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- Title
Identification of Imaging Predictors Discriminating Different Primary Liver Tumours in Patients with Chronic Liver Disease on Gadoxetic Acid-enhanced MRI: a Classification Tree Analysis.
- Authors
Park, Hyun; Jang, Kyung; Kang, Tae; Song, Kyoung; Kim, Seong; Kim, Young; Cha, Dong; Kim, Joungyoun; Goo, Juna; Park, Hyun Jeong; Jang, Kyung Mi; Kang, Tae Wook; Song, Kyoung Doo; Kim, Seong Hyun; Kim, Young Kon; Cha, Dong Ik
- Abstract
<bold>Objectives: </bold>To identify predictors for the discrimination of intrahepatic cholangiocarcinoma (IMCC) and combined hepatocellular-cholangiocarcinoma (CHC) from hepatocellular carcinoma (HCC) for primary liver cancers on gadoxetic acid-enhanced MRI among high-risk chronic liver disease (CLD) patients using classification tree analysis (CTA).<bold>Methods: </bold>A total of 152 patients with histopathologically proven IMCC (n = 40), CHC (n = 24) and HCC (n = 91) were enrolled. Tumour marker and MRI variables including morphologic features, signal intensity, and enhancement pattern were used to identify tumours suspicious for IMCC and CHC using CTA.<bold>Results: </bold>On CTA, arterial rim enhancement (ARE) was the initial splitting predictor for assessing the probability of tumours being IMCC or CHC. Of 43 tumours that were classified in a subgroup on CTA based on the presence of ARE, non-intralesional fat, and non-globular shape, 41 (95.3 %) were IMCCs (n = 29) or CHCs (n = 12). All 24 tumours showing fat on MRI were HCCs. The CTA model demonstrated sensitivity of 84.4 %, specificity of 97.8 %, and accuracy of 92.3 % for discriminating IMCCs and CHCs from HCCs.<bold>Conclusions: </bold>We established a simple CTA model for classifying a high-risk group of CLD patients with IMCC and CHC. This model may be useful for guiding diagnosis for primary liver cancers in patients with CLD.<bold>Key Points: </bold>• Arterial rim enhancement was the initial splitting predictor on CTA. • CTA model achieved high sensitivity, specificity, and accuracy for discrimination of tumours. • This model may be useful for guiding diagnosis of primary liver cancers.
- Subjects
CHOLANGIOCARCINOMA; BILE duct diseases; LIVER cancer; CLASSIFICATION algorithms; TUMORS
- Publication
European Radiology, 2016, Vol 26, Issue 9, p3102
- ISSN
0938-7994
- Publication type
journal article
- DOI
10.1007/s00330-015-4136-y