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Updated: Jul 23, 2025
Measurement of Liver Stiffness Using Atomic Force Microscopy Coupled with Polarization Microscopy
Published on: July 20, 2022
Dynamics in Liver Stiffness Measurements Predict Outcomes in Advanced Chronic Liver Disease
Georg Semmler1, Zhenwei Yang2, Laurenz Fritz3
1Division of Gastroenterology and Hepatology, Department of Internal Medicine III, Medical University of Vienna, Vienna, Austria; Vienna Hepatic Hemodynamic Laboratory, Division of Gastroenterology and Hepatology, Department of Internal Medicine III, Medical University of Vienna, Vienna, Austria.
Background & Aims:
Liver stiffness measurements (LSMs) provide an opportunity to monitor liver disease progression and regression noninvasively. We aimed to determine the prognostic relevance of LSM dynamics over time for liver-related events and death in patients with chronic liver disease.
Methods:
Patients with chronic liver disease undergoing 2 or more reliable LSMs at least 180 days apart were included in this retrospective cohort study and stratified at baseline (BL) as nonadvanced chronic liver disease (non-ACLD, BL-LSM < 10 kPa), compensated ACLD (cACLD; BL-LSM ≥ 10 kPa), and decompensated ACLD. Data on all consecutive LSMs and clinical outcomes were collected.
Results:
There were 2508 patients with 8561 reliable LSMs (3 per patient; interquartile range, 2-4) included: 1647 (65.7%) with non-ACLD, 757 (30.2%) with cACLD, and 104 (4.1%) with decompensated ACLD. Seven non-ACLD patients (0.4%) and 83 patients with cACLD (10.9%) developed hepatic decompensation (median follow-up, 71 months). A 20% increase in LSM at any time was associated with an approximately 50% increased risk of hepatic decompensation (hazard ratio, 1.58; 95% CI, 1.41-1.79; P < .001) and liver-related death (hazard ratio, 1.45; 95% CI, 1.28-1.68; P < .001) in patients with cACLD. LSM dynamics yielded a high accuracy to predict hepatic decompensation in the following 12 months (area under the receiver operating characteristics curve = 0.933). The performance of LSM dynamics was numerically better than dynamics in Fibrosis-4 score (0.873), Model for End-Stage Liver Disease (0.835), and single time-point LSM (BL-LSM: 0.846; second LSM: 0.880). Any LSM decrease to <20 kPa identified patients with cACLD with a substantially lower risk of hepatic decompensation (hazard ratio, 0.13; 95% CI, 0.07-0.24). If reliable, LSM also confers prognostic information in decompensated ACLD.
Conclusions:
Repeating LSM enables an individual and updated risk assessment for decompensation and liver-related mortality in ACLD.
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