title: Assessment of cancer cell differentiation in small hepatocellular carcinoma by computed tomography and magnetic resonance imaging.
abstract: OBJECTIVE
  To study whether cancer cell differentiation in small hepatocellular carcinoma (HCC) can be assessed by computed tomography (CT) and magnetic resonance (MR) imaging.
  
  
  METHODS
  We retrospectively evaluated the relationship between cancer cell differentiation in 127 HCC 3 cm or less in diameter (113 patients) and CT and MR images. Images were reviewed in a consensus conference by three authors (SA, TY, and ME). Histopathological diagnosis of HCC was made from liver specimens obtained by sonographically guided biopsy.
  
  
  RESULTS
  The degree of histological differentiation of cancer cells was significantly different between HCC that were isodense with liver parenchyma in both artery-dominant and equilibrium phases in contrast-enhanced CT and tumors that were hyperdense in the artery-dominant phase and iso- or hypodense in the equilibrium phase (P = 0.0054), as well as tumors that were iso- or hypodense artery-dominant and hypodense equilibrium (P = 0.0002). Histological differentiation of lesions that were hyperintense in T1-weighted images and hypointense in T2-weighted images differed significantly from those with the opposite MR characteristics (P = 0.0122). In T1-weighted fat-suppression images and T2-weighted images, respectively, the degree of histological differentiation was significant between the hypointense/hyperintense and the hyperintense/hypointense patterns (P < 0.0001), as well as the hyperintense/isointense (P = 0.0296), the hyperintense/hyperintense (P = 0.0434), and the isointense/hyperintense (P = 0.0171). Using these differences an equation was developed that could determine with 76% accuracy whether the tumors were well or less-well differentiated.
  
  
  CONCLUSIONS
  CT and MR imaging patterns were useful in predicting the degree of histological differentiation of cancer cells in HCC.
authors.affiliation: Department of Medicine and Clinical Oncology, Chiba University School of Medicine, Chiba-shi, Japan.
authors.forename: Susumu
authors.initials: S
authors.lastname: Amano
authors.forename: Masaaki
authors.initials: M
authors.lastname: Ebara
authors.forename: Takayuki
authors.initials: T
authors.lastname: Yajima
authors.forename: Hiroyuki
authors.initials: H
authors.lastname: Fukuda
authors.forename: Masaharu
authors.initials: M
authors.lastname: Yoshikawa
authors.forename: Nobuyuki
authors.initials: N
authors.lastname: Sugiura
authors.forename: Kazuki
authors.initials: K
authors.lastname: Kato
authors.forename: Fukuo
authors.initials: F
authors.lastname: Kondo
authors.forename: Tooru
authors.initials: T
authors.lastname: Matsumoto
authors.forename: Hiromitsu
authors.initials: H
authors.lastname: Saisho
mesh_terms: D000328:Adult; D000368:Aged; D006528:Carcinoma, Hepatocellular / Q000175:diagnosis* / Q000503:physiopathology*; D002471:Cell Transformation, Neoplastic; D005260:Female; D022781:Hepatocytes / Q000166:cytology / Q000473:pathology; D006801:Humans; D007564:Japan / Q000453:epidemiology; D008113:Liver Neoplasms / Q000175:diagnosis* / Q000503:physiopathology*; D008279:Magnetic Resonance Imaging; D008297:Male; D008875:Middle Aged; D015999:Multivariate Analysis; D009367:Neoplasm Staging; D011237:Predictive Value of Tests; D015995:Prevalence; D012189:Retrospective Studies; D012680:Sensitivity and Specificity; D013223:Statistics as Topic; D014057:Tomography, X-Ray Computed; D018084:Ultrasonography, Interventional