Literature DB >> 20393717

Liver virtual non-enhanced CT with dual-source, dual-energy CT: a preliminary study.

Long-Jiang Zhang1, Jin Peng, Sheng-Yong Wu, Z Jane Wang, Xin-Sheng Wu, Chang-Sheng Zhou, Xue-Man Ji, Guang-Ming Lu.   

Abstract

PURPOSE: To compare virtual non-enhanced liver CT (VNCT) from dual-energy CT (DECT) with true non-enhanced liver CT (TNCT) in patients.
METHODS: A total of 102 patients underwent multi-phase abdominal CT. Liver arterial VNCT (VNCT(A)) and portovenous VNCT (VNCT(V)) images were derived from the arterial and portovenous DECT data. The mean CT number, signal to noise ratio (SNR), image quality, contrast to noise (CNR) of liver lesions, lesion detectability and radiation dose were compared.
RESULTS: There was no difference in mean CT numbers of all organs (all P>0.05). SNR on VNCT images was higher than that of TNCT (all P<0.001). Image quality of VNCT was diagnostic but lower than that of TNCT (P<0.001). VNCT(A) images were superior to VNCT(V) (P<0.001). VNCT(A) and VNCT(V) detected 78 (91%) and 70 (81%) of 86 hepatic focal lesions visualised on TNCT. There was no difference in the size, attenuation and CNR of focal hepatic lesions (all P>0.05), but SNR of the lesions on VNCT was higher than that on TNCT (P<0.001). Radiation dose of biphase DECT was lower than that of routine triphase CT (P<0.001).
CONCLUSION: VNCT(A) may potentially replace TNCT as part of a multi-phase liver imaging protocol with consequent saving in radiation dose.

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Year:  2010        PMID: 20393717     DOI: 10.1007/s00330-010-1778-7

Source DB:  PubMed          Journal:  Eur Radiol        ISSN: 0938-7994            Impact factor:   5.315


  17 in total

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  34 in total

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9.  Multi-material decomposition using statistical image reconstruction for spectral CT.

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10.  Model-based iterative reconstruction versus adaptive statistical iterative reconstruction and filtered back projection in liver 64-MDCT: focal lesion detection, lesion conspicuity, and image noise.

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Journal:  AJR Am J Roentgenol       Date:  2013-05       Impact factor: 3.959

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