"12","author":"G Zhang","year":"2022","unstructured":"Zhang G, et al. A machine learning model based on ultrasound image features to assess the risk of sentinel lymph node metastasis in breast cancer patients: applications of scikit-learn and SHAP. Front Oncol. 2022;12:944569. https:\/\/doi.org\/10.3389\/fonc.2022.944569","journal-title":"Front Oncol"},{"key":"803_CR21","doi-asserted-by":"publisher","first-page":"5025","DOI":"10.1002\/cam4.5225","volume":"12","author":"BL Bai","year":"2023","unstructured":"Bai BL, Wu ZY, Weng SJ, Yang Q. Application of interpretable machine learning algorithms to predict distant metastasis in osteosarcoma. Cancer Med. 2023;12:5025\u201334. https:\/\/doi.org\/10.1002\/cam4.5225","journal-title":"Cancer Med"},{"key":"803_CR22","doi-asserted-by":"publisher","first-page":"551","DOI":"10.3389\/fendo.2020.00551","volume":"11","author":"F Medas","year":"2020","unstructured":"Medas F, et al. Predictive Factors of Lymph Node Metastasis in patients with Papillary Microcarcinoma of the thyroid: retrospective analysis on 293 cases. Front Endocrinol (Lausanne). 2020;11:551. https:\/\/doi.org\/10.3389\/fendo.2020.00551","journal-title":"Front Endocrinol (Lausanne)"},{"key":"803_CR23","doi-asserted-by":"publisher","first-page":"1054","DOI":"10.1002\/ohn.161","volume":"168","author":"JW Feng","year":"2023","unstructured":"Feng JW, et al. Nomograms for prediction of high-volume lymph node metastasis in papillary thyroid carcinoma patients. Otolaryngol Head Neck Surg. 2023;168:1054\u201366. https:\/\/doi.org\/10.1002\/ohn.161","journal-title":"Otolaryngol Head Neck Surg"},{"key":"803_CR24","doi-asserted-by":"publisher","first-page":"716728","DOI":"10.3389\/fendo.2021.716728","volume":"12","author":"Y Wang","year":"2021","unstructured":"Wang Y, et al. Risk factors and a prediction model of lateral lymph node metastasis in CN0 papillary thyroid carcinoma patients with 1\u20132 Central Lymph Node metastases. Front Endocrinol (Lausanne). 2021;12:716728. https:\/\/doi.org\/10.3389\/fendo.2021.716728","journal-title":"Front Endocrinol (Lausanne)"},{"key":"803_CR25","doi-asserted-by":"publisher","first-page":"1004913","DOI":"10.3389\/fendo.2022.1004913","volume":"13","author":"JW Feng","year":"2022","unstructured":"Feng JW, et al. A comparative analysis of eight machine learning models for the prediction of lateral lymph node metastasis in patients with papillary thyroid carcinoma. Front Endocrinol (Lausanne). 2022;13:1004913. https:\/\/doi.org\/10.3389\/fendo.2022.1004913","journal-title":"Front Endocrinol (Lausanne)"},{"key":"803_CR26","doi-asserted-by":"publisher","first-page":"55","DOI":"10.1186\/s40644-023-00568-5","volume":"23","author":"J Zhu","year":"2023","unstructured":"Zhu J, et al. Nomogram for preoperative estimation risk of lateral cervical lymph node metastasis in papillary thyroid carcinoma: a multicenter study. Cancer Imaging. 2023;23:55. https:\/\/doi.org\/10.1186\/s40644-023-00568-5","journal-title":"Cancer Imaging"},{"key":"803_CR27","doi-asserted-by":"publisher","first-page":"176","DOI":"10.1016\/j.surg.2008.09.003","volume":"145","author":"A Machens","year":"2009","unstructured":"Machens A, Hauptmann S, Dralle H. Lymph node dissection in the lateral neck for completion in central node-positive papillary thyroid cancer. Surgery. 2009;145:176\u201381. https:\/\/doi.org\/10.1016\/j.surg.2008.09.003","journal-title":"Surgery"},{"key":"803_CR28","doi-asserted-by":"publisher","first-page":"622","DOI":"10.1186\/s12885-019-5835-6","volume":"19","author":"C Liu","year":"2019","unstructured":"Liu C, et al. Risk factor analysis for predicting cervical lymph node metastasis in papillary thyroid carcinoma: a study of 966 patients. BMC Cancer. 2019;19:622. https:\/\/doi.org\/10.1186\/s12885-019-5835-6","journal-title":"BMC Cancer"},{"key":"803_CR29","doi-asserted-by":"publisher","first-page":"731","DOI":"10.1177\/0194599815601412","volume":"153","author":"X Lan","year":"2015","unstructured":"Lan X, et al. A Meta-analysis of Central Lymph Node Metastasis for Predicting lateral involvement in papillary thyroid carcinoma. Otolaryngol Head Neck Surg. 2015;153:731\u20138. https:\/\/doi.org\/10.1177\/0194599815601412","journal-title":"Otolaryngol Head Neck Surg"}],"container-title":["Cancer Imaging"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s40644-024-00803-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1186\/s40644-024-00803-7\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s40644-024-00803-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,11,15]],"date-time":"2024-11-15T09:09:27Z","timestamp":1731661767000},"score":1,"resource":{"primary":{"URL":"https:\/\/cancerimagingjournal.biomedcentral.com\/articles\/10.1186\/s40644-024-00803-7"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,11,15]]},"references-count":29,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2024,12]]}},"alternative-id":["803"],"URL":"https:\/\/doi.org\/10.1186\/s40644-024-00803-7","relation":{},"ISSN":["1470-7330"],"issn-type":[{"value":"1470-7330","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,11,15]]},"assertion":[{"value":"22 August 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"11 November 2024","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"15 November 2024","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"This study was supported by the Medical Science Research Ethics Committee of the First Affiliated Hospital of China Medical University.(AF-SOP-07-1.2-01).","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":"Consent for publication"}},{"value":"The authors declare no competing interests.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"155"}}