IEEE Spectrum November, 2014 - 36

t o gr A sp t h e v i tA l i m portance of this technology, you have
to understand today's standard of
cardiac care. So imagine a patient-
let's call him Jim-who has survived a serious heart attack. It was
a terrifying experience. He fell
down, clutching his chest, fearing
he was about to expire. But he was
rushed to the emergency room,
where doctors took swift action
to restore the flow of oxygen-rich
blood to his heart muscle. Jim is
alive-but not quite as alive as he used
to be. Some of the heart muscle, which
was deprived of oxygen during the crisis, has died. The resulting patches of
scar tissue can interfere with the electrical signals that propagate through
the heart muscle, thus disrupting the
contractions that should pump blood
through the body in a steady rhythm.
If Jim develops an irregular heartbeat,
called an arrhythmia, he may be in serious danger of cardiac arrest. His doctors
must assess whether he's at high risk of
developing this life-threatening condition and decide whether to implant a
36

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nORTh aMERICan

defibrillator in his chest. Just like external defibrillators used in ambulances
and emergency rooms, an implanted
device shocks the heart back into normal
rhythm if arrhythmia develops, thus saving the patient's life. To keep an at-risk
patient like Jim from ending up in the ER,
doctors may insert the internal device
as a precautionary measure.
How can doctors judge whether or not
to implant such a device in Jim? It's a big
decision, because they don't want to needlessly put him through this invasive procedure and expose him to the possible
complications that come with the defibril-

Doctors can
poke and prod
a virtual heart
in ways that
simply aren't
possible with
a patient's fleshand-blood heart
lator. Currently, cardiologists make their
decision based on the patient's ejection
fraction-the proportion of blood that is
pumped out of the heart with every beat.
If this number is below 35 percent, then
doctors advise the patient to undergo the
implantation procedure. Lots of patients
are getting implants based on this strategy,
but in the first year after the procedure
only 5 percent will go on to develop ventricular arrhythmias and receive a necessary shock. In other words, 20 devices are
implanted for every one life saved.
It's clear that many patients are needlessly risking surgical complications,

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infections, and device breakdowns. The
defibrillators aren't perfect, and the electrodes that monitor the heart can malfunction, triggering an unnecessary
shock. And a shock is a serious event-
it can feel like getting kicked in the chest
by a horse. Patients sometimes lose consciousness, which could prove deadly if
they're driving, for example, or soaking
in the tub. Most important, the ejection
fraction isn't a good predictor of arrhythmia; it misses many at-risk patients. Many
patients who don't fit the current criteria for an implanted defibrillator go on to
die of sudden cardiac arrest, often in the
prime of their lives.
My colleagues and I are now
test i ng whet her we c a n u se
patient-specific heart models
to make better predictions of a
person's risk of developing a lifethreatening arrhythmia, and
hence his or her need for an
implanted defibrillator. To do
that, we run simulations on the
patient's virtual heart to assess
how prone it is to arrhythmia. We
can do risky things to the virtual
heart that physicians are reluctant
to do to a live patient-such as generate small electric pulses in different locations and then watch to
see whether arrhythmia develops.
Our first retrospective study at
Johns Hopkins, in Baltimore, was
promising. We created heart models for about 40 patients who had
suffered heart attacks and received
implanted defibrillators, and we predicted
which of them would develop arrhythmias in the five years after surgery. Then
we compared our forecast with the real
data from that group of patients, revealing which of them had indeed received
shocks from their devices to terminate
arrhythmia episodes. With our virtual
heart simulations, we correctly identified those at-risk patients 85 percent of
the time over that five-year time span. In
comparison, the accuracy of standard
predictions for this group based on ejection fraction was only 51 percent over the
same period of time.

JoHns HopkIns UnIversIty (6)

Such models have already proved their
value for basic cardiac research, allowing scientists to plug in experimental
data and study what goes on in both
normal and diseased hearts. Now, virtual hearts are poised to deliver breakthroughs at the bedside.
Starting with a patient's MRI scans,
specialists in computational cardiology
can create a personalized model of the
patient's heart to study his or her unique
ailment. Doctors can then poke and prod
the computerized organ in ways that
simply aren't possible with a flesh-andblood heart. With these models at their
disposal, cardiologists should be
able to improve therapies, minimize the invasiveness of diagnostic
procedures, and reduce health-care
costs. While this simulation-based
medicine is still in the experimental stages, I believe upcoming clinical trials will show the real value of
virtual hearts.

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Table of Contents for the Digital Edition of IEEE Spectrum November, 2014