The document evaluates the ability of computer-assisted quantitative image analysis to differentiate hepatocellular carcinoma (HCC) grades based on nuclear morphology. Nuclear features such as area, axis, and perimeter were measured in HCC samples of different grades (I-III) using imaging software. Results found that higher grade HCC had significantly larger nuclear features and greater nuclear density and nuclear-to-cytoplasmic ratios compared to lower grades, indicating computerized nuclear analysis can help diagnose and grade HCC tumors.

1. 102
Analytical and Quantitative Cytopathology and Histopathology®
0884-6812/19/4103-0102/$18.00/0 © Science Printers and Publishers, Inc.
Analytical and Quantitative Cytopathology and Histopathology®
OBJECTIVE: To evaluate the ability of computer-
assisted quantitative methods using morphometric im-
aging software to differentiate between hematoxylin and
eosin–stained nuclei of different pathological grades of
hepatocellular carcinoma (HCC).
STUDY DESIGN: Computerized morphometric fea-
tures of cell nuclei in paraffin-embedded histological
sections of HCC were analyzed using Image-Pro Plus 6
software. Morphometric analysis was performed using
an optical microscope and micro camera. Seventy-five
cases of HCC with different histological grades (I, II,
and III) were collected from 75 slides. Nuclear imag­
ing analysis was performed to measure different mor­
phometric variables in each sample by computer image
analysis software. An average of 10 fields of vision
were systematically chosen under the microscope, and a
minimum of 150 nuclei were analyzed from each imaging
field. The correlation between the pathological grading
and the examined parameter was statistically analyzed.
RESULTS: The nuclear morphometric parameters (area,
major axis, minor axis, and perimeter) of tumor cells
were significantly increased in HCC with higher his­
tological grading (p<0.05). There was significant differ­
ence in the density number and nuclear area of tumor
cells between the low- and high-grade HCC (p<0.05).
Interestingly, the nuclear to cytoplasmic ratios were in-
creased with grading degree of the HCC.
CONCLUSION: Computer-assisted imaging analysis
of nuclear morphometric and densitometric features
of HCC cells are important diagnostic parameters for
histological grading of tumors and might help for sig­
nificant diagnosis of HCC. (Anal Quant Cytopathol
Histpathol 2019;41:102–110)
Keywords: analysis, computer-assisted image;
computer-assisted image analysis; computer-
assisted image processing; diagnostic imaging;
hepatocellular carcinoma; hepatoma; image
analysis, computer-assisted; image processing,
computer-assisted; image reconstruction; liver
cancer, adult; liver cell carcinoma; morphometry,
nuclear area; tumor grading.
Nuclear grading systems for hepatocellular carci­
noma (HCC) include a variety of criteria, such as
size, shape, and polymorphism of nuclei, struc­
ture, and densitometric parameters.1 However,
HCC represents over 90% of liver cancer.2 HCC
Evaluating the Diagnostic Efficiency of
Computerized Image Analysis Based on
Quantitative Nuclear Parameters in Different
Grades of Hepatocellular Carcinoma
Rowaida Saadawi, M.Phil., Jiexia Guan, M.Phil., Zhenning Zou, Ph.D., and
Hong Shen, Ph.D., M.D.
From the Department of Pathology, Nan Fang Hospital, and School of Basic Medical Sciences, Southern Medical University, Guangzhou,
China.
Drs. Saadawi, Guan, and Zou are Pathologists.
Dr. Shen is Professor.
Address correspondence to: Hong Shen, Ph.D., M.D., Department of Pathology, Nan Fang Hospital, and School of Basic Medical Sciences,
Southern Medical University, 1023 Sha-Tai South Road, Baiyun District, Guangzhou 510515, China (shenhong2010168@163.com).
Financial Disclosure: The authors have no connection to any companies or products mentioned in this article.

2. Volume 41, Number 3/June 2019 103
Computerized Image Analysis in HCC
is considered to be the fifth most common cancer
and the second cause of cancer-related death
through most of the health problem burden in
Asia, especially in China.3 In Asia the major risk
factor for HCC is the consumption of aflatoxin B1
(AFB1)-contaminated foodstuffs, while in China
the major risk factor is chronic hepatitis B virus
(HBV) infection.4 The most common age at pre­
sentation is generally between 30 and 50 years.5
The core etiological factors for HCC are hepatitis
B and C, alcoholic cirrhosis, hemochromatosis
tyrosinemia, alpha-antitrypsin deficiency autoim­
mune hepatitis, and porphyrias.6
Nuclear profiles have been reported as useful
prognostic predictors in various cancers. Data from
computerized morphometry are objective and can
be derived quickly by using conventional micro­
scopic analysis. However, image analysis of nu-
clear features is rarely applied to investigate grad­
ing of HCC.7 Based on the nuclear profiles such as
nuclear size are a polygonal, or major and minor
axis of the nucleus, densitometry and nuclear to
cytoplasmic ratio (N/C ratio) by using new im-
aging software techniques like Image-Pro Plus 6
(Media Cybernetics, Rockville, Maryland). Previ­
ously, a new prognostic estimation method in
breast carcinoma compared the prognostic accu­
racy of lymph node status with that obtained by
computer analysis of breast FNA cytology.8 Hence,
the malignant hepatocytes are mainly character­
ized by nuclear variations, such as enlargement,
change in shape, and adaptation of the chro­
matin arrangement, which morphologically ex-
pressed the genetic and epigenetic changes oc-
curring during histological nuclear differentiation
and carcinogenesis methods.9 However, various
approaches have been reported in the literature
for automatic cytological/histological image anal­
ysis, for classification of breast cancers, follicular
lymphoma, bone marrow, and brain tumors.10
Only a few works have used Image-Pro Plus 6
software in the liver tumor’s grading classifica-
tion.11 According to the criteria described by
Edmondson and Steiner, HCC was classified into
grade I (well differentiated), grade II (moderately
differentiated), and grade III (poorly differenti-
ated) on the basis of tumor size, blood vessel
proliferation, and mitotic activity.12 The major
disadvantage of this type of diagnostic grading
is that it provides only descriptive information
about the diagnosis without quantitative stan-
dards. Since HCC is an aggressive cancer that
occurs in the setting of cirrhosis and is common­
ly diagnosed in late stages,3 the grading system
classification was only applicable for the com-
prehensive assessment of the total resection of
a tumor, while it is not applicable for the pre­
operative biopsy of small samples and cannot
evaluate the cancer. An automatic classification
of HCC images has been introduced by Kiyuna
et al based on 13 types of nuclear and structural
features, where each feature consists of 6 statis-
tical distributions.13 The modern development in
histopathology is to translate nuclear morpho-
logical changes into quantitative features.14 Track­
ing the HCC-related histological changes by com­
puterized morphometry may be a reliable way to
identify the pathogenesis of HCC and should be
considered more than ever.10 On the other hand,
a retrospective study on quantitative analysis of
liver biopsy specimens revealed the presence of
slight variations in the volume density of smooth
cytoplasmic reticulum elements in chronic mixed
hepatitis C virus (HCV)+HBV infection.15 This
observation indicates the requirement of further
investigations in this area concerning the mor­
phological and structural characteristics of HCC.
Materials and Methods
Collections of HCC Specimens
The Medical Research Ethics Committee of
Guangdong Nan Fang Hospital, Southern Med-
ical University, reviewed and approved this
study. Written informed consent was obtained
from each participant prior to the study. Archival
routine histopathology was performed based on
formalin-fixed, paraffin-embedded samples from
75 Chinese patients who underwent surgery at
Guangdong Nan Fang Hospital from 2017–2018.
Each specimen with 1–6 paraffin blocks was cut
into a 4 µm thick section and stained with hema­
toxylin and eosin. The diagnosis was confirmed
by at least 2 independent pathologists, and none
of the patients had received preoperative radio­
therapy or chemotherapy. The patients included
49 males and 26 females with an average age
of 52 (range, 31–72). The pathological grading
of HCC was assigned according to the labeling
criteria of Edmondson and Steiner.12 The patients
can be categorized as follows: 25 cases were
well differentiated HCC (grade I), 25 cases were
moderately differentiated HCC (grade II), and the
remaining 25 cases showed poorly differentiated
HCC (grade III) (Figure 1).

3. 104 Analytical and Quantitative Cytopathology and Histopathology®
Saadawi et al
Experimental Methods
This study identified and analyzed 865 cells from
grade I, 662 from grade II, and 669 from grade
III. Data acquirement and image analysis were
carried out in the Nanfang Hospital Laboratory
using an Axio Lab optical microscope (Zeiss), a
micro camera (Champion Image MD-300), and
Image-Pro Plus 6 software. The microscope was
first calibrated through objective micrometer, and
the prepared samples were employed under op-
tical microscope using magnification 400× to
capture the microscopical field randomly. The
areas with inflammation and necrosis (if present)
were carefully avoided. Following microscope
calibration, 4–12 microscopical fields for each
sample were taken by microscopical imaging
system (Champion Image MD-300) and input into
the computer as described in Figure 2. Image-Pro
Plus 6 software was used to measure the mor­
phological features of nuclei in different grades
of HCC by choosing manual draw objects (Figure
3). From each slide, 90–120 nuclei with complete
and clearly detectable outlines, in nonoverlapping
and nonfragmented cells, were measured. Then
the number of the nuclei inside cells was counted
using a computer mouse to select the boundaries
of each nucleus, and the shape of the nucleus in
each image was described by Image-Pro Plus 6
software. From each nucleus, 4 variables includ-
ing nuclear area (polygonal), major axis, minor
axis, and nuclear perimeter16 were directly mea­
sured. The cell number was automatically count-
ed under amplification lens (40×). Furthermore,
the cell number density, nuclear area density,
and N/C ratio were calculated according to the
stereological formula.17 Cell number density is the
number of cells of interest per unit of the refer-
ence area.18
Nuclear area density referred to the sum of a
total nuclear area per unit of entire area divided
by the total area (reference area) and can be cal­
culated by using the following formula:
An ∑Ani
AAn = ____ = ______ ,
Aref ∑Arefi
where An, Aref, and i represent the nuclear area,
reference area, and number of tested nuclear or
reference field from 1 to n, respectively.
The N/C ratio can be defined as the summa-
tion of total nuclear areas divided by the total
cytoplasmic areas (summation of the cell area
minus the entire nuclear area). The N/C ratio was
calculated according to the following equation:
Figure 1 Measurements of 3 grades of HCC. (A) Grade I HCC, (B) grade II HCC, and (C) grade III HCC. The HCC samples were
examined under a 40× lens and evaluated by Image-Pro Plus 6. There are clear differences in nuclear density and nuclear size among
HCC with various histological grades.

4. Volume 41, Number 3/June 2019 105
Computerized Image Analysis in HCC
∑Ani
N/C = __________ ,
∑Aci_∑Ani
where An, Aref, and i represent the nuclear area,
reference area, and number of tested nuclear or
reference field from 1 to n, respectively.
Statistical Analysis
All the data were analyzed by GraphPad Prism 7.0
and expressed as mean values±standard devia­
tions. Furthermore, the intergroup comparisons
were performed by Dunn’s Kruskal-Wallis multi-
ple comparisons test. The probability value of p<
0.05 was considered as significant.
Results
Variations of Nuclear Morphometric Parameters in
Different Grades of HCC
The results of the statistical analysis for all pa-
tients are summarized in Table I. The present
Figure 2 Specific operation by Image-Pro Plus 6 software. (A) Spatial calibration New is selected in the order: Create new ruler name,
select the unit, select image, draw a line at the ruler or 2 points of known length, select and analyze set scale to display the image of the
line under the set scale window, (B) choose the measurement, count/size, edit, (C) draw objects, (D) draw outline manual, click OK,
(E) select measurement (area polygonal, major and minor axes, perimeter, density mean, (F) the saved measurement data in special file in
computer, statistical analysis.

5. 106 Analytical and Quantitative Cytopathology and Histopathology®
Saadawi et al
results showed that the well differentiated HCC
grade I was significantly lower than poorly dif­
ferentiated grade III in nuclear area, major and
minor axes, and perimeter. Furthermore, a slight
difference was presented by grade I and moder­
ately differentiated grade II. It should be men-
tioned that grade I was significantly lower than
those of grade III in nuclear axis, nuclear area
polygonal, and perimeter. The mean value of
each nuclear morphometric parameter of poorly
differentiated HCC grade III was the highest
among all the tumor grades (Table I). Among all
grades, grade I showed the lowest standard devia­
tion of nuclear parameter. Furthermore, smaller
nuclei of the well differentiated grade I generally
presented a critical stereological feature that can
be used to identify different histological grades of
HCC. Beside grade I, grade II also demonstrated
moderate differences in morphometric parameters.
Since the standard deviation of nuclear param­
eter of grade I was much smaller than that of
grade III, this feature may also clearly indicate
the differences in nuclear area and axis diameter
of tumor cells in the poorly differentiated HCC
grade III. The low-grade HCC was much smaller
than that in high-grade HCC, which suggested
that there was obviously varied nuclear size of
tumor cells in high-grade HCC. This variability
of nuclear parameters and morphology (Table I)
might be responsible for cell pleomorphism of
tumor cells in high-grade HCC.1
Differences in Densitometric Parameters of HCC in
Different Grades
The present study also showed that there was
a significant difference (p<0.05) in cell densities
between grades I and III. The grade I HCC pre­
sented the lowest cellular density (0.353±0.09081)
as compared to those in grades II (0.645±0.09947)
and III (1.071±0.3364) (Table II). The results sug­
gested that as the grade increased, the cellular
density also increased. Furthermore, for the sec­
ond time there is a direct association between
the increases of nuclear area density and grades
of HCC (Figure 4). The mean of the 3 grades
I (0.0179±0.01201), II (0.0317±0.01171), and III
(0.0389±0.01327) showed a significant difference
(p<0.05) between grades I and III and a slight
difference between grades I and II (Table II).
Differences in an N/C Ratio of HCC in Different
Grades
The N/C ratio significantly increased from low
(grade I) to high (grade III) grades (p<0.05), with
the means 0.0284±0.015 and 0.918±0.05329, re-
spectively (Figure 5).
Discussion
HCC is a health problem around the world, with
more than 700,000 diagnosed cases per year.19
Figure 3 Marking of the total area (reference area) by Image-Pro
Plus 6 software under objective lens 40× amplification.
Table I Evaluation of the Main Morphometric Variables for the Different Histological Grades of HCC
Nuclear morphological parameters*
Nuclear area Nuclear axis Nuclear axis Nuclear
Cell polygonal (major) (minor) perimeter
Histological grade numbers (μm2) (μm) (μm) (μm)
I 865 16.96±2.205 6.069±0.4952 4.333±0.5071 15.936±0.7936
II 662 24.828±1.858 7.017±0.584 6.12±0.4933 20.029±0.6796
III
669
41.779±5.797
8.682±0.78 7.636±0.9574
30.315±4.456
p Value (grade I vs. III) <0.05 <0.05 <0.05 <0.05
*Data expressed as mean±standard deviation. Results of different groups were analyzed using Dunn’s Kruskal-Wallis multiple comparisons test.

6. Volume 41, Number 3/June 2019 107
Computerized Image Analysis in HCC
HCC develops through a progressive pathway
from premalignant lesions in the cirrhotic liver.
However, it is very complex to differentiate be-
tween premalignant lesions and HCC.1 In this
scientific research, a morphometric approach was
used to assess and quantify the nuclear mor-
phometric features in patients with HCC in dif­
ferent histological grades by using computerized
image analysis (Image-Pro Plus 6), because nu-
clear morphology can be used as a potential pre-
dictor for HCC.20 Previous studies reported that
the morphometry had a powerful role in surgical
pathology and may supply clinically relevant in-
formation on the degree of grading and malignant
potential of different cancers. From this stand­
point of pathology and according to Edmondson
and Steiner’s classification (1954), grade I HCC
resembling normal hepatocytes was classified in-
to well differentiated, grade II observed with
mild positive nuclear atypia, and grade III HCC
with the presence of multinucleated giant cells,
clear pleomorphism, and nuclear atypia.12 The
grading system was based on invasiveness, cellu­
lar morphology, and mitotic index. This classifi-
cation applied for complete resection of a tumor
and not for a partial biopsy because of the
difficulty of assessing the histological grade by
the abovementioned characteristics and due to
limited surveillance. Therefore, it is necessary to
find some certain diagnostic parameters to clearly
investigate the histological grading of HCC. In-
creasing irregularities of nuclear morphometric
features combined with tumor progression have
been reported in thyroid tumors, colorectal can­
cer, renal cell carcinoma, and breast cancer, while
nuclear outline has been reported to be a signifi­
cant predictive factor for patients with colorectal
carcinoma.21 So, variable nuclear size and shape
appear to be a general condition among neo­
plastic disease.20 Therefore, this study initiates a
significant diagnostic parameter for HCC based
on the assessment of medical images by com­
puterized morphometry.22 Retrospective studies
showed that the size of the nuclear area increased
from cirrhotic liver cells to well differentiated
carcinoma and increased from well differentiated
Table II Relationship Between Histological Grade and Tumor
Cell Density Parameters in HCC
Cell density parameters*
Cell number Nuclear area
Histological grade density density
I 0.353±0.09081 0.0179±0.01201
II 0.645±0.09947 0.0317±0.01171
III 1.071±0.3364 0.0389±0.01327
p Value (grade I vs. III) <0.05 <0.05
*Data expressed as mean±standard deviation. Results of different groups
were analyzed using Dunn’s Kruskal-Wallis multiple comparisons test.
Figure 4
Cell number and nuclear area
densities in different HCC
histological grades. There
was a significant difference
between grades I and III.
The symbols * and & indicate
the significance (p<0.05),
calculated with Dunn’s
Kruskal-Wallis multiple
comparisons test.

7. 108 Analytical and Quantitative Cytopathology and Histopathology®
Saadawi et al
or moderately differentiated to poorly differenti­
ated carcinoma. Thus, the size of the nuclear area
of HCC was significantly correlated with cell
differentiation.23 In this study the morphometric
and densitometric parameters of HCC cells were
quantitatively determined by stereological meth­
ods. The nuclear area was more informative and
more reproducible than were long and short axes
and perimeter.24 Low grade (grade I) HCC was
significantly different from grade III HCC in nu-
clear area polygonal, nuclear axis (major and mi-
nor), and nuclear perimeter (p<0.05). These results
suggested that the grade I HCC cells have small
nuclei as compared to those of grade III HCC.
The differences in these parameters can be used
as an identification tool for the HCC grading. The
lower variations in the nuclear morphology of
HCC in lower grade might be caused by the
polymorphism of tumor cells. This variation fea­
ture in nuclear morphology can be used for HCC
identification and severity. In agreement with a
previous study, which used the same method
to investigate tumor cell nuclei of glioma cancer
with various histological grades,9 our results suc-
cessfully confirmed that there was a significant
difference in low grade in the nuclear parameters
such as nuclear area, nuclear axis (major and minor),
and nuclear perimeter among the HCC histological
grading III. The densitometric param­
eter is a
measure of the number of tumor cell nuclei, which
reflects the volume of the tumor cell in a certain
space or the size of the surface area.25 From the data
in Table II we could see that the number density of
grade I HCC was the lowest as compared to grades
II and III, probably due to the lack of other high-level
features (mitotic increase, vascular proliferation,
and necrosis).25 The nuclear area density reflects the
ratio of area of nucleus to total area of the cell. The
increased rate in grade III suggested the nuclear
crowding of grade III, which was significantly
more than that in grade I. Furthermore, nuclear
atypia was increased due to fast growth of tumor
cells, which was associated with the prolifera-
tion and metabolic rates of tumor cells. Interest­
ingly, this feature was consistent with the bio­
logical behavior of high-grade HCC. Accordingly,
the number and nuclear area densities reflected
the primary index for evaluation of the histolo­
gical grading of HCC.28 Although there are a lot
of works by automatic cytological/histological
image analysis on tumor classification from breast
cancers, follicular lymphoma, bone marrow, and
subtyping of brain glioblastoma,9 we noticed lim­
ited works using Image-Pro Plus 6 software in
the classification of HCC grading. The previous
study represented that in comparison to cell den­
sity among cirrhotic nodules, low-grade dyspla­
stic nodules, and high-grade dysplastic nodules
in the liver at the same magnification. Low-grade
dysplastic nodules showed slightly increased cell
density as compared to extranodular cirrhotic liver
and mild cellular atypia. High-grade dysplastic
nodules showed high cell density, a thin trabecu­
lar pattern, and small cell changes with an in-
creased N/C ratio.27 Similar results were ob-
tained in the current study, in which the cellular
density increased in higher grades of HCC as
compared to lower grades. This suggests that,
as the grade increased, the cellular density was
also increased. The grade of HCC was also esti­
mated by diffusion-weighted magnetic resonance
imaging.26 It was found that the N/C ratio was
significantly increased in high-grade HCCs (as
compared to grade I) and might be responsible
for evaluating the relationship between HCC his­
topathological grades and qualitative diffusion-
weighted imaging. Although our study used a
different method (Image-Pro Plus 6 software),
our results were consistent with their findings
and indicated that the N/C ratio of HCC was
significantly increased from low (grade I) to high
Figure 5 N/C ratio in different grades of HCC. There was a
significant difference between grades I and III. *The p value
<0.05 was calculated with Dunn’s Kruskal-Wallis multiple
comparisons test.

8. Volume 41, Number 3/June 2019 109
Computerized Image Analysis in HCC
(grade III) grades. These results show that the
low grade has a low level of N/C ratio, suggest­
ing that the N/C ratio can be used for the cor-
rect stereological grading of HCC. Thus, nuclear
morphometry (nuclear area, major and minor
axes, nuclear perimeter), cellular and nuclear area
density, and the N/C ratio can be introduced as
a new morphometric prognostic marker for his-
tological grading of HCC, especially for the pa-
tient who has lost the opportunity for surgery.
Finally, these patients might benefit from this
valuable histological information in diagnosis,
and therefore an appropriate therapy can be rec­
ommended for treatment. Although this study
showed promising results, there are some limita­
tions, such as the relatively small study popula­
tion, the study included only 3 histological grades
of liver cancer, and the evaluation of histological
grading of HCC by computerized imaging anal­
ysis was inaccurate and has other drawbacks.
Highly advanced HCCs such as infiltrative HCC
were not included in our study. In this case, how­
ever, predicting histopathological grades plays a
far less significant role in deciding the treatment
strategy. Finally, this study focused only on the
correlation of tumor histological grading and nu-
clear morphometry value in the biopsy site, which
cannot represent the whole tumor. This should be
kept in mind as a useful aim for our future anal-
ysis, using a larger series of patients.
Conclusion
The combination of nuclear morphometry (area,
major axis, minor axis, and perimeter) and den­
sitometry (nuclear area density, cell density) pa-
rameters enables improved classification rate in
HCC detection using Image-Pro Plus 6 software.
Furthermore, the analysis of N/C ratio can aid in
HCC grading and might be helpful for accurate
diagnosis. The complete primary computerized
imaging analysis data in the form of continuous
quantitative variables have been made available
as a complement to this paper. Practical recom­
mendation for designing studies that engage
computerized imaging analysis evaluations of the
size and shape, nuclearity, and density of HCC is
provided.
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