Biomedical engineers at Duke University have developed a method using data from wearable devices such as smartwatches to digitally mimic an entire week's worth of an individual's heartbeats. The previous record covered only a few minutes.
Called the Longitudinal Hemodynamic Mapping Framework (LHMF), the approach creates "digital twins" of a specific patient's blood flow to assess its 3D characteristics. The advance is an important step toward improving on the current gold standard in evaluating the risks of heart disease or heart attack, which uses snapshots of a single moment in time -- a challenging approach for a disease that progresses over months to years.
The research was conducted in collaboration with computational scientists at Lawrence Livermore National Laboratory and was published on November 15, 2023, at the International Conference for High Performance Computing, Networking, Storage, and Analysis (SC23). The conference is the leading global conference in the field of high-performance computing.
"Modeling a patient's 3D blood flow for even a single day would take a century's worth of compute time on today's best supercomputers," said Cyrus Tanade, a PhD candidate in the laboratory of Amanda Randles, the Alfred Winborne and Victoria Stover Mordecai Associate Professor of Biomedical Sciences at Duke. "If we want to capture blood flow dynamics over long periods of time, we need a paradigm-shifting solution in how we approach 3D personalized simulations."
Over the past decade, researchers have steadily made progress toward accurately modeling the pressures and forces created by blood flowing through an individual's specific vascular geometry. Randles, one of the leaders in the field, has developed a software package called HARVEY to tackle this challenge using the world's fastest supercomputers.
One of the most commonly accepted uses of such coronary digital twins is to determine whether or not a patient should receive a stent to treat a plaque or lesion. This computational method is much less invasive than the traditional approach of threading a probe on a guide wire into the artery itself.
While this application requires only a handful of heartbeat simulations and works for a single snapshot in time, the field's goal is to track pressure dynamics over weeks or months after a patient leaves a hospital. To get even 10 minutes of simulated data on the Duke group's computer cluster, however, they had to lock it down for four months.
"Obviously, that's not a workable solution to help patients because of the computing costs and time requirements," Randles said. "Think of it as taking three weeks to simulate what the weather will be like tomorrow. By the time you predict a rainstorm, the water would have already dried up."
Source: ScienceDaily
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