Assessment of Non-Invasive Tests for MASLD, MASH and At-Risk MASH in a Multicentre Prospective Real-World Study

Why clinicians should know about it

• Picked for Biochemistry (medical) (paper of the day, 30 October 2026): Prospective validation of noninvasive MASLD biomarkers against biopsy

Abstract

BACKGROUND AND AIMS: Accurate non-invasive identification of metabolic dysfunction-associated steatohepatitis (MASH) and at-risk MASH remains a major unmet need in MASLD. We evaluated the diagnostic performance and optimal cutoffs of commonly used non-invasive tests (NITs) in a real-world setting. METHODS: In this multicentre prospective study, 328 cases from 226 participants underwent contemporaneous liver biopsy, MRI-PDFF, FibroScan and biochemical assessment, and were classified into MASL, MASH and at-risk MASH based on histopathology. Diagnostic performance was evaluated using area under the receiver operating characteristic curve (AUC), sensitivity and specificity. RESULTS: CAP at 248 dB/m detected histological steatosis with AUC of 0.80 (sensitivity: 94.7%, specificity: 30.4%); raising the threshold to 304 dB/m increased specificity to 91.3% (sensitivity: 60.3%). The two-step CAP-ALT algorithm achieved a more balanced sensitivity and specificity (78.3% and 82.6%, respectively; AUC: 0.80). MRI-PDFF quantified steatosis accurately (AUC: 0.92; cutoff: 7.78%; sensitivity: 77.1%; specificity: 100%) and differentiated grades, with diagnostic discordance versus histopathology mainly in mild disease. FAST score (AUC: 0.85; cutoff: 0.29; sensitivity: 70.0%; specificity: 83.3%) and MRI-PDFF (AUC: 0.82; cutoff: 17.78%; sensitivity: 56.2%; specificity: 92.6%) identified MASH, while LSM (AUC: 0.92; cutoff: 8.95 kPa; sensitivity: 86.5%; specificity: 84.1%) detected at-risk MASH. CONCLUSIONS: CAP provides an accessible approach for steatosis detection, whereas MRI-PDFF offers quantitative assessment of liver fat and may provide additional information relevant to MASH. FAST may serve as an initial tool for MASH risk stratification, while LSM provides effective identification of at-risk MASH. These findings support a targeted, stepwise non-invasive approach to MASLD assessment and follow-up.

Abstract as published, via PubMed.