Mo phologie
(2019)
103,
169—179
Disponible
en
ligne
su
ScienceDi ec
www.sciencedi ec .com
ORIGINAL
ARTICLE
Imp o ing
he
clinical
unde s anding
o
hype ophic
ca diomyopa hy
by
combining
pa ien
da a,
machine
lea ning
and
compu e
simula ions:
A
case
s udy
Combine
données
cliniques,
machine
lea ning
e
modélisa ion
in o ma ique
pou
une
meilleu e
comp éhension
clinique
de
la
ca diomyopa hie
hype ophique
A.
Lyona,b,
A.
Mincholéa,
A.
Bueno-O o ioa,
B.
Rod igueza,∗
aDepa men
o
Compu e
Science,
Uni e si y
o
Ox o d,
Ox o d,
Uni ed
Kingdom
bCa dio ascula
Resea ch
Ins i u e
Maas ich
(CARIM),
Maas ich
Uni e si y,
Maas ich ,
Ne he lands
A ailable
online
27
Sep embe
2019
KEYWORDS
Hype ophic
ca diomyopa hy;
Elec oca diog aphy;
e-ca diology;
Pheno yping;
Compu a ional
clus e ing;
Compu e
modeling;
Pe sonalized
simula ions;
Ca diac
magne ic
esonance
imaging;
VPH
Summa y
Mos
pa ien s
wi h
hype ophic
ca diomyopa hy
(HCM),
he
mos
common
gene ic
ca diac
disease,
emain
asymp oma ic,
bu
o he s
may
su e
om
sudden
ca diac
dea h.
A
be e
iden ifica ion
o
hose
pa ien s
a
isk,
oge he
wi h
a
be e
unde s anding
o
he
mechanisms
leading
o
a hy hmia,
a e
c ucial
o
a ge
high- isk
pa ien s
and
p o ide
hem
wi h
app op ia e
ea men .
Howe e ,
his
cu en ly
emains
a
challenge.
In
his
pape ,
we
p esen
a
success ul
example
o
implemen ing
compu a ional
echniques
o
clinically- ele an
applica ions.
By
combining
elec oca diog am
and
imaging
da a,
machine
lea ning
and
high
pe o mance
compu ing
simula ions,
we
iden ified
ou
pheno ypes
in
HCM,
wi h
di e ences
in
a hy hmic
isk,
and
p o ided
wo
dis inc
possible
mechanisms
ha
may
explain
he
he e o-
genei y
o
HCM
mani es a ion.
This
led
o
a
be e
HCM
pa ien
s a ifica ion
and
unde s anding
o
he
unde lying
disease
mechanisms,
p o iding
a
s ep
u he
owa ds
ailo ed
HCM
pa ien
managemen
and
ea men .
©
2019
The
Au ho s.
Published
by
Else ie
Masson
SAS.
This
is
an
open
access
a icle
unde
he
CC
BY
license
(h p://c ea i ecommons.o g/licenses/by/4.0/).
Résumé
La
plupa
des
pa ien s
a ein s
de
ca diomyopa hie
hype ophique
(CMH),
une
mal-
adie
ca diaque
géné ique,
son
sou en
asymp oma iques,
mais
ce e
maladie
es
la
cause
p emiè e
de
mo
subi e
chez
les
jeunes.
Une
meilleu e
iden ifica ion
des
pa ien s
à
isque,
e
une
meilleu e
comp éhension
des
mécanismes
esponsables
des
a y hmies
es
essen ielle
∗Co esponding
au ho :
Depa men
o
Compu e
Science,
Uni e si y
o
Ox o d,
Ox o d,
Uni ed
Kingdom.
E-mail
add ess:
[email p o ec ed]
(B.
Rod iguez).
h ps://doi.o g/10.1016/j.mo pho.2019.09.001
1286-0115/©
2019
The
Au ho s.
Published
by
Else ie
Masson
SAS.
This
is
an
open
access
a icle
unde
he
CC
BY
license
(h p://
c ea i ecommons.o g/licenses/by/4.0/).
170
A.
Lyon
e
al.
pou
iden ifie
ces
pa ien s
à
hau
isque
e
leu
ou ni
un
ai emen
app op ié.
Cependan ,
cela
es e
un
défi.
Dans
ce
a icle,
nous
p ésen ons
un
exemple
éussi
de
l’implémen a ion
de
echniques
in o ma iques
pou
une
applica ion
clinique.
En
associan
données
d’image ie
e
d’élec oca diog aphie,
machine
lea ning
e
modélisa ion
in o ma ique,
nous
a ons
iden-
ifié
qua e
phéno ypes
pa mi
la
popula ion
de
CMH,
p ésen an
di é en s
ni eaux
de
isque
d’a y hmie
e
de
mo
subi e,
e
a ons
p oposé
deux
mécanismes
possibles
pou
explique
l’hé é ogénéi é
obse ée
dans
la
CMH.
Ce e
é ude
a
donc
amelio é
la
s a ifica ion
du
isque
chez
les
pa ien s
a ein s
de
CMH
e
une
meilleu e
comp éhension
des
mécanismes
sous-jacen
à
la
maladie,
ou nissan
une
a ancée
e s
une
p ise
en
cha ge
indi iduelle
de
ces
pa ien s
e
un
ai emen
pe sonnalisé.
©
2019
Les
Au eu s.
Publi´
e
pa
Else ie
Masson
SAS.
Ce
a icle
es
publi´
e
en
Open
Access
sous
licence
CC
BY
(h p://c ea i ecommons.o g/licenses/by/4.0/).
In oduc ion
Ca dio ascula
diso de s
emain
a
majo
bu den
wo ldwide
and
a e
esponsible
o
30%
o
dea hs
in
he
wo ld.
Among
hem,
hype ophic
ca diomyopa hy
(HCM)
is
a
gene ic
ca -
diac
disease
cha ac e ized
by
he
hickening
o
he
le
en icula
muscle
o
he
hea ,
and
i
is
a
majo
cause
o
sudden
ca diac
dea h
(SCD),
especially
among
young
adul s
and
a hle es
[1].
Mos
pa ien s
wi h
HCM
emain
asymp-
oma ic
wi h
no mal
li e
expec ancy,
bu
some
o
hem
may
die
suddenly
o
ca diac
a es
wi h
no
p e ious
signs.
Ge ing
a
be e
clinical
unde s anding
o
his
he e ogeneous
clin-
ical
cou se
and
de ec
high- isk
pa ien s
o
p o ide
hem
wi h
app op ia e
ea men
is
he e o e
a
challenge
and
a
p io i y
in
he
managemen
o
HCM
[2].
HCM
hea s
su e
om
s uc u al
changes
such
as
hype -
ophy
[3],
ca diomyocy e
disa ay
[4],
fib osis
[5],
as
well
as
ion-channel
dys unc ion
[6],
which
may
c ea e
an
uns a-
ble
elec ical
milieu
p edisposing
o
a hy hmia.
In
he
pas ,
non-in asi e
ools
o
assess
he
he e ogenei y
o
he
HCM
popula ion
ha e
been
de eloped
based
on
he
elec oca -
diog am
(ECG)
[7,8],
bu
hey
lack
specifici y
o
iden i y
he
pa ien s
a
highe
isk
[9,10].
In
he
absence
o
eliable
ECG
bioma ke s,
con en ional
isk
ac o s
(non-sus ained
en-
icula
achyca dia,
unexplained
syncope,
amily
his o y
o
SCD,
massi e
le
en icula
hype ophy
and
abno mal
exe cise
blood
p essu e
esponse)
a e
also
used
o
e al-
ua e
he
a hy hmic
isk
o
he
pa ien s,
and
a
alida ed
HCM
Risk-SCD
p edic ion
model
has
been
p oposed
in
2014
[11],
bu
s ill
shows
limi a ions
[12].
Mo eo e ,
hese
clin-
ical
obse a ions
do
no
cap u e
he
amoun
o
unde lying
myoca dial
abno mali ies
ha
may
lead
o
a hy hmia,
and
he
pa hophysiological
mechanisms
ha
may
inc ease
HCM
isk
a e
s ill
poo ly
unde s ood.
In
his
ansla ional
case
s udy,
we
p esen
how
he
use
o
compu a ional
me hods
such
as
machine
lea ning
and
high
pe o mance
compu ing
simula ions
helped
imp o e
he
isk
s a ifica ion
o
HCM
pa ien s
and
shed
ligh
on
he
mechanisms
unde lying
he
HCM
disease.
Fig.
1
p o ides
an
o e all
summa y
o
he
findings
and
po en ial
clinical
impac
o
he
case
s udy
p esen ed
in
his
pape .
In
a
fi s
pa ,
we
epo
how
he
de elopmen
o
a
clus e ing
algo-
i hm
based
on
no el
mo phological
bioma ke s
de i ed
om
he
ECG
helped
iden i y
ou
dis inc
pheno ypes
among
he
HCM
popula ion,
which
exhibi ed
di e ences
in
a hy hmic
isk
and
dis ibu ion
o
le
en icula
hype ophy.
In
a
second
pa ,
we
show
how
he
use
o
high
pe o mance
compu ing
simula ions
based
on
clinical
ca diac
magne ic
esonance
(CMR)
images
p o ided
mechanis ic
unde s and-
ing
o
he
di e en
ECG
pheno ypes,
and
helped
o
be e
unde s and
he
he e ogenei y
o
HCM.
This
pape
desc ibes
how,
by
de eloping
no el
compu a ional
echnologies
o
analysis,
in eg a ion
and
augmen a ion
o
clinical
da a,
we
con ibu ed
o
ad ancing
clinically- ele an
insigh
in o
HCM
and
made
a
s ep
owa ds
indi idual
pa ien
managemen .
Me hods
and
esul s
ECG-based
mo phological
ma ke s
iden i y
ou
dis inc
HCM
pheno ypes
ha
associa e
wi h
di e en
a hy hmic
isk
In
he
fi s
pa
o
his
p ojec ,
we
aimed
a
de eloping
ma hema ical
modeling
and
machine
lea ning
me hods
o
iden i y
ECG
bioma ke s
ha
may
help
imp o e
he
unde -
s anding
and
cha ac e iza ion
o
he
he e ogenei y
o
he
HCM
popula ion
[13].
To
his
end,
we
analyzed
high-fideli y
ECG
eco dings
om
85
HCM
pa ien s
and
38
heal hy
olun ee s
ec ui ed
as
pa
o
a
p ospec i e
s udy
om
he
John
Radcli e
Hospi al
in
Ox o d,
UK.
12-lead
ECGs,
measu ing
he
ca -
diac
elec ical
ac i i y
om
wel e
di e en
pe spec i es
on
he
body
su ace,
we e
eco ded
o
24
hou s
using
Hol e
moni o s.
CMR
imaging
was
also
pe o med
o
hese
pa ien s
and
p o ided
in o ma ion
on
he
ex en
and
dis-
ibu ion
o
he
hype ophy.
Finally,
gene ic
in o ma ion,
con en ional
isk
ac o s
and
amily
his o y
we e
ob ained
as
pa
o
ou ine
examina ion.
We
hen
de eloped
signal
p ocessing
and
ma hema ical
modeling
ools
o
compu e
bioma ke s
om
he
di e en
ECG
wa es
in
o de
o
cha -
ac e ize
hei
mo phology.
We
ocused
specifically
on
he
QRS
complex,
ep esen ing
he
elec ical
ac i a ion
o
he
en icles,
and
he
T
wa e,
cha ac e izing
en icula
elax-
a ion.
S anda d
bioma ke s
such
as
ampli ude
and
wid h
o
he
wa es
we e
measu ed.
The
QRS
shape
was
also
cha ac-
e ized
by
a
combina ion
o
He mi e
basis,
well-es ablished
ma hema ical
unc ions
able
o
p o ide
a
compac
desc ip-
ion
o
he
QRS
complex.
Fou
He mi e
unc ions
allowed
o
cap u e
HCM
he e ogenei y,
and
each
pa ien
was
cha-
ac e ized
by
a
ec o
o
mo phological
QRS
and
T
wa e
Imp o ing
he
clinical
unde s anding
o
hype ophic
ca diomyopa hy
171
Figu e
1
App oach
and
clinical
impac
o
he
case-s udy.
Using
signal
p ocessing,
ma hema ical
modeling
and
clus e ing,
we
iden ified
ou
di e en
pheno ypes
in
hype ophic
ca diomyopa hy
based
on
he
ECG.
This
had
a
clinical
impac
by
p o iding
imp o ed
pa ien
isk
s a ifica ion.
High
pe o mance
simula ions
hen
in es iga ed
he
po en ial
mechanisms
unde lying
hese
pheno ypes.
This
p o ided
new
op ions
o
indi idual
pa ien
managemen
and
di e en
he apeu ic
app oaches.
bioma ke s.
We
used
an
unsupe ised
ea u e
selec ion
app oach
combined
wi h
a
clus e ing
algo i hm
o
in es i-
ga e
and
ex ac
subg oups
om
he
HCM
popula ion.
This
was
pe o med
blinded
o
he
clinical
da a.
S a is ical
anal-
ysis
was
finally
pe o med
o
compa e
he
isk
ma ke s
be ween
he
g oups.
Fig.
2
summa izes
he
me hodological
app oach
aken.
Based
on
QRS
mo phology
only,
h ee
HCM
subg oups
we e
iden ified.
Pa ien s
in
G oup
1
(52%
o
he
popula-
ion)
displayed
no mal
QRS
mo phology.
G oup
2
(22%
o
pa ien s)
showed
di e ences
in
he
fi s
h ee
He mi e
bases
in
lead
V4
compa ed
o
heal hy
olun ee s
and
G oup
1,
bu
no
di e ences
in
V6.
On
he
ECG,
his
was
obse ed
as
a
sho e
R
wa e
du a ion
and
deepe
S
wa es
in
lead
V4
compa ed
o
G oup
1.
G oup
3
(26%
o
pa ien s)
exhib-
i ed
la ge
di e ences
in
lead
II
and
V4—V6
compa ed
o
he
o he
HCM
g oups
and
heal hy
olun ee s,
mo e
specifically
sho
R
wa e
du a ion
and
ampli ude,
and
longe
S
wa e
du a ion
and
ampli ude.
Among
hese
h ee
g oups,
ECG
ea u es
we e
he e o e
significan ly
di e en ,
bu
clinical
ma ke s
and
ma ke s
o
a hy hmic
isk
we e
no .
This
sug-
ges ed
ha
QRS
bioma ke s
alone
we e
no
su ficien
o
HCM
isk
s a ifica ion.
We
hen
combined
bo h
QRS
mo phology
and
T
wa e
bioma ke s
in
he
clus e ing
algo i hm.
This
led
o
he
iden ifica ion
o
ou
dis inc
subg oups.
G oups
2
and
3
emained
he
same
han
he
ones
iden ified
wi h
QRS
ea u es
only.
Howe e ,
he
addi ion
o
he
pola i y
o
he
T
wa e
as
a
bioma ke
sepa a ed
G oup
1
in o
G oup
1A,
wi h
in e ed
T
wa es
in
leads
V4—V6,
and
G oup
1B,
wi h
up igh
T
wa es
in
hese
leads
(Fig.
3,
Panel
A).
In e es ingly,
G oup
1A,
wi h
no mal
QRS
mo phology
bu
in e ed
T
wa es,
showed
he
highes
median
HCM
Risk-SCD
sco e
among
he
ou
g oups
(Fig.
3,
Panel
C).
G oup
1A
also
exhibi ed
he
mos
pa ien s
wi h
a
mixed
hype ophy
dis ibu ion,
wi h
combined
sep al
and
apical
hype ophy,
while
G oups
2
and
3
had
mos ly
sep al
hype ophy
only.
G oup
1B
pa ien s
exhibi ed
li le
o
no
hype ophy
(Fig.
3,
Panel
B).
This
s udy
he e o e
iden ified
ou
dis inc
HCM
phe-
no ypes
based
on
newly
de eloped
ECG
mo phological
bioma ke s
ex ac ed
om
high-fideli y
eco dings.
Such
pheno ypes
showed
di e ences
in
a hy hmic
isk
sco es
and
dis ibu ion
o
le
en icula
hype ophy.
Thus,
ou
s udy
showed
he
po en ial
o
using
ECG
pheno yping
combined
wi h
machine
lea ning
o
dissec
he
he e ogenei y
o
HCM
and
help
imp o e
indi idual
pa ien
managemen .
High
pe o mance
compu e
simula ions
based
on
CMR
images
p o ide
di e en
mechanisms
o
ECG
abno mali ies
in
HCM
The
p e ious
s udy
iden ified
ou
subg oups
in
he
HCM
popula ion
ha
showed
di e ences
in
a hy hmic
isk
and
172
A.
Lyon
e
al.
Figu e
2
Me hodological
app oach
o
he
iden ifica ion
o
ou
HCM
pheno ypes
( om
[13]).
dis ibu ion
o
hype ophy.
Following
up
on
his
wo k,
ou
nex
objec i e
was
o
unde s and
he
mechanisms
behind
such
a
pheno ypic
he e ogenei y,
and
p o ide
po en ial
explana ions
o
he
di e en
subg oups
iden ified
[14].
Clinically,
imp o ing
he
mechanis ic
unde s anding
o
HCM
may
yield
a
key
impac
on
he
indi idual
managemen
o
hese
pa ien s,
including
po en ial
ea men
and
ailo ed
he apies.
To
his
end,
we
de eloped
a
high
pe o mance
com-
pu e
simula ion
amewo k
based
on
CMR
imaging
da a.
We
selec ed
ep esen a i e
pa ien s
om
G oup
1A
(wi h
no mal
QRS
mo phology
and
in e ed
T
wa es,
and
high-
es
isk
sco e
o
sudden
ca diac
dea h),
G oup
1B
(wi h
no mal
ECG
mo phology)
and
G oup
3
(wi h
abno mal
QRS,
no mal
T
wa e,
and
second
highes
isk
sco e).
F om
he
CMR
images
o
hese
pa ien s,
we
compu ed
a
pe sonal-
ized
olume ic
mesh
o
each
pa ien ’s
hea
and
o so.
The
elec ical
ac i i y
ac oss
he
en icles
was
hen
defined
by
implemen ing
a
cellula
compu a ional
ac ion
po en ial
model
[15]
a
each
node
o
he
olume ic
mesh,
o
simu-
la e
p opaga ion
o
he
elec ical
signal.
Vi ual
elec odes
we e
addi ionally
modelled
o
eco d
he
simula ed
ECG
on
he
i ual
pa ien s.
Wi h
his
simula ion
amewo k,
ou
aim
was
o
ep oduce
he
ECG
abno mali ies
iden ified
in
he
di -
e en
HCM
pheno ypes
o
he
p e ious
s udy,
and
p o ide
po en ial
mechanis ic
explana ions
o
his
ECG
he e ogene-
i y
using
compu e
simula ions.
We
he e o e
e alua ed
he
influence
o
a ious
abno mali ies
epo ed
in
HCM
on
he
ECG
mo phology,
including
inc eased
wall
hickness,
ca -
diomyocy e
fibe
disa ay,
changes
in
conduc ion
eloci y,
ionic
emodeling
o
abno mal
coupling
be ween
he
Pu kinje
as
conduc ion
laye
and
he
myoca dium.
These
di e en
simula ions
allowed
us
o
in es iga e
he
indi idual
e ec s
o
hese
HCM
abno mali ies
on
he
ECG
and
iden i y
hose
ha
may
be
esponsible
o
he
HCM
phe-
no ypes
iden ified.
The
dis ibu ion
o
hype ophy
and
he
Imp o ing
he
clinical
unde s anding
o
hype ophic
ca diomyopa hy
173
Figu e
3
Fou
pheno ypes
we e
iden ified
in
HCM,
exhibi ing
di e ences
in
ECG
mo phology
(A),
dis ibu ion
o
hype ophy
(B)
and
a hy hmic
isk
(C)
( om
[13]).
ana omy
o
he
pa ien
yielded
simila
QRS
mo phology
and
no mal
T
wa es
in
all
cases
(Fig.
4).
The e o e,
inc eased
wall
hickness
could
no
explain
he
QRS
and
T
wa e
abno -
mali ies
obse ed
in
G oups
1A
and
3.
We
hen
ocused
on
he
impac
o
issue
mic os uc u e
on
he
ECG,
and
e al-
ua ed
he
e ec
o
fibe
disa ay
and
al e ed
conduc ion
eloci y
due
o
fib osis
o
hype ophy
in
a ious
egions
o
he
myoca dium
(such
as
he
sep um,
o
he
apex).
These
led
o
abno mal
QRS
complexes,
bu
did
no
ansla e
in o
he
specific
deep
S
wa es
in
lead
V6
ha
cha ac e ized
G oup
3
(Fig.
5).
We
hen
ocused
on
he
influence
o
al e ing
he
conduc ion
sys em
by
modi ying
he
ac i a ion
sequence
o
he
en icles,
and
he
coupling
be ween
he
Pu kinje
endoca dial
laye
and
he
myoca dium.
Simula ing
a ious
conduc ion
blocks
a ec ed
he
QRS
complexes
mo phology
bu
did
no
lead
o
he
abno mali ies
o
G oup
3
(Fig.
6).

174
A.
Lyon
e
al.
Figu e
4
E ec
o
he
ana omy
on
he
ECG.
G oups
1B,
3
and
1A
exhibi
simila
ECG
mo phologies
despi e
di e ences
in
ex en
and
dis ibu ion
o
hype ophy.
Ana omy
alone
does
no
explain
G oup
3
and
1A
specific
abno mali ies.
Taken
om
[14].
Howe e ,
modeling
an
abno mal
coupling
be ween
he
as
endoca dial
laye
and
he
myoca dium
was
he
only
way
o
simula e
he
deep
S
wa es
in
leads
V4—V6
iden ified
in
G oup
3
(Fig.
7,
Panel
D),
by
c ea ing
a
pa chy
elec ical
ac i a ion
wi h
a eas
o
la e
ac i a ion
(Fig.
7,
Panels
A
o
C).
Finally,
we
modelled
he
HCM
ionic
emodeling
(Fig.
8),
including
an
inc ease
o
he
la e
sodium
and
he
L- ype
calcium
cu en s,
a
educ ion
o
he
po assium
cu en s,
and
emodeling
o
he
calcium
handling
subsys em,
in
hype ophic
a eas.
This
led
o
a
p olonged
du a ion
o
he
ac ion
po en ial
in
hese
egions
and
ansla ed
in o
in e sed
T
wa es
on
he
la e al
leads
o
he
ECG,
explaining
he
pheno ype
o
G oup
1A.
These
simula ions
he e o e
iden ified
wo
dis inc
po en-
ial
mechanisms
o
he
ECG
abno mali ies
associa ed
wi h
an
inc eased
isk
o
SCD
in
HCM.
They
also
sugges ed
ha
he
HCM
ionic
emodeling
exp essed
in
G oup
1A,
subg oup
wi h
he
highes
SCD
isk
sco e,
may
play
a
key
ole
in
a hy hmogenesis.
The
na u e
o
hese
mechanisms
is
e y
di e en :
one
is
based
on
conduc ion
abno mali ies,
while
he
o he
in ol es
ionic
emodeling.
This
has
implica ions
on
he
di e en
possible
he apies
o
hese
g oups
o
pa ien s.
Indeed,
while
G oup
1A
may
benefi
om
a
pha macological
ea men
a ge ing
he
exp ession
o
ion
channels,
G oup
3
may
no
espond
o
such
he apy.
Discussion
Combining
compu a ional
me hods
imp o es
he
clinical
unde s anding
o
ca diac
diseases
In
his
pape ,
we
epo
an
example
o
success ul
imple-
men a ion
o
compu a ional
echnology
o
a
clinical
applica ion
in
ca diology.
The
compu a ional
me hods
conside ed
he e
combine
signal
p ocessing,
ma hema ical
modeling,
machine
lea ning
and
high
pe o mance
com-
pu ing,
and
hey
con ibu e
o
un angle
he
he e ogenei y
o
HCM
and
p o ided
mo e
insigh
in
i s
mechanisms.
As
illus a ed
in
ou
case
s udy,
he
powe
o
hese
echniques
is
wo old.
Fi s ly,
hey
a e
able
o
make
sense
o
mul i-
a ia e,
complex
and
he e ogeneous
da ase s
and
de ec
di e ences
ha
migh
be
challenging
o
he
human
eye
Imp o ing
he
clinical
unde s anding
o
hype ophic
ca diomyopa hy
175
Figu e
5
E ec
o
conduc ion
changes
in
a ious
egions
o
he
myoca dium
on
he
QRS
complex
( om
[14]).
[16].
These
echniques
make
ewe
assump ions
by
selec ing
disc imina o y
ea u es
om
he
whole
ECG
da a.
Wi h
he
g owing
amoun
o
eco ded
da a
in
clinical
se ings,
he
in eg a ion
o
hese
me hods
in
he
clinic
may
be
c ucial
o
aid
heal hca e
decisions
and
imp o e
pa ien
s a ifica ion
in
la ge
coho s.
Secondly,
compu a ional
echniques,
such
as
compu e
modeling,
allow
he
independen
assessmen
o
he
influence
o
indi idual
pa ame e s
o ming
a
sys em.
This
is
a
key
s eng h
compa ed
o
s anda d
expe imen al
echniques,
o
which
isola ing
pa ame e s
o
s udy
hei
e ec
emains
a
challenge.
As
a
consequence,
compu-
a ional
echniques
a e
ecei ing
a
g owing
a en ion
176
A.
Lyon
e
al.
Figu e
6
E ec
o
ac i a ion
blocks
in
a ious
egions
o
he
myoca dium
on
he
QRS
complex
( om
[14]).
o
analyze
medical
da a
and
add ess
clinical
p oblems
[17—19],
and
despi e
ha
se e al
challenges
emain,
mos ly
due
o
he
na u e
o
eal-wo ld
da a
(p in -ou
ECGs,
incomple e
da ase s,
need
o
expe
consensus),
hey
can
help
unco e
new
mechanisms,
imp o e
disease
knowledge,
guide
he apies
and
aid
clinical
decisions.
Clinical
impac
o
he
wo k
As
men ioned
p e iously
in
he
ex ,
his
wo k
showed
clin-
ical
implica ions
in
wo
ways.
Fi s ,
i
p o ided
a
new
classifica ion
o
HCM
pa ien s
based
on
ECG
bioma ke s,
p o-
iding
insigh
in
he
he e ogenei y
o
he
disease.
We
showed
Imp o ing
he
clinical
unde s anding
o
hype ophic
ca diomyopa hy
177
Figu e
7
Abno mal
Pu kinje-myoca dium
coupling
led
o
a
pa chy
ac i a ion
(A,
B)
wi h
a eas
o
la e
ac i a ion
(C),
and
ansla ed
in o
deep
S
wa es
in
lead
V6,
explaining
G oup
3
abno mali ies.
Taken
om
[14].
ha
HCM
pa ien s
wi h
a
p ima y
T
wa e
in e sion
(and
no mal
QRS)
ha e
a
g ea e
isk
o
SCD
and
a hy hmia,
com-
pa ed
o
pa ien s
wi h
solely
QRS
abno mali ies,
highligh ing
he
key
ole
o
epola iza ion
in
a hy hmogenesis
in
HCM.
We
also
showed
ha
he
loca ion
and
dis ibu ion
o
hype -
ophy
was
associa ed
o
highe
SCD
isk,
a he
han
he
ex en
o
hype ophy.
Secondly,
he
use
o
compu e
simu-
la ions
p o ided
wo
dis inc
mechanisms
ha
may
explain
he
di e en
pheno ypes
we
iden ified
in
HCM.
Abno mal
Pu kinje
conduc ion
can
explain
he
QRS
abno mali ies
o
G oup
3,
while
HCM
ionic
emodeling
in
he
egion
o
hype -
ophy
may
be
esponsible
o
in e ed
T
wa es
in
G oup
1A.
The
ac
ha
G oup
1A
displayed
he
highes
SCD
isk
sco e
sugges ed
ha
ionic
emodeling
in
HCM
may
play
a
key
ole
in
a hy hmogenesis,
while
he
conduc ion
abno -
mali ies
in
he
Pu kinje
sys em
may
be
less
p oa hy hmic.
Finally,
his
o e all
be e
unde s anding
o
HCM
he e o-
genei y
may
ha e
implica ions
in
pa ien
managemen ,
as
pe sonalized
ea men
o
HCM
pa ien s
could
be
p o ided
depending
on
he
mechanisms
unde lying
hei
ECG
abno -
mali ies.
Indeed,
a
pa ien
om
G oup
1A
may
benefi
om
a
pha macological
ea men
imp o ing
ion
channels
unc-
ion,
while
his
would
ha e
no
e ec
on
a
pa ien
o
G oup
3.
Cu en
and
po en ial
de elopmen s
o
he
wo k
De elopmen s
o
he
wo k
p esen ed
in
his
pape
a e
cu -
en ly
ongoing.
A
new
da abase
o
HCM
ECG
eco dings
is
being
collec ed
and
will
enable
he
applica ion
o
he
mod-
eling
and
clus e ing
echnology
on
a
la ge
da ase .
This
will
allow
us
o
e alua e
he
ECG
c i e ia
p esen ed
in
he
s udy
on
a
la ge
coho
wi h
a
la ge
numbe
o
ca -
dio ascula
end-poin s
and
e en s.
This
could
lead
o
he
defini ion
o
a
new
classifica ion
c i e ion
used
in
he
clinic
o
isual
inspec ion
o
ECGs
in
HCM.
Mo eo e ,
his
wo k
gene a ed
s ong
mo i a ion
o
deepe
clinical
in es iga-
ions,
such
as
he
use
o
endoca dial
o
epica dial
mapping
s udies
o
e i y
he
hypo hesis
p esen ed
he e
o
he
mech-
anisms
esponsible
o
he
HCM
pheno ypes.
The
use
o
new
echnologies
such
as
ECG
imaging
may
add
e en
mo e
in o -
ma ion
o
hese
findings.