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Genetic obesity disorders : quantitating visceral fat as a predictor of cardiometabolic risk Musa, Lara; Attariwala, Raj; Xiang, Qing-San; Gibson, William 2017

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REFERENCES1)
Brambilla,
P.,
Bosio,
L.,
Manzoni,
P.,
Pietrobelli,
A.,
Beccaria,
L.
&
Chiumello,
G.
(1997).
Peculiar
body
composiCon
in
paCents
with
Prader‐Labhart‐Willi
syndrome.
Am
J
Clin
Nutr,
65,
1369‐1374.
2)
Hayashi,
T.,
Boyko,
E.J.,
McNeely,
M.J.,
LeoneQ,
D.L.,
Kahn,
S.E.
&
Fujimoto,
W.Y.
(2008).
Visceral
adiposity,
not
abdominal
subcutaneous
fat
area,
is
associated
with
an
increase
in
future
insulin
resistance
in
Japanese
Americans.
Diabetes,
57,
1269‐1275.
3)
Meaney,
F.J.
&
Butler,
M.G.
(1989).
CharacterizaCon
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obesity
in
Prader‐Labhart‐Willi
syndrome:
Fatness
pa^erning.
Medical
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Quarterly
3(3),
294‐305.
4)
Ross,
R.,
Shaw,
K.D.,
Martel,
Y.,
de
Guise,
J.
&
Avruch,
L.
(1993)
Adipose
Cssue
distribuCon
measured
by
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resonance
imaging
in
obese
women.
Am
J
Clin
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57,
470‐475.
5)
Thomas,
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Saeed,
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Hajnal,
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Figure
1:
h^p://media‐files.gather.com/images/d444/d147/d744/d224/d96/f3/full.jpgGene<c
obesity
disorders:Quan<ta<ng
visceral
fat
as
a
predictor
of
cardiometabolic
riskLara
Musa1,2,
Raj
A^ariwala3,
Qing‐San
Xiang4
and
William
Gibson1,21
Department
of
Medical
GeneCcs,
BC
Children’s
Hospital,
Vancouver
B.C.
2
Diabetes
Research
Program,
Child
and
Family
Research
InsCtute,
Vancouver
B.C.

3
AIM
Medical
Imaging,
Vancouver
B.C.
4
Department
of
Radiology,
BC
Children’s
and
St.
Paul’s
Hospital,
Vancouver
B.C.OBJECTIVES Develop
a
method
to
quanCtate
total
visceral
and
total
subcutaneous
fat
mass Determine
 the
 absolute
 amount
 and
 proporCon
accounted
for
by
each
layerMETHODSWhole‐body
MRI
scanT1‐weighted
MRI
scan
in
the
“Superman”
posiConAdipose
Tissue
IsolaConAdipose
Tissue
Layer
IsolaConIsolate
the
adipose
CssuePixCount
AnalysisDifferenCate
between
subcutaneous
and
visceral
fatDetermine
the
proporCon
of
each
layer
via
pixel
quanCtaConFUTURE
DIRECTIONS
&
APPLICATIONSFuture
Direc<ons Use
of
mulCple
 coronal
 slices,
 instead
of
axial
slices,
may
 provide
 the
 same
 amount
 of
 data
with
less
processing
Cme
Applica<ons Genotype‐phenotype
correlaConIdenCfy
 novel
 determinants
 of
 visceral
 fat
accumulaCon
 and
 the
 parCConing
 of
 fat
 into
the
subcutaneous
and
visceral
depots.
 Rare
geneCc
obesity
disorders
Improve
 understanding
 of
 how
 individuals
with
 rare
 geneCc
 obesity
 disorders,
 such
 as
Prader‐Willi
 syndrome,
are
affected
by
visceral
adiposity.

Figure
3:
An
example
of
a
T1‐weighted
whole
body
coronal
slice
imageDISCUSSION
&
CONCLUSION Fat
distribuCon
varies
between
individuals Visceral
 fat
 percentage
 cannot
 be
 predicted
 from
the
 total
 body
 fat
 mass
 among
 individuals
 with
geneCc
obesity
disorders Pixel
 quanCtaCon
 of
 MRI
 images
 provides
 a
potenCal
 means
 to
 segregate
 fat
 mass
 into
 two
compartments

STUDY
SUBJECTSChest Abdomen ThighA012,
MaleNormal
controlChest Abdomen Thigh*A040,
FemaleAcquired
parCal
lipodystrophyA058,
FemaleLipodystrophyChest Abdomen ThighACKNOWLEDGEMENTSContact
Informa<on:
Lara
Musa
at
lmusa@cfri.ca604‐875‐2000
ext
6783
Thank
you
to
Dr.
Raj
A^ariwala,
Wayne
Picker
and
other
staff
members
from
AIM
Medical
Imaging
for
conducCng
the
whole‐body
MRI
scans.
Special
thanks
to
Dr.
Qing‐San
Xiang
for
developing
the
PixCount
and
DicomSorter
programs
used
for
this
study.
Dr.
 Gibson
 gratefully
 acknowledges
 the
 salary
 support
provided
by
the
Child
and
Family
Research
InsCtute
and
the
Canadian
 InsCtutes
 of
 Health
 Research
 Clinician
 ScienCst
programs.
 This
 work
 is
 supported
 by
 the
 BriCsh
 Columbia
Prader‐Willi
 Syndrome
 AssociaCon
 student
 research
 award
and
CIHR.
BCPWSABACKGROUNDMethods
for
measuring
body
composi<onMany
 different
 techniques
 are
 used
 to
 measure
 body
composiCon,
 in
 parCcular
 body
 fat
 percentage.
 However,
 these
techniques
are
limited
since
they
do
not
reliably
disCnguish
visceral
from
 subcutaneous
 fat.
 Whole‐body
 MRI
 captures
 data
 on
 both
layers,
which
must
first
be
separated
with
computaConal
methods.The
 human
 body
 can
 be
 modeled
 as
 a
three
 compartment
 system:
 bone
 mass,
 fat
mass
and
lean
body
mass
(muscle,
heart,
liver
and
other
organs).
We
know
that
 an
 increase
in
a
person’s
body
fat
 is
open
associated
with
increased
 risk
 for
 severe
 diseases,
 but
 the
distribuBon
of
 body
 fat
 also
 affects
 one’s
 risk
level.Fat
 may
 be
 classified
 into
 two
 categories:
the
 subcutaneous
 and
 the
 visceral
 layer.
Visceral
 fat
breakdown
leads
to
the
release
of
low‐density
lipoproteins
(LDL)
and
triglycerides
into
 the
 bloodstream.
 Thus,
 the
 amount
 of
visceral
 fat
 correlates
 strongly
 with
 serious
diseases,
 namely
 hypertension,
 diabetes
 and
coronary
heart
disease.



Visceral
fat“Inside
fat”Subcutaneous
fat“Outside
fat”Figure
1:
The
distribuCon
and
accumulaCon
of
subcutaneous
and
visceral
adipose
Cssue
(Gather
Health
2007).Body
Composi<onSubcutaneous
FatVisceral
Fat Subcutaneous
FatVisceral
FatRESULTSTotal
Fat
Mass A012,
male
 normal
 control,
 is
 shown
 to
 have
 the
 greatest
 amount
 of
 total
 fat
mass
while
both
females
have
significantly
lower
levels
of
total
fat.Fat
Distribu<on
 Men
have
a
greater
proporCon
of
their
total
 fat
as
visceral
 fat
 than
do
women.
A058,
 female
with
 lipodystrophy,
has
the
same
proporCon
of
visceral
 fat
as
the
male
control
which
is
different
from
the
norm
for
a
female.
 A040
has
a
significant
decrease
in
her
subcutaneous
adipose
Cssue,
but
appears
to
retain
normal
amounts
of
visceral
fat.

Figure
2:
Images
from
each
step
of
the
complete
procedure
for
the
isolaCon
of
the
subcutaneous
and
visceral
layers
from
a
T1‐weighted
axial
MRI
image.Propor<on
of
Subcutaneous
and
Visceral
FatPercentage
of
Total
Fat
(%)A012 A058 A040Subcutaneous
FatVisceral
FatA012 A058 A040Total
Fat
Mass
based
on
Number
of
PixelsNumber
of
PixelsSubcutaneous
FatVisceral
Fat*The
right
leg
shows
muscle
mass
instead
of
fat
mass

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