title: Physiologically realistic and validated mathematical liver model reveals [corrected] hepatobiliary transfer rates for Gd-EOB-DTPA using human DCE-MRI data.
abstract: OBJECTIVE
  Diffuse liver disease (DLD), such as non-alcoholic fatty liver disease (NASH) and cirrhosis, is a rapidly growing problem throughout the Westernized world. Magnetic resonance imaging (MRI), based on uptake of the hepatocyte-specific contrast agent (CA) Gd-EOB-DTPA, is a promising non-invasive approach for diagnosing DLD. However, to fully utilize the potential of such dynamic measurements for clinical or research purposes, more advanced methods for data analysis are required.
  
  
  METHODS
  A mathematical model that can be used for such data-analysis was developed. Data was obtained from healthy human subjects using a clinical protocol with high spatial resolution. The model is based on ordinary differential equations and goes beyond local diffusion modeling, taking into account the complete system accessible to the CA.
  
  
  RESULTS
  The presented model can describe the data accurately, which was confirmed using chi-square statistics. Furthermore, the model is minimal and identifiable, meaning that all parameters were determined with small degree of uncertainty. The model was also validated using independent data.
  
  
  CONCLUSIONS
  We have developed a novel approach for determining previously undescribed physiological hepatic parameters in humans, associated with CA transport across the liver. The method has a potential for assessing regional liver function in clinical examinations of patients that are suffering of DLD and compromised hepatic function.
authors.affiliation: Wolfram MathCore AB, Linköping, Sweden, and Center for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden; Department of Radiation Physics and Division of Radiological Sciences, Department of Medical and Health Sciences, Linköping University, Linköping, Sweden.
authors.forename: Mikael Fredrik
authors.initials: MF
authors.lastname: Forsgren
authors.affiliation: Department of Radiation Physics and Division of Radiological Sciences, Department of Medical and Health Sciences, Linköping University, Linköping, Sweden; Center for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden.
authors.forename: Olof
authors.initials: O
authors.lastname: Dahlqvist Leinhard
authors.affiliation: Center for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden; Department of Radiology and Division of Radiological Sciences, Department of Medical and Health Sciences, Linköping University, Linköping, Sweden.
authors.forename: Nils
authors.initials: N
authors.lastname: Dahlström
authors.affiliation: Department of Experimental Medicine, Linköping University, Linköping, Sweden; Systems Biology, Department of Biomedical Engineering, Linköping University, Linköping, Sweden.
authors.forename: Gunnar
authors.initials: G
authors.lastname: Cedersund
authors.affiliation: Center for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden; Department of Radiation Physics, Department of Radiology and Division of Radiological Sciences, Department of Medical and Health Sciences, Linköping University, Linköping, Sweden.
authors.forename: Peter
authors.initials: P
authors.lastname: Lundberg
mesh_terms: D000465:Algorithms; D003287:Contrast Media; D019786:Gadolinium DTPA; D006801:Humans; D008107:Liver Diseases / Q000175:diagnosis* / Q000473:pathology*; D008279:Magnetic Resonance Imaging; D008962:Models, Theoretical; D015203:Reproducibility of Results; D012189:Retrospective Studies; D012680:Sensitivity and Specificity
chemical_list: D003287:Contrast Media; C073590:gadolinium ethoxybenzyl DTPA; D019786:Gadolinium DTPA
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