A national security and defense lab has created the fastest computer simulation of the human heart. Using a highly scalable code called Cardioid, which they created along with IBM, researchers at Lawrence Livermore National Laboratory modeled the electrical signals travelling from cell to cell, triggering them to contract. Their digital mock-up can simulate an hour of heart activity over 7 hours. Doesn't sound impressive? Previous models took 45 minutes just to simulate one beat. In theory, everything from drugs to pacemakers could be tested on Cardioid before being tested on humans.

The LLNL scientists aren't the first to model the electrical or chemical processes in organs, principal investigator Dave Richards says. "In fact, some of the numerical processes that we used were inspired by a paper that we read about how people are modeling the electrical flow in the brain," he says. Other labs are working on similar models for many body systems, including the heart. But Lawrence Livermore's model has one major advantage: It runs on Sequoia, the most powerful supercomputer in the world and a recent PM Breakthrough Award winner.

Why did a national defense lab decide to simulate the heart? "There are legitimate national security implications for understanding how drugs affect human organs, but I can't go into a lot of detail about it," says Fred Streitz, director of the Institute for Scientific Computing Research at LLNL. "This was a way to push the boundaries of supercomputing in a way that is easy to talk about with the American public."

But they had to hurry. Sequoia was created for nuclear weapons simulations and will soon be classified. Like most supercomputers, Sequoia is open during the "shakedown period" as it is first being set up and tested, so the team rushed to complete this simulation. Sequoia will still be available for the team to run Cardioid and for other projects after it's classified, but it will be harder to access. "Once it's classified, no one will ever find out what it's actually used for," Richards says.

Cardioid is still in the end stages of development and is not yet totally finished. Smaller versions of the processors in Sequoia exist in various other open networks, and IBM will continue to sell the smaller ones, so the code will still be useful once Sequoia is classified. "We might not be able to run it with quite the same performance, but we'll still be able to demonstrate the capability of this application," Richards says. "Most of what we have now are ideas for things we'd like to do with it; we haven't actually done that much yet,"

The team hasn't decided yet whether the finished product will be open-source. "It's basically a portable code," says computational scientist Art Mirin of LLNL.

Sim Heart

Modeling programs like Cardioid approximate the heart by breaking the organ down into units: The smaller the units, the higher the resolution and the more accurate the approximation of a real heart. Before Cardioid, the best resolution anyone could get was 0.2 mm in each direction, but Cardioid can run at 0.1 mm. "People typically have run these simulations for tens of heartbeats, but we are able to run for thousands of heartbeats on the full Sequoia, and at higher resolution," Mirin says. The simulation runs up to 300 times faster than was possible before.

Cardioid treats each cell like a unit. Streitz explains that they can't look into a cell and watch the behavior of specific organelles—at least not yet. "The processes within a cell are captured in a set of 19 ordinary differential equations, so we can't get inside that because they're treated as a single entity," says Streitz. "But the kinds of resolution we're talking about approach the cellular level," Mirin adds.

That should allow the team to investigate the competing theories for how cells are arranged in the heart. When the code is fully operational, the LLNL researchers will be able to make different assumptions about how cells are arranged, simulate an electrocardiogram (ECG), and compare the results to actual electrocardiograms on real patients. By the process of elimination they should land on the best idea for cell arrangement.

The Cardioid model works well for researching arrhythmia, an abnormal rhythm of the heart caused by confused electrical signals, in which the organ doesn't pump blood efficiently. Arrhythmias are the cause of some congestive heart failures, when the heart can't pump well enough to supply the whole body.

Cardiod's longer run time means the LLNL scientists can simulate the introduction of an anti-arrhythmic drug into the bloodstream, seeing the point when drug levels spike and then when they drop off. And its higher resolution accounts for areas of compromised blood flow, like scar tissue resulting from a past heart attack or other trauma, which affects how a drug works in the heart. "At a very coarse level of resolution, everyone's heart looks the same," Richards says. "The details that differentiate individual hearts can be very fine, and our ability to model at extraordinarily high resolution, currently a factor of eight greater than previously, that allows us to capture very fine differences. We also want to look at how variations in heart tissue types have an influence on how arrhythmias begin."

They're also working on improving the resolution further, down to 0.05 mm. "Ultimately this could lead to a diagnostic ability," Streitz says, explaining that someday a doctor could look at an ECG and notice "a little squiggle" and know what that means about the patient based on what they've seen in the model.

The next step is to create a mechanical simulation—"taking electrical simulation coupled with mechanical simulations, so the two talk to each other and inform each other," Richards says. Mechanics and electrophysiology are linked in a feedback system—electric signals trigger contraction, which itself affects the signaling processing. Another future project would model the blood flow as well. "We'll be much better able to model the heart realistically," Mirin says.

Streitz, Richards, and Mirin will reveal their results publicly for the first time at the Supercomputing Conference on November 13, where the team is one of five finalists for the Gordon Bell Prize, given annually for highest scientific achievement in supercomputing.

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