Publication:
Multimodal ultrasonography evaluation in thyroid nodule characterization: What is the ideal algorithm?

dc.contributor.authorGürsel, Başak Erdemli
dc.contributor.authorÇağlar, Barış
dc.contributor.authorÖzpar, Rıfat
dc.contributor.authorSaraydaroğlu, Özlem
dc.contributor.authorGökalp, Gökhan
dc.contributor.authorTopal, Naile Bolca
dc.contributor.buuauthorERDEMLİ GÜRSEL, BAŞAK
dc.contributor.buuauthorÇAĞLAR, BARIŞ
dc.contributor.buuauthorÖZPAR, RİFAT
dc.contributor.buuauthorSARAYDAROĞLU, ÖZLEM
dc.contributor.buuauthorGÖKALP, GÖKHAN
dc.contributor.buuauthorBOLCA TOPAL, NAİLE
dc.contributor.departmentTıp Fakültesi
dc.contributor.departmentRadyoloji Anabilim Dalı
dc.contributor.departmentPatoloji Anabilim Dalı
dc.contributor.orcid0000-0002-0047-1780
dc.contributor.researcheridAAH-6568-2021
dc.contributor.researcheridJKZ-6522-2023
dc.contributor.researcheridKLB-7345-2024
dc.contributor.researcheridDPZ-1981-2022
dc.contributor.researcheridAAI-2336-2021
dc.contributor.researcheridKKH-5506-2024
dc.date.accessioned2025-02-13T12:48:17Z
dc.date.available2025-02-13T12:48:17Z
dc.date.issued2024-01-01
dc.description.abstractAims: The aim of this study is to investigate the diagnostic performances of Ultrasonography (US), Shear-wave Elastography (SWE), and Superb Microvascular Imaging (SMI) findings in the diagnosis of malignant thyroid nodules (MTNs) and to determine the US algorithm with the best diagnostic performance. Material and methods: Eighty-one nodules in 77 patients who had underwent multimodal US with biopsy results, were evaluated. Echogenicity, nodule components, contours, presence and type of calcification, and size were analyzed with US. Nodule stiffness and vascular index (VI) measurements were performed via SWE and SMI. The power of the US algorithm in predicting malignancy was evaluated. Results: Hypoechogenicity, irregular contour, aspect ratio (anteroposterior (AP)/transvers diameter) >1, and >43.9 kPa were the characteristics had significant efficacy in the diagnosis of MTNs. Sensitivity, specificity, and AUC values were respectively 100%, 48.5%, and 0.742 for hypoechogenicity; 80%, 90.1%, and 0.855 for irregular contour; 60%, 71.2%, and 0.656 for aspect ratio >1; 60%, 72.7%, and 0.671 for >43.9 kPa; and 93.3%, 90.9%, and 0.921 for the US algorithm. VI did not show significant efficacy in diagnosis. Conclusion: Some B-mode and SWE findings showed sufficient efficacy in differentiating benign and malign nodules on their own. However, diagnostic accuracy increased significantly when the US algorithm was applied.
dc.identifier.doi10.11152/mu-4325
dc.identifier.eissn2066-8643
dc.identifier.endpage49
dc.identifier.issn1844-4172
dc.identifier.issue1
dc.identifier.scopus2-s2.0-85189271765
dc.identifier.startpage41
dc.identifier.urihttps://doi.org/10.11152/mu-4325
dc.identifier.urihttps://medultrason.ro/medultrason/index.php/medultrason/article/view/4325
dc.identifier.urihttps://hdl.handle.net/11452/50372
dc.identifier.volume26
dc.identifier.wos001198428000014
dc.indexed.wosWOS.SCI
dc.language.isoen
dc.publisherSoc Romana Ultrasonografe Medicina Biologie-srumb
dc.relation.journalMedical Ultrasonography
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectShear-wave elastography
dc.subjectDiagnostic performance
dc.subjectColor doppler
dc.subjectGray-scale
dc.subjectUltrasound
dc.subjectMalignancy
dc.subjectPrediction
dc.subjectThyroid nodules
dc.subjectUltrasonography
dc.subjectAlgorithm
dc.subjectShear wave elastography
dc.subjectSuperb microvascular imaging
dc.subjectScience & technology
dc.subjectTechnology
dc.subjectLife sciences & biomedicine
dc.subjectAcoustics
dc.subjectRadiology, nuclear medicine & medical imaging
dc.titleMultimodal ultrasonography evaluation in thyroid nodule characterization: What is the ideal algorithm?
dc.typeArticle
dspace.entity.typePublication
local.contributor.departmentTıp Fakültesi/Radyoloji Anabilim Dalı
local.contributor.departmentTıp Fakültesi/Patoloji Anabilim Dalı
local.indexed.atWOS
local.indexed.atScopus
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relation.isAuthorOfPublication.latestForDiscovery67499dad-8aad-4b13-9547-dde1bfaf4441

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