Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Model-inferred mechanisms of liver function from magnetic resonance imaging data: Validation and variation across a clinically relevant cohort
Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics. Linköping University, Center for Medical Image Science and Visualization (CMIV).ORCID iD: 0000-0003-4630-6550
Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV).
Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics. Linköping University, Center for Medical Image Science and Visualization (CMIV).
Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Diagnostics, Department of Radiology in Linköping. Linköping University, Center for Medical Image Science and Visualization (CMIV).ORCID iD: 0000-0002-4111-1693
Show others and affiliations
2019 (English)In: PloS Computational Biology, ISSN 1553-734X, E-ISSN 1553-7358, Vol. 15, no 6, article id e1007157Article in journal (Refereed) Published
Abstract [en]

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 summary

Being 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.

Place, publisher, year, edition, pages
San Francisco, CA, United States: Public Library of Science , 2019. Vol. 15, no 6, article id e1007157
National Category
Pharmaceutical Sciences
Identifiers
URN: urn:nbn:se:liu:diva-159165DOI: 10.1371/journal.pcbi.1007157ISI: 000474703000068PubMedID: 31237870Scopus ID: 2-s2.0-85069296906OAI: oai:DiVA.org:liu-159165DiVA, id: diva2:1339540
Note

Funding Agencies|Swedish Research Council [2014-6157, 2007-2884]; Medical Research council of Southeast Sweden [12621]; Vinnova [2013-01314]; Linkoping University, CENIIT [15.09]; Swedish fund for research without animal experiments [Nytank2015]

Available from: 2019-07-30 Created: 2019-07-30 Last updated: 2019-11-05Bibliographically approved
In thesis
1. The Non-Invasive Liver Biopsy: Determining Hepatic Function in Diffuse and Focal LiverDisease
Open this publication in new window or tab >>The Non-Invasive Liver Biopsy: Determining Hepatic Function in Diffuse and Focal LiverDisease
2017 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

The liver is one of the largest organs within the human body and it handles many vital tasks such as nutrient processing, toxin removal, and synthesis of important proteins. The number of people suffering from chronic liver disease is on the rise, likely due to the present ‘western’ lifestyle. As disease develops in the liver there are pathophysiological manifestations within the liver parenchyma that are both common and important to monitor. These manifestations include inflammation, fatty infiltration (steatosis), excessive scar tissue formation (fibrosis and cirrhosis), and iron loading. Importantly, as the disease progresses there is concurrent loss of liver function. Furthermore, postoperative liver function insufficiency is an important concern when planning surgical treatment of the liver, because it is associated with both morbidity and mortality. Liver function can also be hampered due to drug-induced injuries, an important aspect to consider in drug-development.

Currently, an invasive liver needle biopsy is required to determine the aetiology and to stage or grade the pathophysiological manifestations. There are important limitations with the biopsy, which include, risk of serious complications, mortality, morbidity, inter- and intra-observer variability, sampling error, and sampling variability. Cleary, it would be beneficial to be able investigate the pathophysiological manifestations accurately, non-invasively, and on regional level.

Current available laboratory liver function blood panels are typically insufficient and often only indicate damage at a late stage. Thus, it would be beneficial to have access to biomarkers that are both sensitive and responds to early changes in liver function in both clinical settings and for the pharmaceutical industry and regulatory agencies.

The main aim of this thesis was to develop and evaluate methods that can be used for a ‘non-invasive liver biopsy’ using magnetic resonance (MR). We also aimed to develop sensitive methods for measure liver function based on gadoxetate-enhanced MR imaging (MRI).

The presented work is primarily based on a prospective study on c. 100 patients suffering from chronic liver disease of varying aetiologies recruited due to elevated liver enzyme levels, without clear signs of decompensated cirrhosis. Our results show that the commonly used liver fat cut-off for diagnosing steatosis should be lowered from 5% to 3% when using MR proton-density fat fraction (PDFF). We also show that MR elastography (MRE) is superior in staging fibrosis.

Finally we presented a framework for quantifying liver function based on gadoxetate-enhanced MRI. The method is based on clinical images and a clinical approved contrast agent (gadoxetate). The framework consists of; state-of the-art image reconstruction and correction methods, a mathematical model, and a precise model parametrization method. The model was developed and validated on healthy subjects. Thereafter the model was found applicable on the chronic liver disease cohort as well as validated using gadoxetate levels in biopsy samples and blood samples. The liver function parameters correlated with clinical markers for liver function and liver fibrosis (used as a surrogate marker for liver function).

In summary, it should be possible to perform a non-invasive liver biopsy using: MRI-PDFF for liver fat and iron loading, MRE for liver fibrosis and possibly also inflammation, and measure liver function using the presented framework for analysing gadoxetate-enhanced MRI. With the exception of an MREtransducer no additional hardware is required on the MR scanner. The liver function method is likely to be useful both in a clinical setting and in pharmaceutical trials.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2017. p. 126
Series
Linköping University Medical Dissertations, ISSN 0345-0082 ; 1564
National Category
Radiology, Nuclear Medicine and Medical Imaging Gastroenterology and Hepatology Biomedical Laboratory Science/Technology Neurology Medical Laboratory and Measurements Technologies
Identifiers
urn:nbn:se:liu:diva-136545 (URN)10.3384/diss.diva-136545 (DOI)9789176855720 (ISBN)
Public defence
2017-05-23, Eken, Campus US, Linköping, 13:15 (English)
Opponent
Supervisors
Note

The original title of Manuscript IV was Quantitative Assessment of Liver Functions by Gadoxetate-Enhanced MRI: a Prospective Study of Chronic Liver Disease.

Available from: 2017-04-19 Created: 2017-04-19 Last updated: 2019-11-05Bibliographically approved

Open Access in DiVA

Model-inferred mechanisms of liver function from magnetic resonance imaging data: Validation and variation across a clinically relevant cohort(2829 kB)7 downloads
File information
File name FULLTEXT01.pdfFile size 2829 kBChecksum SHA-512
4342f32705beeb476fe19dabee48968de4b272a76a410a9405770ebe375322f1520b5670f48c9f273b9856578511dde823ad52d51a0a6a0acab824ce03c5b8bf
Type fulltextMimetype application/pdf

Other links

Publisher's full textPubMedScopus

Search in DiVA

By author/editor
Forsgren, MikaelKarlsson, MarkusDahlqvist Leinhard, OlofDahlström, NilsNorén, BengtRomu, ThobiasIgnatova, SimoneEkstedt, MattiasKechagias, StergiosLundberg, PeterCedersund, Gunnar
By organisation
Division of Radiological SciencesFaculty of Medicine and Health SciencesDepartment of Radiation PhysicsCenter for Medical Image Science and Visualization (CMIV)Department of Radiology in LinköpingDepartment of Biomedical EngineeringFaculty of Science & EngineeringDivison of NeurobiologyClinical pathologyDivision of Cardiovascular MedicineDepartment of GastroentorologyMedical radiation physicsDivision of Biomedical EngineeringDepartment of Clinical and Experimental Medicine
In the same journal
PloS Computational Biology
Pharmaceutical Sciences

Search outside of DiVA

GoogleGoogle Scholar
Total: 7 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

doi
pubmed
urn-nbn

Altmetric score

doi
pubmed
urn-nbn
Total: 178 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf