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A
Quaglia, A Dhillon, A Godfrey, AP Dhillon,
Department of Histopathology, Royal Free and University College
Medical School, Pond Street, London NW3 2QG, United Kingdom R
Togni, Department of Histopathology,
Ospedale Santa Chiara, Largo Medaglie d扥ro
9, Trento 38100, Italy P
Bioulac-Sage, C Balabaud, Lab
pathology, INSERM E9917, Universit Victor S�galen,
146 rue L�o
Saignat, Bordeaux 33076, France M
Winnock, MA Jutand, INSERM U593,
Universit Victor S�galen,
146 rue L�o
Saignat, Bordeaux 33076, France Correspondence
to: Dr. A Quaglia, Department of
Histopathology, Royal Free Hospital, Pond Street, London NW3 2QG, United
Kingdom. alberto.quaglia@kingsch.nhs.uk Telephone:
+44-20-7830-2227
Fax: +44-20-7435-3289 Received:
2005-01-26 Accepted:
2005-05-24 Abstract AIM:
To design a classification tool for the histological assessment of
hepatocellular carcinoma (HCC), dysplastic nodules (DN), and
macroregenerative nodules (MRN) in cirrhotic liver. METHODS:
Two hundred and twelve hepatocellular nodules (106 HCC; 74 MRN; 32
DN) were assessed systematically, quantitatively, and
semiquantitatively as appropriate for 10 histological features that
have been described as helpful in distinguishing small HCC, DN, and
MRN in cirrhotic livers. The data were analyzed by multiple
correspondence analysis (MCA). RESULTS:
MCA distributed HCC, DN, and MRN as defined by traditional
histological evaluation as well as the individual histological
variables, in a 搈alignancy
scale. Based on the MCA data representation, we created a
classification tool, which categorizes an individual nodular lesion
as MRN, DN, or HCC based on the balance of all histological features
(i.e., vascular invasion, capsular invasion, tumor necrosis, tumor
heterogeneity, reticulin loss, capillarization of sinusoids,
trabecular thickness, nuclear atypia, and mitotic activity). The
classification tool classified most (83%) of a validation set of 47
nodules in the same way as the routine histological assessment. No
discrepancies were present for DN and MRN between the routine
histological assignment and the classification tool. Of 25 HCC
assigned by routine assessment in the validation set, 8 were
assigned to the DN category by the classification tool. CONCLUSION:
We have designed a classification tool for the histological
assessment of HCC and its putative precursors in cirrhotic liver.
Application of this tool systematically records histological
features of diagnostic importance in the evaluation of small HCC. � 2005
The WJG Press and Elsevier Inc. All rights reserved. Key
words:
Hepatocellular carcinoma; Cirrhosis; Multiple correspondence
analysis; Large regenerative nodule; Dysplastic nodule Quaglia
A, Jutand MA, Dhillon A, Godfrey A, Togni R, Bioulac-Sage P,
Balabaud C, Winnock M, Dhillon AP. Classification tool for the
systematic histological assessment of hepatocellular carcinoma,
macroregenerative nodules, and dysplastic nodules in cirrhotic
liver. World J Gastroenterol
2005; 11(40): 6262-6268 http://www.wjgnet.com/1007-9327/11/6262.asp INTRODUCTION The
current histological classification of hepatocellular carcinoma
(HCC) and its putative precursor nodular lesions is controversial
and unsatisfactory, particularly with small lesions of 1-2 cm in
diameter. Most of the histological criteria for the evaluation of
early HCC and its putative precursors have not been validated
properly, and the diagnosis of these lesions still depends largely
on subjective interpretation of histological features, which are
rarely recorded either in routine diagnostic practice or in the
published literature. The
aim of this study was to derive a classification tool based on
individual histological features that enable the distinction between
HCC, dysplastic nodules (DN), and macroregenerative nodules (MRN) in
cirrhotic liver. The design of this classification tool was based on
the correspondence between the routine histological classification
of liver cell nodules and the classification of the same liver cell
nodules by a systematic analysis of the individual histological
features that may contribute towards the subjective diagnostic
assignment. Lesion size was considered specifically in addition
because this aspect is currently the most important item that
determines the management of HCC in cirrhotic patients according to
the recent Barcelona guidelines[1]. MATERIALS
AND METHODS Dataset
for construction of the classification tool Two
hundred and twelve liver hepatocellular nodules were retrieved from
the files of the Department of Histopathology of the Royal Free
Hospital using the Liver Tumor Database of the Royal Free Liver
Pathology Unit. These nodules had been isolated during the routine
diagnostic pathological examination of the cirrhotic livers, which
were removed from 321 consecutive liver transplant patients who
received liver transplantation at the Royal Free Hospital between
1996 and 2001 for various etiologies. Sixty-eight of these patients
(59 males, 26 HCV, 19 HBV, 10 cryptogenic cirrhosis, 6 alcoholic
liver disease, 3 alcoholic liver disease and HCV, 2 HCV and HBV, 1
Wilson�s
disease, 1 primary biliary cirrhosis) were found to have HCC in the
explanted liver, and/or DN and/or MRN, and livers of these patients
constitute our study group. For each nodule, a hematoxylin and eosin
(H&E)-stained section was performed as part of the routine
histological assessment, as well as a silver impregnation for
reticulin fibers using the Gordon and Sweets method and an
immunohistochemical staining for CD34 and smooth muscle actin (SMA). Histological
assessment The
overall assessment was performed assigning each liver cell nodule to
one of the three groups: HCC; DN; or MRN by 搕raditional
subjective diagnostic assessment (APD), using the histological
criteria defined by Ferrell et al.[2],
and the International Working Party[3].
The systematic scoring procedure (AQ) was conducted separately from
the overall assignment, in order to eliminate bias. Histological
features used to construct the classification tool The
following histological features were chosen for the systematic
histological assessment of each lesion: nodule size, nodule
heterogeneity, reticulin loss, trabecular thickness,
capillarization, number of solitary arterioles, cellular atypia and
mitotic activity, necrosis, vascular invasion, and capsular
invasion. These features were chosen because they are currently considered by many liver pathologists as the most useful histological criteria in the histological assessment of hepatocellular lesions, as it appears from published work on this subject[4-8]. Each lesion was reviewed with systematic documentation of these individual features, and a semiquantitative score was given to reticulin loss, capillarization, and cellular atypia (Table 1), as described below.
Table 1 Scheme for the systematic assessment of histological features in liver cell nodules in cirrhotic livers Size
The
evolution from cirrhotic liver to MRN, DN, and HCC is usually
accompanied by an increase in nodule size. In other words, the
greater the size of the lesion, the greater the likelihood that it
is a dysplastic nodule or HCC[2-4,7,9,10].
Size was determined macroscopically as maximum diameter of the
lesion and expressed in millimeters. Reticulin
loss
This has been traditionally considered to be a diagnostic
feature of HCC. The following scale was used: grade 0 was given when
the reticulin stroma was preserved; grade 1-5 was defined by the
number of liver cells included between residual strands of
silver-staining reticulin, with grade 1 when liver plates were
3-cell thick; and subsequent 1-cell increments up to grade 5 when
liver plates were 7-cell thick or more. Trabecular
thickness
This means, the number of liver cells composing a hepatocyte
plate and may be considered as a corollary of reticulin loss (see
above). In overt HCC, hepatocyte plates tend to be thicker than
normal[3,11].
Trabecular thickness was assessed using H&E staining and graded
as number of liver cells composing a trabecular plate. Arterialization
and capillarization Number
of solitary arterioles[12-14]
and capillarization[15]
are related to the changes of vascular supply in the evolution of
HCC from precursor nodular lesions including acquisition of a
predominantly arterial vascular supply and of a diffuse pattern of
expression of CD34 by sinusoidal endothelium. Capillarization
was graded as 0 when marginal (i.e., staining only septal
endothelium and endothelium of limiting plate of the nodule); Patchy
(grades 1-2) when non-confluent patches (grade 1 = in one-third of
the nodule; grade 2 in at least two-thirds of the nodule) showing
diffuse CD34 immunostaining were seen; incomplete (grade 3) when
confluent areas showing diffuse CD34 immunostaining were seen,
occupying approximately two-thirds of the nodule; diffuse incomplete
(grade 4) when diffuse CD34 staining was seen in the whole nodule
apart from scattered CD34-ve patches; diffuse (grade 5) when the
entire nodule stained for CD34. Solitary
arterioles: these were counted as average of unpaired arteries
detected in 10 medium (100) power fields, on H&E sections[14]. Cellular
atypia and mitotic activity The
International Working Party included both cellular atypia and
mitotic activity in morphological diagnostic criteria of HCC[3].
Cellular atypia was graded as mild (grades 1-2), moderate or severe
(grades 4-5) depending on the similarity in terms of features, such
as nuclear contour, hyperchromatism, and nuclear cytoplasmic ratio,
when compared to background cirrhotic liver[8]
with mild atypia described as minimal difference (and grade 1 or 2
depending on the extent of the changes within the nodule, grade 1 in
1/3 of the surface examined; grade 2 in 2-3/3 of the surface
examined), severe atypia as prominent nuclear changes with marked
pleomorphism and severe hyperchromatism (and grade 4 or 5 depending
on the extent of the changes within the nodule, grade 1 in 1/3 of
the surface examined; grade 2 in 2-3/3 of the surface examined), and
moderate atypia as intermediate changes. Mitotic
activity was graded as shown in Table 1, counting the number of
mitoses in 10 high (400) power fields[3]. Heterogeneity
This
term describes the morphological changes seen in a hepatocellular
lesion and presumably related to the clonal evolution seen in the
development of HCC. This is evident morphologically, for example, as
a �nodule in nodule pattern� and consists of areas with
one or more morphological changes distinct from the parent nodule
and often with compression of the parent nodule suggesting an
increased growth rate. These morphological changes include small
cell change, microacinar change, clear cell change, fatty change,
groups of Mallory body or fibrinogen containing cells, and loss or
accumulation of iron or bile compared to the background liver[3,4]. Tumor
necrosis usually occurs when cell growth exceeds the vascular supply
and is usually seen in tumors at a relatively advanced biological
stage. Necrosis was considered to be diagnostically relevant only
when it was �spontaneous�
in the absence of previous history of pre-transplantation local
treatment (e.g., trans-arterial chemoembolization, percutaneous
ethanol injection, etc.). Invasion
Vascular
invasion was considered as invasion of vascular structures
identified histologically. Capsular invasion was recorded when there
was invasion of perinodular dense fibrous tissue[5,8,16]. For
each nodule, H&E-stained section was performed as part of the
routine histological assessment, as well as a silver impregnation
for reticulin fibers using the Gordon and Sweets method and an
immunohistochemical staining for CD34 and SMA. Dataset
for validation of the classification tool The
classification tool (Table 3) was tested prospectively on a
subsequent separate set of hepatocellular nodules identified in 11
consecutive liver explants with 47 distinct nodular liver cell
lesions removed at transplantation in the year 2002. The test set of
nodules consisted of 25 HCC (mean size, 19.4 mm; SD, 14 mm), 9 DN
(mean size, 10.7 mm; SD, 3 mm), and 13 MRN (mean size, 7.7 mm; SD,
2.2 mm). Statistical
analysis The
individual histological features described above were analyzed by
multiple correspondence analysis (MCA). MCA is an exploratory
technique[17]
allowing the synthesis, description, and graphic analysis of large
contingency tables. The results provide information that is similar
in nature to those produced by factor analysis techniques, and they
allow one to explore the structure of categorical variables included
in the table. No tests of statistical significance are applied to
the results and the main goal is to produce a �simplified�
representation of the data. In
the present work, MCA was used in two ways: (1) To see whether this
method could reliably categorize HCC, DN, and MRN using the
individual histological features described above, and how this
analysis compared to the overall (routine) histological assessment.
MCA produces a graphic representation of the data in the form of a
horizontal line, which represents a �malignancy�
scale and shows how each nodule is placed in a �malignancy�
scale. In theory, malignant nodules are placed at one end of the
scale and benign nodules are placed at the opposite end of the
scale, with equivocal nodules in between. Each variable has a
certain value in an axis, and the � position �
in the chart represents the composite point of different planes
(features) for a given nodule; (2) To see if this method could rank
the individual histological features in order to assess the relative
contribution of each individual histological observation in the
assignment of a liver cell nodule to one of the three categories
(HCC, DN, and MRN), so that the histological features could be
incorporated into a classification tool to distinguish HCC from DN
from MRN. RESULTS Multiple
correspondence analysis An exploratory set of 212 hepatocellular nodules (106 HCC mean size 18.8 mm, SD 13 mm; 74 MRN mean size 10 mm, SD 3.2 mm; 32 DN mean size 12.4 mm, SD 5.5 mm, as per routine histological assessment) were analyzed histologically. Figure 2 shows how MCA redistributes these nodules. The horizontal line represents a �malignancy� scale. In other words, the projection of every dot towards the horizontal line (e.g., three dotted lines in chart) shows how each nodule is placed in a �malignancy� scale. HCC are placed in the left-hand side of the chart, whereas MRN are placed towards the other end. Each variable has a certain value in an axis, and the � position � in the chart represents the resulting point of different planes for a given nodule. Size (Figure 1) does not allow a reliable classification of nodules. In other words, HCC can be of all sizes, and although large nodules are usually HCC, small nodules may also be HCC. Conversely, MRN and DN can be of considerable size (up to 21 and 24 mm, respectively, in our series).
Figure 1 MCA of exploratory set of 212 hepatocellular nodules in cirrhotic livers. The relative lesion size of the hepatocellular nodules is depicted as blue dots. The diameter of the dots varies according to the size of the nodule observed. Size does not seem to allow a classification of nodules, in other words, HCC can be of all sizes, and large nodules are usually HCC. However, small nodules are not necessarily MRN or DN. Figure 2B shows how the individual variables (e.g., capsular invasion, vascular invasion, etc.) relate to each other, and how they are distributed along the �malignancy� scale. As in Figure 2A, the horizontal line represents a �scale of malignancy�. The projection of each group of values in the horizontal axis shows that the variables form a continuum, with capsular invasion being the �most� malignant feature, and absence of heterogeneity the �least� malignant feature. Table 2 shows how the groups of values depicted in Figure 2B are distributed in the three types of nodular lesions.
Figure 2 A: MCA of exploratory set of 212 hepatocellular nodules in cirrhotic livers; B: Distribution of histological variables in the exploratory set of 212 hepatocellular nodules. This chart shows how MCA redistributes the different types of nodules (i.e. HCC, DN, and MRN as assigned by routine histological evaluation), taking into consideration all variables of the scoring system except size. Each variable has a certain value in an axis, and the � position � in the chart represents the resulting point of different planes for a given nodule. Please note that the total number of � nodules � shown does not equal 212 because there is a certain degree of overlapping among observations and there is a lack of resolution in the chart.
Table 2 MCA of the values of the histological variables in the three categories (HCC, MRN, and DN) in the exploratory set of 212 hepatocellular nodules in cirrhotic livers These
data were used to create a classification tool for the assessment of
these nodular lesions. Construction
of the classification tool The
values shown in Figure 2 and Table 2 can be distributed into six
main groups, depending on their proportional representation in the
three categories HCC, DN, and MRN, as follows: Group
1 (capsular invasion, vascular invasion). Features present
exclusively in HCC 44 (41.5%) and 27 (25.5%), respectively, by
definition. Group
2 (necrosis present, mitosis present, capillarization = 5, cellular
atypia = 3-5, reticulin loss = 4-5, trabecular thickness>4).
Features present, in 16-52.8% (mean 36%) of HCC but not present in
MRN or DN. Group
3 (solitary arterioles ≥1,
heterogeneity present, capillarization = 4, reticulin loss = 1-3,
trabecular thickness = 4). Features present in 21.7-94.3 (mean =
47%) HCC, 3-72% (mean = 37%) DN and 0-14% (mean = 20%) MRN. Group
4 (capsular invasion not present, vascular invasion not present,
necrosis not present, mitosis not present). Features present in 100%
MRN and DN, and in 53-84% (mean 67%) of HCC. Group
5 (capillarization = 3, cellular atypia = 1-2). Features present in
25-38% (mean = 31%) DN, 17.9-34.9% (mean = 26%) HCC and 3-22% (mean
= 12%) MRN. Group
6 (solitary arterioles<1, heterogeneity not present,
capillarization = 0-2, reticulin loss = 0, trabecular
thickness<4). Features present in 78-97% (mean = 91%) MRN, 59-72%
(mean = 63%) DN and 0.9-41.5 (mean = 11%) HCC. These six groups can be organized into a three column table as shown in Table 3. This table constitutes the classification tool.
Table 3 Classification tool for hepatocellular lesions in cirrhotic liver. Assess each individual histological feature (as per Table 1) and go to Table 4a The
histological features of a given nodule are assessed individually
and then allocated to the classification tool. Validation
of the classification tool This
classification tool, when tested prospectively on the separate set
of liver cell nodules described above gave the following results:
out of 47 nodules, 39 (83%) were classified in the same way as the
routine histological assessment. All 13 MRN and all 9 DN, as defined
by routine histological assessment were considered as such by the
classification tool. Of the 25 HCC, as defined by routine
histological assessment, 8 were considered as DN by the
classification tool (Table 4). Table
4
Performance
of the classification tool on a second validation set of liver cell
nodules in cirrhotic livers
DISCUSSION Despite
the consensus document published by the International Working Party[3],
the terminology used in the literature is still confusing,
particularly due to the use of different classifications and
different histological criteria by different centers[6].
In fact, the bulk of the relevant literature offers few clues about
which precise observations allocated any particular lesion (however,
named) into the given categorical assignment. In this work, we have
investigated how those individual histological features considered
in the literature will be helpful in the histological assessment of
small hepatocellular nodular lesions in cirrhosis that can be used
to create a classification tool for the evaluation of these nodules.
Application of the classification tool documents systematically the
individual histological features that contribute to the categorical
assignment of MRN, DN, and HCC. MCA
is a descriptive technique, which identifies the best factor
representing a set of data. In the present analysis, the horizontal
factor, which could be called �malignancy�
is the most important one in representing the dataset. The nodular
lesions of the present study can be imagined as a �cluster�
of dots in space, and the distance between two points depends on the
plane (axis of assessment, or histological features) used to look at
them. For example, if the horizontal axis is used to look at two
lesions, and the projections of these lesions are close together on
that axis, these lesions may be considered to be at a similar degree
of malignancy. The same lesions on another plane may be very far
apart from each other. MCA
distributes the 212 lesions assessed by the components of the
histological assessment placing HCC at the left and MRN at the right
of the �malignancy�
scale, and DN in the middle, although some �misclassifications�
are present, with overlap between different categories (Figure 2A),
i.e. between HCC and DN and DN and MRN. This is not unexpected, as
this analysis represents the nodular lesions as a continuum in a �malignancy�
scale. Moreover (Figure 2A), one could also imagine different
degrees of malignancy within the HCC subgroup. When
tested on a second set of nodules, the classification tool
classified the large majority of all nodules (83%) in the same way
as the routine histological assessment. No discrepancies were noted
for DN and MRN between the routine diagnosis and the assignment by
the classification tool. Eight of twenty-five HCC (32% of HCC, 17%
of all nodules, as defined by routine histological assessment) were
assigned to the DN category by the classification tool, which is not
surprising given the well-recognized difficulties in separating
these two categories[3].
The reason for this discrepancy is obscure, and underlines the need
for correlation with other modalities of investigation, such as
molecular data and clinical follow-up, which may be informative to
validate the histological criteria[3]
(and this will be the subject of further work). Overall, the
classification tool seems to correspond reasonably well to the
routine histological assessment. The
classification tool has several advantages. Firstly, the idea of
including all important histological features in the evaluation,
systematically ensures that the final assignment does not rest on a
single feature subjectively or selected group of features, but on
the balance of all components. This classification tool is based on
a systematic collection of histological data and can be integrated
in a database. Once all the fields required for the completion of
the classification tool have been entered, a computer can easily run
the classification tool and return the result. As more data become
available[18],
and as additional informative histological features of HCC (such as
stromal invasion) are characterized[16,19,20],
the accumulated information can be used to improve and refine the
classification tool. In conclusion, we have designed a classification tool for the histological assessment of HCC and its putative precursor nodular lesions in cirrhotic liver. The classification tool is based on a systematic and balanced assessment of 10 histological features. REFERENCES 1
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