title: Evaluation of a method for improving the detection of hepatocellular carcinoma.
abstract: OBJECTIVE
  To improve the detection of liver lesions in patients with hepatocellular carcinoma (HCC) via an iodine contrast enhancement tool.
  
  
  METHODS
  Thirty-two patients with clinically proven HCCs underwent imaging with a three-phase protocol on a 256-slice MDCT. The contrast enhancement in the reconstructed slices was improved via a post-processing tool. Mean image noise was measured in four different regions: liver lesion, healthy liver, subcutaneous fat and bone. For each image set the image noise and contrast-to-noise ratio (CNR) were assessed. For subjective image assessment, four experienced radiologists evaluated the diagnostic quality.
  
  
  RESULTS
  While employing the post-processing algorithm, CNR between the liver lesion and healthy liver tissue improves significantly by a factor of 1.78 (CNRwithout vC = 2.30 ± 1.92/CNRwith vC = 4.11 ± 3.05) (P* = 0.01). All results could be achieved without a strengthening of artefacts; mean HU values of subcutaneous fat and bone did not significantly change. Subjective image analysis illustrated a significant improvement when employing post-processing for clinically relevant criteria such as diagnostic confidence.
  
  
  CONCLUSIONS
  With post-processing we see a significantly improved detection of arterial uptake in hepatic lesions compared with non-processed data. The improvement in CNR was confirmed by subjective image assessment for small lesions and for lesions with limited uptake.
  
  
  CONCLUSIONS
  • Enhancement with iodine-based contrast agents is an essential part of CT. • A new post-processing tool significantly improves the diagnostics of hepatocellular carcinoma. • It also improves detection of small lesions with limited iodine uptake.
authors.affiliation: Department of Radiology, Technische Universität München, Munich, Germany, edgar.bendik@gmx.de.
authors.forename: Edgar
authors.initials: E
authors.lastname: Bendik
authors.forename: Peter B
authors.initials: PB
authors.lastname: Noël
authors.forename: Daniela
authors.initials: D
authors.lastname: Münzel
authors.forename: Alexander A
authors.initials: AA
authors.lastname: Fingerle
authors.forename: Martin
authors.initials: M
authors.lastname: Henninger
authors.forename: Christian
authors.initials: C
authors.lastname: Markus
authors.forename: Alain
authors.initials: A
authors.lastname: Vlassenbroek
authors.forename: Ernst J
authors.initials: EJ
authors.lastname: Rummeny
authors.forename: Martin
authors.initials: M
authors.lastname: Dobritz
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D016477:Artifacts; D006528:Carcinoma, Hepatocellular / Q000000981:diagnostic imaging*; D003287:Contrast Media; D003937:Diagnosis, Differential; D005260:Female; D006801:Humans; D008113:Liver Neoplasms / Q000000981:diagnostic imaging*; D008297:Male; D008875:Middle Aged; D061330:Multidetector Computed Tomography / Q000379:methods*; D011857:Radiographic Image Interpretation, Computer-Assisted; D012189:Retrospective Studies
chemical_list: D003287:Contrast Media