Teza doctorat gersak mariana mirela final

UNIVERSITY OF MEDICINE AND PHARMACY “IULIU HAŢIEGANU” CLUJ-NAPOCA
PhD SCHOOL
CLUJ-NAPOCA 2017
Ion-Radu
Badea
Digitally signed by
Ion-Radu Badea
Date: 2017.10.31
12:13:03 +02'00'

The impact of technical factors
on liver fibrosis staging, using
sonoelastography

LIST OF PUBLICATIONS
Articles published "in extenso" as result of the PhD research
First author
1. Gersak MM, Badea R, Lenghel LM, Vasilescu D, Botar-Jid C, Dudea SM. Influence
of Food Intake on 2-D Shear Wave Elastography Assessment of Liver Stiffness
in Healthy Subjects. Ultrasound Med Biol. 2016 Jun;42(6):1295-302. ISI Impact
Factor 2.494 (the study may be found in personal contribution, study II).
2. Gersak MM, Sorantin E, Windhaber J, Dudea S, Riccabona M. The influence of
acute physical effort on liver stiffness estimation using Virtual Touch
Quantification (VTQ). Preliminary results. Med Ultrason. 2016 Jun;18(2):151-6.
ISI Impact Factor 1.118 (the study may be found in personal contribution, study
III).
3. Gersak MM, Lupsor-Platon M, Badea R, Ciurea A, Dudea SM. Strain Elastography
(SE) for liver fibrosis estimation– which elastic score to calculate? Med
Ultrason. 2016 Dec 5;18(4):481-487. ISI Impact Factor 1.118 (the study may be
found in current state of the art).
Co-author
1. Lupșor-Platon M, Badea R, Gersak M, Maniu A, Rusu I, Suciu A, Vicas C,
Stefănescu H, Urs R, Al Hajjar N. Noninvasive Assessment of Liver Diseases
using 2D Shear Wave Elastography. J Gastrointestin Liver Dis, December 2016;
25(4):525-532. ISI Impact Factor 1.837.
Other: Electronic poster published online:
1. Gersak M, Botar-Jid C, Vasilescu D, Lenghel LM, Dudea SM. Liver stiffness
estimation using sonoelastographic technologies – a practical approach.
European Congress of Radiology (ECR) 2016/C-1305, 2015, doi:
10.1594/ecr2016/C-1305.

7
The impact of technical factors on liver fibrosis staging, using sonoelastography
CONTENTS
INTRODUCTION
15
CURRENT STATE OF THE ART 17
1. Liver fibrosis- definition and clinical importance 19
1.1. Introduction 19
2. Sonoelastographic methods for liver stiffness estimation 20
2.1. Strain elastography (SE) 20
2.2. Shear-wave elastography (SWE) 20
3. Liver fibrosis estimation using sonoelastographic methods -
current state of the art
22
3.1.Strain elastography (SE) 22
3.2 Shear-wave elastography (SWE) 25
3.2.1. Transient one-dimensional elastography (TE) 25
3.2.2. Acoustic radiation force induced elastography or virtual touch
quantification elastography (ARFI/VTQ)
25
3.2.3. ElastPQ technique 26
3.2.4. 2D-Shear Waves Elastography 27
4. Technical factors which may influence non-invasive liver stiffness
estimation
28
4.1. Local conditions 28
4.2. Elevated aminotransferases levels and cholestasis 29
4.3. Steatosis 29
4.4. Congestive heart failure 29
4.5. Ascites 29
4.6. Food intake 30
PERSONAL CONTRIBUTION 31
1. Work hypothesis and objectives 33
2. General methodology 34
2.1. Reference standard 34
2.2. Sonoelastographic examination protocol 35
2.3. Image analysis 35
2.4. Statistical analysis 36

8 Gersak Mariana Mirela
3. Study I. The role of frame average and manual selection of
images in liver fibrosis staging, with strain elastography
37
3.2. Work hypothesis 37
3.3. Material and Method 40
3.3.1. Patients 40
3.3.2. Liver stiffness evaluation 40
3.3.2.1. Transient elastography (TE) 40
3.3.2.2. Strain elastography (SE) 40
3.3.2.3. Statistical analysis 42
3.4. Results 43
3.4.1. Sample 1. Biopsy vs. manual quantification SE and ElastoBreast 2.8
processed average color map (SE).
43
3.4.2. Sample II. TE vs. SE 43
3.5. Discussion 44
3.6. Conclusions 45
4. Study II. Influence of food intake on 2-d shear wave elastography
assessment of liver stiffness in healthy subjects
47
4.3.1. Selection of subjects 48
4.3.2. Real-time two dimensional shear wave elastography 49
4.3.3. Statistical analysis 51
4.4. Results 51
4.5. Discussion 57
4.6. Conclusions 60
5. Study III. The influence of acute physical effort on liver stiffness
estimation using Virtual Touch Quantification (VTQ). Preliminary
results.
61
5.3.1. Subjects 62
5.3.2. Study design 62
5.3.3. Statistical analysis 63
5.4. Results 63
5.5. Discussion 65

9
5.6. Conclusions 68
6. General conclusions 69
7. Limitations and further developments 71
8. Originality and innovative contribution 73
REFERENCES 75

11
ABBREVIATIONS*
%AREA Percentage area
2D-SWE Two dimensional shear-wave elastography
ALT Alanine aminotransferase
ARFI/VTQ Acoustic radiation force impulse
(elastography)/Virtual touch quantification
ASM Angular second moment
AUROC Area Under the Receiver-Operator Curve
BMI Body mass index
CHC Chronic hepatitis C
COMP Complexity
CONT Contrast
CORR Correlation
ECG Electrocardiogram
EFSUMB European Federation of Societies for Ultrasound in
Medicine and Biology
ENT Entropy
F (0,1,2,3,4) Liver fibrosis stage 0,1,2,3,4
FA Frame average
GGT Gamma-glutamyl transpeptidase
ICC Interclass correlation coefficient
IDM Inverse difference moment
KURT Kurtosis
LFI Liver fibrosis index
MR elastography Magnetic Resonance Elastography
NASH Non-alcoholic steatohepatitis
NPV Negative predictive value
ns Statistically not significant (p-value>0.05)
ROI Region of interest
RTE/SE Real-time elastography/Strain elastography
SD standard deviation
Se Sensitivity
SKEW Skewness
Sp Specificity
SR Strain Ratio
SWE Shear-wave elastography
TE Transient elastography (FibroScan)
UNL Upper normal limit
US Ultrasonography
XL Extra large
*
All abbreviations are explained in text on first use

13
ACKNOWLEDGEMENTS
These studies couldn`t be performed without the contribution of my scientific
coordinator, Prof. Dr. Sorin M. Dudea, whom I am deeply grateful for all the help,
professional advices, coordination, and for giving me the great opportunity to learn from
him all these years.
I would like to bring special acknowledgments to Prof. Dr. Michael Riccabona, Dr.
Jana Windhaber and the Children`s Radiology Department from Graz University, for
their trust, interest and involvement in my research.
I am addressing my gratitude to the entire Imaging Department of the Regional
Institute of Gastroenterology and Hepatology Cluj-Napoca, and also to the Radiology
Department of the Emergency County Hospital, Cluj-Napoca as well as to all the
voluntary subjects and colleagues; without their help these studies would not exist.
Also, I am eternally grateful to my family and also to my beloved husband, for
their love and support, which gave me strength, balance and peace of mind to complete
this research.
This research was co-financed by the Romanian National Authority for Scientific
Research and Innovation CNCS-UEFISCDI, 2015-2017, project number PN-II-RU-TE-
2014-4-2023.

15
INTRODUCTION
Liver fibrosis occurs as a consequence of chronic liver injuries and is most
commonly encountered in chronic viral hepatitis and alcoholic and non-alcoholic
steatohepatitis.
This makes liver fibrosis an important, global issue since the underlying
diseases causing liver fibrosis are increasing worldwide, stirring the interest for
research, in the past years.
Staging liver fibrosis is important, as the patient management may depend on it.
Although liver biopsy is considered the reference method for liver fibrosis
quantification, this has also multiple biases and inconveniences for the patients,
considering that it is an invasive method and, as a matter of fact, liver fibrosis often has
an uneven distribution in the liver parenchyma, thus making liver fibrosis staging much
more difficult on small biopsy samples.
In the beginning, elastography was used for assessing cheese maturity.
Nowadays, multiple, reliable ways to estimate liver stiffness, based on elastography
were developed. In current practice, liver fibrosis staging is estimated by transient
elastography (TE), mainly because this type of elastography has been tested over time
and it proved to have similar results with liver biopsy, the latter being preserved for
difficult cases or when the etiology of the fibrosis is unknown.
TE has a few confounding factors which must be taken into account when
performing liver stiffness measurements, such as food intake, perihepatic ascites,
cholestasis, hepatic cytolysis, acute decompensated heart failure, steatosis, thick
subcutaneous tissue, narrow intercostal spaces and obesity.
TE is not the only type of elastography able to estimate liver stiffness. Recently,
besides TE, estimation of the liver stiffness was achieved by using multiple types of liver
elastography such as strain elastography (SE), two-dimensional real-time shear wave
elastography (2D-SWE), point shear wave elastography (pSWE/ARFI, elastPQ) and also
Magnetic Resonance Elastography (MR elastography).
The research in liver fibrosis diagnosis and staging is focused on developing and
improving non-invasive methods for estimating liver fibrosis, among which are the
sonoelastographic imaging technologies. TE is already well studied in all its aspects but
it requires a special, independent device. It is of great interest to study the limits and
the possible technical factors which may influence or impair the results of the new
elastographic technologies as, they have become more accessible lately, on most of the

ultrasound equipment and also because, in the literature there are still some gaps to
fulfill in this respect.
The aim of this thesis is to study the impact of several technical factors which may
possibly impair liver stiffness estimation using sonoelastographic techniques. Point
SWE, two dimensional real-time SWE and strain elastography, have been studied
intensely researching for factors which may possibly impair these techniques regarding
liver stiffness estimation.
At first, SE was intensively studied, since this type of elastography had a wide
availability on the ultrasound machines. Surprisingly, in the literature, there was no
information regarding the settings of all the available parameters on GE
sonoelastography, making this research a good opportunity to discover new shores in
this domain.
Soon after 2D-SWE was available on ultrasound equipments, its utility in liver
stiffness estimation was quickly showed in the literature. Since this type of elastography
is also based on shear waves, like TE, some of limiting factors were easily deductible.
One of these limiting factors is food intake. In the literature, we found a lack of studies
regarding the influence of food intake on liver stiffness estimation with 2D-SWE. In
order to perform a good estimation of liver stiffness, in our opinion, studies were also
needed regarding this aspect.
While performing the second study, there was a particular subject who was in a
hurry, therefore he ran a few minutes before arriving at SWE measurements. Although
he was very exhausted, the 2D ultrasound examination was performed in order to
exclude an eventual underlying liver disease. A first measurement of liver stiffness was
performed, where very high values were found, corresponding almost of cirrhosis. Since
there were no other gray scale ultrasound signs for cirrhosis or antecedents of viral
infections, we assumed that physical exhausting may have had a contribution.
Due to the great availability of Children`s Radiology Department from Graz
University, a small study was possible to perform with ARFI/VTQ elastography
regarding physical exhausting and its influence on liver stiffness estimation.
Three studies were conducted, regarding food intake (with real-time 2D-SWE),
acute physical effort (with ARFI/VTQ), and the combined frame average different values
(with SE) and average of the frame average (with SE), thus contributing with new
information in the literature.

17
CURRENT STATE OF THE ART

19
1. Liver fibrosis- definition and clinical importance
1. 1. Introduction
Liver fibrosis is an accumulation in excess of connective tissue, secondary to a
persistent aggression on hepatic tissue. The natural evolution of liver fibrosis is
insidious, quite asymptomatic till the final stage: cirrhosis. Once cirrhosis appears, the
occurrence of complications is only matter of time: ascites, variceal bleeding, hepatic
encephalopathy and renal failure1. In the meantime, the risk of hepatocellular carcinoma
increases1. The main cause of liver fibrosis is diffuse chronic liver disease [chronic
hepatitis C (CHC), chronic hepatitis B, non-alcoholic steatohepatitis (NASH) and alcohol
consumption]1. Staging liver fibrosis subsequent to chronic viral hepatitis has a
particular clinical importance, mainly because significant liver fibrosis (METAVIR score
≥F2) is an important criterion for recommending antiviral therapy2–4.
There are several histopathological liver fibrosis scoring systems for viral and
autoimmune hepatitis: METAVIR5, Scheuer score6, Batts and Ludwig score7 and Ishak
modified Knodell score8. Among all these scores, METAVIR score is the most commonly
used and has 5 stages: F0- no fibrosis, F1- periportal fibrosis, without septa, F2-
periportal fibrosis with a few septa, F3- numerous septa without cirrhosis and F4-
cirrhosis. Scheuer and Chinese Program of Prevention and Cure for Viral Hepatitis score
are extremely similar to METAVIR score, defining S0 – S4 in a similar fashion6,9.
Liver biopsy is considered the reference method for the diagnosis and staging of
liver fibrosis. It is well documented that inter- and intraobserver variability of reporting
liver biopsy pathology is relatively high10,11. False negative results were reported in up
to 30% of the cases 10,11; complications were reported, some of them requiring medical
care (1-3% of liver biopsy cases)12. Up to 25% of the patients complained of post
procedural local pain12. Due to these inconveniences, non-invasive methods for
predicting liver fibrosis, as an alternative to liver biopsy, have been studied intensely.
Multiple imaging techniques were developed, such as ultrasound-based methods
(sonoelastography) and magnetic resonance- based methods, which, besides the non-
invasiveness, show good results for liver stiffness estimations4,13.

21
2. Sonoelastographic methods for liver stiffness
estimation
The ultrasound based methods for liver stiffness estimation belong to two
groups: strain elastography (SE) and shear-wave elastography. This latter group
comprises several different techniques: transient elastography (TE), Virtual Touch
Quantification (VTQ)/ Acoustic Radiation Force Imaging (ARFI elastography), elastPQ
techique and two dimensional Shear-Wave elastography (2D-SWE)14,15. Table I.
2.1. Strain Elastography (SE)
SE was, historically, the first elastographic technique developed. At first, SE was
available on linear probes2. This type of elastography displays a color-coded map, which
depends on the degree of tissues compressibility. The colour scale ranges from blue
(stiff) to red (soft)3 but lately there are some developers which changed the colour
range, from red (stiff) to blue (soft). SE assesses relative tissue stiffness by comparing
surrounding tissues in terms of elasticity. Various groups explored the use of
mathematical formulas, in the attempt to obtain a numerical indicator for the
characterization and staging of liver fibrosis with SE4,15.
2.2. Shear-wave elastography (SWE)
SWE includes transient one-dimensional elastography (TE), acoustic radiation
induced force elastography (ARFI)/ virtual touch quantification elastography (VTQ),
elastPQ techique and real-time two-dimensional shear-wave elastography (2D-SWE).
Shear-wave elastography is a quantitative ultrasound method for liver stiffness
estimation which uses mechanic force induced waves propagating in the liver
parenchyma where, subsequently, shear waves are formed. These shear waves are
recorded by the transducer and registered as shear wave velocities, being expressed
either in kilopascals (TE), or in m/s (ARFI) or both (ElastPQ and 2D-SWE)15. Transient
elastography (TE) was initially used only for cheese maturity determination16 but later
on, its utility in liver stiffness estimation was clearly observed. Once the role of non-
invasive methods for liver stiffness estimation was firmly proven, liver biopsies became

reserved only for difficult cases, thus limiting the prospective studies based on
comparing elastography with the reference pathology method13.
Table I. Classification of elastography techniques, according to the EFSUMB Guidelines and
Recommendations 15,17.
Method
displacement or strain
imaging
shear-wave speed
measurement
shear-wave speed imaging
Strain
elastography
(SE) and Strain-
rate imaging
(SRI)
Acoustic
radiation
force
impulse
(ARFI)
imaging
Transient
elastograp
hy (TE)
Point shear-
wave
elastograph
y (pSWE)/
ARFI
quantificati
on
Shear-wave elastography
(2D-SWE/3D-SWE)
Applied
force
mechanically
induced- either
active external
displacement of
tissue surface or
passive internal
physiologically
induced
ultrasoun
d induced-
focused
radiation
force
impulse at
depth
mechanical
ly induced
– impulse
(“thump”)
at tissue
surface
ultrasound
induced -
focused
radiation
force
impulse at
depth
ultrasound
induced-
radiation
force
impulses
focused at
various
depths
ultrasound
induced-
radiation
force focus
swept over
depth faster
than shear-
wave speed
to create a
Mach cone
Property
displayed
strain or strain
rate
displacem
ent
shear-wave speed
Commercial
implementation
Esaote, GE,
Hitachi Aloka,
Philips, Samsung
Medison,
Siemens,
Toshiba,
Ultrasonix,
Zonare
Siemens Echosens
Siemens,
Philips
Siemens
SuperSonic
Imagine

23
3. Liver fibrosis estimation using sonoelastographic
methods - current state of the art
3.1. Strain elastography (SE)
SE offers qualitative (colour-coded map) and semi-quantitative elasticity
measurement. It is well documented that colour-coded map has as the main
inconvenience- that is operator and experience - dependent method18. Overall, this
method had shown a good inter- and intra-observer variability despite the eventual
operator`s subjectivity4. Researchers computed multiple formulas and strain ratios in
order to diminish these limitation and improve liver stiffness estimation with this
technique4.
Fujimoto et al19 used a linear probe and a Hitachi equipment, to elaborate an
elasticity score with 4 stages: the higher the score, the more advanced the fibrosis (fig 1
and fig 2). They positioned the region of interest (ROI) immediately under the liver
capsule and the patient stopped breathing for a moment, until the image acquisition was
performed. In order to diminish the subjectivity of colour map interpretation, 6
operators blindly and independently interpreted the images.
Figure 1. Elasticity score according to Fujimoto et al4,19.
Score 1: Almost the entire ROI is green. Score 2: The ROI is mostly green, with a few spots of blue.
Score 3: The blue and green colours are mixed, almost in the same percentage (50%).

Score 4: The ROI is mostly blue.
Figure 2. Liver stiffness colour map, with ROI placed around 1cm under the liver capsule, corresponding to
Elasticity score 1 according to Fujimoto et al19.
Friedrich-Rust et al2 used also a Hitachi equipment and a linear probe, when they
developed another elasticity score, based on the colour map analysis. They obtained a
sensibility (Se) of 80% and a negative predictive value (NPV) of 78.6% for detecting
clinically significant fibrosis (F≥2). When introducing platelets number and gamma-
glutamyl transpeptidase (GGT) values in their formula, the results were improved2.
The liver fibrosis index (LFI) was computed by many authors. The first to do so
were the group of Tatsumi et al20, with only a 4 parameters analysed. Later on, the final
formula included 11 parameters: mean, standard deviation (SD), percentage of blue area
in the ROI (%AREA), length squared divided by blue area (COMP), inverse difference
moment (IDM), kurtosis of strain histogram (KURT), skewness of strain histogram
(SKEW), entropy (ENT), angular second moment (ASM), correlation (CORR) and
contrast (CONT)21. Using all these parameters, Meng et al obtained a Se of 88.1% and Sp
of 74.7% for detecting F≥221. Unfortunately, the final LFI formula was not published but
since Hitachi implemented LFI formula in their system, liver stiffness quantification
became easier than before4.
In the meantime, other authors focused on estimating liver stiffness using strain
ratio (SR). Thus, SR between small intrahepatic veins and liver parenchyma9,22–24 (fig 3)
and SR between intercostal muscles and liver parenchyma 23,25,26 (fig 4). When
intercostal muscles were used as a reference tissue for SR, Se was up to 96.2% and Sp
was up to 85.3% for detecting F≥223,25,26. When small intrahepatic veins were used as a
reference tissue for SR, Se was up to 92.3% and Sp was up to 90.9% for detecting F≥29,22–
24.

25
Figure 3. Elastic ratio between liver parenchyma (A) and small hepatic vein (B), according to Koizumi et
al4,22.
Figure 4. Elastic ratio between liver parenchyma (B) and intercostal muscles (A), according to Kanamoto et
al4,25
Both strain ratios were positively correlated with liver fibrosis stage but SR
where small hepatic veins were used, presented better results23.
Elastic index is another way for SE quantification, using the same 11 parameters
like in LFI, but with a calculus of 4 main functions which were subsequently integrated
in another formula. This way, the results were Se up to 81.6% and a Sp up to 88.2% for
F≥2 detection3,27.
Among all the above described SE quantification methods, the recent Guidelines
and Recommendations for Clinical Use of Ultrasound Elastography recommend Liver
Fibrosis Index28

3.2. Shear-wave elastography (SWE)
SWE is a popular sonoelastographic technique, not only for liver stiffness
estimation but also for small parts assessment. The SWE technique is used in transient
one-dimensional elastography (TE) , point SWE (ARFI and ElastPQ) and real-time SWE
(2D-SWE and 3D-SWE)14.
3.2.1. Transient one-dimensional elastography (TE)
TE is integrated in FibroScan equipment (Echosens, Paris), which has a 3.5MHz
ultrasound transducer with a vibrator device on it. This way, the produced vibration
propagates onto the liver parenchyma through the skin and produces shear-waves. The
resulting shear-waves are registered by the same transducer which express tissue
stiffness by converting velocities in kPa18. Unfortunately, TE does not offer a 2D
visualisation of liver parenchyma. Nevertheless it is currently used for liver stiffness
measurement, mostly because this technique combines non-invasiveness with high
performance29. The volume of tissue of which the estimation is performed, is larger than
a biopsy sample, producing similar results and a good inter- and intra- observer
agreement of up to 0.93-0.9618,29. TE examination takes about 5-10 minutes, is
completely painless and may be repeated without any additional risks14,18. The learning
curve is very short, 50 cases being enough to learn how to perform a correct FibroScan
examination14.
3.2.2. Acoustic radiation force induced elastography or virtual touch
quantification elastography (ARFI/VTQ)
ARFI/VTQ is integrated in Siemens equipment. This type of SWE basically
functions on the acoustic “push” pulse which is produced by the transducer and directed
to the sample size (ROI) (fig 5). Then, the transducer detects the velocities of the shear
waves which were produced, secondarily to the “push” pulse which was sent into the
liver parenchyma18. The values are expressed in m/s15,18. In a small sample, the overall
inter- and intra- observer agreement was relatively good ( ICC of 0.81 and 0.90
respectively)30. In terms of detecting clinically significant fibrosis, ARFI elastography
showed Se up to 89.4% and a Sp up to 100%31,32.

27
Figure 5. ARFI liver elastography. Courtesy of Prof. Dr. Michael Riccabona References: Department
of Radiology, Division of Pediatric Radiology, University Hospital Graz, Austria
3.2.3. ElastPQ technique
ElastPQ (fig 6) is implemented by Phillips in their ultrasound systems but it may
be found also on Samsung ultrasound equipment. ElastPQ was also assigned to point
shear-waves technology like ARFI but from the manufacturer`s descriptions, it results a
relatively similar elastography with 2D-SWE. This type of elastography is relatively new
for liver stiffness estimation, thus, not many information regarding its effectiveness,
confounding factors and feasibility but a good interobserver reproducibility was found
(ICC=0.798)33.
Figure 6. ElastoPQ liver elastography.

3.2.4. 2D-Shear Waves Elastography
Real-time SWE elastography (2D-SWE) is available on Aixplorer (SuperSonic
Imagine S.A., Aix-en-provence, France) ultrasound machines (fig 7). This type of
elastography uses “radiation force induced into the tissues by focused ultrasonic
beams and a very high frame rate ultrasound imaging sequence, able to capture the
propagation of resulting shear waves in real time18. Although 2D-SWE is a relatively new
technique, already showed promising results: for detecting clinically significant fibrosis,
2D-SWE presented an AUROC higher than TE not only in patients with HVC (0.92 vs.
0.84) but in patients with HVB (0.88 vs. 0.78). Also, intra-operator correlation coefficient
(ICC) is up to 0.95, inter-operator correlation coefficient is up to 0.8834–36.
Figure 7. Real-time liver “shear wave” elastography, in a healthy patient

29
4. Technical factors which may influence non-invasive
liver stiffness estimation
It is well known that all non-invasive methods for liver stiffness estimation,
besides the advantages, also have a few limitations which must be acknowledged and all
the situations which may impair a correct and valid liver stiffness estimation must be
avoided or corrected, as much as possible.
The known factors which impair liver stiffness estimation are: local conditions,
liver cytolysis, cholestasis, food intake, acute decompensated heart failure, steatosis and
ascites13,14,18.
4.1. Local conditions
The main local conditions which may impair liver stiffness estimation are: narrow
intercostal spaces, thick subcutaneous fat tissue and dense subcutaneous tissue.
Although these factors cannot be changed or influenced in the moment of liver
stiffness estimation, the operator must acknowledge and explain all of them in his
report. It is well known that narrow intercostal spaces impair TE and 2D-SWE18,37.
Obesity and dense subcutaneous tissue also impair liver stiffness estimation, a
BMI>40kg/m2 being associated with a failure rate up to 59% when performing TE14,37.
This percent has been clearly improved since XL probe became available for TE, which
has a central frequency of 2.5 MHz18. At the moment, it is not known if ElastPQ is
influenced by these local conditions. SE can be performed in patients with narrow
intercostal spaces and obese patients, with a wider range (but not with a significant
difference) of interobserver agreement, in patients with a skin fold >20mm and
BMI>25kg/m222.
The limited penetration and attenuation artefact given by the ribs impair SE liver
stiffness estimation but since SE is also available on convex probes, the penetration has
been clearly improved18. Also, real-time 2D-SWE showed a lower reproducibility and
reliability rate in obese patients38 but when comparing difficult-to-scan cases, TE with
an XL probe showed its superiority39.

4.2. Elevated aminotransferases levels and cholestasis
Multiple studies showed that elevated aminotransferases seriously impair liver
stiffness estimation by TE40–43. A large, comprehensive study showed that TE presents
more accurate results if ALT values are lower than 3x ULN (upper normal limit)43. Also,
another study showed that TE values are impaired when AST>100 U/L44. Other studies,
found the contrary, TE and real-time 2D-SWE not being influenced by elevated
transaminases37.
ARFI elastography is influenced by moderately elevated aminotransferase levels (ALT
~1.1-5xULN) but in a lower extent, comparing with TE45,46.
Cholestasis also impairs TE and ARFI values, most probable due to the impaired bile
flow and increased intracellular pressure47,48.
Unfortunately, the influence of cholestasis and elevated transaminases were not
sufficiently tested yet, on 2D-SWE.
4.3. Steatosis
TE was reported to have some limitations in patients with steatosis49 while other
studies disagreed on this aspect50,51, for obese patients the XL probe being
recommended14. Liver stiffness estimation using real-time 2D-SWE and ElastPQ was not
influenced by steatosis52–54, in contrast with ARFI elastography, where, an influence of
steatosis on ARFI measurements was described32
4.4. Congestive heart failure
Since TE was widely studied, it is already known that congestive heart failure may
impair liver stiffness estimation, due to increased central venous pressure55,56. Also, for
ARFI elastography, right heart failure might be a confounding factor57.
At the moment, it is not known if 2D-SWE, ElastPQ and SE are influenced by congestive
heart failure18.
4.5. Ascites
TE is seriously impaired by large amounts of perihepatic ascites but 2D-SWE
elastography might be performed in patients with perihepatic ascites14. Although SE
may be performed in patients with ascites14, and a recent study showed promising
results58, it must be taken into account that SE shows a relative elasticity and practically,
compares the displacement of the tissues. Thus, in the presence of ascites, liver might
appear stiffer than it really is18
Presently, it is not known if ElastPQ is influenced by ascites but ARFI elastography
showed good feasibility for up to 96.8% of the cases59.

31
4.6. Food intake
Postprandial hyperaemia in superior mesenteric artery and portal vein were
evaluated since Doppler echography was available60.
Moreover, Sabba et al60 discovered that healthy patients and cirrhotic patients
present a different amplitude of postprandial hyperaemia. In terms of liver stiffness,
Mederacke et al61 discovered that TE estimation is influenced by food intake, both
in healthy subjects and in patients with chronic hepatitis C, most probably, based on the
same phenomena: postprandial hyperaemia61.
Later on, food intake was confirmed by many authors to be a serious confounding
factor for TE and, a recent study showed that ARFI elastography is also impaired by this
confounding factor 62. Thus, the recent guidelines recommend at least 2 hours of fasting
before performing a TE and ARFI liver stiffness estimation while the influence of food
intake is unknown for strain elastography and ElastPQ.
Since the influence of food intake on 2D-SWE was published only as a congress
abstract, which describes a study performed on 10 patients63, it is difficult to conclude
whether 2D-SWE is biased by food intake or not.

33
PERSONAL
CONTRIBUTION

35
1. Work hypothesis and objectives
Liver fibrosis staging is important for the patient management, mainly in chronic
viral hepatitis where, the antiviral therapy decision depend on liver fibrosis stage.
Liver biopsy is the reference method for liver stiffness measurement but since it is
invasive and has many associated disadvantages, lately, the tendency is to estimate liver
stiffness by TE, when it is possible.
Sonoelastographic technologies are great tools for liver stiffness estimation.
Although not all of them present performance similar to that of TE, in time, some of them
might increase their accuracy. Shear-wave elastography showed promising results in
terms of liver stiffness estimation. Still, there are some confounding factors which may
seriously impair the accuracy of elastographic liver stiffness assessment.
Strain elastography lost its popularity since shear-wave elastography was
discovered. Since SE is more widely available than SWE, and also under continuous
improvement, SE might present also good performances, with the proper adjustments.
It is well known that the interpretation of color maps of SE is highly subjective.
Therefore, a software was produced which processes all the valid images, transforming
them into an average color map which was subsequently interpreted according to
Fujimoto`s elastic score. The aim of the first study was to compare strain elastography
with liver biopsy and TE, in patients with diffuse chronic liver disease, in order to
evaluate SE value in liver stiffness estimation.
The second study was centered on 2D-SWE, on a sample of healthy subjects. The
aim of the study was to assess the influence of food intake on liver stiffness estimation
and also to explore the importance of body mass index (BMI) and gender on liver
stiffness variation after a standardized meal.
The third study was centered on ARFI/VTQ elastography, also on a small sample of
healthy subjects. The aim of this study was to assess whether liver stiffness estimation
is influenced by physical effort or not, and if so, to also determine when liver stiffness
measurements return to baseline values.
To the best of our knowledge these ideas of studies were not yet tested or shared in
the literature, making this a good opportunity to find out more about potential
confounding factors for liver stiffness estimation.

37
2. General methodology
The first study was performed at the Ultrasound Department of Regional
Gastroenterology and Hepatology Institute “Prof. Dr. Octavian Fodor” Cluj-Napoca. The
second study was performed at the Ultrasound Department of Emergency County
Hospital and "Iuliu Haţieganu" University of Medicine and Pharmacy, Cluj-Napoca. Last
but not the least, the third, pilot study was performed at the Ultrasound Department of
Pediatric Radiology, Medical University of Graz. The studies were approved by the local
Ethical Committee, excepting the pilot study where, all the participants were volunteer
medical doctors thus, according to national regulations and local institutional policy, the
Ethical Board approval was waived.
All the participants gave their written informed consent.
The subjects were carefully selected in every study, the inclusion and exclusion
criteria being detailed and respected for each study in part.
2.1. Reference standard
Although liver biopsy has multiple disadvantages and inconveniences, it is
considered the reference method for liver stiffness measurement. Since non-invasive
methods were developed, liver biopsy is avoided in many follow-up cases, being applied
only in difficult cases. This leads to the lack of a reference method and represents a real
hindrance for new studies in this domain. Still, since TE is well tolerated and it was
proven to have similar results as liver biopsy, for liver fibrosis grading, nowadays
multiple studies use TE as a reference method.
In the first study of this thesis, liver biopsy was used as the reference method for
a small size sample and then, TE was considered as a reference for the larger sample, in
the same study.
In the second and the third studies, which were performed on 2D-SWE and
ARFI/VTQ, on healthy subjects, there was no need for any reference method, since the
measurements were performed before and after food intake and physical effort
respectively.

2.2. Sonoelastographic examination protocol
TE was performed with a FibroScan machine (Echosens, Paris). For each patient,
10 valid measurements were performed and the final value was considered the median
of the 10 measurements. A valid estimation of liver stiffness was considered when
success rate (SR) was above 60% and interquartile (IQR) range was below 30%.
SE was performed by an operator who used a Logiq E9 (General Electric)
ultrasound machine, with a convex probe. A total of 10 strain elastography movies of 7-
10 seconds were recorded for each patient: five with a frame average (FA) of 0 and five
with FA of 10. A valid SE image was considered when the quality scale for SE was green,
according to the manufacturer`s recommendation.
For the second study, the Aixplorer (SuperSonic Imagine, Aix-en-Provence,
France) ultrasound machine with a SC6-1 convex transducer was used. The first series
of measurements were performed in fasting condition and then, after food intake
multiple series of measurements were performed in the same intercostal space, at
different times from food intake. Liver stiffness was estimated in the right lobe, while
the subject breathed with normal amplitude and was asked to stop breathing for a few
seconds till acquisition was made.
For the third study, VTQ elastography was performed using an Acuson S3000
(Siemens Inc., Forchheim, Germany) device with a 6C1HD abdominal curved array, by
the same operator. Liver stiffness was assessed in fasting conditions, using similar
positioning of the patient and of the ROI as in the other studies. The first series of
measurements were performed before physical effort. Consequently, the subjects
performed physical exercise using a cycle ergometer (Excalibur Sport, company LODE).
The workload was increased every minute until exhaustion. Then, three consecutive
series of liver stiffness measurements were performed: immediately after
spiroergometry as well as five minutes and ten minutes after spiroergometry
respectively.
Liver stiffness estimation was performed according to recent EFSUMB guidelines.
The patients were in dorsal decubitus, with the right hand above their head, liver
stiffness estimation being performed in the right liver lobe, through an intercostal space.
The ROI was placed at least 1cm under the liver capsule.
As additional criteria for accurate liver stiffness estimation, IQR (interquartile
range) and SR (success rate) were calculated, according to EFSUMB guidelines.
2.3. Image analysis
Image acquisition and analysis was performed by the same operator. In the first
study, where frame average, manual and average SE images were compared, and where
short liver SE movies were recorded, the ElastoBreast software was used. This software
averages the color map from all valid images. For color map interpretation, the operator

39
used Fujimoto`s elastic score, adding F0 stage of fibrosis representing a fibrosis free liver
parenchyma.
In all studies, image analysis and liver stiffness estimation were interpreted
according to recent studies and cutoff values which are detailed in each study.
2.4. Statistical analysis
For all studies, Microsoft Excel, MedCalc Statistical Software (v.16.8) and IBM®
SPSS Statistics (v.19.0 Armonk, NY) software packages were used, both for data
representation and for statistical analysis,
For the first study, in order to compare TE/liver biopsy and SE outcomes,
Wilcoxon test was applied, for paired data.
Regarding the second and the third study, after the distribution data was checked
with the Shapiro–Wilk test, the multivariate analysis of variance (MANOVA) test for
repeated measures was used for comparison of data. For the post hoc data analysis, the
t-test for paired samples was used. The outcomes of the t-test were validated by
simulations, using the bootstrap method.

41
3. Study I. The role of frame average and manual
selection of images in liver fibrosis staging with strain
elastography
3.1. Introduction
Among all types of sonoelastography, strain elastography was one of the first
types developed but soon after that, the researchers turned their interest towards shear
wave- based elastography. Still, SE is the most widely available type of elastography. In
the same time, SE is not influenced by inflammation, high values of transaminases,
cholestasis, congestion or small amount of ascites like TE and other type of SWE
elastography28,58. These are the main reasons why in our opinion, SE is worth further
analysis and research the available parameter`s correct adjustments, in order to
perform it properly and thus, discovering its real usefulness in liver stiffness estimation.
Since liver biopsy is rarely performed in current practice, and although TE is not a
considered as a “gold standard” method for liver fibrosis staging, there are many studies
in the literature which use TE a reference method.
Since SE shows a color map based on colors from red (soft) to blue (hard/stiff),
Fujimoto et al developed an elastic score in order to stage liver fibrosis19. The authors
used a Hitachi ultrasound system and a linear probe to develop this elastic score,
showing promising results in liver fibrosis estimation19.
3.2. Work hypothesis
One of the main limits of SE is the operator`s subjectivity in acquiring and
interpreting the color maps. The mitigation or avoidance of the influence of this aspect
was approached in multiple studies by the blinding method, the operators having no
information regarding the patients, by increasing the number of operators19 or by
coding the color map`s colors thus, transforming the map into numbers and formulas4.
A software product, which was initially developed for breast elastography in a
cooperative project between UTCN Cluj-Napoca and UMF Cluj-Napoca (project grant no
149/2006, Viasan, CEEX, RO), named ElastoBreast v. 2.8, was used. The software allows
to calculate, from short movies, the average of the color map. With the use of this
software, it may be possible to decrease the subjectivity of single image and of the short
movies interpretation.

One of the aims of this study was to compare liver stiffness estimation using
strain elastography (with and without Elasobreast software .avi processing) with liver
biopsy and TE, in patients with diffuse chronic liver disease.
During SE acquisition, the operators may adjust some of the color map`s
parameters, like frame average (FA): the higher the FA, the stable/persistent the color
elastographic map. Another aim of this study is to determinate whether FA has an
influence on color map and thus, on liver fibrosis stage classification.
Since patients without liver fibrosis have been included in this study and
Fujimoto et al 19 presented only 4 elastic scores, corresponding to the 4 liver fibrosis
stages, it was necessary to add another score, F0 when the color map was mainly red
(soft) with a thin blue/green (stiff/intermediate elasticity) line under the capsule,
corresponding to normal liver elasticity (fig 8 and 9).
Figure 8. Strain elastography. Normal liver elasticity- score 0.

43
Figure 9. Modified elastic liver score, according to Fujimoto et al19, where score 0 was added: score
0 (a) score 1 (b) score 2 (c), score 3 (d) and score 4 (e).
To all above patients, the elastic scores were compared to liver biopsy outcomes, their elastic sores
corresponding to their liver fibrosis stage. An exception was the patient with score 4 where gray-scale
ultrasound and TE values were considered enough for cirrhosis diagnosis and thus, confirming elastic score
4.

3.3. Material and Method
3.3.1. Patients
Firstly, liver stiffness was estimated in patients known with diffuse liver disease
and who recently performed liver biopsy, in order to validate SE method. In 5 months,
while this study was performed, there were 25 patients who were presenting in our
department for routine control and who had a recent liver biopsy. The patients who
were treated with interferon or other type of antiviral treatment between liver biopsy
and SE were excluded. Also, the patients with severe cholestasis or hepatic cytolysis
were excluded. Finally, the first sample of the patients included 13 patients. The
characteristics of the first sample (validation sample) is detailed in table II.
The sampling for the second sub-study was performed simultaneous with the first
sampling. For the second sample, we examined a total of 105 patients, including patients
with different types of diffuse liver diseases, without a liver biopsy, who presented for
their periodical medical control. Patients with severe hepatic cytolysis or cholestasis
were excluded from the study, as TE is influenced by these parameters. Also, in one
patient, SE was not possible, most probable because the narrow intercostal spaces.
Finally, the second sample included 89 patients who underwent liver stiffness
estimation with TE and SE (table IV).
The study design was constructed according to Helsinki Declaration, in 2008 and
was approved by local institutional ethics committee. All the patients signed a consent
form, expressing their willingness to participate in this study.
3.3.2. Liver stiffness evaluation
For liver stiffness estimation, there were used two elastographic methods:
Transient elastography and strain elastography. Both TE and SE were performed in
fasting conditions. The patients were in supine position, with their right hand above
their head, breathing normally for TE and in expiration for SE. The measurements were
performed in a right intercostal space, avoiding large intrahepatic vessels and
gallbladder.
3.3.2.1. Transient elastography (TE) was performed by an operator who had more
than 6 years of experience in liver stiffness estimation who used a FibroScan machine
(Echosens, Paris). For each patient, 10 measurements were performed and the final
value was considered the median of the 10 measurements. Also, a correct estimation of
liver stiffness was considered when success rate (SR) was above 60% and interquartile
(IQR) range was below 30%14,18. The results were expressed in kilopascals (kPa). The
used liver stiffness cutoff values for TE were 5.3 kPa for F≥ 1; 7.4 kPa for F≥2; 9.1 kPa
for F≥3 and 13.2 kPa for F4, according to Lupsor Platon et al43.
3.3.2.2. Strain elastography (SE) was performed by an operator (MMG) with more
than 4 years of experience in strain elastography who used a Logiq E9 (General Electric)
ultrasound machine, with a convex probe. A total of 10 strain elastography movies of 7-
10 seconds were recorded for each patient: five with a frame average (FA) of 0 and five

45
with FA of 10. A valid SE image was considered when the quality scale for SE was green,
according to the manufacturer`s recommendation. In order to avoid operator`s
subjectivity, all patients personal data were coded by numbers. Then, for every subject,
there were randomly selected two movies: one with FA= 0 and one with FA=10. These
movies were blindly reviewed by the operator and an elastic score was established,
according to Fujimoto et al 19 elastic score. F0 was considered when the color map was
mainly red (soft) with a thin blue/green (stiff/intermediate elasticity) line under the
capsule.
The same movies were processed frame by frame by another operator and only
the valid images were selected. Using ElastoBreast 2.8 software, which was developed
for breast elasticity evaluation, all the valid frames were selected and processed. Thus,
the software created from the valid images the average color map image for each movie
and patient (fig 10b and 10d).
Later on, the operator interpreted all the averaged images according to
Fujimoto`s elastic score (fig 10, 11), adding F0 when the color map was mainly red (soft)
with a thin blue/green (stiff/intermediate elasticity) line under the capsule (fig 8).
Figure 10. Liver elasticity score in a patient with chronic hepatitis C.
a) FA=0 (score 1); b) Average FA=0 (score 1), with ElastoBreast
average imaging processing; c) FA=10 (score 0); d) Average FA=10 (score
0), with ElastoBreast average imaging processing.
Both biopsy and TE revealed fibrosis stage 1 METAVIR; (5.9kPa).

Figure 11. Liver elasticity score in a patient with chronic hepatitis C.
a) FA=0 (score 1); b) Average FA=0 (score 1), with ElastoBreast average
imaging processing; c) FA=10 (score 0); d) Average FA=10 (score 0), with
ElastoBreast average imaging processing.
The TE revealed fibrosis stage 4 (23.1 kPa).
3.3.2.3. Statistical analysis.
The patients and all the obtained data were introduced in Microsoft Office Excel
worksheets. MedCalc Statistical Software version 16.8 was used for data processing and
statistical analysis. In order to compare TE/liver biopsy and SE outcomes, the Wilcoxon
test was applied, for paired data. For the first sample, the null hypothesis (H0)was that
there is no significant difference between SE and liver biopsy. For the second sample,
the null hypothesis (H0) was that there is no significant difference between SE and TE.
A significant difference is revealed by a p-value<0.05, when the null hypothesis is
rejected. A non-significant difference is considered for a p-value>0.05.

47
3.4. Results
3.4.1. Sample 1. Biopsy vs. manual quantification SE and ElastoBreast
2.8 processed average color map (SE).
The data from sample 1 did not have a normal distribution thus, for data analysis,
Wilcoxon test for paired data was applied the operator interpretation (manual) and
average images obtained using ElastoBreast 2.8 software, were compared with TE and
liver biopsy. No significant differences were found between FA 0 (manual) vs. Average
FA 0; FA 0 (manual) vs. liver biopsy; FA 0 (manual) vs. TE; Average FA 0 vs. liver biopsy;
Average FA 0 vs. TE (table III).
3.4.2. Sample II. TE vs. SE
The data from sample 2 also did not present a normal distribution. This is the reason
why, the same Wilcoxon test for paired data was applied. When comparing SE with TE,
there were found significant differences between all the parameters analyzed excepting
FA 0 (manual) vs. Average FA 0 where p-value was >0.05 (showing no significant
differences between parameters).
Table II. The samples description and patient`s characteristics
SAMPLE I SAMPLE II
PATIENTS 13 89
FEMALES 9 45
MALES 4 44
AGE (MEAN±SD) 59.84±9.99 years 58.06±11.7 years
BMI (MEAN±SD)
26.62±3.35 kg/m
2
25.99±4.23 kg/m
2
LIVER DISEASE ETIOLOGY
VHC 9 39
VHB - 7
VHB+VHC - 2
OTHER CHRONIC HEPATOPATHIES
(WILSON DISEASE, NASH, ETC)
4 41
SD= standard deviation; BMI=body mass index; VHC= viral hepatitis C; VHB= viral hepatitis B; NASH= Non-
alcoholic steatohepatitis

Table III. Wilcoxon test for paired data, applied for sample I and sample II.
SAMPLE I SAMPLE II
WILCOXON TEST FOR PAIRED DATA p-values
FA 0 (MANUAL) VS. FA 10 (MANUAL) < 0.05 < 0.05
FA 0 (MANUAL) VS. AVERAGE FA 0 ns ns
FA 0 (MANUAL) VS. LIVER BIOPSY ns -
FA 10 (MANUAL) VS. LIVER BIOPSY < 0.05 -
FA 0 (MANUAL) VS. TE ns < 0.05
FA 10 (MANUAL) VS. TE < 0.05 < 0.05
AVERAGE FA 0 VS. AVERAGE FA 10 < 0.05 < 0.05
AVERAGE FA 0 VS. LIVER BIOPSY ns -
AVERAGE FA 10 VS. LIVER BIOPSY < 0.05 -
AVERAGE FA 10 VS FA 10 (MANUAL) ns <0.05
AVERAGE FA 0 VS. TE ns < 0.05
AVERAGE FA 10 VS. TE < 0.05 < 0.05
LIVER BIOPSY VS. TE ns -
ns= non-significant differences (p-value>0.05); FA= frame average; TE- transient elastography
3.5. Discussion
The results from the first sample showed that there were significant differences
between FA 0 and FA 10 both with and without ElastoBreast software image processing.
Also, there were no significant difference between FA 10 and Average FA 10. Thus, the
outcomes suggest that, in this sample, averaging all the valid frames did not influenced
the liver fibrosis staging at a statistically significant level.
There were no significant differences between FA 0 and liver biopsy fibrosis
staging but there were differences between FA 10 and liver biopsy. Thus, although from
this data analysis alone it is not possible to conclude that F0 is the best choice for SE
estimation the results suggest that, if choosing between FA 10 and FA 0 for liver stiffness
estimation and movie acquisition, the latter would be preferred and more recommended
by the data analysis of the above outcomes.
When SE with TE were compared in the small sample, the ElastoBreast software
processed images showed similar p-values like the other SE images, without the
software utilization (table III). Thus, it seems that SE color map interpretation are the
same, with or without averaging all the valid images, the operator being able to stage SE
color map without significant differences.
Further on, the data from the second sample were processed where only TE with
SE were compared, in the lack of recent biopsies. Significant differences were found
between FA 0 (manual), Average FA 0, FA 10 (manual) and Average FA 10 vs. TE.

49
Surprisingly, there was a significant difference between FA 10 and Average FA 10 but
not between FA 0 and Average FA 0. However, in the large sample, SE was different from
TE no matter of the chosen FAs.
Two examples of SE estimation are illustrated: one from the first sample where a
patient known with chronic hepatitis presented an elastic score of 1 on SE, using FA 0
and where, biopsy confirmed fibrosis stage 1 (fig 10). Another example is in fig 11
where, despite the elastic scores of 1 and 0 given by SE, FA=0 and FA=1 respectively,
liver stiffness estimation by TE measured 23.1 kPa, which corresponds to F4 (cirrhosis).
Since in this case, gray scale ultrasound showed discreet micro nodular pattern it is
plausible a METAVIR F4 score.
The main limitation of the study was the lack of liver biopsy for the second sample
but since TE is currently used for liver stiffness estimation, liver biopsy is avoided both
by practitioners and patients, leaving the biopsy only for complex cases.
Also, the study design included the extreme values of FA available on Logiq
ultrasound; it is unknown if a middle value of FA would have shown better results for
liver stiffness estimation.
3.6. Conclusions
ElastoBreast software did not significantly influence liver stiffness interpretation,
when liver biopsy was the reference method. Also, in the same sample, there were no
significant differences between liver biopsy fibrosis staging and SE with frame average
0.
When TE was used as a reference method, there were significant differences on
color maps, with frame average 10 manual interpretation versus ElastoBreast software
movie processing. Also, liver strain elastography movies, with frame average of 0 and 10
significantly differed from TE staging in the second sample.
Since the results from the two samples are so contradictory, it is very hard to
conclude if using Fujimoto`s modified elastic score using strain elastography would be
useful for liver fibrosis estimation, a larger sample with liver biopsy being mandatory.

51
4. Study II. Influence of food intake on 2-d shear wave
elastography assessment of liver stiffness in healthy
subjects
4.1. Introduction
Among all non-invasive methods used for liver stiffness estimation, elastography
is the one most commonly used, with a good predictability for liver fibrosis64–68. Some
factors have already been proven to influence liver stiffness estimation using
elastography techniques. To avoid misleading increased liver stiffness assessment, all
confounding factors must be taken into account and excluded as much as possible.
Among these factors, food intake has an important role in defining liver stiffness because
of changes in intrahepatic vascularization69,70. Both transient elastography (TE) and
Acoustic Radiation Force Impulse (ARFI) imaging are influenced by food intake; liver
stiffness values increase starting 15 min after meal and return to baseline values about
2–3 h after the meal57,61,62,71. It is well documented that about 15–40 min after food
intake, hemodynamic changes occur in splanchnic vessels, with differences between
healthy subjects and patients with cirrhosis 69,70. Because of these changes, liver stiffness
prediction with TE and ARFI methods is not reliable immediately after food
intake57,61,62,71.
Using transient elastography, Mederacke et al.61, in 12 apparently healthy
subjects, measured an overall increase in liver stiffness of 20% immediately after a meal
(from 4± 0.7 to 4.8±0.9 kPa), with a mean peak value up to 24% after food intake
(4.0±0.7 to 5.1±0.9 kPa). Arena et al.71 found that liver stiffness increases more
conspicuously in patients with cirrhosis than in healthy subjects or patients with chronic
hepatitis, as predicted by TE. In the same study, mean liver stiffness values increased 30
min post-prandial by up to 24% of baseline values in patients with chronic hepatitis
stage F0–F1, with mean peak values up to 33%; then, 120 min after the meal, liver
stiffness returned to baseline values. In the control group, which had water instead of
food, the mean values of liver stiffness were not modified at all, and the mean peak
values were only 3.7% higher for all measurements71.
Popescu et al.62 used ARFI elastography to analyze liver stiffness before and after
a standardized meal in healthy volunteers. The authors described a significant increase
in liver stiffness values (>15% of baseline values) 1 h after the meal in 45.7% of the
subjects. At the same time, in 50.8% of cases, they observed modest increases in liver

stiffness (≤15% of baseline values). In the remaining 3.5% of cases, there were lower
liver stiffness values 1 h after the meal compared with fasting conditions (>15% of
baseline values). Within 3 h after the meal, liver stiffness values did not significantly
differ from the values in the control study 62; liver measurements made only under
fasting conditions and 1 and 3 h after the meal and the complete curve of the liver
stiffness after food intake could not be established. In the study group, mean liver
stiffness before the meal was 1.27±0.23 m/s, within 1 h after the meal it was 1.51±0.40
m/s, and within 3 h after the meal, mean liver stiffness was 1.46±0.51 m/s62. Within 1 h
after the meal, mean liver stiffness measured by ARFI elastography increased by 19%
compared with fasting conditions.
In the control group, 1 h after the first measurement, the mean stiffness was
similar to the first measurement (1.28±0.21 m/s vs. 1.22±0.19 m/s). It is worth noting
that maintaining the same depth for each measurement per subject was not mentioned
in the study design, which is an important parameter for multiple liver stiffness
measurements with ARFI and 2-D shear wave elastography (SWE)72,73.
In a similar study, Goertz et al.57 compared liver stiffness values of the same
patients before and after food intake. At 30 min after the meal, the authors reported a
significantly higher (#8.74%) mean liver stiffness value (1.03±0.10 m/s vs. 1.12±0.11
m/s).
Two-dimensional shear-wave elastography is a relatively new elastographic
ultrasound technique, with promising results in prediction, assessment and diagnosis of
significant liver fibrosis67.
Liver stiffness estimation using 2-D SWE performed on the same day has been
reported to have an intra-class correlation coefficient (ICC) up to 0.9574. This type of
elastography is able to express hepatic elasticity both as the velocity of the shear wave
(m/s) and in absolute elasticity modulus units (kPa).
To the best of our knowledge, there weren`t published studies on the influence of
food intake on liver stiffness values, as measured by SWE with an Aixplorer ultrasound
system (SuperSonic Imagine). The aims of this study were to assess the influence of food
intake on liver stiffness values estimated by 2-D SWE and to explore the importance of
body mass index (BMI) and gender on liver stiffness variation after a standardized meal.
4.3.1 Selection of subjects
The study included 36 healthy volunteers without medical history relevant for
liver disease and with a normal clinical examination. Laboratory tests were not
performed. Abdominal ultrasonography was performed before the study, resulting in
exclusion of 4 volunteers because of an echogenic liver compatible with fatty infiltration.

53
Another volunteer was excluded for higher than normal liver stiffness values under
fasting conditions52.
Finally, 31 participants complying with the inclusion criteria (normal abdominal
ultrasound, no history of liver disease and normal liver stiffness values under fasting
conditions), were enrolled in the study. The participants consumed no solid or fluid food
for at least 6 h before the study. The first measurement of liver stiffness was conducted
under fasting conditions. Thereafter, each volunteer consumed a standardized meal of
748 kcal (51.71 g carbohydrates, 44.33 g lipids and 35.52 g protein) within 5 min.
Subsequently, another six measurements were made regularly from 20 min after to 120
min after the meal.
The study was approved by the local institutional ethics committee. All
volunteers signed an informed consent form in accordance with the Declaration of
Helsinki (2008).
4.3.2. Real-time two dimensional shear wave elastography
An Aixplorer (SuperSonic Imagine, Aix-en-Provence, France) ultrasound machine
with a SC6-1 convex transducer was used.
Liver stiffness was measured in the right lobe, through an intercostal approach.
The subject was placed in the supine position, with the right hand above the head, and
was asked to breathe with normal amplitude.
The position of the transducer for the first measurement was marked on the skin,
and consecutive measurements were obtained with the transducer in the same location.
After the area of interest was identified, the subject was asked to stop breathing for a
few seconds until the color box stabilized, while steady external compression was
applied to the transducer, according to the manufacturer’s instructions.
Anatomic landmarks next to the area of interest (such as intrahepatic vessels and
gallbladder position) were used to direct measurement to the same approximate area
each time (fig 12a and 12b). The region of interest (ROI) was set to 15 mm in diameter,
positioned with the upper edge at least 1 cm under the liver capsule, but not more than
5 cm, avoiding large intrahepatic vessels, gallbladder and liver ligaments (fig 12a and
12b).

Figure 12a. Liver stiffness estimation before (0’) and after the standardized meal, at 20, 40 and 60 min
respectively
Figure 12b. Liver stiffness estimation after the standardized meal, at 80, 100 and 120 min respectively.

55
The ROI depth set for each subject during the first measurement was kept
constant during all consecutive measurements. The elasticity of the liver was measured
in kilopascals. Five valid values were obtained for each measurement.
A value was considered valid when the ROI was placed with its upper edge at least
1 cm below the capsule, but not deeper than 5 cm. It did not include intrahepatic large
vessels or ligaments, and the standard deviation was ≤10% of the mean value measured
on each image.
The unique value defining liver stiffness measurement at a given time was
obtained by averaging the five individual valid values, according to Sporea et al.75. The
normal liver stiffness range estimated by SWE was 2.6–6.2 kPa52.
All measurements were performed by a single researcher (M.M.G.) with 4 years
of experience in ultrasonography and liver elastography.
4.3.3. Statistical analysis
Statistical processing was performed using dedicated software: IBM SPSS
Statistics for Windows, Version 19.0 (IBM, Armonk, NY, USA).
The distribution of the data was checked with the Shapiro–Wilk test. The
multivariate analysis of variance (MANOVA) test for repeated measures was used for
comparison of data. For the post hoc data analysis, the t-test for paired samples was
used. The outcomes of the t-test were validated by simulations, using the bootstrap
method.
4.4. Results
The demographic characteristics of the enrolled volunteers are listed in Table IV.
Mean liver stiffness values for the entire sample and for each gender, before (baseline
values) and after the meal, are listed in Table V. Baseline values were considered those
values obtained at the first measurement under fasting conditions. Mean liver stiffness
values, standard deviations (given by the ultrasound for each measurement) and depth
(at which the region of interest was placed) were analyzed using the MANOVA test for
repeated measurements, with a general linear model. Sphericity of the data was
assumed, and a significant difference between liver stiffness measurements was
observed (p-value <0.01) (Table V).

Table IV. Main characteristics of the subjects involved in the study
Parameter Study group
Nr of subjects 31
Mean age (y) 31.39 ± 8.1
Gender
Male
Female
n=14 (45%)
n=17 (55%)
Mean body mass index (BMI) (kg/m2)
Females
21.83 ± 2.6
21.71 ± 2.8
Males 21.97 ± 2.5
*values are n, n (%) or mean ± standard deviation
No significant differences were identified between the depths at which
measurements were performed or between standard deviation values before and after
the meal (p >0.05) (Table V).
When gender and BMI were introduced as factors in the statistical analysis of
liver stiffness, there was a significant difference between genders in relation with the
meal (p <0.01). BMI was not found to significantly influence liver stiffness in relation to
the meal (p >0.05) (Table V).
Post hoc data analysis (paired t-test) revealed significantly increased liver
stiffness values 40 min after food intake and significantly decreasing stiffness values
between 60 and 80 min after the meal (p <0.05). Also, values 120 min after the meal
were significantly lower compared with values under fasting conditions
(p <0.05) (Table V).

57
Table V. Liver stiffness values for the entire sample and also for each gender, during all
measurements*
Measurements (min) Mean liver stiffness±SD (kPa)
Sample Females Males
0 min (fasting) 4.6±0.63** 4.3±0.63 4.9±0.45
20 min 4.7±0.79 4.3±0.70 5.2±0.63
40 min 4.7±0.70 4.4±0.63 5.2±0.52
60 min 4.6±0.71 4.3±0.60 5.1±0.59
80 min 4.5±0.66 4.2±0.60 4.9±0.52
100 min 4.5±0.65 4.2±0.64 4.9±0.45
120 min 4.4±0.58 4.2±0.59 4.7±0.44
* Mean liver stiffness for the entire sample increased slightly after the meal (0.1 kPa between fasting and 20–
40 min after the meal) and then continuously decreased until the last measurement (120 min). The difference
in liver stiffness between fasting conditions and 40 min after the meal was more obvious in males than in
females (0.3 kPa vs. 0.1 kPa).
**Mean ± standard deviation.
Table VI. Application of the MANOVA test for multiple measurements to liver stiffness*
MANOVA test for multiple measurements p-value
Standard deviation (kPa) >0.05
Depth (cm) >0.05
Liver stiffness (kPa) <0.01**
Introduced as factor: BMI >0.05
Gender <0.01**
MANOVA = multivariate analysis of variance.
* The depth of the region of interest, for all seven series of measurements (before and after the meal), is given.
Gender and body mass index were introduced as factors in the liver stiffness data analysis and the only
significant difference was for gender (p <0.01).
**p< 0.05 was considered to indicate statistically significant difference.

Table VII. Application of paired t-test to comparison of liver stiffness under fasting conditions (0
min) and various times after a meal*
Measurement (min) Liver stiffness (p-value)
0 min vs:
20 min p>0,05
40 min p <0.05**
60 min p>0.05
80 min p>0,05
100 min p>0,05
120 min p <0.05**
20 min vs 40 min p>0.05
40 min vs 60 min p>0.05
60 min vs 80 min p <0.05**
80 min vs 100 min p>0.05
100 min vs 120 min p>0.05
* There were significant differences between 0 and 40 min, between 60 and 80 min and between 0 and 120
min, respectively.
**p < 0.05 was considered to indicate statistically significant difference.

59
Fig. 13. a) Mean liver stiffness (kPa) and SD under fasting conditions (0 min) and after food intake at 20, 40,
60, 80, 100 and 120 min, respectively, only for females. There is a slight increase in mean liver stiffness values
40 min after the meal (from 4.3±0.63 to 4.4±0.63 kPa).
b) Mean liver stiffness (kPa) and SD in fasting (0 min) and after a standardized meal at 20, 40, 60, 80,100 and
120 min, respectively, for males. It is worth noting that the mean liver stiffness values in males were higher
values within 20–40 min after the meal (from 4.9±0.45 to 5.2±0.52 to 5.2±0.63 kPa, respectively). Also, there
liver stiffness values were decreased between 60 and 80 min, with similar liver stiffness behavior observed in
the entire sample. SD=standard deviations.
The overall difference between mean stiffness values obtained under fasting
conditions and those obtained 40 min after the meal was 2.2% for the entire sample,
6.1% for males and 2.3% for females. The mean liver stiffness values for males and
females, for all seven measurements, are illustrated in Figure XII (a, b).

Table VIII. Liver stiffness peak values after food intake for the entire sample and for each gender*
Liver stiffness mean peak values after meal± SD (kPa)
Sample Females Males
5±0.72** (↑8%) 4.6±0.62 (↑7%) 5.5±0.53 (↑12%)
* The mean peak liver stiffness value was considered the average of the highest liver stiffness values after the
meal.
** Mean±standard deviation.
Table IX. Liver stiffness modification after food intake*
↑<15% 74,20% (23 subjects)
↑>15% 12,9% (4 subjects)
Decrease/ No increase 12,9% (4 subjects)
* Only 4 of 31 subjects had more than 15% increased liver stiffness values after the meal; 23 subjects had
slightly increased values after the meal. Also, 4 subjects had a decrease in the liver stiffness or remained stable
after the meal. The increase in liver stiffness was calculated as % = (liver stiffness peak value–liver stiffness
value under fasting condition)/liver stiffness value under fasting condition x 100.
Table X. Liver stiffness peak values after the meal*
Liver stiffness peak values after the meal Total
20 min 26% (8)
87% (27)
40 min 36% (11)
60 min 19% (6)
80 min 3%(1)
100 min 3% (1)
120 min 0% (0)
No increase/ slow decrease 13% (4) 13% (4)
Total 100% (31)
* The majority of the subjects (62%, 19/31) had peak liver stiffness values 20–40 min after the meal. Liver
stiffness was increased after the meal in 87% (27/31) of the subjects or slightly decreased during all
measurements.

61
For subjects who had increased liver stiffness after the meal, we also calculated
the mean peak value, which was defined as the highest value encountered after food
intake. From a clinical point of view, this value is more representative of the importance
of individual increases in liver stiffness rather than the mean values at 40 min, as not all
subjects peaked at this time. The mean liver stiffness peak value was ≤8% higher (≤12%
for males and ≤7% for females) than the mean liver stiffness value under fasting
conditions (Table 6).
The outcomes of the t-test were validated by simulations of a sample of 1,000
cases with characteristics similar to those of our sample, using the bootstrap method.
Consequently, the significant differences observed in our sample became even
more obvious, with p <0.01.
Liver stiffness modification after the meal (% = [liver stiffness peak value-liver
stiffness value under fasting conditions]/liver stiffness value under fasting conditions x
100) was computed, and the results are summarized in Table IX. In most of the
participants, liver stiffness increased 20 or 40 min after food intake (26% and 36%,
respectively), but in some, presented values increased 60 min (19%) or even 80 and 100
min (3% and 3%, respectively) after the meal. In 13% of the subjects, liver stiffness
values did not increase at all or slightly decreased (Table X).
4.5. Discussion
Using SWE, we measured significantly increased mean liver stiffness values 40
min after the meal (p <0.05). Between 60 and 80 min after the meal, liver stiffness
significantly decreased, then returned to baseline values at 80 min (comparing mean
liver stiffness values before and 80 min after the meal, p <0.05). Thereafter, liver
stiffness exhibited a continuously and slowly decreasing slope until the last
measurement at 120 min.
The difference between baseline values and values 120 min after the meal was
statistically significant (p<0.05). We have no clear explanation for this observation.
Most of the published studies on liver hemodynamics in healthy subjects stopped
earlier or around 120 min after food intake. Immediately after food intake, portal blood
flow increases and, thereafter, decreases until it reaches the baseline values. After 100–
120 min, portal flow might still be slowly decreasing, thus explaining the still decreasing
liver stiffness we observed. Only a few studies describe the circadian variations in portal
venous blood flow in cirrhotic patients76,77. Although these studies did not include
healthy subjects, we assume that if a similar circadian portal flow is also present in
healthy subjects, it might explain our findings. Late post-feeding liver depletion might
be another explanation.
Late post-feeding (>120 min) analysis of portal blood flow in healthy subjects
might provide data explaining the observed phenomenon. To the best of our knowledge,
this observation has not been previously reported.

When we introduced gender and BMI as determinant factors in liver stiffness
value data analysis, we observed a significant difference related to gender
(p<0.01), but not to BMI (p>0.05) (Table VI). The differences between liver stiffness
under fasting conditions and liver stiffness 40 min after the meal and also between mean
liver stiffness under fasting conditions and mean peak values were higher in males than
in females (Tables V and VIII). Most probably, the differences found in the entire sample
were due predominantly to the increased liver stiffness observed in male subjects.
The literature describes differences between male and female baseline liver
stiffness values72,78, but, to the best of our knowledge, there are no published studies
describing different-amplitude increases in liver stiffness in males and females after
food intake. Although Szinnai et al.78 had already reported that after a meal there is a
greater increase in portal flow in males than in females, the difference was not found to
be statistically significant.
Increasing stiffness >15% of the baseline values after a meal was reported to be
significant by Popescu et al.62, but in a similar study, Goertz et al.57 reported only 8.74%
higher values of liver stiffness, compared with fasting conditions.
In our study, the difference between mean stiffness values under fasting
conditions and values after the meal (40 min) was 2.2% for the entire sample, 6.1% for
males and 2.3% for females. From a statistical point of view, the difference between
mean liver stiffness values under fasting (0 min) and those 40 min after the meal was
significant (p <0.05). However, the clinical relevance of a 2.2% or 6.1% change after the
meal is debatable. Because the values did not increase in all subjects 40 min after the
meal, we calculated the mean peak liver stiffness value, which more accurately
expresses the relevance of increased liver stiffness after a meal. Mean peak liver stiffness
increased by 12% in males, 7% in females and 8% in the entire sample.
For healthy persons, this percentage might seem negligible. However, at times, a
smaller change might reflect the difference between significant and insignificant liver
fibrosis, as the cut-off values for different liver fibrosis stages predicted by ARFI and
SWE are very tight.
Using transient elastography, Mederacke et al.61 reported an increase in liver
stiffness ≤20% and a mean peak value ≤27.5% in 12 apparently healthy subjects after
food intake. Although Arena et al.71, in a larger study, reported higher liver stiffness
values after a meal (mean values at 30 min ≤24% higher and a mean peak value ≤33%
higher than baseline values), it must be taken into account that both the control group
and the study group included patients known to have with chronic liver disease, stage
F0–F1, who may exhibit a different magnitude of change in liver stiffness after a meal,
compared with healthy subjects.
There were no significant differences between depth and standard deviations,
which indicates that the acquisition parameters established at the beginning remained
constant during all seven measurements.

63
It is worth noting that the standardized meal used in this differed, in terms of
percentage composition, from that used in previous studies for healthy subjects and
patients with chronic hepatitis or cirrhosis62,69–71. However, 748 kcal (52.71 g
carbohydrates, 44.33 g fat, 35.52 g protein), should be sufficient to induce changes in
liver blood supply, given that a 300-kcal meal caused significant hemodynamic changes
in splanchnic vasculature70 and liver stiffness estimated by TE79. Moreover, it was
documented that, in terms of meal content, there were no differences in post-meal portal
blood flow between the highcarbohydrate/low-fat and low-carbohydrate/high-fat
meals80.
Multiple acquisition parameters, such as ROI diameter, depth, marking the exact
intercostal space and using anatomic landmarks to identify the same intrahepatic
section, were set with the aim of decreasing as much as possible intra-observer
variability. However, inter- and intra-observer variability was not tested, as it was
beyond the scope of this work.
A limitation of this study is the small number of healthy volunteers enrolled in
the study. A simulated bootstrap with a sample of 1000 similar cases produced the same
results, with a p value even smaller than 0.01, which indicates that our findings were
correct for a given population, despite the small number of subjects enrolled in the
study.
Also, it must be admitted that from a technical standpoint that it is relatively
difficult to obtain exactly the same scan plane in liver ultrasound, at regular intervals of
time, as this depends not only on the operator, but also on the subject position and
moment of respiration.
To reduce the impact of this error, acquisition parameters such as depth,
intercostal space, transducer position and diameter of the ROI were set for each subject.
Anatomic landmarks were used for spatial orientation accuracy.
The study was designed and approved without a control group, similar to other
published studies57. The rationale for this approach was that it has already been
reported that, on serial measurements, liver stiffness did not change significantly over
time in control groups62,71. It is worth mentioning that the ICC for liver stiffness
estimation by 2-D SWE performed on the same day is up to 0.9574. Still, the absence of
the control group is considered a limitation of the study.
Another limitation of the study is the lack of blood tests for liver disease. Healthy
subjects were defined as asymptomatic, with normal physical examination and normal
abdominal ultrasound, as suggested by other authors62,75.
Normal-range values at SWE, as published by Suh et al.52, were included in this
study as an additional criterion of normality.

4.6. Conclusions
Prediction of liver stiffness using 2-D SWE in healthy subjects reveals complex
variation after food intake. We observed that food intake in healthy subjects not only
causes an immediate increase in liver stiffness, but also has influence later, as a
continuing decrease in stiffness 120 min after the meal. In our study, gender apparently
played an important role in determining the amplitude of liver stiffness changes after
the meal, with a mean peak value increase of 12% in males. Our results suggest that after
food intake, liver stiffness might increase more in healthy males than in females17.
However, it must be stressed that before drawing any conclusions on this aspect, more
studies on larger numbers of subjects are needed.
Although in most cases the magnitude of change was lower than that reported for
TE or ARFI, our results are similar to already published observations and thus constitute
another argument for using 2-D SWE for estimation of liver stiffness under fasting
conditions.
Note: This study was published in Ultrasound in Medicine and Biology Journal17.

65
5. Study III. The influence of acute physical effort on
liver stiffness estimation using Virtual Touch
Quantification (VTQ). Preliminary results.
5.1. Introduction
Virtual Touch Quantification (VTQ) elastography uses focused ultrasound
(US) pulses which are sent to the tissue using a conventional US transducer and
dedicated equipment/software. The tissue responds to these pulses with different
amount of displacement creating shear waves of variable velocities81. The stiffer the
tissue is, the higher is the shear wave velocity – thus these shear wave velocities can be
used to estimate stiffness of the respective tissue; the velocity measurements are usually
given in (c) m/sec and can be transferred by simple equations in Pascals82,83. As tissues
have different components, ultra-structural compositions and densities, normal shear
wave velocity cut-off values also vary84.
For example, in kidneys, shear wave velocities are influenced mainly by external
pressure, tissue vascularization, intravascular pressure, and tissue anisotropy81,85. Thus,
increased shear wave velocities were described without a necessarily stiffer kidney
parenchyma, just due to different tissue compartments, anisotropy, the high
vascularization and elevated urinary collecting system pressure85.
Some of these parameters are responsible also for increased liver shear wave velocities
in different pathologies, actually without a stiffer liver parenchyma itself. Examples for
this phenomenon are cholestasis, increased level of liver enzymes, acutely
decompensated cardiac failure; also food intake may impair liver elasticity values
derived from US elastography47,48,56,57,62,86.
There are studies describing that liver stiffness measurements increase
immediately after food intake, most probably due to a markedly increased blood flow in
the portal vein69. In acutely decompensated heart failure, there is an increased venous
pressure causing stasis in the inferior vena cava, influencing blood flow in the
intrahepatic liver veins which is also transmitted into the liver parenchyma and
therefore, liver stiffness appears increased56.

It is little known about another cause of blood flow redistribution is during
physical effort. There are many studies describing some sort of physiological
gastrointestinal ischemia during physical exercise, as more than 50% of the lower
abdominal arterial blood flow is redistributed to the muscles (86–89). This assumption
suggests that during physical exercise liver stiffness measurements will be impacted too
and probably should be lower than baseline values.
To our knowledge, there are no studies which describe how physical exercise
influences liver stiffness estimations. Moreover, it would be of great clinical importance
to know, what happens with liver stiffness estimations after physical exercise,
especially, to know the appropriate timing for accurate liver stiffness estimation tests.
The purpose of this prospective study was to evaluate if liver stiffness measurements
are influenced by physical exercise in apparently healthy subjects and, if so, also to
determine when liver stiffness measurements return to baseline values.
5.3.1. Subjects
Seven healthy volunteers (32.14±4.52 years, 6 females and 1 male) were included
in this pilot study. All volunteers were medical staff, whose annual blood samples were
within normal limits, with no history of liver or heart disease. All volunteers were
physicians. They agreed to participate in this pilot study without any remuneration;
according to national regulations and local institutional policy, the Ethical Board
approval for this study was waived.
5.3.2. Study design.
The study protocol was as follows:
Step 1: a baseline abdominal US examination including VTQ elastography was
performed using an Acuson S3000 (Siemens Inc., Forchheim, Germany) device with a
6C1HD abdominal curved array transducer by a radiologist with four years of
experience in liver elastography.
VTQ liver stiffness estimation was always performed in fasting conditions,
following international guidelines 14,18.
Step 2 consisted of a spiroergometry which was performed in a stepwise fashion 87.
Exercise stress testing was performed as an incremental exercise on a cycle
ergometer (Excalibur Sport, company LODE). The workload was increased every minute
until exhaustion 87.
ECG and oxygen consumption were continuously recorded, blood pressure and
lactate were measured every two minutes. Maximal heart rate, maximal lactate, and
respiratory exchange ratio were documented as a sign of exhaustion.

67
Step 3 was represented by three consecutive series of liver stiffness estimation:
immediately after spiroergometry as well as five minutes and ten minutes after
spiroergometry respectively.
For liver stiffness estimation, the volunteers were lying in supine position, with
the right hand placed above the head. The transducer was placed perpendicular to the
abdominal wall avoiding intrahepatic vessels, ligaments and the gallbladder. Each time,
liver elasticity was assessed in the same intercostal space in the mid-axillary line in the
right liver lobe. The region of interest (ROI) was placed at least 1cm under the liver
capsule, where the liver parenchyma was at least 5 cm thick. The depth and position of
the ROI was established for each subject during the first series of liver VTQ elastography
individually and then was kept constant for all measurements.
When the ROI was placed in the proper place, the subjects stopped their breath
for a few seconds, till the shear wave velocity was acquired. The median of ten correctly
performed measurements was used to estimate the liver stiffness value for every series
of measurement. The individual increase of liver shear wave velocities was calculated
immediately after exercise using the following formula: %= (shear wave velocity
immediately after exercise– shear wave velocity before exercise)/ shear wave velocity
before exercise x 100).
As additional criteria for accurate liver stiffness estimation, IQR (interquartile range)
and SR (success rate) were calculated, according to EFSUMB guidelines14,18.
5.3.3. Statistical analysis
For statistics, Microsoft Excel and IBM® SPSS Statistics (v.19.0 Armonk, NY)
software packages were used, both for data representation and for statistical analysis.
Data distribution was tested with the Shapiro-Wilk test and then, the MANOVA test for
multiple measurements and the t-test for paired samples were applied. The paired t-
tests outcomes were checked by the bootstrap method, for a 100 patients, with similar
characteristics.
5.4. Results
One subject stopped the exercise before exhaustion due to muscle pain. Although
an elastography was performed immediately after she had stopped the exercise, she was
excluded from further statistical analysis. Thus, finally, a total of six healthy subjects
were available for analysis (5 female, 1 male) with a mean age of 32±4.94 years and a
body mass index (BMI) of 21.83±4.29 kg/m2. Mean liver shear wave velocities were
1.05±0.12 m/sec before exercise, 1.34 ±0.16 m/sec immediately after exercise,
1.23±0.14 m/sec five minutes after exercise, and 1.05±0.11 m/sec ten minutes after
exercise. For all series of measurements, IQR was below 30% and SR above 60%.

Fig 14. Individual liver shear wave velocity values over time (m/sec). Data before, immediately after, five
minutes after, and ten minutes after exercise. Immediately after exercise, liver stiffness values increased
abruptly, and then slowly returned to baseline values within ten minutes.
Fig 15. Comparison of shear wave velocities. The individual median values at each point of time during the
measurement series are given in range (blue boxes) and standard deviation (whisker).
The single subject who had stopped the exercise complaining of muscle pain only
had a 1.43% increase in liver shear wave velocity immediately after she stopped the
exercise. The other six subjects who successfully finished the exercise until exhaustion

69
had highly increased in liver shear wave velocities (19.07%, 21.60%, 30.10%, 35.05%,
40.00%, and 52.76%); development of the individual liver shear wave velocity values
over time are shown in figure 14. Using the MANOVA test for multiple measurements,
there were significant differences between the four series of liver stiffness evaluation
(before exercise, immediately after exercise, five min and ten minutes after effort), p
<0.01. Then, as a post-hoc data analysis, we applied paired t-tests to find where the
differences between these measurements were. Immediately after spiroergometry liver
stiffness values were increased compared with baseline values (p<0.01). There were
also significant differences between the values immediately after physical effort and five
minutes after the exercise (p<0.01). No significant differences were identified between
baseline values and the last measurement, at ten minutes after exercise (p> 0.05) (fig
15). Using the bootstrap method, a sample of 100 patients with similar characteristics
was simulated. This method reinforced the outcomes of the paired t-tests applied for
our study sample, showing the p-values in the same fashion as the study sample.
5.5. Discussion
Many parameters may cause higher intrahepatic tissue shear wave velocities (e.g.
fibrosis, acutely decompensated cardiac failure, increased level of liver enzymes, food
intake, and cholestasis); in such conditions there is also an increased intracellular
hepatic pressure or increased liver, mainly portal venous, blood flow – both also
influencing liver stiffness. Most probably, those latter phenomena are explained by the
fact that the liver capsule is relatively inextensible and does not allow large expansion
in sudden liver volume variations. There are a few physiological and pathological
conditions that are affected by these variations and may – when using tissues sound
propagation velocity depending methods for liver stiffness estimation (such as US
elastography methods) – be influenced by these situations such as increased
postprandial liver blood supply immediately after food intake48,62,69 or with acutely
decompensated heart failure56,57 and with extra-hepatic cholestasis47,48.
Another, yet undescribed potential liver stiffness estimation variation may occur
in comparable physiological conditions which are associated with the redistribution of
arterial blood flow such as during physical exercise.
It is well known that during physical effort heart rate and blood pressure are
increasing and blood flow is redistributed mostly to the skeletal muscles. During
physical exercise, splanchnic blood flow decreases to more than 50% of baseline values
due to sympathetic activity88.
In healthy subjects, heart rate returns to baseline values in around 1-14 min after
the end of the physical exercise and mean blood pressure returns to baseline values in
around 3-8 min, depending on exercise level intensities89. Also, the decreased lower
abdominal arterial blood flow returns to baseline values in around 2-6 min after the end
of physical exercise in healthy subjects89.

Portal venous flow decreases during exercise, down to 80% of baseline
values90,91. But the literature also describes a “hepatic arterial buffer response”
phenomenon, i.e., the hepatic artery dilates to compensate for the decreased portal
venous flow92–94. This response is due to adenosine accumulation and may compensate
up to 25-60% of the decreased portal venous flow93,95.
However, some authors found that after physical exercise, the portal venous flow
velocity remained relatively unchanged and the decreased portal blood flow volume was
then explained by a decreased calibre of the portal vein96.
When analysing the liver blood flow velocities after exercise, hepatic veins are
also important. There are reports on increased blood flow velocities in hepatic veins
after exercise, with values up to 148% in the systolic phase of the three-phasic
undulating liver vein flow profile, up to 139% for diastolic phase, and up to 372% during
atrial contraction – with a consecutive backward flow into the hepatic veins96. Thus,
immediately after exercise, there is a considerable regurgitation flow in hepatic veins,
probably related to atrial contractions.
Finally, motion transmitted from heart beat and aortic pulsations may cause
artificially increased elastography results – this however has been reported only for the
left liver lobe 97; our measurements were taken in the right liver lobe. It nevertheless
may be another reason explaining our results: if one considers the increased heart
frequency, stronger heart beats and aortic pulsations as obviously present in the state
of heavy physical effort it might be hypothesized that these motions are event
transmitted to the right liver lobe and thus this may be one of the factors why US
elastography measurements immediately after physical exercise are unreliable.
Our results show that liver shear wave velocities used for estimating liver
stiffness increase immediately after physical exercise and return to normal after some
rest, in a similar fashion as the other factors that indicate the state of the circulation
regulation. The reason for the obvious and significant increased shear wave velocities,
however, remains unclear. Most probably, the markedly increased regurgitation flow
velocities in hepatic veins during atrial contraction might explain the impact on liver
shear wave velocities, with an increase up to 52%. It is also possible that the hepatic
arterial buffer response might have an additional contribution to an increased
intrahepatic pressure and thus might contribute to the elevated “stiffness” values found
in this study; but probably also more complex mechanisms might be responsible for this
marked increased shear wave velocity after exhaustion which are not yet completely
understood.
Potentially also some underlying physical phenomena intrinsic to the
measurement method may also contribute to these findings, such as US pulse wave and
shear wave propagation or depiction.
Nevertheless – in our series liver shear wave velocities returned to the baseline
values by ten minutes after cessation of the physical effort, when heart rate, blood
pressure and lower abdominal arterial blood flow return to baseline values in healthy

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