{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,9]],"date-time":"2026-04-09T12:18:50Z","timestamp":1775737130127,"version":"3.50.1"},"reference-count":27,"publisher":"Springer Science and Business Media LLC","issue":"16","license":[{"start":{"date-parts":[[2023,8,21]],"date-time":"2023-08-21T00:00:00Z","timestamp":1692576000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,8,21]],"date-time":"2023-08-21T00:00:00Z","timestamp":1692576000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["82160335"],"award-info":[{"award-number":["82160335"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["82160335"],"award-info":[{"award-number":["82160335"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["82160335"],"award-info":[{"award-number":["82160335"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["82160335"],"award-info":[{"award-number":["82160335"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["82160335"],"award-info":[{"award-number":["82160335"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["82160335"],"award-info":[{"award-number":["82160335"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["82160335"],"award-info":[{"award-number":["82160335"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Cancer Res Clin Oncol"],"published-print":{"date-parts":[[2023,11]]},"DOI":"10.1007\/s00432-023-05263-3","type":"journal-article","created":{"date-parts":[[2023,8,21]],"date-time":"2023-08-21T16:02:02Z","timestamp":1692633722000},"page":"14901-14910","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Development and validation of a contrast-enhanced CT-based radiomics nomogram for differentiating mass-like thymic hyperplasia and low-risk thymoma"],"prefix":"10.1007","volume":"149","author":[{"given":"Wentao","family":"Dong","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Situ","family":"Xiong","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaolian","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shaobo","family":"Hu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yangchun","family":"Liu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hao","family":"Liu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xin","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiaqi","family":"Chen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yingying","family":"Qiu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bing","family":"Fan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2023,8,21]]},"reference":[{"key":"5263_CR1","doi-asserted-by":"publisher","first-page":"122","DOI":"10.1016\/j.ejmp.2017.05.071","volume":"38","author":"M Avanzo","year":"2017","unstructured":"Avanzo M, Stancanello J, El Naqa I (2017) Beyond imaging: The promise of radiomics. Phys Med 38:122\u2013139. https:\/\/doi.org\/10.1016\/j.ejmp.2017.05.071","journal-title":"Phys Med"},{"issue":"24","key":"5263_CR2","doi-asserted-by":"publisher","first-page":"24TR02","DOI":"10.1088\/1361-6560\/aba798","volume":"65","author":"R Da-Ano","year":"2020","unstructured":"Da-Ano R, Visvikis D, Hatt M (2020) Harmonization strategies for multicenter radiomics investigations. Phys Med Biol 65(24):24TR02. https:\/\/doi.org\/10.1088\/1361-6560\/aba798","journal-title":"Phys Med Biol"},{"key":"5263_CR3","doi-asserted-by":"publisher","first-page":"944005","DOI":"10.3389\/fonc.2022.944005","volume":"12","author":"W Dong","year":"2022","unstructured":"Dong W, Xiong S, Lei P, Wang X, Liu H, Liu Y et al (2022) Application of a combined radiomics nomogram based on CE-CT in the preoperative prediction of thymomas risk categorization. Front Oncol 12:944005. https:\/\/doi.org\/10.3389\/fonc.2022.944005","journal-title":"Front Oncol"},{"issue":"6","key":"5263_CR4","doi-asserted-by":"publisher","first-page":"2730","DOI":"10.1007\/s12350-020-02109-0","volume":"28","author":"M Edalat-Javid","year":"2021","unstructured":"Edalat-Javid M, Shiri I, Hajianfar G, Abdollahi H, Arabi H, Oveisi N et al (2021) Cardiac SPECT radiomic features repeatability and reproducibility: a multi-scanner phantom study. J Nucl Cardiol 28(6):2730\u20132744. https:\/\/doi.org\/10.1007\/s12350-020-02109-0","journal-title":"J Nucl Cardiol"},{"issue":"3","key":"5263_CR5","doi-asserted-by":"publisher","first-page":"761","DOI":"10.3390\/cancers12030761","volume":"12","author":"K Ekert","year":"2020","unstructured":"Ekert K, Hinterleitner C, Baumgartner K, Fritz J, Horger M (2020) Extended texture analysis of non-enhanced whole-body MRI image data for response assessment in multiple myeloma patients undergoing systemic therapy. Cancers (basel) 12(3):761. https:\/\/doi.org\/10.3390\/cancers12030761","journal-title":"Cancers (basel)"},{"issue":"8","key":"5263_CR6","doi-asserted-by":"publisher","first-page":"994","DOI":"10.1089\/thy.2017.0086","volume":"27","author":"U Haider","year":"2017","unstructured":"Haider U, Richards P, Gianoukakis AG (2017) Thymic hyperplasia associated with Graves\u2019 Disease: pathophysiology and proposed management algorithm. Thyroid 27(8):994\u20131000. https:\/\/doi.org\/10.1089\/thy.2017.0086","journal-title":"Thyroid"},{"issue":"1","key":"5263_CR7","doi-asserted-by":"publisher","first-page":"147","DOI":"10.1186\/s12957-021-02259-6","volume":"19","author":"A Kayi Cangir","year":"2021","unstructured":"Kayi Cangir A, Orhan K, Kahya Y, \u00d6zak\u0131nc\u0131 H, Kazak BB, Konuk Balc\u0131 BM et al (2021) CT imaging-based machine learning model: a potential modality for predicting low-risk and high-risk groups of thymoma: \u201cImpact of surgical modality choice.\u201d World J Surg Oncol 19(1):147. https:\/\/doi.org\/10.1186\/s12957-021-02259-6","journal-title":"World J Surg Oncol"},{"issue":"7","key":"5263_CR8","doi-asserted-by":"publisher","first-page":"698","DOI":"10.1002\/cyto.a.24260","volume":"99","author":"HK Lee","year":"2021","unstructured":"Lee HK, Kim CH, Bhattacharjee S, Park HG, Prakash D, Choi HK (2021) A paradigm shift in nuclear chromatin interpretation: from qualitative intuitive recognition to quantitative texture analysis of breast cancer cell nuclei. Cytometry A 99(7):698\u2013706. https:\/\/doi.org\/10.1002\/cyto.a.24260","journal-title":"Cytometry A"},{"issue":"14","key":"5263_CR9","doi-asserted-by":"publisher","first-page":"3208","DOI":"10.7150\/jca.30240","volume":"10","author":"HR Li","year":"2019","unstructured":"Li HR, Gao J, Jin C, Jiang JH, Ding JY (2019) Comparison between CT and MRI in the diagnostic accuracy of thymic masses. J Cancer 10(14):3208\u20133213. https:\/\/doi.org\/10.7150\/jca.30240","journal-title":"J Cancer"},{"key":"5263_CR10","doi-asserted-by":"publisher","first-page":"628534","DOI":"10.3389\/fonc.2021.628534","volume":"11","author":"J Liu","year":"2021","unstructured":"Liu J, Yin P, Wang S, Liu T, Sun C, Hong N (2021) CT-Based Radiomics Signatures for Predicting the Risk Categorization of Thymic Epithelial Tumors. Front Oncol 11:628534. https:\/\/doi.org\/10.3389\/fonc.2021.628534","journal-title":"Front Oncol"},{"issue":"6","key":"5263_CR11","doi-asserted-by":"publisher","first-page":"868","DOI":"10.1002\/mus.27220","volume":"63","author":"D Menon","year":"2021","unstructured":"Menon D, Katzberg H, Barnett C, Pal P, Bezjak A, Keshavjee S et al (2021) Thymoma pathology and myasthenia gravis outcomes. Muscle Nerve 63(6):868\u2013873. https:\/\/doi.org\/10.1002\/mus.27220","journal-title":"Muscle Nerve"},{"issue":"2","key":"5263_CR12","doi-asserted-by":"publisher","first-page":"471","DOI":"10.1148\/radiology.201.2.8888243","volume":"201","author":"S Nicolaou","year":"1996","unstructured":"Nicolaou S, M\u00fcller NL, Li DK, Oger JJ (1996) Thymus in myasthenia gravis: comparison of CT and pathologic findings and clinical outcome after thymectomy. Radiology 201(2):471\u2013474. https:\/\/doi.org\/10.1148\/radiology.201.2.8888243","journal-title":"Radiology"},{"key":"5263_CR13","doi-asserted-by":"publisher","first-page":"7305619","DOI":"10.1155\/2018\/7305619","volume":"2018","author":"T Phung","year":"2018","unstructured":"Phung T, Nguyen T, Tran D, Phan N, Nguyen H (2018) A thymic hyperplasia case without suppressing on chemical shift magnetic resonance imaging. Case Rep Radiol 2018:7305619. https:\/\/doi.org\/10.1155\/2018\/7305619","journal-title":"Case Rep Radiol"},{"issue":"2","key":"5263_CR14","doi-asserted-by":"publisher","first-page":"315","DOI":"10.3390\/cancers13020315","volume":"13","author":"S Porubsky","year":"2021","unstructured":"Porubsky S, Popovic ZV, Badve S, Banz Y, Berezowska S, Borchert D et al (2021) Thymic Hyperplasia with Lymphoepithelial Sialadenitis (LESA)-like features: strong association with lymphomas and non-myasthenic autoimmune diseases. Cancers (basel) 13(2):315. https:\/\/doi.org\/10.3390\/cancers13020315","journal-title":"Cancers (basel)"},{"issue":"5","key":"5263_CR15","doi-asserted-by":"publisher","first-page":"e230","DOI":"10.1016\/j.crad.2014.01.005","volume":"69","author":"AM Priola","year":"2014","unstructured":"Priola AM, Priola SM (2014) Imaging of thymus in myasthenia gravis: from thymic hyperplasia to thymic tumor. Clin Radiol 69(5):e230\u2013e245. https:\/\/doi.org\/10.1016\/j.crad.2014.01.005","journal-title":"Clin Radiol"},{"issue":"1128","key":"5263_CR16","doi-asserted-by":"publisher","first-page":"20210583","DOI":"10.1259\/bjr.20210583","volume":"94","author":"N Rajamohan","year":"2021","unstructured":"Rajamohan N, Goyal A, Kandasamy D, Bhalla AS, Parshad R, Jain D et al (2021) CT texture analysis in evaluation of thymic tumors and thymic hyperplasia: correlation with the international thymic malignancy interest group (ITMIG) stage and WHO grade. Br J Radiol 94(1128):20210583. https:\/\/doi.org\/10.1259\/bjr.20210583","journal-title":"Br J Radiol"},{"issue":"1","key":"5263_CR17","doi-asserted-by":"publisher","first-page":"36","DOI":"10.1186\/s41747-018-0068-z","volume":"2","author":"S Rizzo","year":"2018","unstructured":"Rizzo S, Botta F, Raimondi S, Origgi D, Fanciullo C, Morganti AG et al (2018) Radiomics: the facts and the challenges of image analysis. Eur Radiol Exp 2(1):36. https:\/\/doi.org\/10.1186\/s41747-018-0068-z","journal-title":"Eur Radiol Exp"},{"issue":"1070","key":"5263_CR18","doi-asserted-by":"publisher","first-page":"20160642","DOI":"10.1259\/bjr.20160642","volume":"90","author":"E Scalco","year":"2017","unstructured":"Scalco E, Rizzo G (2017) Texture analysis of medical images for radiotherapy applications. Br J Radiol 90(1070):20160642. https:\/\/doi.org\/10.1259\/bjr.20160642","journal-title":"Br J Radiol"},{"issue":"5","key":"5263_CR19","doi-asserted-by":"publisher","first-page":"1809","DOI":"10.21037\/jtd.2019.05.32","volume":"11","author":"H Sui","year":"2019","unstructured":"Sui H, Liu L, Li X, Zuo P, Cui J, Mo Z (2019) CT-based radiomics features analysis for predicting the risk of anterior mediastinal lesions. J Thorac Dis 11(5):1809\u20131818. https:\/\/doi.org\/10.21037\/jtd.2019.05.32","journal-title":"J Thorac Dis"},{"issue":"3","key":"5263_CR20","doi-asserted-by":"publisher","first-page":"381","DOI":"10.1016\/j.hoc.2008.03.001","volume":"22","author":"S Suster","year":"2008","unstructured":"Suster S, Moran CA (2008) Histologic classification of thymoma: the World Health Organization and beyond. Hematol Oncol Clin North Am 22(3):381\u2013392. https:\/\/doi.org\/10.1016\/j.hoc.2008.03.001","journal-title":"Hematol Oncol Clin North Am"},{"issue":"9","key":"5263_CR21","doi-asserted-by":"publisher","first-page":"1243","DOI":"10.1097\/JTO.0000000000000630","volume":"10","author":"WD Travis","year":"2015","unstructured":"Travis WD, Brambilla E, Nicholson AG, Yatabe Y, Austin JHM, Beasley MB et al (2015) The 2015 World Health Organization classification of lung tumors: impact of genetic, clinical and radiologic advances since the 2004 classification. J Thorac Oncol 10(9):1243\u20131260. https:\/\/doi.org\/10.1097\/JTO.0000000000000630","journal-title":"J Thorac Oncol"},{"issue":"1","key":"5263_CR22","doi-asserted-by":"publisher","first-page":"91","DOI":"10.1186\/s13244-020-00887-2","volume":"11","author":"JE van Timmeren","year":"2020","unstructured":"van Timmeren JE, Cester D, Tanadini-Lang S, Alkadhi H, Baessler B (2020) Radiomics in medical imaging-\"how-to\" guide and critical reflection. Insights Imaging 11(1):91. https:\/\/doi.org\/10.1186\/s13244-020-00887-2","journal-title":"Insights Imaging"},{"key":"5263_CR23","doi-asserted-by":"publisher","first-page":"3616852","DOI":"10.1155\/2019\/3616852","volume":"2019","author":"X Wang","year":"2019","unstructured":"Wang X, Sun W, Liang H, Mao X, Lu Z (2019) Radiomics Signatures of Computed Tomography Imaging for Predicting Risk Categorization and Clinical Stage of Thymomas. Biomed Res Int 2019:3616852. https:\/\/doi.org\/10.1155\/2019\/3616852","journal-title":"Biomed Res Int"},{"issue":"1","key":"5263_CR24","doi-asserted-by":"publisher","first-page":"447","DOI":"10.1007\/s00330-020-07074-3","volume":"31","author":"G Xiao","year":"2021","unstructured":"Xiao G, Hu YC, Ren JL, Qin P, Han JC, Qu XY et al (2021) MR imaging of thymomas: a combined radiomics nomogram to predict histologic subtypes. Eur Radiol 31(1):447\u2013457. https:\/\/doi.org\/10.1007\/s00330-020-07074-3","journal-title":"Eur Radiol"},{"issue":"9","key":"5263_CR25","doi-asserted-by":"publisher","first-page":"785","DOI":"10.1080\/00207454.2016.1257993","volume":"127","author":"J Yang","year":"2017","unstructured":"Yang J, Liu C, Li T, Li C (2017) Prognosis of thymectomy in myasthenia gravis patients with thymus hyperplasia. Int J Neurosci 127(9):785\u2013789. https:\/\/doi.org\/10.1080\/00207454.2016.1257993","journal-title":"Int J Neurosci"},{"issue":"29","key":"5263_CR26","doi-asserted-by":"publisher","first-page":"47816","DOI":"10.18632\/oncotarget.18001","volume":"8","author":"X Zhang","year":"2017","unstructured":"Zhang X, Yan LF, Hu YC, Li G, Yang Y, Han Y et al (2017) Optimizing a machine learning based glioma grading system using multi-parametric MRI histogram and texture features. Oncotarget 8(29):47816\u201347830. https:\/\/doi.org\/10.18632\/oncotarget.18001","journal-title":"Oncotarget"},{"issue":"2","key":"5263_CR27","doi-asserted-by":"publisher","first-page":"328","DOI":"10.1148\/radiol.2020191145","volume":"295","author":"A Zwanenburg","year":"2020","unstructured":"Zwanenburg A, Valli\u00e8res M, Abdalah MA, Aerts HJWL, Andrearczyk V, Apte A et al (2020) The image biomarker standardization initiative: standardized quantitative radiomics for high-throughput image-based phenotyping. Radiology 295(2):328\u2013338. https:\/\/doi.org\/10.1148\/radiol.2020191145","journal-title":"Radiology"}],"container-title":["Journal of Cancer Research and Clinical Oncology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00432-023-05263-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00432-023-05263-3\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00432-023-05263-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,10,26]],"date-time":"2023-10-26T11:18:06Z","timestamp":1698319086000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00432-023-05263-3"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,8,21]]},"references-count":27,"journal-issue":{"issue":"16","published-print":{"date-parts":[[2023,11]]}},"alternative-id":["5263"],"URL":"https:\/\/doi.org\/10.1007\/s00432-023-05263-3","relation":{},"ISSN":["0171-5216","1432-1335"],"issn-type":[{"value":"0171-5216","type":"print"},{"value":"1432-1335","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,8,21]]},"assertion":[{"value":"28 June 2023","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"8 August 2023","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"21 August 2023","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare no competing interests.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}},{"value":"The authors have no relevant financial or non-financial interests to disclose.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}},{"value":"This is an observational study. The Jiangxi Provincial People's Hospital Research Ethics Committee has confirmed that no ethical approval is required.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval"}},{"value":"Written informed consent was waived by the Institutional Review Board.","order":5,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent to participate"}},{"value":"The authors affirm that human research participants provided informed consent for publication of the images in Fig.\u00a0.","order":6,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent to publish"}}]}}