{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,12]],"date-time":"2026-06-12T03:16:16Z","timestamp":1781234176037,"version":"3.54.1"},"reference-count":14,"publisher":"Springer Science and Business Media LLC","issue":"4","license":[{"start":{"date-parts":[[2024,12,18]],"date-time":"2024-12-18T00:00:00Z","timestamp":1734480000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2024,12,18]],"date-time":"2024-12-18T00:00:00Z","timestamp":1734480000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/100030993","name":"Universit\u00e0 della Svizzera italiana","doi-asserted-by":"crossref","id":[{"id":"10.13039\/100030993","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Endocrinol Invest"],"abstract":"<jats:title>Abstract<\/jats:title>\n          <jats:sec>\n            <jats:title>Objectives<\/jats:title>\n            <jats:p>Ultrasound (US) evaluation is recognized as pivotal in assessing the risk of malignancy (RoM) of thyroid nodules (TNs). Recently, various US-based risk-classification systems (Thyroid Imaging and Reporting Data Systems [TIRADSs] have been developed. An important ongoing project concerns the creation of an international system (I-TIRADS) using unique terminology. Since online tool allow clinicians and patients to stratify the RoM of any TN, the role of computer scientist (CS) should be relevant. This study explored the performance of CS in assessing TNs across the TIRADS categories.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Methods<\/jats:title>\n            <jats:p>The most diffused TIRADSs (i.e., ACR, EU, and K) were considered. Three-hundred scenarios were created. A CS was asked to assess the 300 TNs according to ACR-, EU-, and K-TIRADS. These data were compared with that of clinicians. The inter-observer agreement was estimated with Cohen kappa (\u03ba). Word-cloud plots were used to graph the US descriptors with disagreement.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Results<\/jats:title>\n            <jats:p>The correspondence of the CS\u2019s assessment with the physicians was 100%, 81%, and 43%, using ACR-, EU-, and K-TIRADS, respectively. The CS was unable to classify 19\/100 TNs according to EU-TIRADS and 15\/100 TNs according to K-TIRADS. The inter-observer agreement between CS and physicians was excellent for ACR-TIRADS (\u03ba\u2009=\u20091), moderate for EU-TIRADS (\u03ba\u2009=\u20090.56), and fair for K-TIRADS (\u03ba\u2009=\u20090.22). Among the non-concordant cases, 16\/22 descriptors for EU-TIRADS and 18\/18 descriptors for K-TIRADS were found.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Conclusion<\/jats:title>\n            <jats:p>CSs are confident with the ACR-TIRADS lexicon and structure while not with EU- and K-TIRADS, probably because they are pattern-based systems requiring medical training.<\/jats:p>\n          <\/jats:sec>","DOI":"10.1007\/s40618-024-02518-9","type":"journal-article","created":{"date-parts":[[2024,12,18]],"date-time":"2024-12-18T10:11:12Z","timestamp":1734516672000},"page":"877-883","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Performance of computer scientists in the assessment of thyroid nodules using TIRADS lexicons"],"prefix":"10.1007","volume":"48","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2125-4937","authenticated-orcid":false,"given":"P.","family":"Trimboli","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"A.","family":"Colombo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0483-7126","authenticated-orcid":false,"given":"E.","family":"Gamarra","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9144-2570","authenticated-orcid":false,"given":"L.","family":"Ruinelli","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6466-7221","authenticated-orcid":false,"given":"A.","family":"Leoncini","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2024,12,18]]},"reference":[{"issue":"17","key":"2518_CR1","doi-asserted-by":"publisher","first-page":"1764","DOI":"10.1056\/NEJMcp031436","volume":"351","author":"L Heged\u00fcs","year":"2004","unstructured":"Heged\u00fcs L (2004) The thyroid nodule. N Engl J Med 351(17):1764\u20131771. https:\/\/doi.org\/10.1056\/NEJMcp031436","journal-title":"N Engl J Med"},{"issue":"5","key":"2518_CR2","doi-asserted-by":"publisher","first-page":"587","DOI":"10.1016\/j.jacr.2017.01.046","volume":"14","author":"FN Tessler","year":"2017","unstructured":"Tessler FN, Middleton WD, Grant EG, Hoang JK, Berland LL, Teefey SA, Cronan JJ, Beland MD, Desser TS, Frates MC, Hammers LW, Hamper UM, Langer JE, Reading CC, Scoutt LM, Stavros AT (2017) ACR Thyroid Imaging, Reporting and Data System (TI-RADS): White Paper of the ACR TI-RADS Committee. Journal of the American College of Radiology: JACR 14(5):587\u2013595. https:\/\/doi.org\/10.1016\/j.jacr.2017.01.046","journal-title":"Journal of the American College of Radiology: JACR"},{"issue":"5","key":"2518_CR3","doi-asserted-by":"publisher","first-page":"225","DOI":"10.1159\/000478927","volume":"6","author":"G Russ","year":"2017","unstructured":"Russ G, Bonnema SJ, Erdogan MF, Durante C, Ngu R, Leenhardt L (2017) European Thyroid Association Guidelines for Ultrasound Malignancy Risk Stratification of Thyroid Nodules in Adults: The EU-TIRADS. European thyroid journal 6(5):225\u2013237. https:\/\/doi.org\/10.1159\/000478927","journal-title":"European thyroid journal"},{"issue":"12","key":"2518_CR4","doi-asserted-by":"publisher","first-page":"2094","DOI":"10.3348\/kjr.2021.0713","volume":"22","author":"EJ Ha","year":"2021","unstructured":"Ha EJ, Chung SR, Na DG, Ahn HS, Chung J, Lee JY, Park JS, Yoo RE, Baek JH, Baek SM, Cho SW, Choi YJ, Hahn SY, Jung SL, Kim JH, Kim SK, Kim SJ, Lee CY, Lee HK, Lee JH, Choi M (2021) 2021 Korean Thyroid Imaging Reporting and Data System and Imaging-Based Management of Thyroid Nodules: Korean Society of Thyroid Radiology Consensus Statement and Recommendations. Korean J Radiol 22(12):2094\u20132123. https:\/\/doi.org\/10.3348\/kjr.2021.0713","journal-title":"Korean J Radiol"},{"key":"2518_CR5","doi-asserted-by":"publisher","DOI":"10.1210\/clinem\/dgz170","author":"M Castellana","year":"2020","unstructured":"Castellana M, Castellana C, Treglia G, Giorgino F, Giovanella L, Russ G, Trimboli P (2020) Performance of Five Ultrasound Risk Stratification Systems in Selecting Thyroid Nodules for FNA. J Clin Endocrinol Metab. https:\/\/doi.org\/10.1210\/clinem\/dgz170","journal-title":"J Clin Endocrinol Metab"},{"issue":"5","key":"2518_CR6","doi-asserted-by":"publisher","first-page":"2877","DOI":"10.1007\/s00330-020-07384-6","volume":"31","author":"PH Kim","year":"2021","unstructured":"Kim PH, Suh CH, Baek JH, Chung SR, Choi YJ, Lee JH (2021) Unnecessary thyroid nodule biopsy rates under four ultrasound risk stratification systems: a systematic review and meta-analysis. Eur Radiol 31(5):2877\u20132885. https:\/\/doi.org\/10.1007\/s00330-020-07384-6","journal-title":"Eur Radiol"},{"issue":"17","key":"2518_CR7","doi-asserted-by":"publisher","first-page":"4316","DOI":"10.3390\/cancers13174316","volume":"13","author":"G Russ","year":"2021","unstructured":"Russ G, Trimboli P, Buffet C (2021) The New Era of TIRADSs to Stratify the Risk of Malignancy of Thyroid Nodules: Strengths. Weaknesses and Pitfalls Cancers 13(17):4316. https:\/\/doi.org\/10.3390\/cancers13174316","journal-title":"Weaknesses and Pitfalls Cancers"},{"issue":"1","key":"2518_CR8","doi-asserted-by":"publisher","DOI":"10.1148\/radiol.231481","volume":"309","author":"C Durante","year":"2023","unstructured":"Durante C, Heged\u00fcs L, Na DG, Papini E, Sipos JA, Baek JH, Frasoldati A, Grani G, Grant E, Horvath E, Hoang JK, Mandel SJ, Middleton WD, Ngu R, Orloff LA, Shin JH, Trimboli P, Yoon JH, Tessler FN (2023) International Expert Consensus on US Lexicon for Thyroid Nodules. Radiology 309(1):e231481. https:\/\/doi.org\/10.1148\/radiol.231481","journal-title":"Radiology"},{"issue":"2","key":"2518_CR9","doi-asserted-by":"publisher","DOI":"10.1530\/ETJ-22-0134","volume":"12","author":"T Solymosi","year":"2023","unstructured":"Solymosi T, Heged\u0171s L, Bonnema SJ, Frasoldati A, Jambor L, Karanyi Z, Kovacs GL, Papini E, Rucz K, Russ G, Nagy EV (2023) Considerable interobserver variation calls for unambiguous definitions of thyroid nodule ultrasound characteristics. European thyroid journal 12(2):e220134. https:\/\/doi.org\/10.1530\/ETJ-22-0134","journal-title":"European thyroid journal"},{"issue":"2","key":"2518_CR10","doi-asserted-by":"publisher","first-page":"237","DOI":"10.1089\/thy.2019.0360","volume":"30","author":"A Persichetti","year":"2020","unstructured":"Persichetti A, Di Stasio E, Coccaro C, Graziano F, Bianchini A, Di Donna V, Corsello S, Valle D, Bizzarri G, Frasoldati A, Pontecorvi A, Papini E, Guglielmi R (2020) Inter- and Intraobserver Agreement in the Assessment of Thyroid Nodule Ultrasound Features and Classification Systems: A Blinded Multicenter Study. 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