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A new risk stratification algorithm for the management of patients with adrenal incidentalomas.
[adrenal incidentaloma]
Although
adrenal
incidentalomas
(
AI
)
are
detected
in
≤
5
%
of
patients
undergoing
chest
and
abdominal
computed
tomography
(
CT
)
,
their
management
is
challenging
.
The
current
guidelines
include
recommendations
from
the
National
Institutes
of
Health
,
the
American
Association
of
Endocrine
Surgeons
(
AAES
)
,
and
the
American
Association
for
Cancer
Education
(
AACE
)
.
The
aim
of
this
study
was
to
develop
a
new
risk
stratification
model
and
compare
its
performance
against
the
existing
guidelines
for
managing
AI
.
A
risk
stratification
model
was
designed
by
assigning
points
for
adrenal
size
(
1
,
2
,
or
3
points
for
tumors
<
4
,
4
-
6
,
or
>
6
Â
cm
,
respectively
)
and
Hounsfield
unit
(
HU
)
density
on
noncontrast
CT
(
1
,
2
,
or
3
points
for
HU
<
10
,
10
-
20
,
or
>
20
,
respectively
)
.
This
model
was
applied
retrospectively
to
157
patients
with
AI
managed
in
an
endocrine
surgery
clinic
to
assign
a
score
to
each
tumor
.
The
utility
of
this
model
versus
the
AAES
/
AACE
guidelines
was
assessed
.
Of
the
157
patients
,
54
(
34
%
)
,
had
tumors
<
4
Â
cm
with
HU
<
10
(
a
score
of
2
)
.
One
third
of
these
were
hormonally
active
on
biochemical
workup
and
underwent
adrenalectomy
.
The
remaining
two
thirds
were
nonsecretory
lesions
and
have
been
followed
conservatively
with
annual
testing
.
In
103
patients
(
66
%
)
,
the
adrenal
mass
was
>
4
Â
cm
and
/
or
had
indeterminate
features
on
noncontrast
CT
(
HU
>
10
,
irregular
borders
,
heterogeneity
)
,
and
adrenalectomy
was
performed
after
hormonal
evaluation
was
completed
(
10
were
hormonally
active
on
biochemical
testing
)
.
Seven
of
these
patients
(
7
%
)
had
adrenocortical
cancer
on
final
pathology
with
tumor
size
<
4
Â
cm
in
0
,
4
-
6
Â
cm
in
1
,
and
>
6
Â
cm
in
5
patients
.
Of
the
hormonally
inactive
patients
,
32
%
had
a
score
of
3
,
38
%
4
,
and
30
%
5
or
6
.
The
incidence
of
adrenocortical
cancer
in
these
subgroups
was
0
,
0
,
and
25
%
,
respectively
.
This
study
shows
that
an
algorithm
that
utilizes
the
hormonal
activity
at
the
first
decision
step
followed
by
a
consolidated
risk
stratification
,
based
on
tumor
size
and
HU
density
,
has
a
potential
to
spare
a
substantial
number
of
patients
from
unnecessary
"
diagnostic
"
surgery
for
AI
.
Diseases
Validation
Diseases presenting
"adrenal incidentalomas"
symptom
adrenal incidentaloma
cushing syndrome
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