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Image analysis of immunohistochemistry is superior to visual scoring as shown for patient outcome of esophageal adenocarcinoma.
[esophageal adenocarcinoma]
Quantification
of
protein
expression
based
on
immunohistochemistry
(
IHC
)
is
an
important
step
in
clinical
diagnoses
and
translational
tissue-based
research
.
Manual
scoring
systems
are
used
in
order
to
evaluate
protein
expression
based
on
staining
intensities
and
distribution
patterns
.
However
,
visual
scoring
remains
an
inherently
subjective
approach
.
The
aim
of
our
study
was
to
explore
whether
digital
image
analysis
proves
to
be
an
alternative
or
even
superior
tool
to
quantify
expression
of
membrane-bound
proteins
.
We
analyzed
five
membrane-binding
biomarkers
(
HER
2
,
EGFR
,
pEGFR
,
β-catenin
,
and
E
-
cadherin
)
and
performed
IHC
on
tumor
tissue
microarrays
from
153
esophageal
adenocarcinomas
patients
from
a
single
center
study
.
The
tissue
cores
were
scored
visually
applying
an
established
routine
scoring
system
as
well
as
by
using
digital
image
analysis
obtaining
a
continuous
spectrum
of
average
staining
intensity
.
Subsequently
,
we
compared
both
assessments
by
survival
analysis
as
an
end
point
.
There
were
no
significant
correlations
with
patient
survival
using
visual
scoring
of
β-catenin
,
E
-
cadherin
,
pEGFR
,
or
HER
2
.
In
contrast
,
the
results
for
digital
image
analysis
approach
indicated
that
there
were
significant
associations
with
disease-free
survival
for
β-catenin
,
E
-
cadherin
,
pEGFR
,
and
HER
2
(
P
Â
=
Â
0
.
0125
,
P
Â
=
Â
0
.
0014
,
P
Â
=
Â
0
.
0299
,
and
P
Â
=
Â
0
.
0096
,
respectively
)
.
For
EGFR
,
there
was
a
greater
association
with
patient
survival
when
digital
image
analysis
was
used
compared
to
when
visual
scoring
was
(
visual
:
P
Â
=
Â
0
.
0045
,
image
analysis
:
P
Â
<
Â
0
.
0001
)
.
The
results
of
this
study
indicated
that
digital
image
analysis
was
superior
to
visual
scoring
.
Digital
image
analysis
is
more
sensitive
and
,
therefore
,
better
able
to
detect
biological
differences
within
the
tissues
with
greater
accuracy
.
This
increased
sensitivity
improves
the
quality
of
quantification
.
Diseases
Validation
Diseases presenting
"that digital image analysis was superior to visual scoring"
symptom
esophageal adenocarcinoma
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