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The severity of portal hypertension by a non-invasive assessment: acoustic structure quantification analysis of liver parenchyma

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Background: Acoustic structure quantification (ASQ) has been applied to evaluate liver histologic changes by analyzing the speckle pattern seen on B-mode ultrasound. We aimed to assess the severity of portal hypertension (PHT) through hepatic ultrasonography. Methods: Sixty patients diagnosed with PHT and underwent surgical treatment with portosystemic shunts were enrolled. Portal pressure (PP) was measured intraoperatively. Patients were divided into subgroups according to the severity of gastroesophageal varices and Child-Pugh class. Three difference ratio (Cm2) values on ASQ histogram mode were analyzed for their relationships with PP, degree of gastroesophageal varices and Child-Pugh liver function. Thirty healthy volunteers matched with the patients for gender and age were enrolled as controls. Comparisons among groups and correlation of the parameters with PP were analyzed. Area under the receive operating characteristic curve was used to evaluate the predicting value of ASQ parameters. Results: In the patients, the ASQ parameters peak Cm2 (Cm2max), mean Cm2 (Cm2mean) and the highest occurred Cm2 value of the obtained red curve (RmaxCm2) were all greatly increased (P < 0.0001, P < 0.0001, P = 0.027). Multiple comparisons indicated that, regardless of Child-Pugh class and degree of gastroesophageal varices, the patients had significantly increased Cm2max and Cm2mean compared with the controls (all P < 0.0001). No differences among subgroups were observed. Cm2max was significantly statistically correlated with PP (r = 0.3505, P < 0.01), degree of varices (r = 0.4998, P < 0.0001). Youden's index for Cm2max with a cut-off value of 140.3 for predicting the presence of PHT, gastroesophageal varices and liver function equal to or worse than Child-Pugh class B were 0.8, 0.91 and 0.84, respectively. Conclusions: ASQ analysis of ultrasonographic images may have a role in the evaluation of the severity of PHT by detecting liver histologic changes in the speckle pattern caused by cirrhosis.
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Caietal. BMC Medical Imaging (2022) 22:85
https://doi.org/10.1186/s12880-022-00817-2
RESEARCH
The severity ofportal hypertension
byanon-invasive assessment: acoustic structure
quantication analysis ofliver parenchyma
Wen‑Bin Cai1,3†, Ji‑Kai Yin2†, Qiao‑ying Li1, Yi‑Lin Yang1, Yun‑You Duan1 and Li Zhang1*
Abstract
Background: Acoustic structure quantification (ASQ) has been applied to evaluate liver histologic changes by ana‑
lyzing the speckle pattern seen on B‑mode ultrasound. We aimed to assess the severity of portal hypertension (PHT)
through hepatic ultrasonography.
Methods: Sixty patients diagnosed with PHT and underwent surgical treatment with portosystemic shunts were
enrolled. Portal pressure (PP) was measured intraoperatively. Patients were divided into subgroups according to the
severity of gastroesophageal varices and Child–Pugh class. Three difference ratio (Cm2) values on ASQ histogram
mode were analyzed for their relationships with PP, degree of gastroesophageal varices and Child–Pugh liver func‑
tion. Thirty healthy volunteers matched with the patients for gender and age were enrolled as controls. Comparisons
among groups and correlation of the parameters with PP were analyzed. Area under the receive operating character‑
istic curve was used to evaluate the predicting value of ASQ parameters.
Results: In the patients, the ASQ parameters peak Cm2 (Cm2max), mean Cm2 (Cm2mean) and the highest occurred
Cm2 value of the obtained red curve (RmaxCm2) were all greatly increased (P < 0.0001, P < 0.0001, P = 0.027). Multiple
comparisons indicated that, regardless of Child–Pugh class and degree of gastroesophageal varices, the patients
had significantly increased Cm2max and Cm2mean compared with the controls (all P < 0.0001). No differences among
subgroups were observed. Cm2max was significantly statistically correlated with PP (r = 0.3505, P < 0.01), degree of
varices (r = 0.4998, P < 0.0001). Youden’s index for Cm2max with a cut‑off value of 140.3 for predicting the presence of
PHT, gastroesophageal varices and liver function equal to or worse than Child–Pugh class B were 0.8, 0.91 and 0.84,
respectively.
Conclusions: ASQ analysis of ultrasonographic images may have a role in the evaluation of the severity of PHT by
detecting liver histologic changes in the speckle pattern caused by cirrhosis.
Keywords: Acoustic, Ultrasound, Portal hypertension, Gastroesophageal varices, Noninvasive
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Introduction
Variceal bleeding due to gastroesophageal varices is
associated with high mortality in patients with portal
hypertension (PHT) [1]. Preventive surgery is recom-
mended and the selection of optimal candidates is based
on an assessment of liver function and portal pressure
(PP). us, measurement of PP is important in patients
with suspected PHT. Hepatic venous pressure gradient
Open Access
Wen‑Bin Cai and Ji‑Kai Yin contributed equally to this work
*Correspondence: lilyzhang319_20@hotmail.com
1 Department of Ultrasound Diagnosis, Tangdu Hospital, The Fourth Military
Medical University, Xin Si Road, Ba Qiao District, Xi’an, China
Full list of author information is available at the end of the article
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Page 2 of 9
Caietal. BMC Medical Imaging (2022) 22:85
(HVPG) is considered the gold standard for PHT assess-
ment in patients with cirrhosis [25], but the invasiveness
and need for expertise in performing the examination
limit its use in routine clinical practice. It would be help-
ful to have noninvasive methods capable of predicting,
with acceptable diagnostic accuracy, the severity of clini-
cally significant PHT.
Many methods have been proposed for assessing
patients with PHT, especially to detect those with a high
risk of variceal bleeding. Based on the dynamic changes
of PHT [6], Doppler parameters have been suggested as
a substitute for the invasive measurement of HVPG [7
9]. Due to the “static component” of PHT—a mechani-
cal consequence of the associated hepatic architectural
disorder—research has focused on analyzing cirrhotic
liver parenchyma by ultrasound. Methods include liver
stiffness measurement by means of transient elastogra-
phy (TE) [1012], strain elastography [1315] or shear
wave elastography [1618] As reported by Yamaguchi
etal. [19, 20] B-mode images of liver parenchyma con-
tain numerous fine echo spots, called “speckle pattern”
images [1921]. Image analysis of speckle patterns can
be used to identify tissue characteristics resulting from
structural changes.
Acoustic structure quantification (ASQ), proposed by
Toyoda etal. [22], uses sonographic software to analyze
statistical information about acquired echo signals. e
physical principle is that the scatter or deflection of the
ultrasound wave when propagating through tissues var-
ies according to the acoustic interfaces it encounters.
In normal liver, the scattering fits a Rayleigh distribu-
tion [23, 24] because of the presence of many structures
smaller than the wavelength of the typical ultrasound
wave. By considering the speckle pattern in a region of
interest (ROI), quantitative analysis of liver tissue can be
used to assess the degree of hepatic fibrosis. Ultrasound
wave scattering is increased in fibrotic liver parenchyma
compared with normal conditions. ASQ could therefore
be a helpful tool in quantifying diffuse liver disease and
monitoring regression/progression in patients with liver
fibrosis and the effects of fibrosis treatment [2527].
In this study, we evaluated this quantitative imaging
technique through intraoperative measurements of the
difference ratio (Cm2) of patients with PHT and PP and
the degree of gastroesophageal varices and liver function
according to Child–Pugh score, aiming to determine the
value of ASQ in predicting the severity of PHT.
Material andmethods
Ethical approval ofthestudy protocol
All subjects included in the study provided written
informed consent to participate. e study protocol was
approved by the ethics committee of the Air Force Medi-
cal University Tangdu Hospital, Xi’an, China.
Patients andcontrol subjects
e subjects of the study were enrolled from a consecu-
tive series of patients with previously or newly diagnosed
PHT who were admitted to the Fourth Military Medi-
cal University Tangdu Hospital between April 2010 and
January 2012. Patients with hepatocellular carcinoma or
intrahepatic thrombosis were excluded from the study.
According to the sample size calculation for a two-
sample comparison, 60 patients were needed. Patients
referred for surgical therapy with portosystemic shunts
were enrolled. e indications for shunt surgery in PHT
patients include: severe hypersplenism with white blood
cell count < 2.0 × 109/L and platelets < 30 × 109/L; and a
history of bleeding or severe gastroesophageal varices
seen on endoscopy. Subjects in the patient group were
further divided into subgroups according to Child–Pugh
scoring criteria [28] and the severity of gastroesophageal
varices (small/large), which was determined by endo-
scopic examination as recommended that quantitative
size with a suggested cut-off diameter of 5mm, with large
varices being those greater than 5mm [29].
irty healthy volunteers matched with the patients
for gender and age were also enrolled. e subjects in
the control group had no history of chronic liver disease,
pulmonary disease or cardiovascular disease. Laboratory
tests showed normal liver function and normal complete
blood count.
ASQ ofliver
e patients underwent ultrasound examination on
the day before surgery with dedicated equipment and a
5–7MHz convex probe (Aplio 500; Toshiba Medical Sys-
tems, Osaka, Japan) to identify the best acoustic window
for ASQ. Each subject was placed in the supine or left
lateral position and two images (axial plane and sagit-
tal plane) of the right lobe at intercostal spaces 7 and 8
were obtained. As reported previously, parenchymal ves-
sels and perivascular connective tissue are responsible
for marked variation in ASQ findings [22]. e display
depth and transmit focus were set to 4cm. When images
showing a high proportion of parenchyma free from large
vascular structures and perivascular connective tissue
were observed, the “ASQ” button was pressed and the
raw data collected and stored for offline processing by
the integrated software. Real time images were collected
over 3s, preferably intercostal and subcostal at maximal
inspiration.
All images obtained for ASQ analysis were displayed as
color-coded maps based on the amplitude of echoes and
on the scattering (i.e. the deflection of the ultrasound
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Caietal. BMC Medical Imaging (2022) 22:85
wave) produced by different tissue interfaces (Fig. 1a).
e ROI was positioned at a depth of 4–6cm depending
on the dimensions of the area of the liver that was most
free from Glisson’s capsules, as previously reported. e
results were displayed on a Cm2 histogram (Fig.1b). e
output data of the ASQ analysis were in the form of Cm2
values, Cm2 being a statistical parameter derived from the
distribution of the echo amplitude. It is calculated using
the equation
C
2
m=
σ
2
m
σ2
R
(µ)
=π
4πσ
2
m
µ2
m and can also be
expressed as:
C2
m
=
Measured Variance
Estimated Variance of normal liver
[%
]
,
where μ and σ2 are the average and variance, respectively,
of the echo amplitude in a small ROI and σm is the vari-
ance calculated from limited samples of less than μ + 4σ.
σR2(µ) is the variance of the Rayleigh distribution esti-
mated from the measured average.
e calculated ASQ parameters were: Cm2max (the
peak value of Cm2); Cm2mean (the mean value of Cm2);
and RmaxCm2 (the highest occurred Cm2 value of the red
curve).As an innovative measurement, it is necessary to
test the reliability. 10 patients and 10 healthy volunteers
were tested by two operators for inter-operator variabil-
ity and were tested by one operator twice for intra-oper-
ator variability. e inter/intra-operator variability were
tested by Intraclass Correlation Coefficient analysis.
Doppler ultrasonography
All subjects underwent conventional abdominal Dop-
pler ultrasonography with a 3.5MHz transducer (Aplio
500; Toshiba Medical Systems, Osaka, Japan). For ASQ,
the probe with a much higher frequency (5–7 MHz)
were applied to acquire high resolution imaging in near
field, but for conventional B mode scanning, especially
for Doppler ultrasound measurement, a low frequency
ultrasound with strong penetration was better. Doppler
parameters including velocity and resistive index were
measured at 30°–60°. e Doppler gate was placed in the
porta hepatis and in the hilum of the spleen to measure
parameters for the portal vein, hepatic artery and splenic
artery. Velocity measurements were made at an angle of
30°–60°. e mean velocity in the portal vein (PVVel),
the hepatic artery resistive index (HARI) and the splenic
artery resistive index (SpARI) were calculated automati-
cally by the machine after the waveform traces for three
cardiac cycles had been obtained. e portal hyperten-
sion index (PHI) was calculated as: PHI = (HARI × 0.69)
(SpARI × 0.87)/PVVel [30, 31]. ey were calculated as
the mean of three measurements.
Measurement ofPP
e drugs used for general anesthesia were the same in
all subjects. Heart rate, electrocardiogram, oxygen satu-
ration, end-tidal carbon dioxide pressure, blood pressure
and temperature were monitored continuously. Intraop-
eratively, with the blood pressure kept constant, the right
gastroepiploic vein was isolated and catheterized with a
pressure gauge to measure the PP. An examiner (Ji-Kai
Yin) with 8years of experience of PP measurement dur-
ing surgery performed all PP studies. e mean value of
PP was calculated from three repeated measurements.
Statistical analysis
Data were presented as the mean ± standard devia-
tion. Differences between the patient group and control
group were tested using the unpaired Student’s t-tests.
As an innovative measurement, the inter/intra-operator
variability of ASQ were tested by Intraclass Correlation
Coefficient analysis. All ASQ variables were normal dis-
tributed. e Tukey–Kramer multiple comparisons was
Fig. 1 Acoustic structure quantification (ASQ) analysis images obtained from a patient with portal hypertension, right lobe of liver. a Histogram
display of the right lobe; b the corresponding ASQ curve for the difference ratio (Cm2). The red curve represents the value of Cm2 in the region of
interest; higher inhomogeneous inconsistent values are indicated by the blue curve
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Caietal. BMC Medical Imaging (2022) 22:85
used for assessing whether there was a significant differ-
ence of the ASQ parameters among subgroups accord-
ing to the Child–Pugh scoring and the gastroesophageal
varices grade. Spearman’s rank correlation coefficient
and linear regression (simple linear model) analysis were
used to assess correlations among the ASQ parameters
with PP, Child–Pugh score and varices grade, as the last
two were semi-quantitative data and ranked data. e
predictive performance of the ASQ parameters for PHT
diagnose, liver function evaluation and varices grading
were tested using receiver operating characteristic (ROC)
curve analysis and expressed in terms of accuracy, sensi-
tivity, specificity and Youden’s index (YI) for several cut-
off values. Results were considered significant at P < 0.05.
e statistical software package SPSS 12.0 (SPSS Inc.,
Chicago, IL) was used for all data analyses.
Results
Sample characteristics
Sixty consecutive patients (46 men and 14 women;
median age, 47 years) who underwent portosystemic
shunt surgery were enrolled in the present study. ere
was no significant difference between patients and
healthy controls (22 males and 8 females; age range,
32–58years) as far as gender and age were concerned.
e main clinical and pathologic data for the patients
were presented in Table1. Hepatitis B was the most com-
mon etiologic factor and was present in 40 cases (67%).
Hepatitis C was the cause of cirrhosis in 14 patients
(23%). Liver function was classified according to Child–
Pugh score as follows: A in 17 (28%) patients; B in 37
(62%); and C in six (10%). Most patients (70%) had light
ascites. Among the PHT patients enrolled in our study,
55 had a history of bleeding (12 patients had suffered
more than one episode; 43 had a single episode). Twelve
patients with multiple bleeding history cannot endure
endoscopic examination, the extent of gastroesophageal
varices was unknown. e rest five patients without a
bleeding history were diagnosed with severe hypersplen-
ism and no gastroesophageal varices were seen on endos-
copy. Of the patients who had suffered a single episode of
bleeding, 35 had large gastroesophageal varices and eight
had small gastroesophageal varices on endoscopy. e
mean PP measured directly from the right gastroepiploic
vein was 28.85 ± 3.134mm Hg.
Comparisons ofASQ andDoppler parameters
As shown in Additional file1, the ICC of patient RmaxCm2
were 0.927 (inter-operator variability) and 0.963 (intra-
operator variability). at of healthy volunteers RmaxCm2
were 0.948 (inter-operator variability) and 0.980 (intra-
operator variability). e inter/intra-operator variabil-
ity of ASQ were highly consistent. Comparisons of the
Doppler and ASQ parameters among the patients and
healthy subjects are shown in Table2. e ASQ parame-
ters Cm2max and Cm2mean, except RmaxCm2 in PHT patients
were much higher than those in the healthy subjects,
with P < 0.01. e Doppler parameter PHI in the patient
group was 1.843 ± 0.6205m s–1, which increased greatly
compared with the healthy controls. Multiple compari-
sons indicated that, regardless of Child–Pugh class and
degree of gastroesophageal varices, the patients had sig-
nificantly increased Cm2max and Cm2mean compared with
the controls (all P < 0.0001). No differences were observed
among the subgroups. e statistical significance of dif-
ferences in Cm2max and Cm2mean between groups was
shown in Fig.2.
Correlations ofASQ parameters withPHT severity
andDoppler parameters
e statistical significance of correlations between ASQ
parameters, PHT and Doppler parameters were evalu-
ated using Spearman’s rank correlation coefficient and
linear regression analysis, as shown in Fig. 3. In the
patients with PHT enrolled in our study, Cm2max was
significantly statistically correlated with PP (r = 0.3505,
P < 0.01), degree of varices (r = 0.4998, P < 0.0001) and
Table 1 Clinical and pathologic characteristics of 60 patients
with PHT
Patient characteristics
Age (years), median (range) 47 (26–59)
Sex (F/M) 14/46
Etiology of liver disease
Post‑hepatitis B 40
Post‑hepatitis C 14
Alcoholic 3
Cryptogenic 3
Child–Pugh class (A/B/C) 17/37/6
Ascites (absent/light/moderate/severe) 8/42/8/2
Gastroesophageal varices
Absent 5
Present (small/large) 8/35
Not available 12
PP (mm Hg), mean ± SD 28.85 ± 3.134
Table 2 Comparison of ASQ and Doppler parameters between
healthy subjects and patients
US variables Healthy Control Patients with PHT P-value
Cm2max 126.8 ± 9.886 153.9 ± 13.30 < 0.0001
Cm2mean
RmaxCm2
PHI(m s1)
111.7 ± 18.12
115.4 ± 8.991
1.434 ± 0.3057
139.5 ± 8.553
119.9 ± 8.511
1.843 ± 0.6205
< 0.0001
0.0272
0.0012
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Caietal. BMC Medical Imaging (2022) 22:85
the Doppler parameter PHI (r = 0.4136, P < 0.01). Cm2mean
was significantly correlated with degree of varices only
(r = 0.4118, P < 0.01). RmaxCm2 in PHT patients showed
no obvious relationship with Child–Pugh scores, varices
grade or PHI. None of the ASQ parameters showed a sig-
nificant correlation with Child–Pugh scores, with P-val-
ues of 0.1663, 0.0920 and 0.5341 for Cm2max, Cm2mean and
RmaxCm2, respectively. PHI correlated with PP; namely,
at higher PP, increased PHI was observed (r = 0.3609,
P = 0.0046) (Fig. 4), but not with Child–Pugh scores and
varices grade.
Given the above statistical results, the predictive per-
formance of Cm2max, as the most ideal parameter, was
analyzed. e diagnostic YI values for Cm2max with a
cut-off value of 140.3 in predicting the presence of PHT,
gastroesophageal varices and liver function equal to or
Fig. 2 Statistical significance of differences for acoustic structural quantification parameters analyzed by unpaired Student’s t‑tests or Tukey’s
multiple comparison tests as indicated. a Peak difference ratio (Cm2max) with Child–Pugh class; b mean difference ratio (Cm2mean) with Child–Pugh
class; c Cm2max with severity of gastroesophageal varices; d Cm2mean with severity of gastroesophageal varices. N.S., not significant
Fig. 3 Correlations among acoustic structure quantification parameters, portal hypertension severity and Doppler parameters. Positive
relationships were found between a peak difference ratio (Cm2max) and portal pressure (PP); b both Cm2max and mean difference ratio (Cm2mean) with
degree of varices; and c Cm2max and the Doppler parameter portal hypertension index (PHI)
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Caietal. BMC Medical Imaging (2022) 22:85
worse than Child–Pugh B were 0.85 (sensitivity, 91.67%;
specificity, 93.33%), 0.91 (sensitivity, 97.67%; specificity,
93.33%) and 0.84 (sensitivity, 90.70%; specificity, 93.33%),
respectively. For predicting the presence of a large area
of gastroesophageal varices, the diagnostic cut-off value
was 142.4 and the corresponding YI was 0.91 (sensitiv-
ity, 94.29%; specificity, 96.67%). In PHT patients with
Child–Pugh C liver function, where Cm2max was 132.3,
YI reached its highest value of 0.73. e predictive per-
formance including the area under the curve, sensitivity,
specificity and YI with corresponding cut-off values is
summarized in Table3. ROC curves are shown in Fig.5.
Discussion
Increased PP in patients with chronic liver disease leads
to a high risk of developing gastroesophageal varices
and decompensation of liver function. Because gastroe-
sophageal varices-induced hemorrhage in patients with
cirrhosis can be fatal, these patients must be routinely
classified according to their risk status and appropriate
therapy should be undertaken to prevent hemorrhage.
Endoscopy is the gold standard method for screening
for esophageal varices in cirrhotic patients; however, the
extent of esophageal varices can vary and follow-up for
variceal bleeds is needed, which limits its routine appli-
cation. HVPG is an acceptable indirect measurement of
PHT and predictor of the complications of PHT. It is a
strong and independent predictor of death in both com-
pensated and decompensated cirrhosis [32, 33]. Variceal
bleeding does not occur at pressures under 12mm Hg as
indicated by HVPG. No noninvasive method is available
to replace HVPG measurement or endoscopy in the rapid
discrimination of stage of liver cirrhosis and post-treat-
ment evaluation, and we remain in need of noninvasive
means to predict the presence or absence of gastroesoph-
ageal varices.
Fig. 4 Correlation between the Doppler parameter portal
hypertension index (PHI) and portal pressure (PP). PHI was found to
be positively correlated with PP
Table 3 Predictive performance of Cm2max for the assessment of PHT severity
a AUC, area under ROC curve
b CI, condence interval
c Child-Pugh class B means that liver function according to the Child–Pugh score was equal to or worse than the Child–Pugh B
AUC
aStd. Error P-value 95% CIbCut-o Sensitivity (%) Specicity (%) YI
Presence of PHT 0.9639 0.0217 < 0.0001 0.9213 to 1.006 140.3 91.67 93.33 0.85
Varices 0.9736 0.0197 < 0.0001 0.9350 to 1.012 140.3 97.67 93.33 0.91
Large area of varices 0.9752 0.0188 < 0.0001 0.9383 to 1.012 142.4 94.29 96.67 0.91
cChild‑Pugh grade B 0.9605 0.0240 < 0.0001 0.9134 to 1.008 140.3 90.70 93.33 0.84
Child–Pugh grade = C 0.9429 0.0427 0.0003 0.8591 to 1.027 144.0 96.67 85.71 0.82
Fig. 5 Receiver operating characteristic curves for peak difference ratio (Cm2max) in diagnosing portal hypertension (PHT) and evaluating PHT
severity
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Caietal. BMC Medical Imaging (2022) 22:85
Histology is an important indicator of the sever-
ity of chronic liver disease and of the degree of PHT.
One method for the histologic evaluation of the liver is
measurement of liver stiffness by ultrasound elastog-
raphy. Much research has been conducted in this field
and some techniques have been applied in routine clini-
cal work to assist the evaluation of PHT. e guidelines
published in 2018 pointed out that liver stiffness meas-
urements of TE > 20kPa can be used to identify patients
likely bearing clinically significant portal hypertension
(HVPG 10 mmHg); liver stiffness measurement using
TE < 20–25 kPa combined with platelet count > 110–
150 × 106/mL is useful in ruling out varices needing
treatment [34]. In the present study, ASQ technology
based on B-mode ultrasonographic images, obtained
through conventional B-mode ultrasonography, was
used to identify homogeneous and heterogeneous liver
changes not subjectively but objectively. It can be diffi-
cult for sonographers to make quantitative diagnoses on
conventional ultrasonography as is possible with com-
puted tomography. ASQ software analyzes the physical
phenomenon of ultrasound wave scattering and by meas-
uring the degree of scattering provides a quantitative
assessment of liver parenchymal histology.
We acquired real time images over 3s depicting liver
parenchyma free from Glisson’s capsules with the patient
holding his or her breath. ree display modes are avail-
able in ASQ analysis: histogram, parametric and basic.
Histogram mode gives the Cm2 value after analyzing the
raw data; we acquired 22 consecutive frames for each
patient. We chose three parameters as indicators of liver
histology: Cm2max, Cm2mean and RmaxCm2, representing
the peak, average and highest occurred value of Cm2 of
the obtained red curve in the ROI, respectively. e final
values we used for statistical analysis were the means of
those from each of the 22 frames. Parametric mode pro-
vides images colored according to echo amplitude, with
Cm2 values coded from red to green. Basic mode provides
another parameter, the probability density function of the
Cm2 values measured in a ROI, displayed against the the-
oretical speckle pattern generated by a Rayleigh distribu-
tion [27]. In the present study, we focused on histogram
analysis.
ree clinical indices – PP measured intraoperatively,
the size of gastroesophageal varices and liver function
classified by Child–Pugh score—were used as indica-
tors of the severity of PHT [3537]. e ASQ param-
eters were significantly increased in patients with PHT;
Cm2max was better correlated with PP and the size of
gastroesophageal varices than Cm2mean and RmaxCm2.
Cm2max was also positively correlated with the index
of hemodynamic change PHI, which increased signifi-
cantly with increased PP. Cm2mean was correlated only
with the size of gastroesophageal varices. No obvious
relationships were found between the ASQ parameters
and Child–Pugh class. According to ROC analysis, the
diagnostic value of Cm2max for PP, severity of varices
and liver function was greater than that of the ASQ
parameters for liver fibrosis [26]. We also evaluated
hemodynamic changes in patients with PHT and their
relationship with liver pathologic changes. PHI, which
was significantly correlated with PP in our previous
studies [38], showed a good correlation with PP and
with Cm2max. To our knowledge, this is the first study
to evaluate this relationship with regard to histology,
hemodynamics and pressure simultaneously.
Our study had limitations. First, we did not assess
the middle stage between normal liver and decompen-
sated liver cirrhosis (e.g. liver fibrosis and liver cirrhosis
without PHT) due to the impossibility to get the data
of portal pressure of the middle stage and this may be
the reason for the high diagnostic value of Cm2max. Sec-
ond, the number of patients was not large enough for a
comprehensive evaluation, especially of varices, which
might be the reason of a week relationship (r = 0.3 ~ 0.4)
to be found between these parameters. Further studies
are needed to confirm the present results regarding the
predictive value of ASQ parameters.
We evaluated correlations between ultrasonographic
images and the histologic changes of liver parenchyma,
hepatic dynamic changes, PP, gastroesophageal varices
and Child–Pugh class. We employed ASQ analysis in
histogram mode because the parameters were most
stable in this mode. Our results show that the predic-
tive performance of Cm2max was satisfactory and war-
rants further validation. We can infer that ASQ analysis
of ultrasound images may have a role in the evaluation
of the severity of PHT by identifying liver histologic
changes from the speckle pattern observed in cirrhosis.
Abbreviations
ASQ: Acoustic structure quantification; PHT: Portal hypertension; PP: Portal
pressure; HVGP: Hepatic venous pressure gradient; TE: Transient elastography;
SE: Strain elastography; SWE: Shear wave elastography; Cm2max: Peak value of
Cm2; Cm2mean: Mean value of Cm2; RmaxCm2: Cm2 value at the peak red occur‑
rence; PVVel: Mean velocity of the portal vein; HARI: Hepatic artery resistive
index; SpARI: Splenic artery resistive index; PHI: Portal hypertension index;
ROC: Receiver operating characteristic; PDF: Probability density function; ROI:
Region of interest; CI: Confidence interval; YI: Youden’s index.
Supplementary Information
The online version contains supplementary material available at https:// doi.
org/ 10. 1186/ s12880‑ 022‑ 00817‑2.
Additional le1. Suppl. Fig 1. Intra‑operator variability of patients:
RmaxCm2 of patients were tested by the same operator on the same
patients for two times. Suppl. Fig 2. Inter‑operator variability of patients:
RmaxCm2 of patients were tested by two operators on the same patients.
Suppl. Fig 3. Intra‑operator variability of healthy volunteers: RmaxCm2 of
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
Page 8 of 9
Caietal. BMC Medical Imaging (2022) 22:85
healthy volunteers were tested by the same operator on the same healthy
volunteers for two times. Suppl. Fig 4. Inter‑operator variability of healthy
volunteers: RmaxCm2 of healthy volunteers were tested by two operators
on the same healthy volunteers.
Acknowledgements
Not applicable
Author contributions
WB Cai and JK Yin drafted the manuscript and carried out data processing.
QYL collected data. YLY recruited the patients. YYD carried out data processing
and guidance. LZ designed the research, conceptualized the manuscript
and involved in data processing. All authors read and approved the final
manuscript.
Funding
This work was supported by a grant from the National Natural Science Foun‑
dation of China, NSFC 81101092.
Availability of data and materials
All data generated or analysed during this study are included in this published
article.
Declarations
Ethics approval and consent to participate
The study was approved by the Ethical Committee of Tangdu Hospital,
the Fourth Military Medical University. All the methods were performed in
accordance with the relevant guidelines and regulations of the institutional
and national research committee. Informed consent was obtained from all
individual participants included in this study.
Consent for publication
Not applicable.
Competing interests
The authors declare that they have no competing interests.
Author details
1 Department of Ultrasound Diagnosis, Tangdu Hospital, The Fourth Military
Medical University, Xin Si Road, Ba Qiao District, Xi’an, China. 2 Department
of General Surgery, Tangdu Hospital, The Fourth Military Medical University,
Xi’an, China. 3 Department of Ultrasound Diagnostics, General Hospital of Tibet
Military Region, Lhasa, China.
Received: 16 September 2021 Accepted: 5 May 2022
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