Computed tomography texture analysis in patients with gastric cancer: a quantitative imaging biomarker for preoperative evaluation before neoadjuvant chemotherapy treatment

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dc.authoridAfsar, Cigdem Usul/0000-0002-3764-7639
dc.authoridYardimci, Veysi Hakan/0000-0003-1395-3882
dc.authoridKILICKESMEZ, Ozgur/0000-0003-4658-2192
dc.authoridYarıkkaya, Enver/0000-0002-4608-1016;
dc.contributor.authorYardimci, Aytul Hande
dc.contributor.authorSel, Ipek
dc.contributor.authorBektas, Ceyda Turan
dc.contributor.authorYarikkaya, Enver
dc.contributor.authorDursun, Nevra
dc.contributor.authorBektas, Hasan
dc.contributor.authorAfsar, Cigdem Usul
dc.date.accessioned2024-09-11T19:50:28Z
dc.date.available2024-09-11T19:50:28Z
dc.date.issued2020
dc.departmentİstanbul Gelişim Üniversitesien_US
dc.description.abstractPurpose The aim of the study is to explore the role of computed tomography texture analysis (CT-TA) for predicting clinical T and N stages and tumor grade before neoadjuvant chemotherapy treatment in gastric cancer (GC) patients during the preoperative period. Materials and methods CT images of 114 patients with GC were included in this retrospective study. Following pre-processing steps, textural features were extracted using MaZda software in the portal venous phase. We evaluated and analyzed texture features of six principal categories for differentiating between T stages (T1,2 vs T3,4), N stages (N+ vs N-) and grades (low-intermediate vs. high). Classification was performed based on texture parameters with high model coefficients in linear discriminant analysis (LDA). Results Dimension-reduction steps yielded five textural features for T stage, three for N stage and two for tumor grade. The discriminatory capacities of T stage, N stage and tumor grade were 90.4%, 81.6% and 64.5%, respectively, when LDA algorithm was employed. Conclusion CT-TA yields potentially useful imaging biomarkers for predicting the T and N stages of patients with GC and can be used for preoperative evaluation before neoadjuvant treatment planning.en_US
dc.identifier.doi10.1007/s11604-020-00936-2
dc.identifier.endpage560en_US
dc.identifier.issn1867-1071
dc.identifier.issn1867-108X
dc.identifier.issue6en_US
dc.identifier.pmid32140880en_US
dc.identifier.scopus2-s2.0-85081608068en_US
dc.identifier.startpage553en_US
dc.identifier.urihttps://doi.org/10.1007/s11604-020-00936-2
dc.identifier.urihttps://hdl.handle.net/11363/7633
dc.identifier.volume38en_US
dc.identifier.wosWOS:000518306800001en_US
dc.identifier.wosqualityQ3en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.language.isoenen_US
dc.publisherSpringeren_US
dc.relation.ispartofJapanese Journal of Radiologyen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.snmz20240903_Gen_US
dc.subjectGastric canceren_US
dc.subjectTexture analysisen_US
dc.subjectMultidetector computed tomographyen_US
dc.subjectTumor stageen_US
dc.subjectTumor gradeen_US
dc.subjectLymph node metastasisen_US
dc.titleComputed tomography texture analysis in patients with gastric cancer: a quantitative imaging biomarker for preoperative evaluation before neoadjuvant chemotherapy treatmenten_US
dc.typeArticleen_US

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