Application of CT texture analysis in predicting histopathological characteristics of gastric cancers.
Objectives: To explore the application of computed tomography (CT) texture analysis in predicting histopathological features of gastric cancers.Methods: Preoperative contrast-enhanced CT images and postoperative histopathological features of 107 patients (82 men, 25 women) with gastric cancers were...
| Publicado en: | European Radiology Vol. 27; no. 12; pp. 4951 - 4960 |
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| Autores principales: | , , , , , , , , , , , , |
| Formato: | Journal Article |
| Publicado: |
Springer Nature
Dec2017
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=126091270&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 126091270 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 09387994 NPH jtl: European Radiology issn: 09387994 maglogo: N pubinfo: dt: Dec2017 vid: 27 iid: 12 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 126091270 126091270 144027787 NLM28643092 10.1007/s00330-017-4881-1 NLM28643092 126091270 ppf: 4951 ppct: 9 formats: fmt: @attributes: type: P tig: atl: Application of CT texture analysis in predicting histopathological characteristics of gastric cancers. aug: au: Liu, Shunli Liu, Song Ji, Changfeng Zheng, Huanhuan Pan, Xia Zhang, Yujuan Guan, Wenxian Chen, Ling Guan, Yue Li, Weifeng He, Jian Ge, Yun Zhou, Zhengyang affil: Department of Radiology, Nanjing Drum Tower Hospital , The Affiliated Hospital of Nanjing University Medical School , No. 321 Zhongshan Road Nanjing China 210008 sug: subj: Tomography, X-Ray Computed Methods Stomach Neoplasms Male Adult Aged Middle Age Aged, 80 and Over Female Retrospective Design Stomach Neoplasms Pathology Analysis of Variance Contrast Media Young Adult Portal Vein Pathology Adult: 19-44 years Aged: 65+ years Middle Aged: 45-64 years Aged, 80 & over Male Female ab: Objectives: To explore the application of computed tomography (CT) texture analysis in predicting histopathological features of gastric cancers.Methods: Preoperative contrast-enhanced CT images and postoperative histopathological features of 107 patients (82 men, 25 women) with gastric cancers were retrospectively reviewed. CT texture analysis generated: (1) mean attenuation, (2) standard deviation, (3) max frequency, (4) mode, (5) minimum attenuation, (6) maximum attenuation, (7) the fifth, 10th, 25th, 50th, 75th and 90th percentiles, and (8) entropy. Correlations between CT texture parameters and histopathological features were analysed.Results: Mean attenuation, maximum attenuation, all percentiles and mode derived from portal venous CT images correlated significantly with differentiation degree and Lauren classification of gastric cancers (r, -0.231 ~ -0.324, 0.228 ~ 0.321, respectively). Standard deviation and entropy derived from arterial CT images also correlated significantly with Lauren classification of gastric cancers (r = -0.265, -0.222, respectively). In arterial phase analysis, standard deviation and entropy were significantly lower in gastric cancers with than those without vascular invasion; however, minimum attenuation was significantly higher in gastric cancers with than those without vascular invasion.Conclusion: CT texture analysis held great potential in predicting differentiation degree, Lauren classification and vascular invasion status of gastric cancers.Key Points: • CT texture analysis is noninvasive and effective for gastric cancer. • Portal venous CT images correlated significantly with differentiation degree and Lauren classification. • Standard deviation, entropy and minimum attenuation in arterial phase reflect vascular invasion. pubtype: Academic Journal doctype: Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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