S index: a predictor comparable to ultrasound shear wave elastography in assessing liver fibrosis in patients with chronic hepatitis B

Abstract

Background

Chronic hepatitis B poses a major global health challenge, especially in developing countries. It significantly contributes to morbidity and mortality from liver cirrhosis and hepatocellular carcinoma.

Objective

To evaluate diagnostic performance of ultrasound shear wave elastography (USWE), S index, Z index, Fibrometer in continuous differentiation of liver fibrosis in a retrospective chronic hepatitis B patients’ cohort.

Materials and methods

We collected liver stiffness values measured by USWE and laboratory indicators from 146 patients with chronic hepatitis B at Baoji Central Hospital. Serum fibrosis models were calculated using formulas, including S index, Z index, and Fibrometer. Using liver biopsy pathology as a reference, the diagnostic efficacy of each indicator for liver fibrosis staging was evaluated using receiver operating characteristic curves (ROC).

Results

S index and USWE demonstrated comparable diagnostic accuracy for liver fibrosis staging with areas under ROC (AUCs) of 0.791 vs. 0.860 (p = 0.679) for significant fibrosis (S ≥ 2), 0.867 vs. 0.942 (p = 0.074) for severe fibrosis (S ≥ 3), and 0.961 vs. 0.932 (p = 0.508) for cirrhosis (S4). The two indices exhibited superior performance over Fibrometer across all stages (S index/USWE vs. Fibrometer-AUCs: 0.791/0.806 vs. 0.575, < 0.001 for S ≥ 2; 0.867/0.940 vs. 0.625, p < 0.001 for S ≥ 3; 0.961/0.932 vs. 0.781, p = 0.004/0.025 for S4). Compared with Z index, they showed better diagnostic capacity for S ≥ 2 (AUCs 0.791/0.806 vs. 0.575, p < 0.001) and S ≥ 3 (0.867/0.942 vs. 0.673, p < 0.001), while maintaining equivalent accuracy for cirrhosis detection (AUCs 0.961/0.932 vs. 0.914, p = 0.209/0.747).

Conclusion

The S index is equally effective as the USWE in diagnosing liver fibrosis among patients with chronic hepatitis B, and it is superior to both the Z index and Fibrometer.

Introduction

Hepatitis B virus (HBV) infection is a major cause of liver fibrosis worldwide. It also presents significant public health challenges [1]. Chronic HBV infection can lead to progressive liver injury, resulting in increased fibrosis that can ultimately advance to cirrhosis and hepatocellular carcinoma [2]. Detecting liver fibrosis early and assessing its severity are essential for making treatment decisions and lowering the risk of serious outcomes for those affected [3].

Traditionally, liver biopsy is regarded as the gold standard for diagnosing liver fibrosis and inflammation due to its direct histological assessment. However, this invasive procedure is associated with complications such as pain, bleeding, and sampling errors, which limit its application in clinical practice [4, 5]. To address these limitations, non-invasive diagnostic methods have gradually gained attention. Among them, elastography and various serum biomarkers have become key tools for assessing liver fibrosis [6].

Transient elastography (FibroScan) assesses the stage of liver fibrosis by determining the elastic modulus of the liver. The basic principle involves using a special probe to generate a transient low-frequency pulse excitation, causing the liver tissue to undergo shear waves. By tracking and collecting the shear waves, the tissue’s elastic modulus can be obtained, displayed in kilopascals (kPa). FibroScan has some limitations when used in patients with ascites, obesity, and narrow intercostal spaces [7].

Real-time ultrasound shear wave elastography (USWE) uses ultrasound technology to measure liver stiffness. It is a new generation technology for measuring liver stiffness, using a conventional two-dimensional ultrasound probe to generate focused sound beams that create shear waves within the liver parenchyma. The degree of liver fibrosis is reflected in the propagation speed of shear waves within the liver parenchyma, and the same probe is used to detect and convert the data into kPa through software [8].

Serum biomarkers provide a non-invasive alternative that can be easily performed in routine blood tests. Many models have been established for assessing liver fibrosis, with commonly used clinical models including APRI [9], FIB-4 [10], Kings’ scores [11], Forns index [12], Hepascores [13], Fibrotest [14], Z index [15], S index [16] and Fibrometer [17]. While these scores offer useful estimates of fibrosis, they may not fully capture the complexities of liver disease, especially when significant inflammation is present, which can mask fibrosis progression [18].

Elastography and serum models each have their advantages and disadvantages in evaluating liver fibrosis. Further comparative studies are necessary to validate their effectiveness in assessing the stages of liver fibrosis in the same group’s patients [19]. A few studies have compared the value of FibroScan, S index, and Z index in diagnosing the stages of liver fibrosis in patients with hepatitis B [20, 21]. In this study, we aimed to evaluate the diagnostic performance of the new generation of elastography technology compared to the S index, Z index, and Fibrometer in detecting the degree of liver fibrosis in patients with chronic hepatitis B, as well as the effectiveness of their combined diagnosis.

Materials and methods

Patients

This study was approved by the ethics committee of Baoji Central Hospital review board, which waived the need for patient informed consent due to the study’s retrospective nature. A total of 177 patients with chronic liver disease who visited Baoji Central Hospital from May 2018 to October 2023 were collected. All patients had previously undergone ultrasound-guided liver puncture biopsy to obtain pathological results, as well as USWE examination and laboratory indicator testing. The inclusion criteria for this study are as follows: (1) Positive hepatitis B surface antigen for more than 6 months; (2) Age 18 years or older; (3) Liver biopsy, USWE measurement, and laboratory indicator tests completed within one week. The exclusion criteria are as follows: (1) Co-infection with non-B hepatitis virus or human immunodeficiency virus; (2) Alcoholic liver disease, or autoimmune hepatitis; (3) Previous liver transplantation; (5) Congestive liver disease; (7) Intrahepatic cholestasis; (8) Unreliable pathological results; (9) Lack of important serum indicators. Among 177 patients, there were 10 cases of hepatitis C; 2 cases of alcoholic liver disease; 1 case of autoimmune hepatitis; 7 cases of unknown hepatitis; 5 cases of hepatitis B combined with severe fatty liver; 1 case of hepatitis B combined with drug-induced hepatitis; 3 cases of failed USWE measurements, and 2 patients were under 18 years old (1 case aged 14 and 1 case aged 17); a total of 31 patients were excluded from this study. Finally, 146 cases of chronic hepatitis B patients were included in this study, with 79 males ranged 19–70 years, mean 39.0 ± 12.9 years, and 67 females ranged 18–61 years, mean 33.9 ± 11.6 years. All included patients had not previously received antiviral treatment (Fig. 1).

Fig. 1.

Flowchart shows patient enrollment. In total, 146 out of 177 patients were included in this study

Liver stiffness measurement using ultrasound shear wave elastography

Using the Supersonic Aixplorer color Doppler ultrasound diagnostic device (Supersonic Imagine, Aix-en-Provence, France) with the SC6-1 convex array probe at a frequency of 1–6 MHz, the patient is instructed to lie supine with both arms raised. After selecting an appropriate segment between the right ribs, the SWE mode is activated, avoiding larger ducts within the liver. The elastic imaging sampling box is placed about 1–2 cm under the hepatic capsule of the right lobe. During SWE imaging, the patient is instructed to hold their breath, and the color filling within the sampling box should exceed 90%. A circular area with a diameter of 2–3 cm is selected for quantitative detection, recording the mean liver elasticity modulus (in kPa) within the detection area (Fig. 2). For each patient, five effective measurements are taken at the same site, and the median value is recorded. All ultrasound examinations are performed by a radiologist with 10 years of experience in abdominal ultrasound and 5 years of experience in ultrasound elastography.

Fig. 2.

Images show liver stiffness measured with ultrasound shear wave elastography in a patient aged thirty to forty with chronic hepatitis B and fibrosis stage S4

Serum index testing

All serological indicators are completed in the same laboratory, collecting serological parameters within one week before and after liver biopsy and USWE examination. Serum index tests require fasting for more than 8 h and taking peripheral venous blood. The main indicators include aspartate aminotransferase (AST), alanine aminotransferase (ALT), total bilirubin (TB), albumin (ALB), gamma-glutamyl transferase (GGT), alkaline phosphatase (ALP), platelet count (PLT), prothrombin time (PT), hyaluronic acid (HA), alpha-2 macroglobulin, and urea. The upper limit of normal (ULN) for ALT and AST is 40 UI, and the normal range for platelet PLT is 100–300 × 10⁹/L. The S index, Z index, and Fibrometer model are calculated using the following formulas:

Z index = -13.995 + 3.220 log (a2-macroglobulin) + 3.096 log (age) + 2.254 log (GGT) + 2.437 log (HA) [15].

S index = 1000×GGT/(PLT×ALB²) [16].

Fibrometer = -0.007 PLT (G/L) -0.049 PI (%) + 0.012 AST (UI/L) + 0.005 A2M (mg/ dL) + 0.021 HA (ug/L) − 0.270 urea (mmol/L) + 0.027 age (years) + 3.718 [17].

Liver biopsy and pathology

Liver biopsy is performed under ultrasound guidance with an 18-gauge tissue core needle. The puncture path avoids large blood vessels within the liver, and samples are taken 2–3 times. The length of the tissue strips must be ≥ 1.5 cm and include at least 6 portal areas. All liver biopsy specimens were read by two experienced liver pathologists with over 10 years of experience. The pathologists were unknown of any clinical data of the patients. The staging of liver fibrosis and grading of inflammation use the Scheuer scoring system. Liver fibrosis is classified into stages S0-S4 (S0: no liver fibrosis; S1: expansion of portal area fibrosis; S2: peripherally located fibrosis around portal areas or formation of a small number of fibrous septa; S3: significant fibrous septa with lobular structural disorder, without cirrhosis; S4: cirrhosis. The degree of inflammatory activity is classified into G0-G4: G0: no inflammation in the portal area and surrounding tissue, no inflammation in the lobules; G1: inflammation in the portal area, hepatocyte degeneration and a small amount of necrosis in the lobules; G2: mild necrosis in the portal area and surrounding cells, cellular degeneration in the lobules, focal necrosis or eosinophilic body formation; G3: moderate necrosis in the portal area and surrounding cells, cellular degeneration in the lobules, extensive necrosis, or bridging necrosis observed; G4: moderate necrosis in the portal area and surrounding cells, extensive bridging necrosis in the lobules, affecting multiple lobules, with lobular structural disorder [22].

Statistical analysis

Statistical analysis was performed using SPSS 13.0 software (IBM, Corporation, Armonk, NY) and MedCalc version 15.2 software (MedCalc Program, Ostend, Belgium). Quantitative data are presented as mean ± standard deviation if the data are normally distributed; otherwise, the median (Interquartile range) is reported. Qualitative data are presented as frequency and percentage. Spearman rank correlation analysis was used to assess the relationship between USWE, Z index, S index, Fibrometer, and liver fibrosis stages. To investigate the independent association between USWE measurements and histologic inflammatory activity, we performed partial correlation analysis with hepatic fibrosis stage as a covariate to account for its potential confounding effects. Logistic regression for binary variables was applied to generate probability prediction functions as combined test indicators. Using liver biopsy pathological staging of liver fibrosis as a reference, the diagnostic effectiveness of each indicator for liver fibrosis staging and inflammation grading was assessed by receiver operating characteristic (ROC) curves, with comparisons of the area under ROC (AUC) conducted using the DeLong test. The sensitivity, specificity corresponding to the maximum Youden index were selected, with P < 0.05 considered statistically significant.

Results

Patient characteristics

We collected 2 to 3 liver biopsy samples from each patient, meaning 3.2 cm in total length, typically containing 12 portal tracts. The pathological results of liver biopsy showed that liver fibrosis stage S0-1 accounted for 32.9% (48/146), stage S2 accounted for 25.3% (37/146), stage S3 accounted for 21.9% (32/146), and stage S4 accounted for 19.9% (29/146). Among them, significant fibrosis (S ≥ 2) was 67.1% (98/146). Patients with liver fibrosis stage S4 had higher age, serum TB, AST, GGT, and HA levels compared to patients in stages S0-1, S2, and S3. Patients in stage S4 had lower serum ALB levels and PLT counts than those in stages S0-1, S2, and S3. All patients had a BMI of less than 30 kg/m² (Table 1). The proportion of patients with ALT above ULN was 25.3% (37/146). The proportion of patients with AST above ULN was 10.3% (15/146). The proportion of patients with PLT counts below the normal lower limit was 19.8% (20/146). The liver stiffness values from USWE showed significant differences between all fibrotic groups (S0-1 vs. S2, S2 vs. S3, S3 vs. S4), and the S index showed significant differences between all inflammation groups (G1 vs. G2, G2 vs. G3, G3 vs. G4) (Table 2).

Table 1.

Patient characteristics

Characteristics	S0-1 (n = 48)	S2 (n = 37)	S3 (n = 32)	S4 (n = 29)	P-value
Age (y)	33.3 ± 13.1	33.5 ± 10.1	36.7 ± 6.9	46.5 ± 12.4	< 0.001**
Sex(male/female)	20/28	22/15	19/13	18/11	< 0.001**
BMI (kg/m2)	20.7 ± 2.5	22.5 ± 2.8	21.7 ± 3.5	21.8 ± 2.9	< 0.001**
PLT (109/L)	180.7 ± 59.6	161.5 ± 48.7	144.0 ± 45.1	96.9 ± 46.1	< 0.001**
TB (µmol/L)	9.8 ± 4.5	10.2 ± 3.6	10.6 ± 3.3	14.5 ± 5.7	< 0.001**
ALT (IU/L)	27.2 ± 19.0	32.8 ± 18.8	39.2 ± 18.9	44.9 ± 30.9	0.12
AST (IU/L)	23.2 ± 8.1	25.3 ± 9.0	29.1 ± 5.8	57.3 ± 49.8	< 0.001**
GGT (IU/L)	16.6 ± 9.5	19.9 ± 12.5	22.4 ± 7.1	82.3 ± 117.8	< 0.001**
ALB (g/L)	41.4 ± 2.9	40.1 ± 7.5	40.3 ± 2.8	36.9 ± 4.2	0.004**
HA (µg/L)	75.0 (56.9–88.8)	56.0 (44.2–95.3)	28.3 (4.03–84.3)	102.7 (68.5–188.3)	< 0.001**
Chol (mg/dL)	3.8 ± 0.9	3.7 ± 0.9	3.6 ± 0.4	3.5 ± 0.7	0.442
PT (sec)	12.0 ± 0.95	12.6 ± 0.81	12.6 ± 0.88	13.7 ± 1.33	0.063
PI (%)	0.93 ± 0.07	0.97 ± 0.08	1.02 ± 0.13	0.92 ± 0.14	0.004**
α2-M	8.6 ± 1.5	7.6 ± 1.4	8.2 ± 1.7	8.1 ± 1.2	0.047*
Urea (mmol/L)	4.1 ± 1.0	4.2 ± 1.4	4.5 ± 1.2	4.4 ± 1.3	0.492

BMI = body mass index, ALT = alanine aminotransferase, AST = aspartate aminotransferase, PLT = Platelet, TB = total bilirubin, GGT = gamma-glutamyl transpeptidase, ALB = albumin, HA = hyaluronic acid, Chol = cholesterol, PI = prothrombin index, α2-M = α2-macroglobulin

Table 2.

Descriptive statistics and spearman coefficient of noninvasive methods for liver fibrosis stage and inflammation grades in patients with CHB

Noninvasive Index	S0-1	S2	S3	S4	p-value (S0-1 vs. S2)	p-value (S2 vs. S3)	p-value (S3 vs. S4)	Spearman Coefficient	p-value
USWE	6.90 (5.80–7.60)	7.50 (6.45–11.05)	12.45 (11.40–18.30)	20.20 (13.60–31.40)	0.043*	< 0.001**	0.005**	0.700	< 0.001**
S index	4.48 (4.01–7.09)	6.22 (4.35–10.61)	9.53 (7.02–15.18)	41.62 (29.19–62.00)	0.016*	0.090	< 0.001**	0.652	< 0.001**
Z index	0.77 (0.03–1.35)	0.65 (-0.01–1.49)	0.21 (-1.42–0.70)	2.54 (1.84–3.96)	0.900	0.084	< 0.001**	0.324	< 0.001**
Fibrometer	-0.76(-1.42–0.19)	-0.52 (-1.40 - -0.03)	-16.0 (-2.10 - -0.57)	1.65 (0.80–4.71)	0.905	0.296	< 0.001**	0.223	0.015*
	G1	G2	G3	G4	p-value (G1 vs. G2)	p-value (G2 vs. G3)	p-value (G3 vs. G4)	Spearman Coefficient	p-value
USWE	7.15 (5.95–8.80)	7.20 (6.15–8.80)	12.10 (10.25–15.75)	18.00 (12.53–29.83)	0.660	< 0.001**	0.002**	0.624	< 0.001**
S index	0.43 (0.31–0.73)	0.56 (0.42–0.95)	0.95 (0.59–1.57)	3.60 (1.15–5.85)	0.022*	0.026*	< 0.001**	0.620	< 0.001**
Z index	1.6 (-5.2–7.5)	7.8 (3.2–16.0)	2.4 (-5.5–11.8)	24.3 (16.0–35.6)	0.005**	0.130	< 0.001**	0.466	< 0.001**
Fibrometer	-1.02 (-1.88 - -0.64)	-0.45 (-1.20–0.25)	-1.54 (-2.0–0.27)	1.35 (-0.94–3.60)	0.043*	0.596	0.007**	0.339	< 0.001**

Note. —Data in parentheses are interquartile ranges. ** Correlation is significant at the 0.01 level (two-tailed). * Correlation is significant at the 0.05 level (two-tailed). USWE = ultrasound shear wave elastography, CHB = chronic hepatitis B

Correlation analysis

USWE, S index, Z index, and Fibrometer are positively correlated with the pathological staging of liver fibrosis in biopsy tissue, with USWE and S index showing significantly stronger correlations (r = 0.700, p < 0.001 and r = 0.652, p < 0.001, respectively). The Z index also shows a significant correlation (r = 0.324, p < 0.001), while Fibrometer has a weaker yet significant correlation (r = 0.223, p = 0.015). Our statistical analysis revealed distinct patterns in liver assessment parameters. Initial Spearman correlation analysis demonstrated a strong positive association between USWE values and hepatic inflammatory grading (r = 0.624, p < 0.001) (Table 2; Fig. 3a). However, subsequent partial correlation analysis controlling for liver fibrosis stage – a potential confounding factor in elastography measurements – eliminated this apparent relationship (adjusted r = 0.085, p = 0.357) (Fig. 3b). This methodological refinement suggests that the observed USWE-inflammation correlation in primary analysis may be mediated through fibrotic changes rather than representing direct inflammatory effects.

Fig. 3.

(a, b). Scatter plots demonstrating the mediating role of liver fibrosis in ultrasound shear wave elastography (USWE)-inflammation associations. (a) Unadjusted analysis revealed significant positive correlation between USWE stiffness values and histologic inflammation severity. (b), After controlling for fibrosis stage using partial correlation analysis, the USWE-inflammation association became nonsignificant, indicating that fibrotic remodelling rather than inflammatory activity primarily drives USWE measurements

Comparing the diagnostic efficacy of USWE, S index, Z index, and fibrometer for staging liver fibrosis

The AUC, sensitivity, specificity for each indicator predicting liver fibrosis staging are shown in Table 3. The diagnostic value of USWE and S index for significant fibrosis (S ≥ 2), severe fibrosis (S ≥ 3), and cirrhosis (S4) are comparable. For S ≥ 2, the AUC is 0.860 vs. 0.791 (p = 0.679), with corresponding cutoff values of 8.0 kPa and 0.75; for S ≥ 3, the AUC is 0.942 vs. 0.867 (p = 0.074), with corresponding cutoff values of 10.5 kPa and 0.81; for S4, the AUC is 0.932 vs. 0.961 (p = 0.508), with corresponding cutoff values of 11.8 kPa and 1.02. In contrast, both indices show superior diagnostic value compared to Fibrometer, with AUCs of 0.806 and 0.791 vs. 0.575 (p < 0.001) for S ≥ 2, 0.940 and 0.867 vs. 0.625 (p < 0.001) for S ≥ 3, and 0.932 and 0.961 vs. 0.781 (p = 0.025 and p = 0.004) for S4. For significant fibrosis (S ≥ 2) and severe fibrosis (S ≥ 3), USWE and S index show better diagnostic value than the Z index, with AUCs of 0.806 and 0.791 compared to 0.575 (p < 0.001) for S2, and 0.942 and 0.867 compared to 0.673 (p < 0.001) for S3. However, for cirrhosis (S4), their diagnostic value is comparable to that of the Z index, with AUCs of 0.932 and 0.961 versus 0.914 (p = 0.747 and p = 0.209). The Z index exhibits superior diagnostic value for cirrhosis (S4) compared to Fibrometer, with an AUC of 0.914 versus 0.781 (p = 0.014) (Fig. 4; Table 3).

Table 3.

AUCs of USWE, S index, Z index, fibrometer and combination tests for assessing liver fibrosis stage

Test of Fibrosis	AUC	Sensitivity (%)	Specificity (%)
≧S2
USWE	0.806 (0.724–0.873)	61.1 (48.9–72.4)	93.8 (82.8–98.6)
S index	0.791 (0.707–0.860)	68.1 (56.0–78.6)	81.3 (67.4–91.0)
Z index	0.591 (0.497–0.680)	43.1 (31.4–55.3)	83.0 (69.2–92.3)
Fibrometer	0.575 (0.481–0.665)	43.1 (31.4–55.3)	78.3 (63.6–89.0)
USWE + S index	0.845 (0.767–0.904)	76.4 (64.9–85.6)	83.3 (69.8–92.5)
USWE + Z index	0.809 (0.727–0.875)	61.1 (48.9–72.4)	93.6 (82.4–98.6)
USWE + Fibrometer	0.803 (0.719–0.870)	63.9 (51.7–74.9)	91.3 (79.2–97.5)
≧S3
USWE	0.942 (0.884–0.976)	92.3 (79.1–98.3)	87.7 (78.5–93.3)
S index	0.867 (0.796–0.924)	87.5 (72.6–95.7)	75.3 (64.5–84.2)
Z index	0.673 (0.581–0.756)	53.9 (37.2–69.9)	87.5 (78.2–93.8)
Fibrometer	0.625 (0.531–0.713)	51.3 (34.8–67.6)	82.3 (72.1–90.0)
USWE + S index	0.944 (0.886–0.977)	94.9 (82.6–99.2)	85.2 (75.5–92.1)
USWE + Z index	0.937 (0.878–0.974)	87.2 (72.6–95.7)	87.5 (78.2–93.8)
USWE + Fibrometer	0.938 (0.878–0.974)	94.9 (82.6–99.2)	83.5 (73.5–90.9)
S4
USWE	0.932 (0.871–0.970)	91.3 (71.9–98.7)	81.4 (72.3–88.6)
S index	0.961 (0.908–0987)	100.0 (85.0–100.0)	82.5 (73.4–89.4)
Z index	0.914 (0.848–0.957)	91.3 (71.9–98.7)	82.3 (73.2–89.3)
Fibrometer	0.781 (0.695–0.852)	78.3 (56.3–92.5)	75.8 (65.9–84.0)
USWE + S index	0.955 (0.901–0.984)	100.0 (85.0–100.0)	84.5 (75.8–91.1)
USWE + Z index	0.976 (0.929–0.995)	100.0 (85.0–100.0)	89.6 (81.7–94.9)
USWE + Fibrometer	0.948 (0.891–0.980)	91.3 (71.9–98.7)	86.3 (77.7–92.5)
Statistical comparison between AUC values
Versus	S ≧ 2	S ≧ 3	S4
USWE vs. S index	0.679	0.074	0.508
USWE vs. Z index	< 0.001**	< 0.001**	0.747
USWE vs. Fibrometer	< 0.001**	< 0.001**	0.025*
S index vs. Z index	< 0.001**	< 0.001**	0.209
S index vs. Fibrometer	< 0.001**	< 0.001**	0.004**
Z index vs. Fibrometer	0.721	0.332	0.014*
USWE + S index vs. USWE	0.351	0.888	0.185
USWE + Z index vs. USWE	0.971	0.639	0.219
USWE + Fibrometer vs. USWE	0.732	0.652	0.483

Note. —Data in parentheses are 95% confidence intervals. ** Correlation is significant at the 0.01 level (two-tailed). * Correlation is significant at the 0.05 level

USWE = shear wave elastography, AUC = area under the receiver operating characteristic curve

Fig. 4.

(a, b, c). Receiver operating characteristic curves of four noninvasive index in different stages of fibrosis in patients with hepatitis B. (a). ≥ S2 stage, (b). ≥ S2 stage, (c). ≥ S3 stage

USWE combined serum fibrosis models

Logistic regression analysis was applied to establish a probability prediction function, using it as a comprehensive indicator to diagnose liver fibrosis. The AUC for diagnosing significant fibrosis (≥ S2) using USWE combined with the S index increased from 0.806 to 0.845, and sensitivity improved from 61.1 to 76.4%, while specificity declined from 93.8 to 83.3%. However, the difference in AUC for diagnosing significant fibrosis (≥ S2) between the combined examination and USWE was not statistically significant (Table 3).

Discussion

Non-invasive indicators are essential for diagnosing liver fibrosis due to the rising prevalence of liver diseases and the drawbacks of invasive procedures like liver biopsies. Non-invasive methods, such as serological markers and elastography techniques, offer promising alternatives that reduce patient burden and enable more frequent monitoring of disease progression. Additionally, these non-invasive methods aid in early detection and prompt intervention, which are critical for enhancing patient outcomes [23]. To further explore this topic, we evaluate the effectiveness of various non-invasive indicators in diagnosing liver fibrosis by analyzing their performance, thereby strengthening their clinical application.

Our prior prospective cohort investigation systematically compared USWE against nine established serum fibrosis indicators (APRI, FIB-4, Forns score, King’s score, FibroIndex, PRP, Hepascore, type IV collagen, and hyaluronic acid) for hepatic fibrosis assessment in chronic hepatitis B patients. Quantitative analysis demonstrated USWE’s superior diagnostic performance over all serum biomarkers in predicting significant fibrosis, severe fibrosis, and cirrhosis [24]. Zhuang et al. conducted a prospective cohort study evaluating liver fibrosis in hepatitis B patients through comparison of USWE with APRI, FIB-4, Forns score, and King’s score. Their findings revealed that USWE exhibited significantly higher diagnostic accuracy than serum fibrosis models in predicting significant fibrosis (S ≥ 2), severe fibrosis (S ≥ 3), and cirrhosis (S4) in these patients [25]. Consistent with previous studies, we found that USWE effectively predicts liver fibrosis staging in patients with chronic hepatitis B. Its diagnostic accuracy is significantly higher than that of the Z index and Fibrometer.

Previous studies have demonstrated that the S index exhibits comparable or lower diagnostic value than FibroScan in staging hepatitis B-related liver fibrosis [20, 21]. Notably, our study represents the first comparative analysis between USWE and the S index for liver fibrosis assessment in hepatitis B patients. The S index demonstrates accuracy comparable to USWE in predicting sequential liver fibrosis stages. In contrast, USWE implementation carries higher costs and technical demands, as measurements may be affected by operator expertise and patient-specific factors like obesity. The S index requires only serum GGT, albumin, and platelet count analysis, conferring operational simplicity. These findings confirm the S index’s reliability as a non-invasive alternative to USWE in clinical settings. While both modalities show equivalent efficacy in cirrhosis diagnosis (S4), the Z index’s dependence on experimental biomarkers and computational complexity limits its clinical utility compared to the S index’s streamlined approach.

The assessment of liver inflammation constitutes another crucial component in this investigation, given that inflammatory activity significantly influences disease progression and precise identification of inflammatory status is fundamental for optimizing HBV therapeutic strategies. In their study, Dou et al. developed predictive models demonstrating AUC values of 0.860, 0.950, and 0.840 for detecting hepatic inflammation at histological grades G ≥ 2, G ≥ 3, and G4, respectively [26]. This study showed that there is no correlation between USWE and liver inflammation, indicating limited applicability for inflammation assessment. This discrepancy may originate from methodological differences: Dou et al.‘s models incorporated dual-elastic imaging parameters, whereas our analysis utilized single-modality shear wave elastography.

Previous studies have shown that combining USWE with AST, ALT, CIV, APRI, and FIB-4 can improve the accuracy of diagnosing hepatitis B liver fibrosis [27, 28]. Building on this, we aimed to evaluate both hepatitis B liver fibrosis and inflammation by combining USWE with the S index, Z index, and Fibrometer. However, combining USWE with the S index, Z index, and Fibrometer did not improve diagnostic accuracy in this study.

The Scheuer scoring was employed for pathological staging of liver fibrosis in this study. Current evidence suggests that the Scheuer, Ishak, METAVIR, and revised Ishak HAI systems demonstrate comparable efficacy for staging when applied by experienced hepatic pathologists [29]. The Scheuer S0-S4 staging aligns well with METAVIR’s F0-F4 classification, with minor technical variations observed. Importantly, both systems exhibit strong diagnostic consistency at clinically significant thresholds, particularly at stage 2 liver fibrosis (where both systems indicate the presence of portal fibrosis as stage 2), which represents a critical treatment decision point for antiviral intervention [30, 31]. This equivalence suggests that our findings of stage 2 fibrosis maintain cross-system comparability with METAVIR-based clinical studies.

This study has the following limitations: First, the retrospective design may introduce selection bias. This bias could affect the characteristics and outcomes of the patient group. Second, the sample size of this study is relatively small. Therefore, future research should aim to increase the sample size for better validation. Third, we only explored the diagnostic value of USWE, S index, Z index, and Fibrometer in patients with chronic hepatitis B, and did not assess their effectiveness in patients with chronic hepatitis C and non-alcoholic fatty liver disease.

In conclusion, this research indicates that the S index presents a promising non-invasive alternative for assessing liver fibrosis in chronic hepatitis B patients. The diagnostic performance shows its potential to improve patient management and lessen the need for invasive procedures. However, to fully achieve the clinical application of the S index, future studies should focus on validating these findings in larger and more diverse populations, while also exploring its utility in other liver diseases. By addressing these research limitations and broadening the validation scope, the S index could become a crucial tool in combating chronic hepatitis B and related liver conditions.

Abbreviations

USWE

Ultrasound Shear Wave Elastography

HBV

Hepatitis B Virus

APRI

Aspartate aminotransaminase-to-platelet ratio index

AST

Aspartate Aminotransferase

ALT

Alanine Aminotransferase

TB

Total Bilirubin

ALB

Albumin

GGT

Gamma-glutamyl Transferase

ALP

Alkaline Phosphatase

PLT

Platelet Count

PT

Prothrombin Time

HA

Hyaluronic Acid

ULN

Upper Limit of Normal

ROC

Receiver Operating Characteristic Curves

AUC

Area under ROC

Author contributions

Study concept and design: Jianxue Liu, sujuan Guo; data acquisition: Lu Gan, Qiannan Meng, Qiang Feng, Jiahua Li, Qinyun Wan, Yaoren Zhang, Feng Du, Yonghao Ji; drafting of the manuscript: Sujuan Guo, Jianxue Liu; critical revision and approval of the final manuscript: all authors.

Funding

This work was supported by the Shaanxi Health Commission Fund Project (No.2021D009), Shaanxi Administration of Traditional Chinese Medicine Fund Project (No.szy-kjcyc-2023-06).

Data availability

The data that support the findings of this study are available from the corresponding author upon reasonable request.

Declarations

Ethical approval

This study was approved by the ethics committee of Baoji Central Hospital review board and adhered to the principles outlined in the Declaration of Helsinki, which waived the need for patient informed consent due to the study’s retrospective nature.

Consent for publication

Not Applicable.

Competing interests

The authors declare no competing interests.