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Liver R2*is affected by both iron and fat: A dual biopsy-validated study of chronic liver disease
Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Medicine and Health Sciences.
Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart and Medicine Center, Department of Gastroentorology.ORCID iD: 0000-0002-5590-8601
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
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
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2019 (English)In: Journal of Magnetic Resonance Imaging, ISSN 1053-1807, E-ISSN 1522-2586, Vol. 50, no 1, p. 325-333Article in journal (Refereed) Published
Abstract [en]

Background Liver iron content (LIC) in chronic liver disease (CLD) is currently determined by performing an invasive liver biopsy. MRI using R2* relaxometry is a noninvasive alternative for estimating LIC. Fat accumulation in the liver, or proton density fat fraction (PDFF), may be a possible confounder of R2* measurements. Previous studies of the effect of PDFF on R2* have not used quantitative LIC measurement. Purpose To assess the associations between R2*, LIC, PDFF, and liver histology in patients with suspected CLD. Study Type Prospective. Population Eighty-one patients with suspected CLD. Field Strength/Sequence 1.5 T. Multiecho turbo field echo to quantify R2*. PRESS MRS to quantify PDFF. Assessment Each patient underwent an MR examination, followed by two needle biopsies immediately following the MR examination. The first biopsy was used for conventional histological assessment of LIC, whereas the second biopsy was used to quantitatively measure LIC using mass spectrometry. R2* was correlated with both LIC and PDFF. A correction for the influence of fat on R2* was calculated. Statistical Tests Pearson correlation, linear regression, and area under the receiver operating curve. Results There was a positive linear correlation between R2* and PDFF (R = 0.69), after removing data from patients with elevated iron levels, as defined by LIC. R2*, corrected for PDFF, was the best method for identifying patients with elevated iron levels, with a correlation of R = 0.87 and a sensitivity and specificity of 87.5% and 98.6%, respectively. Data Conclusion PDFF increases R2*. Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;50:325-333.

Place, publisher, year, edition, pages
WILEY , 2019. Vol. 50, no 1, p. 325-333
Keywords [en]
liver iron content; liver fat; R2*; PDFF; iron overload
National Category
Radiology, Nuclear Medicine and Medical Imaging
Identifiers
URN: urn:nbn:se:liu:diva-158842DOI: 10.1002/jmri.26601ISI: 000471831600033PubMedID: 30637926OAI: oai:DiVA.org:liu-158842DiVA, id: diva2:1337519
Note

Funding Agencies|Region Ostergotland; Medical Research council of Southeast Sweden [FORSS #12621]; Swedish Research Council [VR/NT #2014-6157, VR/MH, #2007-2884]; Forskningsradet i Sydostra Sverige; Linkoping University; Linkoping University Hospital Research Foundations; Vinnova [#2013-01314]; Vetenskapsradet

Available from: 2019-07-15 Created: 2019-07-15 Last updated: 2023-09-29
In thesis
1. Non-Invasive Characterization of Liver Disease: By Multimodal Quantitative Magnetic Resonance
Open this publication in new window or tab >>Non-Invasive Characterization of Liver Disease: By Multimodal Quantitative Magnetic Resonance
2019 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

There is a large and unmet need for diagnostic tool that can be used to characterize chronic liver diseases (CLD). In the earlier stages of CLD, much of the diagnostics involves performing biopsies, which are evaluated by a histopathologist for the presence of e.g. fat, iron, inflammation, and fibrosis. Performing biopsies, however, have two downsides: i) biopsies are invasive and carries a small but non-negligible risk for serious complications, ii) biopsies only represents a tiny portion of the liver and are thus prone to sampling error. Moreover, in the later stages of CLD, when the disease has progressed far enough, the ability of the liver to perform its basic function will be compromised. In this stage, there is a need for better methods for accurately measuring liver function. Additionally, measures of liver function can also be used when developing new drugs, as biomarkers for drug-induced liver injury (DILI), which is a serious drug-safety issue.

Magnetic resonance imaging (MRI) is a non-invasive medical imaging modality, which have shown much promise with regards to characterizing liver disease in all of the abovementioned aspects. The aim of this PhD project was to develop and validate MR-based methods that can be used to non-invasively characterize liver disease.

Paper I investigated if R2* mapping, a MR-method for measuring liver iron content, can be confounded by liver fat. The results show fat does affect R2*. The conclusion was therefore that fat must be taken into account when measuring small amounts of liver iron, as a small increase in R2* could be due to either small amounts of iron or large amounts of fat.

Paper II examined whether T1 mapping, which is another MR-method, can be used for staging liver fibrosis. The results of previous research have been mixed; some studies have been very promising, whereas other studies have been less promising. Unfortunately, the results in Paper II belongs to the less promising studies.

Paper III focused on measuring liver function by dynamic contrast-enhanced MRI (DCEMRI) using a liver specific contrast agent, which is taken up the hepatocytes and excreted to the bile. The purpose of the paper was to extend and validate a method for estimating uptake and efflux rates of the contrast agent. The method had previously only been applied in health volunteers. Paper II showed that the method can be applied to CLD patients and that the uptake of the contrast agent is lower in patients with advanced fibrosis.

Paper IV also used studied liver function with DCE-MRI in patients with primary sclerosing cholangitis (PSC). PSC is a CLD where the bile ducts are attacked by the immune system. When diagnosing PSC patients, it is common to use magnetic resonance cholangiopancreatography (MRCP), which is a method for imaging the bile ducts. Paper IV examined if there was any correlation between number and severity of the morphological changes, seen on MRCP, and measures of liver function derived using DCE-MRI. However, the results showed no such correlation. The conclusion was that the results indicates that MRCP should not be used to predict parenchymal function.

Paper V developed a method for translating DCE-MRI liver function parameters from rats to humans. This translation could be of value when developing new drugs, as a tool for predicting which drugs might cause drug-induced liver injury.

In summary, this thesis has shown that multimodal quantitative MR has a bright future for characterizing liver disease from a range of different aspects.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2019. p. 77
Series
Linköping University Medical Dissertations, ISSN 0345-0082 ; 1722
National Category
Radiology, Nuclear Medicine and Medical Imaging
Identifiers
urn:nbn:se:liu:diva-162653 (URN)10.3384/diss.diva-162653 (DOI)9789179299422 (ISBN)
Public defence
2020-01-30, Granitsalen, Campus US, Linköping, 09:15 (English)
Opponent
Supervisors
Available from: 2019-12-13 Created: 2019-12-12 Last updated: 2020-08-14Bibliographically approved

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Dahlqvist Leinhard, Olof

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