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Viscoelastic parameters derived from multifrequency MR elastography for depicting hepatic fibrosis and inflammation in chronic viral hepatitis.
Wang, Yikun; Zhou, Jiahao; Lin, Huimin; Wang, Huafeng; Sack, Ingolf; Guo, Jing; Yan, Fuhua; Li, Ruokun.
Afiliación
  • Wang Y; Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, No. 197 Ruijin Er Road, 200025, Shanghai, China.
  • Zhou J; Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, No. 197 Ruijin Er Road, 200025, Shanghai, China.
  • Lin H; Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, No. 197 Ruijin Er Road, 200025, Shanghai, China.
  • Wang H; Department of Phathology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, No. 197 Ruijin Er Road, 200025, Shanghai, China.
  • Sack I; Department of Radiology, Berlin Institute of Health, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin, Germany.
  • Guo J; Department of Radiology, Berlin Institute of Health, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin, Germany.
  • Yan F; Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, No. 197 Ruijin Er Road, 200025, Shanghai, China. yfh11655@rjh.com.cn.
  • Li R; College of Health Science and Technology, Shanghai Jiao Tong University School of Medicine, Shanghai, China. yfh11655@rjh.com.cn.
Insights Imaging ; 15(1): 91, 2024 Mar 26.
Article en En | MEDLINE | ID: mdl-38530543
ABSTRACT

OBJECTIVES:

The capability of MR elastography (MRE) to differentiate fibrosis and inflammation, and to provide precise diagnoses is crucial, whereas the coexistence of fibrosis and inflammation may obscure the diagnostic accuracy.

METHODS:

In this retrospective study, from June 2020 to December 2022, chronic viral hepatitis patients who underwent multifrequency MRE (mMRE) were included in, and further divided into, training and validation cohorts. The hepatic viscoelastic parameters [shear wave speed (c) and loss angle (φ) of the complex shear modulus] were obtained from mMRE. The logistic regression and receiver operating characteristic (ROC) curves were generated to evaluate performance of viscoelastic parameters for fibrosis and inflammation.

RESULTS:

A total of 233 patients were assigned to training cohort and validation cohorts (mean age, 52 years ± 13 (SD); 51 women; training cohort, n = 170 (73%), and validation cohort, n = 63 (27%)). Liver c exhibited superior performance in detecting fibrosis with ROC (95% confidence interval) of ≥ S1 (0.96 (0.92-0.99)), ≥ S2 (0.86 (0.78-0.92)), ≥ S3 (0.89 (0.84-0.95)), and S4 (0.88 (0.83-0.93)). Similarly, φ was effective in diagnosing inflammation with ROC values of ≥ G2 (0.72 (0.63-0.81)), ≥ G3 (0.88 (0.83-0.94)), and G4 (0.92 (0.87-0.98)). And great predictive discrimination for fibrosis and inflammation were shown in validation cohort (all AUCs > 0.75).

CONCLUSION:

The viscoelastic parameters derived from multifrequency MRE could realize simultaneous detection of hepatic fibrosis and inflammation. CRITICAL RELEVANCE STATEMENT Fibrosis and inflammation coexist in chronic liver disease which obscures the diagnostic performance of MR elastography, whereas the viscoelastic parameters derived from multifrequency MR elastography could realize simultaneous detection of hepatic fibrosis and inflammation. KEY POINTS • Hepatic biomechanical parameters derived from multifrequency MR elastography could effectively detect fibrosis and inflammation. • Liver stiffness is useful for detecting fibrosis independent of inflammatory activity. • Fibrosis could affect the diagnostic efficacy of liver viscosity in inflammation, especially in early-grade of inflammation.
Palabras clave

Texto completo: 1 Bases de datos: MEDLINE Idioma: En Revista: Insights Imaging Año: 2024 Tipo del documento: Article País de afiliación: China

Texto completo: 1 Bases de datos: MEDLINE Idioma: En Revista: Insights Imaging Año: 2024 Tipo del documento: Article País de afiliación: China