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Differentiation between metastatic and tumour-free cervical lymph nodes in patients with papillary thyroid carcinoma by grey-scale sonographic texture analysis

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Differentiation between metastatic and tumour-free cervical lymph nodes in patients with papillary thyroid carcinoma by grey-scale sonographic texture analysis

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dc.contributor.author Abbasian Ardakani, Ali pl
dc.contributor.author Rasekhi, Alireza pl
dc.contributor.author Mohammadi, Afshin pl
dc.contributor.author Motevalian, Ebrahim pl
dc.contributor.author Najafabad, Bahareh Khalili pl
dc.date.accessioned 2018-05-08T10:41:29Z
dc.date.available 2018-05-08T10:41:29Z
dc.date.issued 2018 pl
dc.identifier.issn 1733-134X pl
dc.identifier.uri https://ruj.uj.edu.pl/xmlui/handle/item/54160
dc.language eng pl
dc.rights Udzielam licencji. Uznanie autorstwa - Użycie niekomercyjne - Bez utworów zależnych 3.0 Polska *
dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/3.0/pl/legalcode *
dc.title Differentiation between metastatic and tumour-free cervical lymph nodes in patients with papillary thyroid carcinoma by grey-scale sonographic texture analysis pl
dc.type JournalArticle pl
dc.description.physical e37-e46 pl
dc.description.additional Bibliogr. s. e45-e46 pl
dc.abstract.en Purpose: Papillary thyroid carcinoma (PTC) is the most common thyroid cancer, and cervical lymph nodes (LNs) are the most common extrathyroid metastatic involvement. Early detection and reliable diagnosis of LNs can lead to improved cure rates and management costs. This study explored the potential of texture analysis for texture-based classification of tumour-free and metastatic cervical LNs of PTC in ultrasound imaging. Material and methods: A total of 274 LNs (137 tumour-free and 137 metastatic) were explored using the texture analysis (TA) method. Up to 300 features were extracted for texture analysis in three normalisations (default, 3sigma, and 1-99%). Linear discriminant analysis was employed to transform raw data to lower-dimensional spaces and increase discriminative power. The features were classified by the first nearest neighbour classifier. Results: Normalisation reflected improvement on the performance of the classifier; hence, the features under 3sigma normalisation schemes through FFPA (fusion Fisher plus the probability of classification error [POE] + average correlation coefficients [ACC]) features indicated high performance in classifying tumour-free and metastatic LNs with a sensitivity of 99.27%, specificity of 98.54%, accuracy of 98.90%, positive predictive value of 98.55%, and negative predictive value of 99.26%. The area under the receiver operating characteristic curve was 0.996. Conclusions: TA was determined to be a reliable method with the potential for characterisation. This method can be applied by physicians to differentiate between tumour-free and metastatic LNs in patients with PTC in conventional ultrasound imaging. pl
dc.subject.en computer-assisted pl
dc.subject.en diagnosis pl
dc.subject.en lymph nodes pl
dc.subject.en pattern recognition pl
dc.subject.en thyroid carcinoma pl
dc.subject.en ultrasonography pl
dc.description.volume 83 pl
dc.identifier.doi 10.5114/pjr.2018.75017 pl
dc.identifier.eissn 1899-0967 pl
dc.title.journal Polish Journal of Radiology pl
dc.language.container eng pl
dc.subtype Article pl
dc.rights.original CC-BY-NC-ND; otwarte czasopismo; ostateczna wersja wydawcy; w momencie opublikowania; 0 pl


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Udzielam licencji. Uznanie autorstwa - Użycie niekomercyjne - Bez utworów zależnych 3.0 Polska Except where otherwise noted, this item's license is described as Udzielam licencji. Uznanie autorstwa - Użycie niekomercyjne - Bez utworów zależnych 3.0 Polska