title: Quantitative hepatic perfusion modeling using DCE-MRI with sequential breathholds.
abstract: OBJECTIVE
  To develop and demonstrate the feasibility of a new formulation for quantitative perfusion modeling in the liver using interrupted DCE-MRI data acquired during multiple sequential breathholds.
  
  
  METHODS
  A new mathematical formulation to estimate quantitative perfusion parameters using interrupted data was developed. Using this method, we investigated whether a second degree-of-freedom in the tissue residue function (TRF) improves quality-of-fit criteria when applied to a dual-input single-compartment perfusion model. We subsequently estimated hepatic perfusion parameters using DCE-MRI data from 12 healthy volunteers and 9 cirrhotic patients with a history of hepatocellular carcinoma (HCC); and examined the utility of these estimates in differentiating between healthy liver, cirrhotic liver, and HCC.
  
  
  RESULTS
  Quality-of-fit criteria in all groups were improved using a Weibull TRF (2 degrees-of-freedom) versus an exponential TRF (1 degree-of-freedom), indicating nearer concordance of source DCE-MRI data with the Weibull model. Using the Weibull TRF, arterial fraction was greater in cirrhotic versus normal liver (39 ± 23% versus 15 ± 14%, P = 0.07). Mean transit time (20.6 ± 4.1 s versus 9.8 ± 3.5 s, P = 0.01) and arterial fraction (39 ± 23% versus 73 ± 14%, P = 0.04) were both significantly different between cirrhotic liver and HCC, while differences in total perfusion approached significance.
  
  
  CONCLUSIONS
  This work demonstrates the feasibility of estimating hepatic perfusion parameters using interrupted data acquired during sequential breathholds.
authors.affiliation: Department of Biomedical Engineering, University of Wisconsin, Madison, Wisconsin, USA.
authors.forename: Eric M
authors.initials: EM
authors.lastname: Bultman
authors.forename: Ethan K
authors.initials: EK
authors.lastname: Brodsky
authors.forename: Debra E
authors.initials: DE
authors.lastname: Horng
authors.forename: Pablo
authors.initials: P
authors.lastname: Irarrazaval
authors.forename: William R
authors.initials: WR
authors.lastname: Schelman
authors.forename: Walter F
authors.initials: WF
authors.lastname: Block
authors.forename: Scott B
authors.initials: SB
authors.lastname: Reeder
mesh_terms: D000328:Adult; D000368:Aged; D001783:Blood Flow Velocity; D062485:Breath Holding; D006528:Carcinoma, Hepatocellular / Q000175:diagnosis* / Q000503:physiopathology*; D003198:Computer Simulation; D003937:Diagnosis, Differential; D005240:Feasibility Studies; D005260:Female; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods; D008102:Liver Circulation; D008103:Liver Cirrhosis / Q000175:diagnosis* / Q000503:physiopathology*; D008113:Liver Neoplasms / Q000175:diagnosis* / Q000503:physiopathology*; D018810:Magnetic Resonance Angiography / Q000379:methods*; D008297:Male; D008875:Middle Aged; D008954:Models, Biological; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D055815:Young Adult
keywords: DCE-MRI; hepatic perfusion modeling; hepatocellular carcinoma; quantitative perfusion MRI; tumor perfusion modeling