Nonalcoholic fatty liver disease (NAFLD) is the most common chronic liver disease and recognized as a major cause of end-stage liver disease. Although hepatic fibrosis is the most important predictor of mortality in NAFLD, early diagnosis of high-risk nonalcoholic steatohepatitis (NASH) is also crucial to identify individuals who may benefit from therapeutic interventions.¹ A recent consensus endorsed a change in nomenclature from NAFLD to metabolic dysfunction-associated steatotic liver disease (MASLD) and NASH to metabolic dysfunction-associated steatohepatitis (MASH).^2-5

Although liver biopsy is the gold standard for assessment of hepatic steatosis, fibrosis, and inflammation, its invasive nature is accompanied by discomfort and complications. Ultrasound (US)-based elastography, such as shear wave elastography (SWE) and strain elastography, has emerged as a noninvasive means for assessing the severity of MASLD.⁶ SWE measures the propagation velocity of shear waves generated by mechanical vibration as in transient elastography (TE). Strain elastography visualizes the relative deformation between the tissue of interest and adjacent tissue by US B-mode, as in real-time tissue elastography (RTE).⁷ The diagnostic performance of TE for hepatic fibrosis by liver stiffness measurement (LSM) and for steatosis by controlled attenuation parameter (CAP), is well-established.⁸ Meanwhile, the recently proposed echo attenuation measurement-based attenuation coefficient (ATT) and RTE image analysis algorithm-derived liver fibrosis index (LF index) have shown promising results in diagnosing hepatic steatosis and fibrosis, respectively.^9,10

However, SWE is affected by confounding factors including hepatic congestion, inflammation, and jaundice,^11,12 where the absence of imaging function in TE is especially a pitfall. Moreover, body movements may also compromise the reliability of SWE, though it may be overcome by shear wave measurement technique.¹³ Strain elastography suffers from inter- and intra-operator variability,¹⁴ although the reproducibility of RTE is enhanced by applying minimal pressure during the examination.¹⁵

Combi-elastography is a novel approach that utilizes both shear wave measurement and RTE measurement simultaneously using a single probe. It overcomes the drawbacks of US-based methods used in isolation,^16-18 and acquisition of features from both types of elastography allows greater histological insight and analysis. Indeed, a recent study using combi-elastography formulated the fibrosis index (F index) for determining fibrosis severity, and the activity index (A index) for assessing hepatic inflammation.¹⁹

The aim of this study was to evaluate the performance of combi-elastography in the diagnosis of hepatic steatosis, significant fibrosis, and high-risk MASH among participants with MASLD.

1. Patients

This study analyzed data from the prospective NAFLD cohort comprising outpatient participants who underwent liver biopsy, combi-elastography (Fujifilm Healthcare Corporation, Tokyo, Japan), and vibration-controlled TE (VCTE) (FibroScan; Echosens, Paris, France) at Seoul Metropolitan Government Seoul National University Boramae Medical Center (NCT 02206841).²⁰ The inclusion criteria for this cohort were as follows: (1) ≥18 years old; (2) bright liver echogenicity on ultrasonography (increased liver/kidney echogenicity and posterior attenuation); and/or (3) unexplained elevated alanine aminotransferase levels above the reference range within the past 6 months. Primary exclusion criteria were as follows: age <18 years; consumption of more than 210 and 140 g per week of alcohol in men and women, respectively; a positive hepatitis B surface antigen or anti-hepatitis C virus antibody test; other competing chronic liver disease etiologies; and diagnosis of malignancy within the last year. The eligible study participants who had at least 2 of the following risk factors underwent liver biopsy: type 2 diabetes or insulin resistance, hypertension, central obesity (waist circumference ≥90 cm for men or ≥80 cm for women), high triglycerides level (≥150 mg/dL), low high-density lipoprotein cholesterol level (<40 mg/dL for men or <50 mg/dL for women), and clinically suspected NASH or fibrosis.

Biopsy-proven MASLD was defined as histological hepatic steatosis >5% and presented with any of the cardiometabolic risk factors (overweight or obesity, dysglycemia or type 2 diabetes, plasma triglyceride, high-density lipoprotein cholesterol, and blood pressure). High-risk MASH was defined as histologically confirmed MASH with NAFLD activity score (NAS) ≥4 and fibrosis stage ≥2.²¹

This study was conducted in accordance with the Declaration of Helsinki and the Declaration of Istanbul for the participation of human subjects in research and was approved by the Institutional Review Board of Seoul Metropolitan Government Seoul National University Boramae Medical Center (IRB number: 16-2013-45). All study participants provided written informed consent for the research.

2. Clinical and laboratory assessments

Collected anthropometric data included body weight and height to calculate body mass index (BMI). After an overnight fast, blood samples were obtained to measure albumin, total bilirubin, aspartate aminotransferase (AST), alanine aminotransferase, gamma-glutamyl transferase (GGT), total cholesterol, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, triglyceride, fasting plasma glucose, glycated hemoglobin, and insulin. Platelet counts were measured using whole blood. Hypertension was defined as systolic blood pressure ≥140 mm Hg, diastolic blood pressure ≥90 mm Hg and/or the current use of anti-hypertensive medication(s). Diabetes was defined as fasting plasma glucose levels of ≥126 mg/dL, glycated hemoglobin levels of ≥6.5%, and/or treatment with anti-diabetic medication(s) at the time of the survey.²² Insulin resistance was determined using the homeostasis model assessment of insulin resistance (HOMA-IR) calculated by insulin (mU/L)×glucose level (mg/dL)/405.²³

3. Histological assessment

Percutaneous US-guided liver biopsy was performed according to local standard procedures. Liver biopsy specimens were fixed in formalin and embedded in paraffin, then stained with hematoxylin and eosin for routine histologic evaluations, and Masson’s trichrome stain was used to evaluate fibrosis stage. Liver specimens were excluded from analysis if specimens were shorter than 20 mm or contained fewer than eight portal tracts.²⁴ A single experienced histopathologist, blind to clinical data, analyzed slides and scored the histological findings based on the NASH-Clinical Research Network histological scoring system: steatosis (0–3), ballooning (0–2), lobular inflammation (0–3), and fibrosis (0–4).²⁵

4. Combi-elastography

All combi-elastography examinations were conducted by one board-certificated radiologist blind to clinical data using a US scanner (ARIETTA 850; Fujifilm Healthcare Corporation) with a C252 Convex probe (1-6 MHz; Fujifilm Healthcare Corporation) within 1 month from liver biopsy. All participants were asked to fast for at least 6 hours prior to the examination. To obtain the optimal intercostal acoustic window, the US examination was performed in the supine position with the right arm in maximal abduction and with participants instructed to hold their breath.²⁶

After B-mode examination of liver parenchyma, combi-elastography was conducted on the right lobe of the liver through the intercostal space, devoid of large blood vessels and surface nodularity (Fig. 1). Optimal positioning was performed by visualizing both the B-mode and static image superimposed on B-mode in real-time. Observations were conducted without further manual pressure on the probe to minimize variability.¹⁵ Data acquired from the region of interest included the propagation velocity of the shear wave (Vs) and Young’s shear modulus (E) for evaluating liver stiffness, and ATT for evaluating hepatic steatosis. Measurements were conducted 10 times and the median value of reliable measurements was included for analysis. Only subjects with the reliability index, namely the percentage of the net amount of effective shear wave velocity, of ≥50% were recruited as eligible study participants.¹³ Detailed examination processes and principles are explained in Supplemental Material.

Figure 1. Representative two measurement screens performed using combi-elastography. The instrument confers data of the attenuation coefficient (ATT) measured in B-mode ultrasound and liver stiffness measurements (Vs and E) using shear wave measurement (SWM). Liver fibrosis index is further calculated using a multiple regression from imaging features. A color-coded map (right) is superimposed on the B-mode image (left). (A) Liver elastogram of a 49-year-old male subject from the control group demonstrates “soft” liver texture indicated by homogenous yellowish green color. (B) Liver elastogram of a 69-year-old female subject from the high-risk metabolic dysfunction-associated steatohepatitis group demonstrates “hard” liver texture indicated by overall dark blue color. The median value of the 10 measurements of each feature is presented in the box underneath the pictures.

The LF index was calculated from features derived from the optimal stable RTE frame. The multiple regression-derived F and A indices for evaluating hepatic fibrosis and inflammation, respectively, were determined using parameters from both shear wave measurement and RTE. Detailed calculations are presented in Supplementary Material.

5. Vibration-controlled transient elastography

Participants underwent VCTE within 1 month from liver biopsy to measure both liver steatosis (CAP) and stiffness (LSM). VCTE was conducted using a standard M probe or an XL probe for measurement failures with an M probe. The M probe and XL probe have different central US frequencies (3.5 MHz vs 2.5 MHz, respectively) and measurement depths (2.5–6.5 cm vs 3.5–7.5 cm, respectively). Participants were asked to fast for at least 4 hours before the examination, and VCTE was performed with the participant in the supine position with the right arm in maximal abduction. The operators had certification for VCTE and experience with more than 1,000 cases, and they were blinded to clinical history and liver biopsy results. Only examinations with at least 10 valid individual measurements were considered for analysis. When the interquartile range to median ratio of VCTE LSMs was >0.3, measurements were considered unreliable and excluded from analysis.²⁷ The median value of the valid measurements was adopted and final CAP and LSM values are expressed in dB/m and kPa, respectively.

6. Noninvasive surrogate markers for LF and high-risk MASH

To compare elastography-derived indices with established, noninvasive tests for evaluating hepatic fibrosis, the severity of hepatic fibrosis was assessed using three fibrosis prediction models. The AST-to-platelet ratio index, fibrosis-4 score, and NAFLD fibrosis score were computed using the available parameters.^28-30

We adopted the FibroScan-AST (FAST) score to assess the presence of high-risk MASH from parameters of VCTE and serology. The FAST score was calculated according to the following formula:³¹

7. Statistical analysis

Continuous variables are expressed as either median (interquartile range) or mean±standard deviation. Categorical variables are expressed as frequency (percentage). Categorical variables between groups were compared using the Pearson chi-square test. Relationship between combi-elastography parameters and liver histology was assessed by the Spearman correlation. Continuous variables among groups were compared using either one-way analysis of variance or the Kruskal-Wallis test. p-values of <0.05 were considered statistically significant.

Receiver-operating characteristic curves were plotted to assess the overall accuracy with 95% confidence intervals (CIs). Cutoff values were identified to maximize the Youden index. Statistical significance of the differences between the areas under receiver-operating characteristics (AUROCs) was examined using the DeLong test. All statistical tests were performed using IBM SPSS version 26.0 (IBM Corp., Armonk, NY, USA), MedCalc software version 19.5.6 (MedCalc, Ostend, Belgium), and GraphPad Prism version 9.4.1 (GraphPad Software, San Diego, CA, USA).

1. Demographic, laboratory, radiologic, and histologic features

A total of 212 participants with a median age of 56 years (interquartile range, 45 to 64 years) were enrolled and their data were analyzed. Among them, 35 (16.5%), 93 (43.9%), and 84 (39.6%) had no-MASLD, MASLD without MASH, and MASH, respectively (Table 1). Significant differences were observed in all combi-elastography parameters among groups, and VCTE measurements of CAP and LSM, as well as FAST scores, also significantly differed by group (all p<0.05), with the no-MASLD group having the lowest values.

Table 1

Baseline Characteristics.

Characteristic	No MASLD (n=35)	MASLD without MASH (n=93)	MASH (n=84)	p-value
Male sex	15 (42.9)	58 (62.4)	27 (32.1)	0.001
Age, yr	62 (56–68)	52 (43–60)	59 (45–66)	0.001
BMI, kg/m2	24.5 (22.8–26.0)	27.4 (24.9–29.6)	27.5 (25.4–29.7)	<0.001
Diabetes	9 (25.7)	32 (34.4)	39 (46.4)	0.071
Hypertension	15 (42.9)	35 (37.6)	36 (42.9)	0.744
Platelet, ×109/L	229±65	244±59	216±74	0.057
Total bilirubin, mg/dL	0.8 (0.6–1.0)	0.7 (0.6–0.9)	0.7 (0.5–0.9)	0.138
Albumin, g/dL	4.1 (3.9–4.2)	4.2 (4.0–4.4)	4.1 (3.9–4.3)	0.025
AST, U/L	25 (22–33)	30 (24–49)	48 (38–75)	<0.001
ALT, U/L	22 (14–35)	39 (25–64)	60 (34–93)	<0.001
GGT, U/L	39 (13–84)	39 (23–60)	56 (36–95)	0.001
Total cholesterol, mg/dL	173±46	187±41	182±42	0.217
Triglycerides, mg/dL	104 (75–159)	139 (99–194)	139 (107–189)	0.013
HDL cholesterol, mg/dL	50 (41–64)	45 (37–52)	46 (40–55)	0.077
LDL cholesterol, mg/dL	97±43	110±34	102±35	0.148
FPG, mg/dL	102 (94–109)	108 (97–122)	118 (100–134)	0.001
HbA1c, %	5.8 (5.5–6.2)	5.9 (5.5–6.4)	6.3 (5.9–7.2)	<0.001
HOMA-IR	2.18 (1.77–3.32)	3.40 (2.19–5.56)	4.73 (3.41–6.35)	<0.001
APRI	0.31 (0.21–0.39)	0.34 (0.25–0.53)	0.65 (0.45–0.88)	<0.001
FIB-4	1.50 (1.15–2.07)	1.09 (0.73–1.57)	1.78 (1.19–2.84)	<0.001
NFS	–2.64±1.62	–3.46±2.12	–2.75±2.46	0.049
VCTE
CAP, dB/m	231±40	299±53	293±55	<0.001
LSM, kPa	4.3 (3.6–6.5)	5.4 (4.3–7.4)	7.9 (5.5–11.9)	<0.001
FAST	0.09 (0.05–0.21)	0.26 (0.12–0.47)	0.50 (0.34–0.70)	<0.001
IQR/M, %	0.1 (0.07–0.14)	0.11 (0.08–0.14)	0.11 (0.07–0.15)	0.437
Combi-elastography
ATT, dB/cm/MHz	0.57±0.12	0.69±0.13	0.67±0.11	<0.001
A index	0.99 (0.90–1.10)	0.97 (0.86–1.07)	1.11 (0.93–1.23)	<0.001
F index	1.28 (0.87–1.40)	1.11 (0.96–1.32)	1.39 (1.08–1.67)	<0.001
LF index	2.51±0.87	2.62±0.80	3.02±0.86	0.001
E, kPa	5.80 (4.55–7.21)	5.41 (4.13–6.39)	6.66 (4.87–8.18)	0.001
Steatosis				<0.001
0	35 (100.0)	0	0
1	0	41 (44.1)	17 (20.2)
2	0	44 (47.3)	28 (33.3)
3	0	8 (8.6)	39 (46.4)
Lobular inflammation				<0.001
0	18 (51.4)	23 (24.7)	1 (1.2)
1	15 (42.9)	67 (72.0)	40 (47.6)
2	2 (5.7)	3 (3.2)	42 (50.0)
3	0	0	1 (1.2)
Ballooning				<0.001
0	31 (88.6)	68 (73.1)	4 (4.8)
1	4 (11.4)	25 (26.9)	65 (77.4)
2	0	0	15 (17.9)
Fibrosis				<0.001
0	14 (40.0)	16 (17.2)	1 (1.2)
1	15 (42.9)	68 (73.1)	20 (23.8)
2	2 (5.7)	9 (9.7)	39 (46.4)
3	2 (5.7)	0	10 (11.9)
4	2 (5.7)	0	14 (16.7)

Data are presented as number (%), median (IQR), or mean±SD. The continuous variables are expressed as the mean±SD (normally distributed) or median (IQR) (non-normally distributed), and the differences between groups were evaluated by one-way analysis of variance or the Kruskal-Wallis test, respectively. Categorical data are presented as the number (%), and the differences between groups were determined by the chi-square test..

MASLD, metabolic dysfunction-associated steatotic liver disease; MASH, metabolic dysfunction-associated steatohepatitis; BMI, body mass index; AST, aspartate aminotransferase; ALT, alanine aminotransferase; GGT, gamma-glutamyl transferase; HDL, high-density lipoprotein; LDL, low-density lipoprotein; FPG, fasting plasma glucose; HbA1c, glycated hemoglobin; HOMA-IR, homeostasis model assessment of insulin resistance; APRI, AST-to-platelet ratio index; FIB-4, fibrosis-4; NFS, NAFLD fibrosis score; VCTE, vibration-controlled transient elastography; CAP, controlled attenuation parameter; LSM, liver stiffness measurement; FAST, FibroScan-AST; IQR/M, interquartile range to median ratio; ATT, attenuation coefficient; A index, activity index; F index, fibrosis index; LF index, liver fibrosis index; E, shear modulus..

Mean ATT values for histological steatosis graded as S0, S1, S2, and S3 were 0.57±0.12, 0.66±0.13, 0.68±0.11, and 0.71±0.12 dB/cm/MHz, respectively; thus, ATT increased in a steatosis grade-dependent manner (Spearman ρ=0.325, p<0.001) (Fig. 2A). Likewise, the median values of the F index for histological fibrosis staged as F0, F1, F2, F3, and F4 were 1.09 (0.87 to 1.34), 1.17 (0.96 to 1.38), 1.31 (1.06 to 1.58), 1.30 (1.10 to 1.53), and 2.34 (2.00 to 2.71), respectively. The F index significantly correlated with fibrosis stage (Spearman ρ=0.371, p<0.001) (Fig. 2B). The A index also significantly correlated with liver histology by groups (Spearman ρ=0.270, p<0.001) (Fig. 2C) and histopathology (Supplementary Table 1). Median A indices were as follows: no-MASLD, 0.99 (0.90 to 1.10); MASLD without MASH, 0.97 (0.86 to 1.07); low-risk MASH, 1.07 (0.92 to 1.20); and high-risk MASH, 1.13 (0.96 to 1.32).

Figure 2. Correlation between ATT and steatosis grade (A), F index and fibrosis stage (B), and patient group and A index (C). The bars represent the median and interquartile ranges of each elastography parameter. ATT, attenuation coefficient; F index, fibrosis index; A index, activity index; MASLD, metabolic dysfunction-associated steatotic liver disease; MASH, metabolic dysfunction-associated steatohepatitis.

2. Diagnostic performance of CAP and ATT for hepatic steatosis

The AUROCs of CAP and ATT for the diagnosis of hepatic steatosis were 0.85 (95% CI, 0.80 to 0.90) and 0.74 (95% CI, 0.68 to 0.80), respectively (Table 2). Patient- and combi-elastography-related factors were analyzed using logistic regression to identify parameters that were associated with MASLD (Supplementary Table 2). In a multiple logistic regression following a stepwise selection procedure among significant variables in univariate analysis, the odds of a patient having MASLD significantly increased with higher ATT values (odds ratio, 305.12; p=0.007) along with a higher BMI and HOMA-IR scores. After adjustment for BMI and HOMA-IR, ATT showed good diagnostic ability for MASLD (AUROC, 0.85; 95% CI, 0.79 to 0.89); the performance of adjusted ATT did not significantly differ from that of CAP (p=0.925) (Table 3, Fig. 3A).

Figure 3. Comparison of the receiver-operating characteristic curves of combi-elastography parameters and liver histology for identifying hepatic steatosis, fibrosis, and high-risk metabolic dysfunction-associated steatohepatitis (MASH). The comparison of the diagnostic performance of the controlled attenuation parameter (CAP) and attenuation coefficient (A), liver stiffness measurement (LSM) and fibrosis (F) index (B), and FibroScan-aspartate aminotransferase (FAST) index and activity (A) index (C) for identifying hepatic steatosis, significant fibrosis, and high-risk MASH, respectively. *Adjusted for body mass index and homeostasis model assessment of insulin resistance (HOMA-IR); ^†Adjusted for sex, gamma-glutamyl transferase (GGT), low-density lipoprotein cholesterol, and HOMA-IR; ^‡Adjusted for GGT.

Table 2

Performance in the Diagnosis of MASLD, Significant Fibrosis, and High-Risk MASH.

Variable	CAP and ATT for MASLD			LSM, F index, LF index, and E for significant fibrosis					FAST score and A index for high-risk MASH among patients with MASLD
	CAP	ATT		LSM	F index	LF index	E		FAST score	A index
AUROC (95% CI)	0.85 (0.80–0.90)	0.74 (0.68–0.80)		0.80 (0.74–0.85)	0.69 (0.63–0.76)	0.63 (0.56–0.69)	0.67 (0.60–0.73)		0.74 (0.67–0.80)	0.69 (0.62–0.76)
Prevalence (%)	177 (83.5)	177 (83.5)		78 (36.8)	78 (36.8)	78 (36.8)	78 (36.8)		52 (29.1)	52 (29.1)
Optimal cutoff
Cutoff	>270	>0.57		>6.0	>1.40	>2.86	>6.88		>0.546	>1.09
Se (95% CI)	71.2 (63.9–77.7)	80.8 (74.2–86.3)		79.5 (68.8–87.8)	51.3 (39.7–62.8)	59.0 (47.3–70.0)	48.7 (37.2–60.3)		53.9 (39.5–67.8)	59.6 (45.1–73.0)
Sp (95% CI)	88.6 (73.3–96.8)	60.0 (42.1–76.1)		68.7 (60.1–76.4)	80.6 (72.9–86.9)	61.2 (52.4–69.5)	82.1 (74.5–88.2)		85.0 (77.6–90.7)	73.2 (64.6–80.7)
PPV (95% CI)	96.9 (92.6–98.8)	91.1 (87.1–93.9)		59.6 (52.9–66.0)	60.6 (50.6–69.8)	46.9 (40.0–54.0)	61.3 (50.8–70.8)		59.6 (47.6–70.5)	47.7 (38.8–56.8)
NPV (95% CI)	37.8 (31.9–44.1)	38.2 (29.2–48.1)		85.2 (78.5–90.0)	74.0 (69.0–78.4)	71.9 (65.5–77.5)	73.3 (68.6–77.6)		81.8 (76.9–85.9)	81.6 (75.8–86.2)
Se ≥90%
Cutoff	>237	>0.52		>4.5	>0.87	>1.92	>4.11		>0.222	>0.84
Se (95% CI)	90.4 (85.1–94.3)	91.0 (85.7–94.7)		92.3 (84.0–97.1)	91.0 (82.4–96.3)	91.0 (82.4–96.3)	91.0 (82.4–96.3)		90.4 (79.0–96.8)	90.4 (79.0–96.8)
Sp (95% CI)	51.4 (34.0–68.6)	42.9 (26.3–60.6)		42.5 (34.0–51.4)	20.2 (13.7–27.9)	22.4 (15.6–30.4)	22.4 (15.6–30.4)		39.4 (30.8–48.4)	18.9 (12.5–26.8)
PPV (95% CI)	90.4 (87.0–93.0)	89.0 (85.8–91.5)		48.3 (44.4–52.3)	39.9 (37.3–42.6)	40.6 (37.8–43.4)	40.6 (37.8–43.4)		37.9 (34.1–41.9)	31.3 (28.8–34.0)
NPV (95% CI)	51.4 (37.8–64.8)	48.4 (33.9–63.2)		90.5 (81.1–95.5)	79.4 (63.8–89.4)	81.1 (66.4–90.3)	81.1 (66.4–90.3)		90.9 (80.9–95.9)	82.8 (65.9–92.2)
Sp ≥90%
Cutoff	>275	>0.70		>8.8	>1.53	>3.73	>7.52		>0.595	>1.21
Se (95% CI)	67.2 (59.8–74.1)	40.7 (33.4–48.3)		46.2 (34.8–57.8)	38.5 (27.7–50.2)	20.5 (12.2–31.2)	38.5 (27.7–50.2)		46.2 (32.2–60.5)	32.7 (20.3–47.1)
Sp (95% CI)	91.4 (76.9–98.2)	91.4 (76.9–98.2)		90.3 (84.0–94.7)	91.0 (84.9–95.3)	90.3 (84.0–94.7)	90.3 (84.0–94.7)		90.6 (84.1–95.0)	90.6 (84.1–95.0)
PPV (95% CI)	97.5 (93.0–99.2)	96.0 (88.9–98.6)		73.5 (61.0–83.0)	71.4 (57.6–82.1)	55.2 (38.5–70.8)	69.8 (56.2–80.6)		66.7 (52.0–78.7)	58.6 (42.2–73.4)
NPV (95% CI)	35.6 (30.4–41.1)	23.4 (20.6–26.3)		74.2 (70.0–78.1)	71.8 (67.9–75.3)	66.1 (63.3–68.9)	71.6 (67.7–75.2)		80.4 (76.0–84.2)	76.7 (72.9–80.0)

MASLD, metabolic dysfunction-associated steatotic liver disease; MASH, metabolic dysfunction-associated steatohepatitis; CAP, controlled attenuation parameter; ATT, attenuation coefficient; LSM, liver stiffness measurement; F index, fibrosis index; LF index, liver fibrosis index; E, shear modulus; FAST, FibroScan-aspartate aminotransferase; A index, activity index; AUROC, area under the receiver-operating characteristic curve; CI, confidence interval; Se, sensitivity; Sp, specificity; PPV, positive predictive ratio; NPV, negative predictive ratio..

Table 3

AUROCs for the Diagnosis of MASLD, Significant Fibrosis, and High-Risk MASH.

	AUROC (95% CI)	Cutoff	Se, %	Sp, %	DeLong
Diagnosis of MASLD
CAP	0.85 (0.80–0.90)	>270	71.2	88.6	(Reference)
ATT*	0.85 (0.79–0.89)		81.5	77.1	0.925
Diagnosis of significant fibrosis
LSM	0.80 (0.74–0.85)	>6.0	79.5	68.7	(Reference)
F index†	0.77 (0.71–0.83)		76.3	66.7	0.573
Diagnosis of high-risk MASH among patients with MASLD
FAST score	0.74 (0.67–0.80)	>0.546	53.9	85.0	(Reference)
A index‡	0.72 (0.65–0.79)		51.0	86.3	0.792

AUROC, area under the receiver-operating characteristic curve; MASLD, metabolic dysfunction-associated steatotic liver disease; MASH, metabolic dysfunction-associated steatohepatitis; CI, confidence interval; Se, sensitivity; Sp, specificity; CAP, controlled attenuation parameter; ATT, attenuation coefficient; LSM, liver stiffness measurement; F index, fibrosis index; FAST, FibroScan-aspartate aminotransferase; A index, activity index..

*Adjusted for body mass index, homeostasis model assessment of insulin resistance (HOMA-IR); ^†Adjusted for sex, gamma-glutamyl transferase (GGT), low-density lipoprotein cholesterol, and HOMA-IR; ^‡Adjusted for GGT..

3. Diagnostic performance of LSM, the F index, LF index, and E for significant fibrosis

Among the four measurements for significant fibrosis (≥F2), LSM from VCTE showed the best diagnostic capacity with an AUROC of 0.80 (95% CI, 0.74 to 0.85), followed by indices of combi-elastography including the F index (AUROC, 0.69; 95% CI, 0.63 to 0.76), E (AUROC, 0.67; 95% CI, 0.60 to 0.73), and the LF index (AUROC, 0.63; 95% CI, 0.56 to 0.69) (Table 2). Variables associated with significant fibrosis included being an older male, higher serum GGT and glycated hemoglobin level, HOMA-IR scores, and lower total cholesterol and low-density lipoprotein cholesterol levels, along with higher scores in combi-elastography measures including the F index, LF index, and E (Supplementary Table 3). In a stepwise multinomial logistic regression of the above variables, the odds of a patient having significant fibrosis significantly increased with higher F index scores (odds ratio, 5.92; 95% CI, 2.41 to 14.55; p<0.001). Other variables associated with increased odds of significant fibrosis included male sex, higher serum GGT levels, higher HOMA-IR scores, and lower low-density lipoprotein cholesterol levels. The diagnostic performance of the F index adjusted for the above variables increased to 0.77 (95% CI, 0.71 to 0.83); the difference in diagnostic performance between LSM from VCTE and the adjusted F index from combi-elastography for significant fibrosis was not significant (p=0.573) (Table 3, Fig. 3B). In a sensitivity analysis consisting of obese patients of BMI >27 kg/m², the diagnostic performance of LSM decreased to 0.78 (0.69 to 0.86) while the adjusted F index increased to 0.80 (0.71 to 0.87), though the difference was not significant (p=0.687) (Supplementary Table 4).

Among serology-based noninvasive tests for diagnosing significant fibrosis, AST-to-platelet ratio index and fibrosis-4 performed best, with AUROCs of 0.72 (95% CI, 0.66 to 0.78) and 0.71 (95% CI, 0.64 to 0.77), respectively (Supplementary Table 5). The diagnostic performance of the adjusted F index outperformed NAFLD fibrosis score (p<0.05), and was comparable to AST-to-platelet ratio index and fibrosis-4 (p>0.05) (Supplementary Table 6).

Meanwhile, the cohort was categorized according to histological steatosis severity to assess its impact on the performance of the F index. Regardless of steatosis, the F index for significant fibrosis exhibited a consistent performance with no significant difference between groups (all p>0.05); S0 (AUROC, 0.82; 95% CI, 0.65 to 0.93), S1 (AUROC, 0.76; 95% CI, 0.63 to 0.86), S2 (AUROC, 0.62; 95% CI, 0.50 to 0.73), and S3 (AUROC, 0.67; 95% CI, 0.52 to 0.80) (Supplementary Table 7).

4. Diagnostic performance of the FAST score and A index for high-risk MASH among participants with MASLD

The FAST score and A index diagnosed high-risk MASH with an AUROC of 0.74 (95% CI, 0.67 to 0.80) and 0.69 (95% CI, 0.62 to 0.76), respectively (Table 2). In a stepwise, multivariate logistic regression adjusted for significant variables in univariate analysis, increased odds of a patient having high-risk MASH were significantly associated with higher GGT and A index scores (Supplementary Table 8). After adjustment for GGT concentration, the AUROC of the A index increased but remained comparable to the FAST score (0.72; 95% CI, 0.65 to 0.79; p=0.792) (Table 3, Fig. 3C).

In this study, we demonstrated that combi-elastography-derived indices perform equivalently to well-established VCTE-based parameters for evaluating liver histology. Specifically, once adjusted for covariates of combi-elastography measures, ATT and the F index, identified hepatic steatosis (≥S1) and significant fibrosis (≥F2) as accurately as CAP and LSM, respectively. Likewise, the A index proved reliable as the FAST score in diagnosing high-risk MASH among the whole MASLD spectra.

Reliably classifying MASH is of paramount importance since subjects with NAS ≥4 and ≥F2 (i.e., high-risk MASH) may benefit from anti-MASH drugs.¹ However, the gold standard liver biopsy poses safety concerns and high costs. Various US-based elastographies have been developed to overcome the inherent invasiveness and selection bias of liver biopsy. While RTE effectively assesses hepatic fibrosis regardless of inflammation and congestion,³² its performance falls behind SWEs because it measures the relative probe-induced deformation compared to adjacent tissues.³³ By contrast, shear wave imaging better discriminates the degree of elasticity, but loses accuracy once accompanied by dispersive inflammatory tissue and hepatic congestion.^11,12 Especially, despite its renowned utility, VCTE fails to anatomically picture the hepatic parenchyma and thus entails a relatively high measurement failure.³⁴ Combi-elastography offers a single-performed multi-parametric means with the anatomical visualization of the liver.¹⁹ However, no study has validated nor compared its diagnostic performance in a large cohort of biopsy-proven MASLD patients.

The current study showed that the covariate-adjusted ATT was comparable to that of CAP in diagnosing hepatic steatosis. Unlike CAP, acquisition of ATT employs US B-mode, thus having an edge by reducing measurement failure and assessing hepatic steatosis in obese individuals with thick subcutaneous tissue.^9,35

Diagnostic performance of combi-elastography-derived indices for detecting fibrosis in MASLD patients is rarely reported. Prior studies using the LF index either had a small cohort or were not conducted with liver biopsy as reference.^10,36 F index is a strong, independent predictor of early recurrence of hepatocellular carcinoma,³⁷ but its efficacy in MASLD has yet been reported. Liver stiffness measured by US B-mode combi-elastography is rarely affected by confounding factors such as inflammation or hepatic congestion.³⁸ Moreover, unlike noninvasive fibrosis tests where the diagnostic performance tends to decrease with increasing steatosis severity,³⁹ our results showed that the F index was uninfluenced by such liver histology. The adjusted F index showed comparable performance to established, noninvasive serological markers in diagnosing significant fibrosis, suggesting its capability as a diagnostic tool utilized in clinical practice.

The internationally validated FAST score is useful for identifying patients with high-risk MASH.³¹ However, its dependence on VCTE measurements is vulnerable to the pitfalls of employing shear wave imaging without anatomical evaluation.⁴⁰ Based on the present findings, we postulate that the A index, derived from parameters extracted from the combination of two elastography modalities, might be utilized for effectively detecting high-risk MASH.¹⁹

The globally validated VCTE has now become a well-incorporated means of liver assessment in MASLD subjects.²¹ In terms of diagnostic utility, the proven non-inferiority of combi-elastography to VCTE in our large biopsy cohort may contribute to employing combi-elastography in future studies. Although the result was statistically insignificant, combi-elastography measurement had a higher performance in detecting significant fibrosis in a sensitivity analysis on obese patients. Such results and the technical background of combi-elastography infer its possible advantage in patients with narrow intercostal spaces, obesity, and ascites–subjects infeasible to assess with VCTE.^6,41,42

Our study has several limitations. First, the region of interest of US-based elastography may not represent the region of the liver biopsy. Second, the availability of the instrument in primary care settings is questionable. Third, the results are vulnerable to inter-operator variability. Lastly, further studies in multi-ethnic cohorts are warranted to externally validate the performances and cut-offs. Nonetheless, this was the first study to test and compare combi-elastography measures using a large-scale biopsy-proven MASLD cohort.

In conclusion, combi-elastography evaluates hepatic histological severity under ultrasonic visualization of the liver, even in circumstances of congestion or inflammation. Its diagnostic performance for hepatic steatosis, fibrosis, and high-risk MASH is comparable to the existing methods of VCTE-derived CAP, LSM, and the FAST score, respectively. Given the potential of combi-elastography to comprehensively assess liver histology in a single examination, further research to validate its diagnostic capability and establish standard procedures is required.

This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (2021R1A2C2005820, and 2021M3A9E4021818) and the SNUH Research Fund (04-2021-0370).

W.K. is an editorial board member of the journal but was not involved in the peer reviewer selection, evaluation, or decision process of this article. No other potential conflicts of interest relevant to this article were reported.

Study concept and design: D.H.L., W.K. Data acquisition: D.H.L., W.K., S.K.J., H.J., Y.H.S., S.J., D.H.L., J.H.P., M.S.C. Data analysis and interpretation: Y.K.L., D.H.L., W.K. Drafting of the manuscript: Y.K.L., D.H.L. Critical revision of the manuscript for important intellectual content: W.K., D.H.L. Statistical analysis: Y.K.L., D.H.L. Obtained funding: W.K. Administrative, technical, or material support; study supervision: W.K. Approval of final manuscript: all authors.

The data presented in this study are available on reasonable request from the corresponding author. Data is not publicly available due to privacy.

Supplementary materials can be accessed at https://doi.org/10.5009/gnl240198.