Abdominal radiology (New York) · 2016
How to not miss alveolar echinococcosis in hepatic lesions suspicious for cholangiocellular carcinoma.
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Mueller J, Stojkovic M, Berger A K, Rosenberger K D, Schlett C L, Kauczor H-U, Junghanss T, Weber T F
Аннотация
PURPOSE: Hepatic alveolar echinococcosis (AE) resembles intrahepatic cholangiocarcinoma (ICC) on radiological imaging. The purpose of this study was to identify criteria to discriminate AE from ICC with CT and MR Imaging.
METHODS: One hundred and sixteen imaging studies of 94 patients (CT n = 65; MRI n = 51) diagnosed with AE (n = 55) or ICC (n = 39) were retrospectively reviewed by two blinded radiologists for lesion features including enhancement pattern and matrix composition. A consensus read was conducted in cases of disagreement. Uni- and multivariate logistic regression with bootstrapping were used for analysis.
RESULTS: Using CT, no or septal enhancement and calcification yielded the highest values of sensitivity/specificity (90.9%/90.6% and 81.8%/96.9%) for AE. Using MRI, no or septal enhancement and cystic components achieved the highest sensitivity/specificity (90.9%/100.0% and 84.8%/66.7%) for AE. Multivariate logistic regression identified the following strong independent predictors for AE: for MRI, no or septal enhancement (odds ratio [OR] 322.4; p < 0.001); for CT, no or septal enhancement and calcification (OR 35.9 and 42.5; p < 0.001 and p < 0.01, respectively). No or septal enhancement and calcification demonstrated the highest interreader agreement (>90%).
CONCLUSION: Enhancement characteristics and matrix calcifications offer the strongest discriminating potential between AE and ICC with a high sensitivity, specificity, and interreader agreement.
METHODS: One hundred and sixteen imaging studies of 94 patients (CT n = 65; MRI n = 51) diagnosed with AE (n = 55) or ICC (n = 39) were retrospectively reviewed by two blinded radiologists for lesion features including enhancement pattern and matrix composition. A consensus read was conducted in cases of disagreement. Uni- and multivariate logistic regression with bootstrapping were used for analysis.
RESULTS: Using CT, no or septal enhancement and calcification yielded the highest values of sensitivity/specificity (90.9%/90.6% and 81.8%/96.9%) for AE. Using MRI, no or septal enhancement and cystic components achieved the highest sensitivity/specificity (90.9%/100.0% and 84.8%/66.7%) for AE. Multivariate logistic regression identified the following strong independent predictors for AE: for MRI, no or septal enhancement (odds ratio [OR] 322.4; p < 0.001); for CT, no or septal enhancement and calcification (OR 35.9 and 42.5; p < 0.001 and p < 0.01, respectively). No or septal enhancement and calcification demonstrated the highest interreader agreement (>90%).
CONCLUSION: Enhancement characteristics and matrix calcifications offer the strongest discriminating potential between AE and ICC with a high sensitivity, specificity, and interreader agreement.