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Prognostication of Liver Disease Patients via the WFUMB 'Rule-of-4' Algorithm Using SSI-2D-SWE-Based Liver Stiffness
Christian Sebesta1,2,3, Georg Kramer1,2,3,4, Nina Dominik1,2,3
1Division of Gastroenterology and Hepatology, Department of Internal Medicine III, Medical University of Vienna, Vienna, Austria.
Summary
The World Federation for Ultrasound in Medicine and Biology (WFUMB)
Area of Science:
- Hepatology
- Medical Imaging
- Diagnostic Accuracy
Background:
- The World Federation for Ultrasound in Medicine and Biology (WFUMB) 2024 guidance proposed the 'rule-of-4' for Acoustic Radiation Force Impulse (ARFI) liver stiffness measurement (LSM).
- This rule stratifies advanced chronic liver disease (ACLD) risk at ≥13 kPa and clinically significant portal hypertension (CSPH) risk at >21 kPa.
Purpose of the Study:
- To prospectively evaluate the WFUMB 'rule-of-4' using supersonic imaging 2D-LSM (SSI-2D-LSM) for risk stratification of liver disease.
- To compare the diagnostic accuracy of SSI-2D-LSM with hepatic venous pressure gradient (HVPG) and vibration-controlled transient elastography (VCTE) for predicting decompensation events.
Main Methods:
- 187 patients underwent same-day SSI-2D-LSM and HVPG measurements.
- Patients were stratified into three LSM groups: <13 kPa, 13-21 kPa, and >21 kPa.
- Follow-up for 1 year (Y1) assessed decompensation events.
Main Results:
- The WFUMB 'rule-of-4' thresholds showed high accuracy for predicting CSPH (AUC: 0.83) and decompensation.
- Y1 decompensation rates were 0% (<13 kPa), 10% (13-21 kPa), and 24.7% (>21 kPa).
- HVPG was superior for predicting decompensation in compensated ACLD (cACLD) (AUC: 0.92), while SSI-2D-LSM (AUC: 0.75) and VCTE (AUC: 0.77) showed similar performance.
Conclusions:
- The WFUMB 'rule-of-4' using ARFI-LSM provides accurate, non-invasive risk stratification for liver disease patients.
- Short-term decompensation risk begins at SSI-2D-LSM ≥13 kPa and is considerable at >21 kPa.
- These findings support the clinical implementation of ARFI-LSM for risk assessment.

