Role of contrast enhancement and corrected attenuation values of renal tumors in predicting renal cell carcinoma (RCC) subtypes : protocol for a triphasic multi-slice computed tomography (CT) procedure

2017
journal article
article
11
dc.abstract.enBACKGROUND: To distinguish RCC subtypes based on contrast enhancement features of CT images. MATERIAL AND METHODS: In total, 59 lesions from 57 patients were included. All patients underwent multi-slice CT imaging with a triphasic protocol, which included non-contrast, corticomedullary, nephrographic and urographic phases. Contrast enhancement features of renal masses were evaluated in terms of CT attenuation values (AV) and differences in contrast density; the aorta or renal parenchyma were evaluated based on corrected or relative values. RESULTS: Clear cell RCC (ccRCC) showed more intense contrast enhancement than other RCC subtypes. When differentiating ccRCC from other RCC subtypes, a cut-off AV of 86-89 HU, aorta-based corrected AV of 89-95 HU and renal parenchyma-based corrected AV of 87-95 HU showed a diagnostic accuracy of 81-86%, 86-88% and 74-78%, respectively, in the corticomedullary phase. Furthermore, a cutoff of 2.42-2.72 for the relative contrast enhancement ratio, a cutoff of 2.59-2.74 for the aorta-based corrected relative contrast enhancement ratio and a cutoff of 2.63-2.76 for the renal parenchyma-based attenuation ratio showed a diagnostic accuracy of 83-88%, 88-90% and 81%, respectively. CONCLUSIONS: The most reliable parameters for differentiating ccRCC from other RCC subtypes are aorta-based corrected AV and aorta-based corrected relative contrast enhancement values in the corticomedullary phase.pl
dc.contributor.authorErtekin, Ersenpl
dc.contributor.authorAmasyalı, Akın Sonerpl
dc.contributor.authorErol, Bulentpl
dc.contributor.authorAcikgozoglu, Saimpl
dc.contributor.authorKucukdurmaz, Farukpl
dc.contributor.authorNayman, Alaaddinpl
dc.contributor.authorErol, Halukpl
dc.date.accessioned2017-07-17T12:34:29Z
dc.date.available2017-07-17T12:34:29Z
dc.date.issued2017pl
dc.date.openaccess0
dc.description.accesstimew momencie opublikowania
dc.description.additionalBibliogr. s. 390-391pl
dc.description.physical384-391pl
dc.description.versionostateczna wersja wydawcy
dc.description.volume82pl
dc.identifier.doi10.12659/PJR.901957pl
dc.identifier.eissn1899-0967pl
dc.identifier.issn1733-134Xpl
dc.identifier.urihttp://ruj.uj.edu.pl/xmlui/handle/item/42865
dc.languageengpl
dc.language.containerengpl
dc.rightsUdzielam licencji. Uznanie autorstwa - Użycie niekomercyjne - Bez utworów zależnych 3.0 Polska*
dc.rights.licenceCC-BY-NC-ND
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/pl/legalcode*
dc.share.typeotwarte czasopismo
dc.subject.encarcinomapl
dc.subject.enrenal cellpl
dc.subject.encontrast mediapl
dc.subject.enmultidetector computed tomographypl
dc.subtypeArticlepl
dc.titleRole of contrast enhancement and corrected attenuation values of renal tumors in predicting renal cell carcinoma (RCC) subtypes : protocol for a triphasic multi-slice computed tomography (CT) procedurepl
dc.title.journalPolish Journal of Radiologypl
dc.typeJournalArticlepl
dspace.entity.typePublication
dc.abstract.enpl
BACKGROUND: To distinguish RCC subtypes based on contrast enhancement features of CT images. MATERIAL AND METHODS: In total, 59 lesions from 57 patients were included. All patients underwent multi-slice CT imaging with a triphasic protocol, which included non-contrast, corticomedullary, nephrographic and urographic phases. Contrast enhancement features of renal masses were evaluated in terms of CT attenuation values (AV) and differences in contrast density; the aorta or renal parenchyma were evaluated based on corrected or relative values. RESULTS: Clear cell RCC (ccRCC) showed more intense contrast enhancement than other RCC subtypes. When differentiating ccRCC from other RCC subtypes, a cut-off AV of 86-89 HU, aorta-based corrected AV of 89-95 HU and renal parenchyma-based corrected AV of 87-95 HU showed a diagnostic accuracy of 81-86%, 86-88% and 74-78%, respectively, in the corticomedullary phase. Furthermore, a cutoff of 2.42-2.72 for the relative contrast enhancement ratio, a cutoff of 2.59-2.74 for the aorta-based corrected relative contrast enhancement ratio and a cutoff of 2.63-2.76 for the renal parenchyma-based attenuation ratio showed a diagnostic accuracy of 83-88%, 88-90% and 81%, respectively. CONCLUSIONS: The most reliable parameters for differentiating ccRCC from other RCC subtypes are aorta-based corrected AV and aorta-based corrected relative contrast enhancement values in the corticomedullary phase.
dc.contributor.authorpl
Ertekin, Ersen
dc.contributor.authorpl
Amasyalı, Akın Soner
dc.contributor.authorpl
Erol, Bulent
dc.contributor.authorpl
Acikgozoglu, Saim
dc.contributor.authorpl
Kucukdurmaz, Faruk
dc.contributor.authorpl
Nayman, Alaaddin
dc.contributor.authorpl
Erol, Haluk
dc.date.accessioned
2017-07-17T12:34:29Z
dc.date.available
2017-07-17T12:34:29Z
dc.date.issuedpl
2017
dc.date.openaccess
0
dc.description.accesstime
w momencie opublikowania
dc.description.additionalpl
Bibliogr. s. 390-391
dc.description.physicalpl
384-391
dc.description.version
ostateczna wersja wydawcy
dc.description.volumepl
82
dc.identifier.doipl
10.12659/PJR.901957
dc.identifier.eissnpl
1899-0967
dc.identifier.issnpl
1733-134X
dc.identifier.uri
http://ruj.uj.edu.pl/xmlui/handle/item/42865
dc.languagepl
eng
dc.language.containerpl
eng
dc.rights*
Udzielam licencji. Uznanie autorstwa - Użycie niekomercyjne - Bez utworów zależnych 3.0 Polska
dc.rights.licence
CC-BY-NC-ND
dc.rights.uri*
http://creativecommons.org/licenses/by-nc-nd/3.0/pl/legalcode
dc.share.type
otwarte czasopismo
dc.subject.enpl
carcinoma
dc.subject.enpl
renal cell
dc.subject.enpl
contrast media
dc.subject.enpl
multidetector computed tomography
dc.subtypepl
Article
dc.titlepl
Role of contrast enhancement and corrected attenuation values of renal tumors in predicting renal cell carcinoma (RCC) subtypes : protocol for a triphasic multi-slice computed tomography (CT) procedure
dc.title.journalpl
Polish Journal of Radiology
dc.typepl
JournalArticle
dspace.entity.type
Publication
Affiliations

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