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Model-inferred mech...
Model-inferred mechanisms of liver function from magnetic resonance imaging data : Validation and variation across a clinically relevant cohort
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- Forsgren, Mikael (author)
- Linköpings universitet,Avdelningen för radiologiska vetenskaper,Medicinska fakulteten,Centrum för medicinsk bildvetenskap och visualisering, CMIV,Region Östergötland, Radiofysikavdelningen US
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- Karlsson, Markus (author)
- Linköpings universitet,Avdelningen för radiologiska vetenskaper,Medicinska fakulteten,Centrum för medicinsk bildvetenskap och visualisering, CMIV
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- Dahlqvist Leinhard, Olof, 1978- (author)
- Linköpings universitet,Avdelningen för radiologiska vetenskaper,Medicinska fakulteten,Centrum för medicinsk bildvetenskap och visualisering, CMIV,Region Östergötland, Radiofysikavdelningen US
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- Dahlström, Nils (author)
- Linköpings universitet,Avdelningen för radiologiska vetenskaper,Medicinska fakulteten,Centrum för medicinsk bildvetenskap och visualisering, CMIV,Region Östergötland, Röntgenkliniken i Linköping
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- Norén, Bengt (author)
- Linköpings universitet,Avdelningen för radiologiska vetenskaper,Medicinska fakulteten,Centrum för medicinsk bildvetenskap och visualisering, CMIV,Region Östergötland, Röntgenkliniken i Linköping
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- Romu, Thobias (author)
- Linköpings universitet,Institutionen för medicinsk teknik,Tekniska fakulteten,Centrum för medicinsk bildvetenskap och visualisering, CMIV
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- Ignatova, Simone (author)
- Linköpings universitet,Avdelning för neurobiologi,Medicinska fakulteten,Region Östergötland, Klinisk patologi
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- Ekstedt, Mattias (author)
- Linköpings universitet,Avdelningen för kardiovaskulär medicin,Medicinska fakulteten,Region Östergötland, Magtarmmedicinska kliniken
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- Kechagias, Stergios (author)
- Linköpings universitet,Avdelningen för kardiovaskulär medicin,Medicinska fakulteten,Region Östergötland, Magtarmmedicinska kliniken
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- Lundberg, Peter (author)
- Linköpings universitet,Avdelningen för radiologiska vetenskaper,Medicinska fakulteten,Centrum för medicinsk bildvetenskap och visualisering, CMIV,Region Östergötland, Medicinsk strålningsfysik
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- Cedersund, Gunnar (author)
- Linköpings universitet,Avdelningen för medicinsk teknik,Tekniska fakulteten,Institutionen för klinisk och experimentell medicin,Medicinska fakulteten
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(creator_code:org_t)
- 2019-06-25
- 2019
- English.
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In: PloS Computational Biology. - San Francisco, CA, United States : Public Library of Science. - 1553-734X .- 1553-7358. ; 15:6
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https://doi.org/10.1...
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https://liu.diva-por... (primary) (Raw object)
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https://doi.org/10.1...
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Abstract
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- Estimation of liver function is important to monitor progression of chronic liver disease (CLD). A promising method is magnetic resonance imaging (MRI) combined with gadoxetate, a liver-specific contrast agent. For this method, we have previously developed a model for an average healthy human. Herein, we extended this model, by combining it with a patient-specific non-linear mixed-effects modeling framework. We validated the model by recruiting 100 patients with CLD of varying severity and etiologies. The model explained all MRI data and adequately predicted both timepoints saved for validation and gadoxetate concentrations in both plasma and biopsies. The validated model provides a new and deeper look into how the mechanisms of liver function vary across a wide variety of liver diseases. The basic mechanisms remain the same, but increasing fibrosis reduces uptake and increases excretion of gadoxetate. These mechanisms are shared across many liver functions and can now be estimated from standard clinical images.Author summaryBeing able to accurately and reliably estimate liver function is important when monitoring the progression of patients with liver disease, as well as when identifying drug-induced liver injury during drug development. A promising method for quantifying liver function is to use magnetic resonance imaging combined with gadoxetate. Gadoxetate is a liver-specific contrast agent, which is taken up by the hepatocytes and excreted into the bile. We have previously developed a mechanistic model for gadoxetate dynamics using averaged data from healthy volunteers. In this work, we extended our model with a non-linear mixed-effects modeling framework to give patient-specific estimates of the gadoxetate transport-rates. We validated the model by recruiting 100 patients with liver disease, covering a range of severity and etiologies. All patients underwent an MRI-examination and provided both blood and liver biopsies. Our validated model provides a new and deeper look into how the mechanisms of liver function varies across a wide variety of liver diseases. The basic mechanisms remain the same, but increasing fibrosis reduces uptake and increases excretion of gadoxetate.
Subject headings
- MEDICIN OCH HÄLSOVETENSKAP -- Medicinska och farmaceutiska grundvetenskaper -- Farmaceutiska vetenskaper (hsv//swe)
- MEDICAL AND HEALTH SCIENCES -- Basic Medicine -- Pharmaceutical Sciences (hsv//eng)
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- ref (subject category)
- art (subject category)
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- By the author/editor
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Forsgren, Mikael
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Karlsson, Markus
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Dahlqvist Leinha ...
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Dahlström, Nils
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Norén, Bengt
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Romu, Thobias
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Ignatova, Simone
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Ekstedt, Mattias
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Kechagias, Sterg ...
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Lundberg, Peter
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Cedersund, Gunna ...
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- About the subject
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- MEDICAL AND HEALTH SCIENCES
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MEDICAL AND HEAL ...
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and Basic Medicine
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and Pharmaceutical S ...
- Articles in the publication
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PloS Computation ...
- By the university
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Linköping University