Abstract
Purpose
To assess the performance of shear wave ultrasound elastography (SWE) for non‐invasive grading of fibrosis in normal BMI patients with varied aetiology chronic liver disease.
Method
Prospective SWE liver and spleen stiffness (LS, SS respectively) of 124 patients (94 men, mean age 45.4 ± 12.4 years, mean BMI 19.66 ± 1.49) with CLD of mixed aetiology, who underwent liver biopsy, between January 2019–20 was analysed using receiver operating curve (ROC) and classification analysis regression tree (CART) to determine fibrosis cut‐off values and nominal logistical regression to quantify fibrosis.
Results
Of 124 patients, 50 (40%) had non‐alcoholic steatohepatitis (NASH), 31 (25%) chronic hepatitis B (CHB) and 43 (35%) alcoholic liver disease (ALD) on biopsy. Overall mean LS and SS of the study population was 11.81 ± 5.9 and 16.88 ± 10.8 kPa, respectively. LS cut‐off value <8 kPa was consistent with F0, 9–14 kPa for F1‐F2 and >14.9 kPa for F3‐F4 fibrosis on biopsy. On application of CART, LS value < 5.3 kPa was discriminative for NASH, 5.32 to <12.64 kPa for CHB, >12.64 kPa for ALD, SS <15.3 kPa was discriminative for NASH, 15.3–30 kPa for CHB and >30 kPa for ALD in our study population.
Conclusion
SWE is a viable non‐invasive tool for assessment of liver fibrosis grading in a population of mixed aetiology CLD. LS values in conjunction with SS are promising predictors of F2‐F3 fibrosis with potential to discriminate select categories like CHB and NASH in such a population.
Keywords: alcoholic liver disease, chronic liver disease, fibrosis, hepatitis B, liver stiffness, NASH, shear wave ultrasound elastography, spleen stiffness
Introduction
Chronic diffuse liver disease (CDLD) is often a progressive condition which pathologically and morphologically converts a soft, smooth, compliant solid organ into a scarred fibrotic and nodular one by its end stage, termed cirrhosis. The intermediate, insidious phase of fibrosis, during which these changes become irreversible, is a diagnostic challenge for every clinician. Elastography‐based measurement of liver stiffness serves as a virtual stethoscope for the hepatologist to detect the progression of fibrosis in asymptomatic individuals, to guide the prudent use of therapeutic drugs, interventions and select the opportune time for liver transplantation.
One of the earliest techniques for measuring tissue stiffness is strain imaging, in which normal stress applied to tissues is measured with response of normal strain.1 This is further subdivided into strain elastography (uses a strain ratio, comparing adjacent reference normal tissue to area under observation, which indicates tissue stiffness) and acoustic radiation force impulse (ARFI) imaging (acoustic pulse displaces tissues perpendicular to the surface and ratio of tissue under evaluation to the reference area is calculated for the exact stiffness measurement).2
Shear wave ultrasound elastography (SWE) is a recently developed and more popular technique which evaluates the resistance encountered by dynamic production of shear waves in parallel and perpendicular planes by measuring the SW speed in a comprehensive qualitative and quantitative manner.3 Three types of techniques of SWE are given as: Point SWE (pSWE), one dimensional transient elastography (1DTE) and 2DSWE. pSWE is the oldest technique (introduced in 2008) and generates stress using ARFI at a ‘point/focal’ ROI, subsequently measuring SW generated perpendicular to it. B‐mode US is used to visualise the ROI with routinely used probes and machines. In 1D‐SWE, a mechanical vibrating device (plunger) is used to generate stress, after which, shear waves are measured parallel to these in a fixed ROI, without B‐mode US image guidance. This technique has been widely used commercially for estimation of LS and is popularly known as transient elastography (TE).4 To date, majority of literature has focused on TE because it is easily accessible, versatile and does not require extensive operator training.5, 6, 7 The disadvantages of TE include use of multiple probes based on patient weight and size, decreased accuracy for lower grades of fibrosis (≤ F2) and patients with ascites.6, 8
Two dimensional (2D) SWE has several distinct advantages and a definite leverage over TE since it can be easily incorporated into existing ultrasound hardware, with real‐time data acquisition (under direct visualisation).9 It is currently, the most popular technique, utilising ARFI for stress generation, involving multiple ROIs rapidly to create real‐time overlapping data in the form of a cylindrical cone which is used to measure the SW speed.
SWE sampling can be optimally targeted, while avoiding undesirable anatomical sampling sites and stiffness values can be interpreted easily over a wide range (2–150 kPa).8 Colour coded maps of SWE have been used to represent quantitative values with generation of elastograms and advancements in algorithm‐based interpretation.8
Tissue sampling is the universally accepted gold standard for appraisal of liver fibrosis.10 However, increasing recognition of various challenges owing to invasiveness related morbidity of the procedure, diversity of sampling and discrepancy amongst observers has shifted the focus from biopsy to non‐invasive diagnostic methods.11 Ultrasound‐based SWE, with its non‐invasive attribute is a far more attractive tool.12
Despite the far reaching impact of this application, use of ultrasound elastography for determination of aetiology and fibrosis grading of chronic liver disease (CLD) is unrealised. No existing study has, to the best of our knowledge, compared the mean liver stiffness and reference range values of mixed aetiology CLD population using 2D SWE. We primarily aimed to determine the SWE‐based cut‐off values and fibrosis grading of a mixed aetiology cohort of patients with CLD. Our secondary objective was to explore the possibility of discrimination of aetiology in the study population using stiffness values.
Patients and Methods
Method
The study was approved by the institutional ethical review board. Informed consent was obtained from all patients. A single centre, cross sectional prospective data of 124 patients was collected and analysed. The study design is illustrated in Figure 1.
Figure 1.
Study design. CLD, Chronic liver disease; EHPVO, Extrahepatic portal venous obstruction; USG, ultrasonography; BMI, Body mass index; 2DSWUE, Two dimensional shear wave ultrasound elastography; kPa, kilopascals; NASH, Nonalcoholic steatohepatitis; HBV, Hepatitis B virus.
Patient inclusion criteria
Patients with chronic liver disease (CLD) (anonymised mixed aetiology population) with BMI <25, referred for US and subsequently planned for percutaneous liver biopsy, solely on the basis of clinical indications (such as staging of disease activity and fibrosis), were included in the study group. The radiologist who performed the ultrasound and the readers who interpreted the ultrasound were blinded to prior clinical records, laboratory parameters, blood tests, imaging or histopathology (whichever was applicable).
Patient exclusion criteria
Patients who did not give consent to 2D SWE or liver biopsy, patients who had CLD attributable to vascular (hepatic venous outflow obstruction, extra‐hepatic portal vein occlusion), autoimmune or storage (Wilsons disease/hemosiderosis/hemochromatosis) disorders were excluded. Patients with incidental focal liver lesions, acute liver failure, severe or moderate hepatosteatosis (i.e. Grade 2–3 steatosis on previous Ultrasound) or BMI > 25 (to limit falsely raised values of LS), inadequate liver biopsy sample were excluded from the study.
The ‘control’ group patients were selected from the patient population who fulfilled the rest of the criteria but showed normal or (F0) fibrosis in all categories, collectively constituted the control group. They were included in the control group only if the fibrosis values were found within normal reference range of the equipment.
Ultrasonography‐elastography measurement
Participants were selected according to the above criteria. 2DSWE was performed at least a week before the planned biopsy. All patients were asked to remain fasting for at least four hours before the examination. B‐mode US scan was performed, using the Aplio 500 TOSHIBA US system with a convex broadband probe (6C‐1, 1–6 MHz), with patient comfortably lying in the supine position. On B‐mode US, the following parameters were measured: cranio‐caudal span of the liver, maximum spleen span (Figure 2), diameter of main portal vein/splenic vein and the presence of ascites (Figure 3). 2D SWE was performed using the convex broadband probe (6C‐1, 1–6 MHz). SWE measurements were obtained from the right lobe of the liver through the intercostal spaces with the patient lying in the supine position and the right arm in abduction. The area under interrogation was visualised by the operator using conventional, real‐time B‐mode imaging. It was ensured that the targeted region was devoid of major vessels, gallbladder or the bile duct. On identification of the suitable area, patients were asked to hold their breath for a few seconds. The 2D SWE was generated and the elasticity sampling region (measuring approximately 4 × 3 cm) was placed at least 2cm deep to the liver capsule (Figure 4a,c). A circular region of interest (ROI) with a 2‐cm diameter was positioned in an area of homogeneous colour within it and the liver stiffness (measured in kilopascals, kPa) was calculated via the automated software (Figure 4b,d). Ten consecutive samples of LS were obtained for each patient, and the mean value was used for each patient (Figure 4e). Splenic stiffness values were obtained, keeping in mind similar protocols. Ten consecutive values were obtained within the parenchyma and the average value was calculated for statistical analysis (Figure 5).
Figure 2.
Measurement of B‐mode US, parameters. (a) Ultrasonography machine used for the B‐mode and 2D SWE measurement, with the (inset) convex broadband probe (6C‐1, 1–6 MHz). (b) Cranio‐caudal span of the liver (longest span of the liver with patient in right oblique position, through the mid‐axillary line (callipers AA+). (c) Maximum spleen span; longest visualised length of spleen in the left hypochondrium (callipers BB+).
Figure 3.
Parameters measured on the B‐mode study a. Maximum diameter of the main portal vein at the porta (yellow arrow) b. Diameter of the splenic vein at the splenic hilum (yellow arrow) c. Presence of ascites (yellow arrow).
Figure 4.
Shear wave elastography (SWE) measurement of liver stiffness. (a, c) 2DSWE generated with the elasticity sampling region (blue rhomboid area, measuring approximately 4 × 3 cm, yellow arrow) placed at least 2 cm deep to the liver capsule within the parenchyma, b. Wave map of shear waves seen within the same area b, d. Circular region of interest (ROI) of 2‐cm diameter positioned in an area of homogeneous colour within the area of sampling d. Shear wave map showing the ROI placement in the centre of the area €. Mean value to represent the liver stiffness of ten consecutive 2‐D SWUE samples calculated via the automated software in the scanner (measured in kilopascals, kPa).
Figure 5.
Shear wave elastography (SWE) measurement of spleen stiffness. (a) 2DSWE generated with the elasticity sampling region (blue rhomboid area, measuring approximately 4 × 3 cm, yellow arrow) placed at least 2 cm deep to the splenic capsule within the parenchyma, b. Wave map of shear waves seen within the same area with circular region of interest (ROI) of 2‐cm diameter positioned in an area of homogeneous colour within the area of sampling c. Mean value to represent the splenic stiffness of ten consecutive 2‐D SWUE samples calculated via the automated software in the scanner (measured in kilopascals, kPa).
Two radiologists (STL, SVS with 13, 5 years’ experience respectively, in abdominal US and 2DSWE) who were blinded to the histopathology results, reviewed the measurements in consensus.
Liver biopsy and histopathology
All biopsy specimens were evaluated and scored in consensus by two experienced hepatopathologists (15, 8 years’ experience). They were blinded to the imaging results, with access to clinical and laboratory parameters. Biopsy was performed using an 18‐gauge biopsy gun and a trucut biopsy needle, after informed consent and ensuring normal coagulation profile. Percutaneous route through right lobe of liver under ultrasound guidance was used and specimens were fixed in formalin, embedded in paraffin. Haematoxylin–eosin (H&E) and Masson's trichrome stains (MTS) were used for examination and evaluation done with scoring system proposed by the NASH CRN, on recommendation of Kleiner et al.13
Morphological features of steatosis, ballooning, and lobular inflammation were semi‐quantitatively graded on H&E‐sections and fibrosis was staged on MTS liver tissue sections. NAS scoring measures features of active injury with unweighted sum of scores of steatosis (0–3), lobular inflammation (0–3), and hepatocellular ballooning (0–2) with final score ranging between 0 and 8. Grading for steatosis was as follows: grade I > 5–33%, grade II >33–66%, and grade III >66%. A calculated value of NAS <3 was classified as non‐NASH, 3–4 as possible NASH, and >5 as NASH. Fibrosis was staged as: stage 0: absence of fibrosis; stage 1: perisinusoidal or portal fibrosis [1a: mild (delicate) zone 3 fibrosis, 1b: moderate (dense) zone 3 fibrosis, 1c: portal fibrosis only]; stage 2: perisinusoidal and portal/periportal fibrosis; stage 3: septal or bridging fibrosis and stage 4: cirrhosis (Figure 6).13, 14
Figure 6.
(a) 2DSWE of a 53‐year‐old gentleman under evaluation for NASH with mean values of 11.9 kPa corroborating with F3 fibrosis as visualised in (b). Biopsy specimen photomicrograph (MT stain) panel shows features of NASH (F3 grade).
Diagnostic criteria for CHB monoinfection were HBsAg positive for 6 months, biopsy sample (at least 15 mm with six portal tracts or more) and treatment naive, confirmatory laboratory tests included hepatitis B e‐antigen, anti‐HBe, HBV DNA quantification, HBsAg, hepatitis B e‐antigen, anti‐HBe, HBV DNA (real‐time polymerase chain reaction, Cobas‐Taqman assay). Patients with coinfection (HCV or HIV), serum bilirubin >2.5 mg/dl or AST/ALT 10 times of the upper limit normal (ULN) range in last 6 months; regular consumption of 20 grams or more alcohol weekly were excluded.15
ALD was defined on a background of heavy regular alcohol intake till at least 60 days prior to the onset of jaundice.16 No single histological parameter is deemed to be characteristic of alcoholic hepatitis, hence a constellation of centrilobular accentuated steatosis, hepatocellular ballooning, Mallory‐Denk bodies, mixed inflammatory reaction comprising neutrophilic granulocytes and mononuclear cells along with perivenular and pericellular fibrosis, were the defining features.
Liver fibrosis was evaluated for HBV and ALD, according to the METAVIR scoring system as follows: F0, no fibrosis; F1, portal fibrosis without septa; F2, portal fibrosis and few septa; F3, numerous septa without cirrhosis; and F4, cirrhosis (Figure 7).17
Figure 7.
Histopathology of liver biopsy specimen photomicrograph (MT stain) panel shows features from 2 different patients: (a) 52 year old gentleman with hepatitis B virus infection, showed Grade F 2 fibrosis. (b) 47 year old male patient with alcoholic liver disease showed F4 fibrosis.
Statistical analysis
All the categorical variables were expressed either as percentage or proportion. Normally distributed continuous variables were expressed as mean ± standard deviations and non‐normal were expressed as median with interquartile range. Comparison of continuous variables which were normally distributed was done either by independent ‘sample t’ test or ANOVA followed by post hoc comparison using Bonferroni correction. The effect of each category of METAVIR on various parameters was analysed using nominal regression and quantification seen by odd ratio along with its 95% confidence interval (CI). An attempt was also made to find out various cut‐off values using either area under the curve by ROC method (ROC‐AUC) or by classification and regression tree (CART) analysis. Diagnostic tests like sensitivity, specificity, positive predictive values, and negative predictive values were derived to assess the performance of the test under the given conditions. Multinomial logistic regression was also applied to find out the quantification of each level. Data analysis was carried out by SPSS version 22.0 (IBM Corp Ltd, Armonk, NY). A p value less than 0.05 was considered as significant.
Ethical approval
Inform IEC/IRB immediately in case of any adverse events and serious adverse events. Inform IEC/IRB in case of any change of research team, study procedure/ protocol/ site/ discontinuation of the study. Provide a ‘final report’ when the project is completed.
Results
A total of n = 124 (94, 75% males, mean age 45.44 ± 12.4 years, mean BMI 19.66 ± 1.49) patients with diffuse liver disease underwent 2DSWE as per the methodology protocol described earlier, followed by liver biopsy. Of these, 50 (40%) patients had non‐alcoholic steatohepatitis (NASH), 31 (25%) had chronic hepatitis B and 43 (35%) had alcoholic liver disease (ALD) on histopathology. The baseline characteristics, LS, SS values and different grades of fibrosis of the entire study population have been enumerated in Table 1.
Table 1.
Comparison of baseline characteristics of three groups of chronic liver disease
| Parameters | Total (n = 124) | NASH (n = 50) | CHB (n = 31) | ALD (n = 43) | P value* |
|---|---|---|---|---|---|
| Age (in years) | 45.44 ± 12.4 | 46.76 ± 10.7 | 45.19 ± 15.9 | 44.09 ± 11.4 | 0.58 |
|
Gender Male: Female |
94: 30 | 31:19 | 26:5 | 37:6 | – |
| Liver span (in cm) | 12.86 ± 2.3 | 12.32 ± 2.3 | 13.06 ± 1.8 | 13.37 ± 2.5 | 0.07 |
| Spleen span (in cm) | 2.26 ± 2.7 | 11.6 ± 2.4 | 12.1 ± 2.3 | 13.23 ± 3.1 | 0.01 |
| Portal vein diameter (in mm) | 13.15 ± 2.1 | 13.3 ± 1.8 | 13.06 ± 2.3 | 13.12 ± 2.2 | 0.83 |
| Splenic vein diameter (in mm) | 10.4 ± 2 | 9.9 ± 2.2 | 10.23 ± 2.4 | 11.14 ± 2.6 | 0.04 |
| Ascites n (%) | 26 (21) | 1 (2) | 7 (22.6) | 18 (41.9) | <0.001 |
| F0 n (%) | 31 (25) | 11 (22) | 8 (25.8) | 12 (27.9) | 0.80 |
| F1 n (%) | 17 (13.7) | 9 (18) | 4 (12.9) | 4 (9.3) | 0.47 |
| F2 n (%) | 16 (12.9) | 6 (12) | 7 (22.6) | 3 (7) | 0.13 |
| F3 n (%) | 33 (26.6) | 13 (26) | 4 (12.9) | 16 (37.2) | 0.06 |
| F4 n (%) | 27 (21.8) | 11 (22%) | 8 (25.8%) | 8 (18.6%) | 0.75 |
Data is in Mean ± SD, ALD, alcoholic liver disease; CHB, chronic hepatitis B; cm, centimetre F0‐F4 (Fibrosis grading on histopathology from (F0) absent fibrosis to frank cirrhosis (F4); kPa, Kilopascals (unit of measurement of shear wave elastography); mm, millimetre; NASH, Non‐alcoholic steatohepatitis, *P value is among three groups of aetiology.
A total of n = 31 (25%) patients without fibrosis (F0) from all categories, collectively constituted the control group. All the parameters, including grades of fibrosis were classified according to disease aetiology (Table 1). It was observed that measurement of spleen span (p = 0.01), mean splenic vein diameter (p = 0.04) and presence of ascites (p < 0.001) showed a significant increasing trend from NASH to ALD. The prevalence of F3 fibrosis 16/33 (48.5%) was highest amongst patients with ALD (p = 0.06). Patients with NASH showed largest number of F1 fibrosis 9/17 (52.9%) p = 0.80, F2: 6/16 (37.5%) p = 0.13 and F4: 11/27 (40.7%) p = 0.75 fibrosis amongst all groups (Table 1).
All the baseline parameters of the study population were evaluated in comparison with grades of fibrosis on histopathology and were found statistically significant (Table 2).
Table 2.
Comparison of baseline characteristics of study population with histopathological grades of fibrosis
| Parameters | F0 (n = 31) | F1 (n = 17) | F2 (n = 16) | F3 (n = 33) | F4 (n = 27) | P value (rounded to 2 decimal points) |
|---|---|---|---|---|---|---|
| Age (in years) | 37.9 ± 11.7 | 53.7 ± 13.6 | 47.4 ± 1 | 46.9 ± 9.4 | 45.93 ± 11.9 | <0.001 |
| Gender M:F | 18:13 | 1:4 | 10:6 | 30:3 | 23:4 | 0.01 |
| Liver span (in cm) | 12.32 ± 1.8 | 12.6 ± 2 | 11.44 ± 2.1 | 13.8 ± 2.7 | 13.41 ± 1.7 | 0.00 |
| Spleen span (in cm) | 9.68 ± 1.2 | 12.41 ± 2.4 | 11.44 ± 1.8 | 13.82 ± 2.6 | 13.78 ± 2.2 | <0.001 |
| Portal vein diameter (in mm) | 11.45 ± 1.2 | 13.47 ± 2.1 | 13.31 ± 1.8 | 14.03 ± 2.3 | 13.9 ± 1.6 | <0.001 |
| Splenic vein diameter (in mm) | 8.29 ± 0.8 | 11.06 ± 2.1 | 10 ± 2.2 | 11.42 ± 2.7 | 11.44 ± 2 | <0.001 |
| Ascites n (%) | 0 | 2 (11.8) | 1 (6.3) | 13 (39.4) | 10 (37) | <0.001 |
Liver and spleen stiffness values were calculated on SWE to discriminate the grades (0‐4) of fibrosis with 0 denoting absence of fibrosis to 4 representing frank cirrhosis, on biopsy. The grades of fibrosis showed optimal differentiation and statistical significance on application of LS and SS values independently. Box‐whisker‐plots were plotted to depict the distribution of LS and SS values for grades of fibrosis and delineation of the three groups of CLD disease (Figure 8a,b).
Figure 8.
Box and whisker plot (a, b) Liver and spleen stiffness (LS, SS) respectively plotted along Y axis in comparison with aetiology of disease (NASH/CHB/ALD) along X axis. (c, d) Liver and spleen stiffness (LS, SS) respectively plotted along Y axis in comparison with grades of fibrosis (F0–F4) on histopathology along X axis.
For each grade of fibrosis (F0‐F4), statistically significant difference (p < 0.001) was demonstrated between LS and SS measurements (Figure 8c,d).
The area under curve (AUC) for the total patient population was calculated for LS and SS values based on three groups of CLD and fibrosis grading (Table 3, Figure S1–S7).
Table 3.
Liver (LS) and spleen (SS) stiffness of study population based on three CLD groups and fibrosis grading
| Final disease aetiology | Liver stiffness (LS) | Spleen stiffness (SS) | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| AUC (95% CI) | P value | Cut‐off (kPa) | Sensitivity | Specificity | AUC (95%CI) | P value | Cut‐off (kPa) | Sensitivity | Specificity | |
| NASH | 57 (46.9–67.2) | 0.18 | 10.5 | 56% | 56.8% | 64.4 (54.8–74) | 0.01 | 12.5 | 60% | 59.5% |
| CHB | 54.7 (43.1–66.3) | 0.43 | 10.5 | 54.8% | 53.8% | 49.2 (38–60.4) | 0.89 | 14.5 | 45.2% | 44.1% |
| ALD | 61.4 (50.3–72.4) | 0.03 | 11.5 | 62.8% | 58% | 64.6 (52.9–76.4) | 0.01 | 14.5 | 58.1% | 59.3% |
| As per pathology grading | ||||||||||
| F0 | 99.5 (98.8–1) | 0.00 | 7.5 | 100% | 93.5% | 98.6 (96.9–1) | 0.00 | 8.5 | 93.5% | 96.8% |
| F1 | 67.6 (58.9–76.3) | 0.02 | 8.5 | 64.7% | 68.2% | 54.4 (43.6–65.2) | 0.55 | 12.5 | 58.8% | 53.3% |
| F2 | 50.7 (40.9–60.5) | 0.93 | 11.5 | 56.3% | 50% | 55.2 (44.3–66.1) | 0.50 | 11.5 | 50% | 58.3% |
| F3 | 70.8 (62.1–79.5) | 0.00 | 12.5 | 66.7% | 68.1% | 73 (63.9–82.1) | 0.00 | 14.5 | 63.6% | 59.3% |
| F4 | 93.2 (88.9–97.5) | 0.00 | 14.5 | 85.2% | 83.5% | 83.7 (76.8–90.5) | 0.00 | 17.5 | 77.8% | 76.3% |
| F0 | 99.8 (99.3–100) | 0.00 | 7.09 | 96.8 | 97.8 | 99.2 (98–100) | 0.00 | 8.65 | 96.8 | 95.7 |
| Combined/merged groups of fibrosis | ||||||||||
| F1+F2 | 61.2 (51.6–70.8) | 0.05 | 10.2 | 63.6 | 59.3 | 55.3 (45.5–65.1) | 0.36 | 12.2 | 60.6 | 58.2 |
| F3+F4 | 96.1 (93.3–99) | 0.00 | 11.4 | 88.3 | 87.5 | 91.1 (86.2–96) | 0.00 | 13.3 | 81.7 | 81.2 |
It was observed that the sensitivity and specificity of cut‐off values for LS (55%, 54% respectively) were higher than SS (45%, 44%) for patients with CHB (p = 0.43) and ALD (LS 63%, 58% vs SS 58%, 59% respectively p = 0.03). LS cut‐off value was non‐discriminatory in NASH with lower sensitivity and specificity than SS values (p = 0.18) (Table 3, Figures S1–S7). For all grades of fibrosis (F1‐F4), LS was an overall better parameter (p < 0.05) than SS with a higher sensitivity and specificity except in F2 (LS p = 0.93 vs SS p = 0.50) (Table 3). To overcome this limitation, the F1‐F2 groups were merged and henceforth a higher discrimination (sensitivity 64%, specificity 60%, p = 0.05) was observed using LS.
Fibrosis values on biopsy of the subgroups of CLD were compared separately for LS and SS using ROC‐AUC values (Table 4). On applying the Post HOC analysis to assess the implication of LS values in differentiation of the three groups of CLD, it was observed that LS values showed higher differentiation between NASH and ALD (p = 0.09) but the differentiation between NASH and CHB (p = 1.0) or CHB and ALD (p = 0.25) as paired groups was lower.
Table 4.
Comparison of Area Under Curve (AUC) of LS and SS of three groups with the fibrosis grading on biopsy
| NASH (n = 50) | CHB (n = 31) | ALD (n = 43) | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| AUC (95% CI) | Cut‐off (kPa)/P value | Sensitivity/specificity | AUC (95% CI) | Cut‐off (kPa)/significance | Sensitivity/Specificity | AUC (95% CI) | Cut‐off (kPa)/P value | Sensitivity/Specificity | ||
| F0 | LS | 99.4 (98–100) | 6.5/0.00 | 90.9/100 | 99.7 (98.6–100) | 7.5/0.000 | 100/95.7 | 100 (100–100) | 7.5/0.00 | 100/100 |
| SS | 99.3 (97.8–100) | 8.5/0.00 | 100/94.9 | 100 (100–100) | 9/0.000 | 100/100 | 97.3 (92.4–100) | 9.5/0.00 | 100/93.5 | |
| F1 | LS | 70.3 (56.7–84) | 8.5/0.05 | 88.9/68.3 | 32.4 (15–49.8) | 8.5/0.26 | 50/33.3 | 68.6 (54–83.1) | 10.5/0.22 | 75/69.2 |
| SS | 58.7 (42.3–75) | 10.5/0.42 | 66.7/61 | 70.8 (44.7–97) | 17.5/0.18 | 75/63 | 60.3 (45–75.5) | 13/0.50 | 50/59 | |
| F2 | LS | 50.2 (33.7–66.6) | 9.5/0.98 | 50/45.5 | 55.4 (36–74.7) | 11/0.67 | 42.9/54.2 | 52.1 (32.2–72) | 13.5/0. 90 | 66.7/57.5 |
| SS | 53.6 (37.4–69.8) | 10.5/0.77 | 50/56.8 | 53 (31.5–74.5) | 16.5/0.81 | 42.9/50 | 73.3 (52.6–94) | 10.5/0.18 | 66.7/65 | |
| F3 | LS | 67.3 (53–81.6) | 10.5/0.06 | 61.5/62.2 | 68 (47–89) | 11/0.25 | 75/59.3 | 72 (56–87.8) | 14.5/0.01 | 68.8/66.7 |
| SS | 64.3 (49.2–79.5) | 12.5/0.12 | 53.8/64.9 | 56.9 (35.3–8.5) | 16.5/0.65 | 50/51.9 | 74.9 (59.8–89.9) | 29/0.01 | 75/74.1 | |
| F4 | LS | 97.7 (94.1–100) | 14.5/0.00 | 90.9/94.9 | 94.6 (87– 100) | 12.5/0.000 | 87.5/87 | 93.9 (86.2–100) | 16.5/0.00 | 75/85.7 |
| SS | 92.9 (85.5–100) | 14.5/0.00 | 90.9/84.6 | 81 (66.1–96) | 17.5/0.010 | 75/69.6 | 90.2 (79.7–100) | 35.5/0.00 | 75/77.1 | |
On considering NASH as the reference (lowest mean liver stiffness values in comparison to other groups) by nominal logistic regression (NLR) analysis, the Odds ratio (OR) of diagnosing CHB was found to be 1.01 (95% CI 0.93–1.01), p = 0.84. The OR of differentiating ALD from NASH was higher, that is 1.08 (95% CI 1.00–1.15) p = 0.04. We were consequently able to correctly classify (CC) 74% of NASH and 54% of ALD using LS values. However, CHB could not be discriminated from NASH or ALD using liver stiffness values on SWE.
Similar results for discrimination of subgroups NASH and CHB (p = 0.50) were observed by using SS values. SS, however, showed higher level of confidence in differentiating NASH from ALD (p < 0.0001) and CHB from ALD (p = 0.005). On applying NLR to the subgroups keeping NASH as reference (lowest mean SS values in comparison to other groups) the OR of diagnosing CHB was found to be 1.05 (95% CI 0.99–1.10), p = 0.98 and OR for ALD was 1.11 (95% CI 1.06–1.16) p < 0.0001 (Figures S1–S7). We could thus, correctly classify 86% of NASH and 52% of ALD on SWUE with a similar challenge for CHB classification. Though SS was observed to be better by 12 %, it is clinically known that liver stiffness values cannot be replaced by SS, hence LS may be assumed to be an optimum independent discriminating parameter.
Since the above ROC analysis could not provide more than 1 cut‐off value, CART was applied to determine a range of cut‐off values for stiffness measurements which would be clinically more relevant to categorise fibrosis. LS < 5.3 kPa would help in distinguishing NASH, 5.32 to < 12.64 kPa for CHB and > 12.64 kPa could be predictive of ALD. With the above cut‐offs, we could correctly classify 62% of NASH, 79% of ALD and 13% of CHB patients (Table 5, Figure S9a) in our study population.
Table 5.
Comparison of the ROC and CART analysis for optimum LS/SS cut‐off values among three groups of CLD
| Parameters | CART analysis | ROC analysis | ||||
|---|---|---|---|---|---|---|
| Cut‐off (kPa) | Correctly classified | Cut‐off (kPa) | Sensitivity | Specificity | ||
| NASH | LS | <5.3 | 62% | <10.5 | 56% | 56.8% |
| SS | <15.3 | 78% | <12.5 | 60% | 59.5% | |
| CHB | LS | 5.32 to <12.64 | 13% | 10.5 | 54.8% | 53.8% |
| SS | 15.3 to <30 | 55% | 14.5 | 45.2% | 44.1% | |
| ALD | LS | > 12.64 | 79% | >11.5 | 62.8% | 58% |
| SS | > 30 | 61% | >14.5 | 58.1% | 59.3% | |
| F0 | LS | <7.2 | 100% | 7.5 | 100% | 93.5% |
| SS | <8 | 90% | 8.5 | 93.5% | 96.8% | |
| F1 | LS | – | – | 8.5 | 64.7% | 68.2% |
| SS | – | – | 12.5 | 58.8% | 53.3% | |
| F2 | LS | – | – | 11.5 | 56.3% | 50% |
| SS | – | – | 11.5 | 50% | 58.3% | |
| F3 | LS | 12–18 | 64% | 12.5 | 66.7% | 68.1% |
| SS | – | – | 14.5 | 63.6% | 59.3% | |
| F4 | LS | >18 | 56% | 14.5 | 85.2% | 83.5% |
| SS | – | – | 17.5 | 77.8% | 76.3% | |
| F1+F2 | LS | 7–12 | 88% | 10.2 | 63.6% | 59.3% |
| SS | 9–14 | 77% | 12.2 | 60.6% | 58.2% | |
| F3+F4 | LS | – | – | 11.4 | 88.3% | 87.5% |
| SS | > 15 | 96% | 13.3 | 81.7% | 81.2% | |
Cut‐off SS values (using CART) were as follows :<15.3 kPa for NASH, CC (78%), 15.3 to <30 kPa for CHB, CC (55%) and >30 kPa indicative of ALD, CC (61%) (Table 5, Figure S9b).
The cut‐off values by CART method for LS/SS to predict fibrosis grading were as follows: LS < 7.2 kPa was equivalent to F0 (no fibrosis) (100% CC), 7–12.16 kPa for F1 and F2 collectively (CC 88%). LS of12.16–17.87 kPa could predict F3 (CC 64%) whereas stiffness >17.87 kPa was indicative of F4 fibrosis (CC 56%) (Table 5, Figure S9c).
SS < 8 kPa could be used for F0 (CC 90%), SS of 9–14 kPa, for F1and F2 collectively (CC 77%) and >14.9 kPa for F3 and F4 group (CC 96%) (Table 5, Figure S9c).
We compared both the methods (AUC‐ROC and CART) to estimate the optimum parameter for consideration (Table 5) and observed that in both methods, LS showed an overall higher percentage of correctly classified values and a greater sensitivity‐specificity for providing cut‐offs for grading of fibrosis and possible discrimination of aetiology in a mixed CLD population.
Discussion
There is a rising trend of annual global death toll (>1.32 million, constituting ≥2.4% of worldwide mortality) related to liver cirrhosis despite universally available diagnostic and therapeutic resources.18 Hence, it is imperative to step up the diagnostic capabilities of existing modalities such as SWE equipped US, for early diagnosis, screening‐ and surveillance of patients with CLD.
Our study aimed at conducting SWE paired with liver biopsy for a cohort of 124 patients who had clinically suspected mixed aetiology CLD, so as to establish the reference range and cut‐off values for LS/SS values as predictors of grade of fibrosis (in comparison with biopsy as the gold standard). Our secondary objective was to explore the possibility of LS‐SS values as reliable markers for discrimination of various subgroups (amongst our cohort: NASH, Alcohol and CHB related CLD) in a mixed population.
The majority (76%) of our study population were males, mean age 45.44 ± 12.4 years. This is in concordance with other studies, where men do not just have an inherently higher incidence and prevalence (approximately 64% men) but also a markedly higher progression to cirrhosis by middle age.19
The constitution of our cohort was based on aetiology: NASH (40%), ALD (35%) and CHB (25%). NASH is known to have a far‐reaching worldwide prevalence (25% of all adult population, 60% of all biopsied patients globally).20 ALD contributes approximately 50% in terms of overall liver mortality due to cirrhosis.21 CHB related infections constitute 3.5% of the world’s population with the second highest prevalence in India (approximately 17 million).22 Our study showed the highest prevalence of patients in NASH followed by ALD and CHB (Tables 1, 2). This likely represents the demography of the indigenous regional population from northern India and reflects the disease burden of our population.
On B‐mode US findings (Table 1), the average liver span (12.86 ± 2.27 cm) was in the normal range (reference 12–15 cm) suggesting that majority of patients either had normal liver size or were cirrhotic.20 Average spleen size was marginally prominent (12.26 ± 2.72 cm). A meta‐analysis has reported smaller spleen size to be a confounding factor for accurate measurement of SS (diagnostic range 54–76%).23, 24 This observation is probably due to a greater proportion of cirrhotic patients in these studies. A larger spleen size, dilated spleno‐portal axis and ascites have been attributed to the presence of decompensated liver function and portal hypertension (PHT) which are sequelae of advanced fibrosis/cirrhosis. In our study, half (49%) of the patients belonged to F3‐F4 fibrosis (p < 0.001) and hence these parameters were statistically significant (Table 1) amongst them. Parameters indicative of PHT had the highest frequency in the ALD group, which also happened to harbour maximum patients with F3‐F4 fibrosis, accounting for this distribution (Table 1). This observation indicates that strict surveillance is required at the F2 level so as to avoid escalation to F3‐F4 levels, wherein all indices have been observed to demonstrate maximum abnormality (Table 2).
Baseline parameters were observed to be statistically significant amongst the different grades of fibrosis (F0‐F4) (Table 2). F0 group (absence of fibrosis) served as the control group. Gradual decline in age was seen from F1‐F4, possibly due to early presentation of NASH (48% of total F3‐F4 patients) in younger patients. This has an important implication in strategising a more aggressive screening/surveillance approach, to facilitate early detection of disease in young people.
Different groups have studied the reference range of LS (5.19 ± 1.03 kPa) and SS (13.82 ± 2.91 kPa) for healthy people.25, 26 Our data showed that F0 values (control group) were in good agreement with values proposed from healthy volunteers in other studies [LS (5.16 ± 1.09 kPa), SS (6.9 ± 1.10)] (Table 5).27
A study by Ozturk et al used SWE to measure LS in NASH and observed the cut‐off values for high‐risk NASH as 8.4 kPa (AUC 0.73, sensitivity 77%, specificity 66%).28 Shi et al. valued cut‐off range for NAFLD in non‐obese population as: 5.8 kPa (F1), 7.6 kPa (F2), 9.1 kPa (F3), and 12.5 kPa (F4).29 A recent study from Singapore validated LS cut‐off values for significant fibrosis (>F2) as 9 kPa and for cirrhosis (F4) in CHB/hepatitis C as 12 kPa. They estimated cut‐off values for NASH (>F2) and (F4) as 11 and 15 kPa respectively.30
It has previously been demonstrated, that both LS and SS are equally good parameters for assessment of fibrosis and their credibility is more pertinent at lower grades of fibrosis rather than at a later stage of cirrhosis, where their ratio has been observed to decrease.24 On our initial observation, we validated both LS and SS as equally good parameters for differentiating all grades of fibrosis (Figure 8). However, on an attempt to corroborate our results by a comparative analysis of ROC‐AUC values with the NLR‐CART results, we observed an overall better performance of LS for fibrosis grading as well as disease discrimination (Table 5). It would however be prudent to use SS as an add‐on tool to improve accuracy in discrimination of CHB (by 32%) and NASH (by 16%) in a mixed aetiology population. The optimal cut‐off values for CHB would require further validation in future studies.
The sensitivity and specificity of LS cut‐off values for F1 and F4 diagnosis were reasonably acceptable (Tables 4, 5). In order to increase the diagnostic efficacy and discriminatory power of 2DSWUE for F2 and F3, SS values were observed to provide value addition to LS (Tables 5, 6). Grouping of F1‐F2 and F3‐F4 categories was also shown to improve discriminatory power, similar to other studies (Table 6).
Table 6.
Comparison of grades of fibrosis and cut‐off values in our study population with previous studies
| Author | (n) | Equipment on which studied | Aetiology | Fibrosis Stage | AUROC | Cut‐off liver stiffness (kPa) | Sensitivity (%) | Specificity (%) |
|---|---|---|---|---|---|---|---|---|
| Suh et al. (2014)27 | 196 | Aixplorer (Supersonic Imagine, Aix Provence, France) | Normal control group |
F0 F > 1 |
92 | 2.6–6.2 | 91 | 96 |
| Laroia et al. (2020) (our analysis) | 124 |
Aplio 500 TOSHIBA |
Normal control group |
F0 (NASH) F0 (CHB) F0 (ALD) |
99.4 100 100 |
6.5 P = 0.00 7.5 P = 0.00 7.5 P = 0.00 |
100 100 100 |
95 96 100 |
| Cassinotto et al. (2016)31 | 291 | Aixplorer (Supersonic Imagine, Aix Provence, France) | NASH |
≥F2 ≥F3 F = 4 |
86 89 88 |
8.9 9.3 10 |
68 84 95 |
94 83 69 |
| Takeuchi et al. (2018)32 | 71 | Aixplorer (Supersonic Imagine, Aix Provence, France) | NASH |
≥F2 ≥F3 F = 4 |
75 82 90 |
11.6 13 15.7 |
52 63 100 |
44 57 82 |
| Herrmann et al. (2018)33 | 156 | Aixplorer (Supersonic Imagine, Aix Provence, France) | NASH |
≥F2 ≥F3 F = 4 |
85 93 91 |
7.1 9.2 13 |
93 93 75 |
52 80 87 |
| Laroia et al. (2020) (our analysis) | 124 |
Aplio 500 TOSHIBA |
NASH |
F ≥ 1 F ≥ 2 F ≥ 3 F = 4 |
70 50 67 97 |
8.5 9.5 10.5 14.5 |
89 50 62 91 |
68 46 62 91 |
| Zeng et al. (2017) 34 | 257 | Not mentioned | CHB |
≥F2 ≥F3 F = 4 |
88 91 92 |
7.1 8.3 11.3 |
89 89 93 |
76 76 87 |
| Zhuang et al. (2017)35 | 304 | Aixplorer (Supersonic Imagine, Aix Provence, France) | CHB |
≥F2 ≥F3 F = 4 |
97 96 98 |
7.6 9.2 10.4 |
92 91 94 |
90 96 94 |
| Herrmann et al. (2018)33 | 379 | Aixplorer (Supersonic Imagine, Aix Provence, France) | CHB |
≥F2 ≥F3 F = 4 |
90 93 95 |
7.1 8.1 11.5 |
87 94 79 |
73 73 93 |
| Laroia et al. (2020) (our analysis) | 124 |
Aplio 500 TOSHIBA |
CHB |
F ≥ 1 F ≥ 2 F ≥ 3 F = 4 |
32 55 68 95 |
8.5 11 11 12.5 |
50 43 75 88 |
69 52 72 94 |
| Thiele et al. (2016)36 | 199 | Aixplorer (Supersonic Imagine, Aix Provence, France) | ALD |
F ≥ 2 F ≥ 4 |
94 95 |
10.2 16.4 |
82 94 |
93 91 |
| Laroia et al. (2020) (our analysis) | 124 |
Aplio 500 TOSHIBA |
ALD |
F ≥ 1 F ≥ 2 F ≥ 3 F = 4 |
69 52 72 94 |
10.5 13.5 14.5 16.5 |
75 66 68 75 |
69 58 67 86 |
Our analysis has shown a comprehensive evaluation of diagnostic accuracy of SWUE for a mixed population of CLD patients with baseline, normal (F0) values for each category as a discrete range (Table 6).27 It is imperative to identify patients with underlying increase in liver stiffness, without obvious liver parenchymal changes on imaging, for better disease management and prognosis. For NASH, we compared our data with recent papers and found our results in approximation to the prescribed reference range (Table 6).31, 32, 33 Similar findings were observed in the CHB subgroup. In addition, we have computed values for each category (F0‐F4) compared to other studies where early fibrosis (F1) has not been included and emphasis is mainly on F2‐F4 (Table 6).34, 35
Only a few studies have reported fibrosis cut‐off using SWUE in ALD.36 Ours is the first study from the Indian subcontinent to estimate the same and provide reasonably adequate cut‐off values for all grades of fibrosis (Table 6).
Our study had a few limitations; sample selection bias (referrals for biopsy within a study population are for suspected disease burden, more often F3‐F4 or asymptomatic patients with abnormal LFT (likely F1‐F2), exclusion of raised BMI patients, performing the study on a specific (in our study‐ Toshiba) system, with inherent variation of stiffness values as per the particular vendor. No existing recommended quality control criteria for accuracy or interpretation of 2DSWUE are known. Intrinsic inconsistency in tissue stiffness of patients with surreptitious acute insult, cholestasis or alcohol abuse may lead to over or under estimation of fibrosis on biopsy.
Through our prospective, biopsy paired study, based on SWUE‐ LS/SS estimation of fibrosis amongst a mixed CLD population, we have successfully demonstrated a range of cut‐off values to quantify fibrosis in different subgroups with adequate discrimination. The cut‐off values for LS (NASH < 5.3 kPa, CHB 5.32 to <12.64 kPa, ALD > 12.64 kPa) could distinguish the three categories of CLD in a mixed population. Supplementing SS values to LS provided better discrimination for select patients with CHB and NASH.
In future, more studies may be required to assess larger cohorts of CLD for a comprehensive approach to quantification of fibrosis using LS/SS as objective parameters.
Conclusion
2D SWE demonstrates potential as a non‐invasive tool for assessment of liver fibrosis staging in a mixed population of CLD. LS is a reliable predictor of fibrosis; however, SS is a valuable add‐on tool for better discrimination of F2‐F3 fibrosis and select categories like CHB and NASH in a mixed population.
Funding
This research work has not received any funding and has no source of financial support. None of the authors have any financial relationship with the organisation.
Conflict of interest statement
There is no conflict of interest of any of the authors who have contributed to this manuscript.
Author contributions
Shalini Thapar Laroia: Conceptualisation (equal); Data curation (equal); Formal analysis (equal); Investigation (equal); Methodology (equal); Project administration (equal); Resources (equal); Software (equal); Supervision (equal); Validation (equal); Visualisation (equal); Writing‐original draft (equal); Writing‐review & editing (equal). Shyam V S : Data curation (equal); Formal analysis (equal); Investigation (equal); Methodology (equal); Resources (equal); Validation (equal); Visualisation (equal); Writing‐review & editing (equal). Komal Yadav: Data curation (equal); Validation (equal); Visualisation (equal); Writing‐review & editing (equal). Archana Rastogi: Data curation (equal); Formal analysis (equal); Investigation (equal); Methodology (equal). Senthil Kumar: Methodology (supporting); Project administration (supporting); Writing‐original draft (supporting). Guresh Kumar: Formal analysis (equal); Software (equal); Validation (equal); Writing‐review & editing (supporting). Manoj Kumar : Data curation (supporting); Investigation (supporting); Project administration (supporting); Supervision (supporting).
Supporting information
Figure S1 ROC curves based on Table SF2 for all parameters using Liver and spleen stiffness (LS/SS).
Table S1 Generalised characteristics and mean values of control group (n = 31)
Table S2 Cut off values for Liver and spleen stiffness.
Acknowledgements
We acknowledge the efforts of our technical staff Abhishek Kumar and Rita Gulabani for their expertise.
Data availability statement
No patient identification data are included in this article.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Figure S1 ROC curves based on Table SF2 for all parameters using Liver and spleen stiffness (LS/SS).
Table S1 Generalised characteristics and mean values of control group (n = 31)
Table S2 Cut off values for Liver and spleen stiffness.
Data Availability Statement
No patient identification data are included in this article.