In
his
new
book,
Super
Agers:
An
Evidence
Based
Approach
to
Longevity,
renowned
cardiologist
Eric
Topol
highlights
a
revolutionary
development
in
heart
disease
prevention:
the
use
of
AI
to
predict
an
individual’s
risk
of
a
fatal
heart
attack
years
before
symptoms
occur.
As
Dr.
Topol
notes,
AI-enhanced
imaging
of
the
fat
surrounding
the
coronary
arteries
now
enables
doctors
to
see
inflammation,
the
previously
invisible
underlying
driver
of
heart
attacks
and
stroke.
Topol
predicts
American
cardiologists
will
soon
use
these
AI
tools
to
identify
high-risk
individuals
long
before
conventional
methods
detect
disease,
potentially
saving
tens
of
thousands
of
lives.
How
radical
is
this
development?
Just
consider.
For
decades,
our
approach
to
coronary
artery
disease
(CAD)
has
revolved
around
identifying
and
treating
blockages
in
coronary
arteries
—
visible
obstructions
to
blood
flow,
such
as
plaque.
But
recent
advances
in
medical
research
and
technology
are
driving
a
fundamental
reassessment
of
this
approach.
We
now
know
that
the
initial
driver
of
heart
attacks
and
strokes
is
not
plaque
alone
but
rather
plaque
in
combination
with
inflammation
of
the
coronary
arteries.
And
new
anti-inflammatory
drugs
provide
a
proven
treatment
for
the
condition.
Despite
this
understanding,
“the
cardiovascular
community
has
not
moved
on
to
change
practice,
acknowledging
our
ability
to
detect
inflammation
and
to
do
something
about
it,”
writes
Topol.
Mostly
that’s
because
we
have
lacked
the
technology
to
diagnose
and
quantify
inflammation
in
the
coronary
arteries.
That’s
finally
beginning
to
change.
As
Topol
points
out,
thanks
to
breakthroughs
in
AI
that
enable
the
visualization
of
inflammation
on
standard
CT
scans,
and
significant
new
regulatory
changes,
the
U.S.
is
on
the
cusp
of
integrating
the
diagnosis
of
coronary
inflammation
into
routine
clinical
practice.
If
the
approach
is
eventually
widely
adopted,
as
Topol
foresees,
the
result
will
be
a
sea-change
in
cardiovascular
medicine,
enhancing
not
only
patient
outcomes
but
how
we
diagnose
and
manage
CAD.
Inflammation:
The
invisible
driver
of
heart
disease
Cardiologists
have
long
understood
that
coronary
inflammation
is
a
key
driver
of
both
plaque
formation
and
instability
leading
to
blockages
and
heart
attacks.
Yet
our
diagnostic
tools
have
focused
only
on
identifying
obstructions
rather
than
the
underlying
inflammation.
And
for
good
reason.
Traditional
stress
tests
and
nuclear
imaging
are
great
when
it
comes
to
assessing
arterial
blockages
but
cannot
measure
the
inflammatory
response
behind
the
physical
symptoms.
An
important
example
of
this
limitation
turned
up
in
a
major
study
in
The
Lancet.
Researchers
examined
cardiac
CT
scans
from
40,000
patients
and
found
that
only
one-third
of
cardiac
events
over
the
next
seven
years
happened
to
those
with
obstructive
CAD.
In
other
words,
two-thirds
of
patients
were
sent
home
believing
they
were
at
low
risk
for
a
heart
attack,
only
to
suffer
one
in
the
next
few
years.
The
study
highlights
the
vast
unmet
need
for
diagnostic
tools
to
detect
silent
coronary
inflammation,
which
precedes
the
development
of
obstructive
CAD.
Technological
breakthroughs:
AI
and
cardiac
inflammation
The
Lancet
study
took
advantage
of
pioneering
research
by
a
team
of
cardiologists
from
the
University
of
Oxford.
In
2017,
Charalambos
Antoniades,
Professor
of
Cardiovascular
Medicine
at
Oxford,
introduced
the
Fat
Attenuation
Index
(FAI),
a
method
for
detecting
coronary
inflammation
in
cardiac
CT
scans
by
analyzing
the
perivascular
fat
that
surrounds
arteries.
Subsequent
research
—
including
the
aforementioned
Lancet
study
—
has
provided
definitive
proof
that
the
FAI
Score
can
accurately
predict
patient
risk
up
to
a
decade
in
advance.
The
practical
application
of
this
knowledge
is
just
beginning.
Several
AI
solutions
visualize
plaque
on
CT
scans
–
but
none
yet
approved
by
the
FDA
can
visualize
inflammation,
which
would
enable
a
far
more
complete
view
of
arterial
plaque
burden
than
was
previously
possible.
Research
by
the
Oxford
team
led
to
the
development
of
the
world’s
first
AI
capable
of
visualizing
coronary
inflammation.
Already
approved
for
use
in
the
UK,
EU,
and
Australia,
this
technology
is
currently
awaiting
FDA
clearance
in
the
United
States.
Regulatory
changes
clear
the
way
for
clinical
adoption
Along
with
advances
in
technology,
widespread
clinical
adoption
is
supported
by
the
development
of
new
regulatory
and
reimbursement
frameworks.
Two
recent
policy
changes
in
the
U.S.
have
set
the
foundation
for
integrating
AI-powered
inflammation
analysis
into
routine
practice:
The
American
Medical
Association
released
a
new
Category
3
CPT
code
for
billing
and
reimbursement:
Beginning
in
2026,
this
code
will
allow
providers
to
bill
for
the
use
of
AI
in
analyzing
cardiac
CT
scans
for
the
presence
of
coronary
inflammation,
ensuring
that
hospitals
and
clinics
have
financial
incentives
to
adopt
the
technology.
Also
beginning
in
2026,
the
Centers
for
Medicare
&
Medicaid
Services
(CMS)
will
nearly
double
current
reimbursement
for
cardiac
CT
scans.
That
will
enable
healthcare
providers
to
prioritize
CT-based
diagnostics
over
traditional
stress
tests,
which
have
shown
significant
limitations
in
predicting
cardiovascular
risk.
Together,
these
regulatory
changes
are
already
accelerating
the
transition
toward
inflammation-focused
diagnostics,
ensuring
that
more
patients
benefit
from
the
new
AI
analysis
of
CT
imaging.
A
new
standard
in
cardiovascular
care
These
changes
have
profound
implications.
The
primary
reason
heart
disease
remains
the
leading
global
killer
is
our
inability
to
identify
high-risk
individuals
before
they
suffer
major
cardiac
events.
Now,
with
the
ability
to
measure
coronary
inflammation
through
AI-enhanced
CT
scans
and
to
more
accurately
determine
a
person’s
risk
of
heart
attack,
we
can
intervene
earlier
and
more
effectively.
This
represents
a
tremendous
shift
in
how
we
detect
and
prevent
heart
attacks.
Now,
patients
can
receive
earlier
interventions
and
improved
prevention,
reducing
the
risk
of
sudden
cardiac
events.
Physicians
finally
have
a
tool
that
goes
beyond
detecting
blockages
to
assess
the
full
spectrum
of
heart
disease
risk.
And
our
healthcare
system
can
dramatically
reduce
the
financial
burden
of
cardiovascular
disease
by
proactively
preventing
major
acute
cardiovascular
events.
What
once
seemed
like
a
theoretical
concept
—
that
coronary
inflammation
could
be
visualized
and
measured
—
has
now
become
a
key
to
driving
preventive
care.
With
clinically
proven
AI-powered
diagnostics
and
expanded
reimbursement
policies,
cardiovascular
medicine
is
entering
a
new
era.
The
next
challenge
is
to
ensure
these
innovations
are
rapidly
adopted
and
made
available
to
the
millions
of
patients
who
can
benefit
from
them.
Author
bio:
Frank
Cheng
is
CEO
of
Caristo
Diagnostics.
Over
the
last
20
years
he
has
led
multiple
digital
health
companies.
Frank
previously
led
two
venture-backed
companies
as
CEO
and
held
executive
positions
with
GE,
Roche,
Hillrom,
and
Stereotaxis.
Prior
to
Caristo,
he
was
President
and
Chief
Commercial
Officer
of
a
diagnostic
company
with
autonomous
AI
technology
that
was
FDA-cleared,
Medicare-reimbursed,
supported
by
a
new
Category
1
CPT
code,
and
adopted
around
the
world.
Image:
Magicmine,
Getty
Images