Open this publication in new window or tab >>Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Diagnostics, Medical radiation physics.
Linköping University, Department of Biomedical and Clinical Sciences. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Diagnostics, Clinical pathology.
Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Surgery, Orthopaedics and Cancer Treatment, Mag- tarmmedicinska kliniken. Linköping University, Center for Medical Image Science and Visualization (CMIV).
Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Surgery, Orthopaedics and Cancer Treatment, Mag- tarmmedicinska kliniken. Linköping University, Center for Medical Image Science and Visualization (CMIV).
Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Surgery, Orthopaedics and Cancer Treatment, Mag- tarmmedicinska kliniken. Linköping University, Center for Medical Image Science and Visualization (CMIV).
Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. 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).
Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. 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).
Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Diagnostics, Department of Radiology in Linköping. Region Östergötland, Center for Diagnostics, Medical radiation physics. Linköping University, Center for Medical Image Science and Visualization (CMIV).
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2026 (English)In: Journal of Magnetic Resonance Imaging, ISSN 1053-1807, E-ISSN 1522-2586, Vol. 64, no 1, p. 306-319, article id jmri.70319Article in journal (Refereed) Published
Abstract [en]
Background: Three-dimensional (3D) MR elastography (MRE) derives viscoelastic parameters that may reflect inflammation, but their frequency dependence and the influence of steatosis on inflammation grading and fibrosis staging remain unclear.
Purpose: To investigate 3D multifrequency MRE for assessing hepatic inflammation, fibrosis stage across frequencies, and the influence of steatosis.
Study Type: Prospective.
Population: Sixty-four (40 men, median age: 58 years) participants with chronic liver disease (CLD); 21 (8 men, median age:28 years) healthy volunteers.
Field Strength/Sequence: 3-T; gradient-echo sequence with mechanical vibrations at low (16.7 and 18 Hz), medium (33.4 and 36 Hz), and high (50.1 and 54 Hz) frequencies.
Assessment: In CLD participants, MRE-derived viscoelastic parameters, shear stiffness, storage modulus, loss modulus, and damping ratio were compared with histologically assessed fibrosis, inflammation, and steatosis. MRE test–retest repeatability over 10 min was evaluated in healthy volunteers.
Statistical Tests: Wilcoxon rank sum test, Spearman's correlation, multivariable regression analysis, and area under the receiver operating curve (AUROC). A p value of < 0.05 was considered statistically significant.
Results: Inflammation was significantly independently associated with damping ratio at medium frequency, which showed moderate performance for grading inflammation (AUROC = 0.76–0.83, sensitivity = 0.83–0.84, specificity = 0.70–0.79). Fibrosis staging using shear stiffness and moduli showed high diagnostic performance (AUROC = 0.82–0.95), with comparable accuracy between medium and high frequencies (p = 0.327–0.896). Steatosis was not significantly correlated with MRE overall (p = 0.212–0.459), but was significantly associated with 19% higher stiffness and 20% higher loss modulus at medium frequency in CLD participants without fibrosis or inflammation.
Data Conclusion: Medium frequency 3D MRE demonstrated an independent association with inflammation while preserving accurate fibrosis assessment. Steatosis seemed not to confound MRE-based evaluation.
Level of Evidence: 1.
Technical Efficacy: Stage 2.
Plain Language Summary: Chronic liver disease can cause both inflammation and scarring (fibrosis). Accurate assessment usually requires a biopsy, which is invasive. This study evaluated a noninvasive imaging method called three-dimensional magnetic resonance elastography (3D MRE) in patients who underwent same-day liver biopsy. The researchers tested whether different vibration frequencies could detect inflammation and fibrosis. They found that medium frequency measurements were associated with liver inflammation while still accurately identifying fibrosis. Fat accumulation in the liver did not significantly affect the results. These findings suggest that 3D MRE may help medical doctors assess liver inflammation and fibrosis noninvasively in a single examination.
Place, publisher, year, edition, pages
John Wiley & Sons, 2026
Keywords
Chronic liver disease, Fibrosis, Inflammation, MR elastography, Steatosis
National Category
Gastroenterology and Hepatology Medical Imaging Radiology and Medical Imaging
Identifiers
urn:nbn:se:liu:diva-222446 (URN)10.1002/jmri.70319 (DOI)001732121800001 ()41924972 (PubMedID)2-s2.0-105034898236 (Scopus ID)
Note
Funding: This work was supported by Vinnova (Sweden's Innovation Agency), the Swedish Research Council for Engineering Sciences and Natural Sciences (VR/NT), 2020-04826, and ALF funding (Avtal om Läkarutbildning och Forskning; Agreement on Medical Education and Research) from Region Östergötland (Östergötland County Council).
2026-04-022026-04-022026-06-26