Literature DB >> 16453115

Detection and characterization of liver metastases: 16-slice multidetector computed tomography versus superparamagnetic iron oxide-enhanced magnetic resonance imaging.

Young Kon Kim1, Seog Wan Ko, Seung Bae Hwang, Chong Soo Kim, Hee Chul Yu.   

Abstract

The aim of our study was to compare the diagnostic performance of 16--slice multidetector computed tomography with that of superparamagnetic iron oxide (SPIO)-enhanced magnetic resonance (MR) imaging in the detection of small hepatic metastases and in the differentiation of hepatic metastases from cysts. Twenty-three patients with 55 liver metastases and 14 liver cysts underwent SPIO-enhanced MR imaging and multiphasic CT using 16-MDCT. Two observers independently analyzed each image, in random order. Sensitivity and diagnostic accuracy for lesion detection and differentiation as metastases or cysts for MDCT and SPIO-enhanced MR imaging were calculated using receiver operating characteristic analysis. For all observers, the Az values of SPIO-enhanced MR imaging for lesion detection and differentiation of liver metastases from cysts (mean 0.955, 0.999) were higher than those of MDCT (mean 0.925, 0.982), but not statistically significantly so (P > 0.05). Sensitivity of SPIO-enhanced MR imaging with regard to the detection of liver metastases (mean 94.5%) was significantly higher than that of MDCT (mean 80.0%) (P < 0.05). SPIO-enhanced MR imaging and 16-MDCT showed similar diagnostic accuracies for detection and differentiation of liver metastases from cysts, but sensitivity of SPIO-enhanced imaging in the detection of liver metastases was superior to that of 16-MDCT.

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Year:  2006        PMID: 16453115     DOI: 10.1007/s00330-005-0140-y

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


  35 in total

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5.  Hepatic lesion detection: comparison of MR imaging after the administration of superparamagnetic iron oxide with dual-phase CT by using alternative-free response receiver operating characteristic analysis.

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  16 in total

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