Marco Dioguardi Burgio1,2, Riccardo Sartoris3,4, Aurélie Beaufrere5, Jules Grégory4,6, Boris Guiu7, Chloé Guillot7, Pierre-Emmanuel Rautou3,8, Laurent Castera8, Mohamed Bouattour9, Valérie Paradis3,5, Valérie Vilgrain3,4, Maxime Ronot3,4. 1. INSERM U1149 "Centre de Recherche Sur L'inflammation", CRI, Université de Paris, 75018, Paris, France. marco.dioguardiburgio@aphp.fr. 2. Department of Radiology, AP-HP.Nord, Hôpital Beaujon, 100 Boulevard du Général Leclerc, 92110, Clichy, France. marco.dioguardiburgio@aphp.fr. 3. INSERM U1149 "Centre de Recherche Sur L'inflammation", CRI, Université de Paris, 75018, Paris, France. 4. Department of Radiology, AP-HP.Nord, Hôpital Beaujon, 100 Boulevard du Général Leclerc, 92110, Clichy, France. 5. Department of Pathology, AP-HP.Nord, Hôpital Beaujon, 100 Boulevard du Général Leclerc, 92110, Clichy, France. 6. INSERM, UMR1153, Epidemiology and Biostatistics Sorbonne Paris Cité Center (CRESS), METHODS team, Hôpital Hôtel Dieu, F-75004, Paris, France. 7. Department of Radiology, St-Éloi University Hospital, 34980, Montpellier, France. 8. Department of Hepatology, AP-HP.Nord, Hôpital Beaujon, 100 Boulevard du Général Leclerc, 92110, Clichy, France. 9. Department of Digestive Oncology, AP-HP.Nord, Hôpital Beaujon, 100 Boulevard du Général Leclerc, 92110, Clichy, France.
Abstract
OBJECTIVES: To evaluate the diagnostic performance of liver surface nodularity (LSN) for the assessment of advanced fibrosis in patients with non-alcoholic fatty liver disease (NAFLD). METHODS: We retrospectively analysed patients with pathologically proven NAFLD who underwent liver MRI. Demographic, clinical, and laboratory data (including FIB-4 scores) were gathered. The SAF score was used to assess NAFLD. MRI-proton density fat fraction (PDFF) and LSN were determined on pre-contrast MR sequences. ROC curve analysis was performed to evaluate the diagnostic performance of MRI-LSN for the diagnosis of advanced (F3-F4) liver fibrosis. RESULTS: The final population included 142 patients. Sixty-seven (47%) patients had non-alcoholic steatohepatitis (NASH), and 52 (37%) had advanced fibrosis. The median MRI-PDFF increased with the grades of steatosis: 8.1%, 18.1%, and 31% in S1, S2, and S3 patients, respectively (p < 0.001). The area under the ROC curve (AUC) of MRI-LSN ≥ 2.50 was 0.838 (95%CI 0.767-0.894, sensitivity 67.3%, specificity 88.9%, positive and negative predictive values 77.8% and 82.5%, respectively) for the diagnosis of advanced fibrosis. Combining FIB-4 and MRI-LSN correctly classified 103/142 (73%) patients. This was validated in an external cohort of 75 patients. CONCLUSIONS: MRI-LSN has good diagnostic performance in diagnosis of advanced fibrosis in NAFLD patients. A combination of FIB-4 and MRI-LSN derived from pre-contrast MRI could be helpful to detect advanced fibrosis. KEY POINTS: • MRI-LSN ≥ 2.5 was accurate for the diagnosis of advanced hepatic fibrosis in NAFLD patients. • The combination of FIB-4 and MRI-LSN improved the detection of advanced fibrosis. • MRI-LSN can be easily derived by unenhanced MRI sequences that are routinely acquired.
OBJECTIVES: To evaluate the diagnostic performance of liver surface nodularity (LSN) for the assessment of advanced fibrosis in patients with non-alcoholic fatty liver disease (NAFLD). METHODS: We retrospectively analysed patients with pathologically proven NAFLD who underwent liver MRI. Demographic, clinical, and laboratory data (including FIB-4 scores) were gathered. The SAF score was used to assess NAFLD. MRI-proton density fat fraction (PDFF) and LSN were determined on pre-contrast MR sequences. ROC curve analysis was performed to evaluate the diagnostic performance of MRI-LSN for the diagnosis of advanced (F3-F4) liver fibrosis. RESULTS: The final population included 142 patients. Sixty-seven (47%) patients had non-alcoholic steatohepatitis (NASH), and 52 (37%) had advanced fibrosis. The median MRI-PDFF increased with the grades of steatosis: 8.1%, 18.1%, and 31% in S1, S2, and S3 patients, respectively (p < 0.001). The area under the ROC curve (AUC) of MRI-LSN ≥ 2.50 was 0.838 (95%CI 0.767-0.894, sensitivity 67.3%, specificity 88.9%, positive and negative predictive values 77.8% and 82.5%, respectively) for the diagnosis of advanced fibrosis. Combining FIB-4 and MRI-LSN correctly classified 103/142 (73%) patients. This was validated in an external cohort of 75 patients. CONCLUSIONS: MRI-LSN has good diagnostic performance in diagnosis of advanced fibrosis in NAFLD patients. A combination of FIB-4 and MRI-LSN derived from pre-contrast MRI could be helpful to detect advanced fibrosis. KEY POINTS: • MRI-LSN ≥ 2.5 was accurate for the diagnosis of advanced hepatic fibrosis in NAFLD patients. • The combination of FIB-4 and MRI-LSN improved the detection of advanced fibrosis. • MRI-LSN can be easily derived by unenhanced MRI sequences that are routinely acquired.
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