Clinical validation of T1ρ mapping for the assessment of hepatic fibrosis in patients with chronic liver disease

European Radiology, vol. 36, pp. 3983–3993

Abstract

OBJECTIVES: To evaluate the diagnostic utility of T1ρ mapping for assessing hepatic fibrosis in patients with chronic liver disease (CLD), including steatotic liver disease (SLD). MATERIALS AND METHODS: In this prospective study (September 2024 to May 2025), consecutive patients with CLD underwent liver MRI, including MR-elastography, PDFF, T1, extracellular volume fraction (ECV), and T1ρ mapping. MRE-based liver stiffness was used as the reference to assess the diagnostic performance of the MRI-derived mapping parameters. MR-elastography-based liver stiffness thresholds for significant fibrosis (≥ F2) were set at > 3.66 kPa for participants without hepatic steatosis (PDFF ≤ 5%), and > 3.14 kPa for participants with hepatic steatosis (PDFF > 5%). The t-test, Spearman's correlation, and the ROC analysis were applied. RESULTS: One hundred twelve CLD participants were included (mean age, 48 ± 16 years; 53 participants with hepatic steatosis). All assessed quantitative mapping parameters were significantly increased in participants with significant fibrosis than in those without (e.g., T1ρ: 110 ± 15 vs 92 ± 6 ms, p < 0.001). T1ρ revealed a moderate to strong correlation with MR-elastography-based stiffness, superior to T1 and ECV (entire cohort: r = 0.75 [T1ρ] vs 0.49 [native T1] vs 0.68 [ECV]; participants with hepatic steatosis: r = 0.67 [T1ρ] vs 0.32 [native T1] vs 0.62 [ECV]; p < 0.05 in each case, respectively). T1ρ provided the highest diagnostic performance for diagnosing significant fibrosis (in the entire cohort: AUC 0.90 [T1ρ] vs 0.73, p < 0.001 [native T1], vs 0.81, p = 0.05 [ECV]; in participants with hepatic steatosis: AUC 0.87 [T1ρ] vs 0.67, p = 0.03 [native T1], vs 0.79, p = 0.047 [ECV], p values are given vs T1ρ). CONCLUSION: Hepatic T1ρ might be a more accurate marker of hepatic fibrosis in CLD, including SLD, compared to hepatic native T1 and ECV mapping. KEY POINTS: Question Accurate non-invasive assessment of hepatic fibrosis remains challenging, particularly in the presence of steatosis, where MRI biomarkers such as native T1 and ECV fraction are limited. Findings T1ρ mapping outperformed native T1 and ECV for identifying significant fibrosis and maintained robust accuracy in the presence of hepatic steatosis. Clinical relevance T1ρ mapping offers a robust, non-invasive MRI biomarker for assessing hepatic fibrosis across the full spectrum of CLD, including SLD, with superior accuracy to native T1 and ECV and reduced influence from hepatic fat infiltration.

Authors 12

1. Narine Mesropyan corresponding

   University Hospital Bonn

   Affiliation as printed

   Department of Diagnostic and Interventional Radiology, University Hospital Bonn, Bonn, Germany. narine.mesropyan@ukbonn.de

2. Johannes Chang

   University Hospital Bonn

   Affiliation as printed

   Department of Internal Medicine I and Cirrhosis Center Bonn, University Hospital Bonn, Bonn, Germany

3. Philipp Ludwig Lutz

   University Hospital Bonn

   Affiliation as printed

   Department of Internal Medicine I and Cirrhosis Center Bonn, University Hospital Bonn, Bonn, Germany

4. Oliver M. Weber

   Philips (Germany)

   Affiliation as printed

   Philips GmbH, Hamburg, Germany

5. Christoph Katemann

   Philips (Germany)

   Affiliation as printed

   Philips GmbH, Hamburg, Germany

6. Tatjana Dell

   University of Bonn · University Hospital Bonn

   Affiliation as printed

   Department of Diagnostic and Interventional Radiology, University Hospital Bonn, Bonn, Germany

7. Dmitrij Kravchenko

   University of Bonn · University Hospital Bonn

   Affiliation as printed

   Department of Diagnostic and Interventional Radiology, University Hospital Bonn, Bonn, Germany

8. Can Yueksel Aachen Department of Diagnostic and Interventional Radiology

   Universitätsklinikum Aachen

   Affiliation as printed

   Department of Diagnostic and Interventional Radiology, University Hospital Aachen, Aachen, Germany

9. Daniel L. R. Kuetting

   University of Bonn · University Hospital Bonn

   Affiliation as printed

   Department of Diagnostic and Interventional Radiology, University Hospital Bonn, Bonn, Germany

10. Claus Christian Pieper

    University of Bonn · University Hospital Bonn

    Affiliation as printed

    Department of Diagnostic and Interventional Radiology, University Hospital Bonn, Bonn, Germany

11. Julian Alexander Luetkens

    University of Bonn · University Hospital Bonn

    Affiliation as printed

    Department of Diagnostic and Interventional Radiology, University Hospital Bonn, Bonn, Germany

12. Alexander Isaak

    University of Bonn · University Hospital Bonn

    Affiliation as printed

    Department of Diagnostic and Interventional Radiology, University Hospital Bonn, Bonn, Germany