Diana Feier1,2, Csilla Balassy1, Nina Bastati1, Romana Fragner1, Friedrich Wrba3, Ahmed Ba-Ssalamah4. 1. Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, General Hospital of Vienna (AKH), Waehringer Guertel 18-20, A-1090, Vienna, Austria. 2. Department of Radiology, Iuliu Hatieganu University of Medicine and Pharmacy, Cluj-Napoca, Emergency County Hospital, Cluj-Napoca, Romania. 3. Department of Pathology, Medical University of Vienna, General Hospital of Vienna (AKH), Vienna, Austria. 4. Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, General Hospital of Vienna (AKH), Waehringer Guertel 18-20, A-1090, Vienna, Austria. ahmed.ba-ssalamah@meduniwien.ac.at.
Abstract
PURPOSE: To assess the diagnostic efficacy of multiparametric MRI using quantitative measurements of the apparent diffusion coefficient (ADC) of the liver parenchyma on diffusion-weighted imaging (DWI), signal intensity (SI) on susceptibility-weighted imaging (SWI), and gadoxetic acid-enhanced T1-weighted imaging during the hepatobiliary phase for the staging of liver fibrosis. MATERIALS AND METHODS: Seventy-seven patients underwent a 3T MRI examination, including DWI/SWI sequences and gadoxetic acid-enhanced T1-weighted MRI. Liver fibrosis according to liver biopsy was staged using the Metavir fibrosis score: F0 (n = 21, 27.3%); F1 (n = 7, 9.1%); F2 (n = 8, 10.4%); F3 (n = 12, 15.6%); and F4 (n = 29, 37.7%). SI of the liver was defined using region-of-interest measurements to calculate the ADC values, the relative enhancement (RE) in the hepatobiliary phase, and the liver-to-muscle ratio (LMR) measurements for SWI. RESULTS: The values of RE, LMR, and ADC measurements were statistically significantly different among the five fibrosis stages (p < 0.004). Combining the three parameters in a multiparametric approach, the AUC for detecting F1 stage or greater (≥ F1) was 94%, for F2 or greater (≥F2) was 95%, for F3 or greater (≥F3) was 90%, and for stage F4 was 93%. CONCLUSIONS: Multiparametric MRI is an efficient non-invasive diagnostic tool for the staging of liver fibrosis. KEY POINTS: • Multiparametric MRI has high accuracy in predicting moderate or greater liver fibrosis. • Relative enhancement post- gadoxetic acid is an independent predictor of liver fibrosis. • Liver SWI signal intensity and ADC values enhance the diagnostic ability.
PURPOSE: To assess the diagnostic efficacy of multiparametric MRI using quantitative measurements of the apparent diffusion coefficient (ADC) of the liver parenchyma on diffusion-weighted imaging (DWI), signal intensity (SI) on susceptibility-weighted imaging (SWI), and gadoxetic acid-enhanced T1-weighted imaging during the hepatobiliary phase for the staging of liver fibrosis. MATERIALS AND METHODS: Seventy-seven patients underwent a 3T MRI examination, including DWI/SWI sequences and gadoxetic acid-enhanced T1-weighted MRI. Liver fibrosis according to liver biopsy was staged using the Metavir fibrosis score: F0 (n = 21, 27.3%); F1 (n = 7, 9.1%); F2 (n = 8, 10.4%); F3 (n = 12, 15.6%); and F4 (n = 29, 37.7%). SI of the liver was defined using region-of-interest measurements to calculate the ADC values, the relative enhancement (RE) in the hepatobiliary phase, and the liver-to-muscle ratio (LMR) measurements for SWI. RESULTS: The values of RE, LMR, and ADC measurements were statistically significantly different among the five fibrosis stages (p < 0.004). Combining the three parameters in a multiparametric approach, the AUC for detecting F1 stage or greater (≥ F1) was 94%, for F2 or greater (≥F2) was 95%, for F3 or greater (≥F3) was 90%, and for stage F4 was 93%. CONCLUSIONS: Multiparametric MRI is an efficient non-invasive diagnostic tool for the staging of liver fibrosis. KEY POINTS: • Multiparametric MRI has high accuracy in predicting moderate or greater liver fibrosis. • Relative enhancement post- gadoxetic acid is an independent predictor of liver fibrosis. • Liver SWI signal intensity and ADC values enhance the diagnostic ability.
Authors: Don C Rockey; Stephen H Caldwell; Zachary D Goodman; Rendon C Nelson; Alastair D Smith Journal: Hepatology Date: 2009-03 Impact factor: 17.425
Authors: Jeanne M Horowitz; Sudhakar K Venkatesh; Richard L Ehman; Kartik Jhaveri; Patrick Kamath; Michael A Ohliger; Anthony E Samir; Alvin C Silva; Bachir Taouli; Michael S Torbenson; Michael L Wells; Benjamin Yeh; Frank H Miller Journal: Abdom Radiol (NY) Date: 2017-08
Authors: S Keller; J Sedlacik; T Schuler; R Buchert; M Avanesov; R Zenouzi; A W Lohse; H Kooijman; J Fiehler; C Schramm; J Yamamura Journal: Eur Radiol Date: 2018-07-16 Impact factor: 5.315