ReviewJournal of translational medicine2026
Innovations in liver disease assessment: clinical insights from spleen stiffness measurement in chronic liver diseases.
Review in Journal of translational medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Authors and funding
9 authors.
Funding
Abstract
backgroundChronic liver diseases are a major global health burden, with cirrhosis and portal hypertension driving morbidity and mortality. Non-invasive assessment of portal hypertension is critical for risk stratification and clinical decision-making. Spleen stiffness measurement (SSM) has emerged as a novel elastography-based biomarker reflecting the hemodynamic consequences of portal hypertension. MAIN BODY: This review summarizes current evidence on SSM across major chronic liver disease etiologies, including viral hepatitis, metabolic-associated fatty liver disease, and autoimmune liver diseases. We outline the principles and technical evolution of SSM across elastography platforms, including transient elastography, shear-wave elastography, and magnetic resonance elastography. Emerging data indicate that SSM provides incremental value beyond established non-invasive markers such as liver stiffness measurement and platelet count, particularly in refining risk stratification for clinically significant portal hypertension and high-risk varices. SSM may reduce unnecessary endoscopic screening and improve patient selection for therapeutic interventions. This review is based on a structured literature search of PubMed and Web of Science.
conclusionsSSM is a promising non-invasive biomarker with increasing translational relevance in the management of chronic liver diseases. With further standardization and prospective validation, SSM has the potential to support precision risk stratification and guide individualized clinical decision-making.
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