In metabolic dysfunction-associated steatotic liver disease (MASLD), liver fibrosis is a key determinant of the long-term prognosis, including the risk of hepatocellular carcinoma and liver-related mortality.¹ A liver biopsy is the gold standard for diagnosing fibrosis, steatohepatitis, and liver inflammation in MASLD. Nevertheless, a liver biopsy has limitations, such as high cost, invasiveness, risks of bleeding or infection, variability among interpreters, and sampling errors.^2,3 As a result, non-invasive methods, such as serum biomarkers, transient elastography, shear wave elastography, and magnetic resonance elastography, are frequently used in clinical practice.^4-8

1. Serum Markers

Several non-invasive fibrosis evaluation studies have been validated using serum biomarkers, such as fibrosis-4 index (FIB-4) and the nonalcoholic fatty liver disease (NAFLD) fibrosis score (NFS) (Table 1). FIB-4 was initially proposed for patients with chronic hepatitis C and HIV co-infection⁹ and has been evaluated for its efficacy in diagnosing liver fibrosis in MASLD patients. In a Japanese study, FIB-4 and NFS were superior in diagnosing advanced fibrosis compared to other panels.¹⁰ Recent meta-analyses reported that FIB-4 had an area under the curve (AUC) of 0.76 for advanced fibrosis, with a sensitivity and specificity of 42% and 93%, respectively.^11,12 Age is a significant consideration when interpreting FIB-4 scores. The diagnostic ability of serum biomarkers is lower in patients younger than 35 years, and alternative non-invasive tests are recommended.¹³ A previous study suggested that the upper cutoff for advanced fibrosis in FIB-4 should be 2.67, while the age-adjusted lower cutoffs should be 1.30 and 2.0 for patients aged 35–64 years and 65 years or older, respectively.¹³

Table 1 . Meta-analysis of the diagnostic performance of serum markers for liver fibrosis in MASLD patients

NFS, which was developed based on a cohort of U.S. MASLD patients, has an AUC of 0.82–0.88 for diagnosing advanced fibrosis.¹⁴ The recommended cutoffs are <−1.455 and >0.676. A meta-analysis of 13 studies with 3,064 patients revealed an AUC of NFS for advanced fibrosis of 0.85, with a sensitivity and specificity of 90% and 60%, respectively, at the lower cutoff.^14-26 A higher cutoff (>0.676) had a sensitivity and specificity of 67% and 97%, respectively, for advanced fibrosis. Recent studies recommend adjusting the lower cutoff to 0.12 in patients aged 65 or older.^13,27

The enhanced liver fibrosis (ELF) score, using three matrix proteins, is used mainly in Europe and some institutions in Korea. The score showed good diagnostic performance for advanced fibrosis, with an AUC, sensitivity, and specificity of 0.90, 80%, and 90%, respectively.¹⁸

Through a global multicenter cohort study, the NIS4 algorithm, consisting of four biomarkers (microRNA-34a, alpha-2 macroglobulin, YKL-40, and glycated hemoglobin), was proposed as a blood test-based approach. The NIS4^® algorithm showed an AUC of 0.80 for identifying high-risk groups with a NAFLD activity score (NAS) of 4 or higher and significant liver fibrosis unaffected by gender, body mass index (BMI), or aspartate aminotransferase (AST)/alanine aminotransferase (ALT) levels.²⁸ Furthermore, the NIS2+™ algorithm, an optimized version of the NIS4 algorithm using only two variables, microRNA-34a and YKL-40, was introduced. NIS2+™ exhibited superior diagnostic performance for identifying high-risk patients (AUC=0.813) to the NIS4^® algorithm (AUC=0.792).²⁹ Based on a single-center Korean cohort, the nonalcoholic steatohepatitis (NASH)-PT scoring system was developed to diagnose high-risk metabolic dysfunction-associated steatohepatitis (MASH) patients.³⁰ The NASH-PT score includes factors such as PNPLA3 and TM6SF2 genotypes, the presence of diabetes, insulin resistance, AST levels, and high-sensitivity C-reactive protein. This score demonstrated a diagnostic AUC of 0.787 for distinguishing between MASLD and MASH at a cutoff value of 0.785. Furthermore, this scoring system was validated in a Chinese cohort of 276 patients, with an AUC of 0.80 at a cutoff value of −0.11.³¹ Recently, the gut microbiome and its metabolites have been proposed as biomarkers for diagnosing significant liver fibrosis in non-obese MASLD patients.³²

2. Vibration-Controlled Transient Elastography

Research on vibration-controlled transient elastography (VCTE) for diagnosing fibrosis in MASLD has revealed high sensitivity and specificity.^10,15,33 In meta-analyses, VCTE showed AUC values of 0.65–0.98 for advanced fibrosis, with cutoffs ranging from 6.6 to 10.4 kPa (Table 2). VCTE was also highly accurate in diagnosing cirrhosis, with AUC values of 0.94–0.97 and cutoffs ranging from 10.3 to 17 kPa.^15,34 On the other hand, in patients with abdominal obesity, the accuracy of TE decreases, and 5–20% of patients may require an XL probe for measurement because the standard M probe may be unsuitable.^35,36 A study of patients undergoing bariatric surgery, with a mean BMI of 42.3 kg/m², reported that VCTE had an AUC of 0.85 for advanced fibrosis, with a cutoff of 7.6 kPa.³⁷ In cases where the skin-to-liver capsule distance was ≥2.5 cm, the XL probe was used successfully in 96% of participants.³⁸ The use of XL probes and different cutoffs was also studied in Japan, where the cutoffs for the XL probe (8.2 kPa) differed from those for the M probe (10.8 kPa).³⁹ Furthermore, VCTE is less accurate in patients with elevated ALT levels (>100 IU/L) or significant steatosis, and caution should be taken when interpreting the results under such conditions.^40,41

Table 2 . Diagnostic performance of VCTE for liver fibrosis in MASLD patients

Recently, a global multicenter cohort study proposed the FAST score (e– 1.65 + 1.07 × In(LSM) + 2.66*10-8 × CAP³ – 63.3 × AST-1/1+e–1.65 + 1.07 × In(LSM) + 2·66*10-8 × CAP³ – 63.3 × AST-1), which incorporates the liver stiffness measurement (LSM), controlled attenuation parameter (CAP), and AST values.⁴² The FAST score was designed to identify high-risk patients with a NAS of 4 or higher and significant fibrosis in patients with MASH. At a cutoff value of 0.35, the FAST score showed positive and negative predictive values of 83% and 85%, respectively. The score also showed a high diagnostic ability, with a c-index of 0.85 in an external validation cohort.

The AGILE score, developed from seven global multicenter cohorts, was reported to have significantly higher positive predictive values for diagnosing advanced fibrosis or cirrhosis than FIB-4 or VCTE alone.⁴³ AGILE 3+ calculates the scores based on age, gender, AST/ALT ratio, platelet count, diabetes status, and VCTE results. AGILE 3+ showed an AUC of 0.86 for diagnosing advanced fibrosis, with a positive predictive value of 0.72 at lower and upper cutoffs of 0.451 and 0.679, respectively. For cirrhosis, AGILE 4 showed an AUC of 0.93, with a positive predictive value of 0.73 at cutoffs of 0.251 and 0.565, overcoming the limitations of the lower predictive values associated with FIB-4, NFS, and ELF.

VCTE also exhibited high diagnostic accuracy in patients with MASLD and type 2 diabetes mellitus. A recent meta-analysis involving 1,780 patients with MASLD and type 2 diabetes reported that when FIB-4 ≥1.3 or NFS ≥1.455, the VCTE (≥8 kPa) or AGILE 3+ score (≥0.45) could be used individually or sequentially to diagnose advanced fibrosis accurately.⁴⁴

3. Shear Wave Elastography

Shear wave elastography (SWE) performs similarly to VCTE in diagnosing significant fibrosis.^45,46 Point SWE and 2D-SWE, which provide simultaneous imaging, offer advantages in reducing the failure rates compared to TE. A study using point SWE reported an AUC of 0.8 or higher for diagnosing significant fibrosis.⁴⁷ A Korean cohort study reported that the AUC for advanced fibrosis using point SWE was 0.861, but the diagnostic performance decreased as the steatosis severity increased.⁷ Meta-analyses of 2D-SWE showed similar diagnostic accuracy to VCTE (Table 3).^48,49 SWE can also be influenced by factors, such as the fasting time, abdominal obesity, liver diseases with cholestasis, AST and ALT levels, and hepatic steatosis. Hence, caution is needed when interpreting the results. In obese patients, however, 2D-SWE allows for real-time adjustment of the measurement location, making it easier to perform compared to VCTE.⁵⁰

Table 3 . Meta-analysis of the diagnostic performance of VCTE, point SWE, 2D-SWE, and MRE for liver fibrosis in MASLD patients

Method	No. of patient	AUC (95% CI)	Cutoff Range	Sensitivity % (95% CI)	Specificity % (95% CI)
VCTE
F2	2,763	0.83 (0.80–0.87)	3.8–10.2	80.0 (76.0–83.0)	73.0 (68.0–77.0)
F3	4,219	0.85 (0.83–0.87)	6.8–12.9	80.0 (77.0–83.0)	77.0 (74.0–80.0)
F4	337	0.89 (0.84–0.93)	6.9–19.4	76.0 (70.0–82.0)	88.0 (85.0–91.0)
Point SWE
F2	805	0.86 (0.78–0.90)	1.18–1.81	69.0 (59.0–77.0)	85.0 (80.0–88.0)
F3	1,209	0.89 (0.83–0.95)	1.34–4.21	80.0 (70.0–88.0)	86.0 (82.0–92.0)
F4	759	0.90 (0.82–0.95)	1.36–2.54	76.0 (59.0–87.0)	88.0 (82.0–92.0)
2D-SWE
F2	488	0.75 (0.58–0.87)	8.3–11.6	71.0 (56.0–83.0)	67.0 (43.0–84.0)
F3	488	0.72 (0.60–0.84)	9.3–13.1	72.0 (65.0–78.0)	72.0 (52.0–86.0)
F4	372	0.88 (0.81–0.91)	14.4–15.7	78.0 (50.0–93.0)	84.0 (74.0–90)
MRE
F2	209	0.91 (0.80–0.97)	2.86–4.14	78.0 (67.0–85.0)	89.0 (83.0–94.0)
F3	214	0.92 (0.88–0.95)	2.99–4.8	83.0 (77.0–88.0)	89.0 (86.0–92.0)
F4	41	0.90 (0.81–0.95)	3.35–6.7	81.0 (66.0–90.0)	90.0 (85.0–94.0)

AUC, area under the curve; CI, confidence interval; SWE, shear wave elastography; MRE, magnetic resonance elastography.

4. Magnetic Resonance Elastography

Magnetic resonance elastography (MRE) offers excellent diagnostic accuracy for fibrosis and can assess the entire liver without being affected by obesity.^51-53 MRE outperforms VCTE in diagnosing liver fibrosis, with AUC values of 0.84–0.93.10,54,55 Failures are rare (<5%) compared to VCTE.^49,56-58 In a meta-analysis involving data from eight international cohorts, MRE had an AUC of 0.92 for diagnosing significant fibrosis, with a cutoff of 3.14 kPa.⁴⁹ MRE is less dependent on operator skill and is unaffected by obesity or iron deposition.^59,60 On the other hand, using MRE universally in all medical institutions is difficult because of the high cost and limited accessibility. In addition, signal strength measurements can be challenging in cases of iron deposition.⁶¹ In addition to liver fibrosis, the MRE results may also be affected by other infiltrative conditions such as severe steatosis, liver congestion, and acute inflammation.⁶²

The MAST score (−12.17+7.07 log MRE+0.037 PDFF+3.55 log AST), based on the MRI-PDFF and MRE results, was recently proposed through a U.S. cohort study.⁶³ The score showed an AUC of 0.929 for diagnosing high-risk MASH patients with a NAS of 4 or higher and significant fibrosis, with a cutoff value of 0.165, outperforming the diagnostic abilities of FIB-4 (AUC 0.711), NFS (AUC 0.689), and the FAST score (AUC 0.868).

A recent multicenter study conducted in the U.S. and Japan compared the diagnostic ability of the MEFIB index (MRE ≥3.3 kPa+FIB-4 ≥1.6)⁶⁴ (MRE ≥3.3 kPa+FIB-4 ≥1.6) with the FAST score⁴² for detecting significant fibrosis. In the U.S. cohort, the diagnostic AUC for the MEFIB index and the FAST score were 0.86 and 0.757, respectively, while in the Japanese cohort, the corresponding AUCs were 0.899 and 0.724, respectively, showing that the MEFIB index had significantly higher diagnostic accuracy.⁶⁵ Although MRE can also be affected by factors, such as fasting time, abdominal obesity, cholestasis, AST/ALT levels, and hepatic steatosis, it was reported that in patients with severe obesity, MRE was less affected by the subcutaneous fat thickness compared to transient elastography, resulting in a higher success rate.⁶⁶

Non-invasive diagnostic tools for liver fibrosis in patients with MASLD have advanced significantly in recent years. Methods, such as serum biomarkers (e.g., FIB-4, NFS), VCTE, SWE, and MRE, have shown strong diagnostic performance for detecting advanced fibrosis. Although liver biopsy remains the gold standard, these non-invasive approaches reduce the need for invasive procedures and allow for more accessible, cost-effective, and safer MASLD patient management. Further research into refining these tools and integrating them with emerging algorithms, such as the NIS4 and AGILE scores, will enhance the identification of MASH-at-risk patients for liver-related complications, improving the prognosis and clinical outcomes. Despite their progress, challenges remain, particularly in patients with obesity or elevated ALT levels, where the diagnostic accuracy may be compromised. Therefore, continued efforts to optimize these methods and expand their accessibility are essential to improve MASLD management and patient care.

None.

None.