Despite the complexity of these models, there was still a missing element: genes. It turns out that genes play an enormous role in heart disease; the inheritance of a single unlucky gene can raise the chances of early death from a long shot to a near certainty. Even genes that normally don’t cause heart problems can do so when they are switched on or off or damaged by environmental influences, such as cigarette smoke or stress. To make things even more complicated, heart disease itself can influence cardiac genes in ways that accelerate the disorder or cause new complications. To accurately model disease in a heart, researchers must account for these genetic factors.
Working with UC San Diego colleagues, McCulloch is using genetically engineered mice to identify genes that play a role in heart disease. He is then using that information to modify virtual-heart models. McCulloch’s lab uses mice with changes in a single gene that render it either constantly active or constantly inactive. These altered mice are then studied for differences in cardiac functioning and susceptibility to heart disease; any such differences can generally be attributed to the altered gene. If a mouse that has had a certain gene made continually active develops heart disease at an unusually early age, for example, then the computer model can be adjusted so that switching that gene on in the virtual heart will trigger disease processes. Such modifications can be critical in making the models more realistic. If the virtual heart is used to investigate a drug designed to prevent the onset of heart failure after a heart attack, for instance, then it has a better chance of predicting how well the drug will work if it includes the genetic processes that the drug might influence.
Built up from the workings of individual cells and genes, the virtual heart presents a vivid image of the vital organ. But is it a realistic one? The models provide what are essentially predictions of how a real heart would behave, and researchers need ways to ensure the accuracy of these predictions. Chris Johnson, a computer scientist who directs the Scientific and Computing Imaging Institute at the University of Utah in Salt Lake City, has created one solution: a way to gauge the models against data from living volunteers.
The main tool for measuring the heart’s electrical activity, an electrocardiogram that takes readings from 12 electrical leads, yields only a relatively crude analysis. But a “jacket” developed at the Cardiovascular Research and Training Institute at Utah that employs 192 leads, along with a standard MRI scan, gives Johnson a much more complete picture. To translate the jacket’s measurements and the MRI data into a detailed picture of the heart’s electrical activity, Johnson first takes into consideration how bone, blood, fat, and muscle distort a signal traveling from a particular point on the heart to a particular point on the skin. He can then infer an electrical map of the heart at any point in time. “We’re taking voltages from the outside and determining what they would be on the surface of the heart,” he says. This allows the modelers to determine whether their millisecond-by-millisecond predictions of the heart’s electrical activity are accurate-and to fine-tune their calculations to bring them closer to reality.
Johnson’s models and the electrode jacket are also in experimental use to help cardiologists spot heart disease. While electrocardiograms of hearts with potentially fatal artery blockages often look completely normal to all but the most expert eyes, the jacket-based system generates almost MRI-like images that can reveal blockages and other defects with such stark clarity that even a layperson can spot them. Johnson’s team has also created software that allows the simulations to be viewed in 3-D with special stereoscopic glasses. The improved view could, for example, allow doctors to initiate drug therapy or perform artery-clearing angioplasty earlier than they might otherwise, which could help prevent heart attacks or avoid the need for more invasive coronary bypass surgery.