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.
abstract: OBJECTIVE
  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).
  
  
  METHODS
  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.
  
  
  RESULTS
  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.
  
  
  CONCLUSIONS
  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.
  
  
  CONCLUSIONS
  • 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.
authors.affiliation: Department of Radiology, Chung-Ang University Hospital, Chung-Ang University College of Medicine, 102 Heukseok-ro, Dongjak-gu, Seoul, 156-755, Republic of Korea.
authors.forename: Hyun Jeong
authors.initials: HJ
authors.lastname: Park
authors.affiliation: Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea. kmmks.jang@samsung.com.
authors.forename: Kyung Mi
authors.initials: KM
authors.lastname: Jang
authors.affiliation: Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea.
authors.forename: Tae Wook
authors.initials: TW
authors.lastname: Kang
authors.affiliation: Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea.
authors.forename: Kyoung Doo
authors.initials: KD
authors.lastname: Song
authors.affiliation: Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea.
authors.forename: Seong Hyun
authors.initials: SH
authors.lastname: Kim
authors.affiliation: Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea.
authors.forename: Young Kon
authors.initials: YK
authors.lastname: Kim
authors.affiliation: Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea.
authors.forename: Dong Ik
authors.initials: DI
authors.lastname: Cha
authors.affiliation: Biostatistics and Clinical Epidemiology Center, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea.
authors.forename: Joungyoun
authors.initials: J
authors.lastname: Kim
authors.affiliation: Biostatistics and Clinical Epidemiology Center, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea.
authors.forename: Juna
authors.initials: J
authors.lastname: Goo
mesh_terms: D000328:Adult; D000368:Aged; D001158:Arteries / Q000473:pathology; D001650:Bile Duct Neoplasms / Q000473:pathology; D001653:Bile Ducts, Intrahepatic / Q000473:pathology; D014408:Biomarkers, Tumor; D006528:Carcinoma, Hepatocellular / Q000473:pathology*; D018281:Cholangiocarcinoma / Q000473:pathology*; D003287:Contrast Media; D003937:Diagnosis, Differential; D005260:Female; D019786:Gadolinium DTPA; D006801:Humans; D008113:Liver Neoplasms / Q000473:pathology*; D008279:Magnetic Resonance Imaging / Q000379:methods; D008297:Male; D008875:Middle Aged; D012189:Retrospective Studies; D012680:Sensitivity and Specificity
chemical_list: D014408:Biomarkers, Tumor; D003287:Contrast Media; C073590:gadolinium ethoxybenzyl DTPA; D019786:Gadolinium DTPA
keywords: Cholangiocarcinoma; Classification tree analysis; Combined hepatocellular-cholangiocarcinoma; Gadoxetic acid; Hepatocellular carcinoma