Math Performing Heart Surgery

Math Performing

Heart Surgery

People are as different on the inside as they are on the outside, so deciding which surgery to perform is sometimes a life-or-death guessing game. 

However, a professor at Stanford University has created a computer program that models each patient's unique cardiovascular system, taking the guesswork out of major heart surgery. 

Predicting Successful Surgeries

Bioengineers Combine Mathematical Equations, Data to Simulate Surgeries

December 1, 2005 — A new hi-tech method takes the guesswork out of cardiovascular surgery. Using mathematical equations, bioengineers build a personalized computer model of each heart patient, then perform the surgery on the computer model before it is ever done on a patient. The aim of this approach is to perform more successful surgeries and eliminate unnecessary operations.

STANFORD, Calif.--People are as different on the inside as they are on the outside, making it difficult to predict which heart surgery will help which patient. Now, a new, high-tech approach may predict which patients will and will not have successful surgeries.

Heart attack survivor, David Lesesky says, "When I started having problems, I just didn't want to take the chance." He didn't take a chance. Lesesky made it through the heart attack and survived surgery and is doing just fine. The outcome, however, is not always the same: Each patient and each surgery brings its own risks.

"There's no way to guess as to how much blood flow is going to be restored," says Charles Taylor, a bioengineer at Stanford University in Calif. But now Taylor may have found a high-tech way of taking the guess work out of cardiovascular surgery. "We build a computer model to predict what will happen to a patient in a given surgical procedure."

The computer model is a personalized layout of each heart patient. Taylor says, "We actually do the surgery on the computer model before it is ever done on a patient." The program shows a 3D model of a patient with cardiovascular disease and incorporates imaging data and mathematical equations.

"The question we have for this patient is that would she benefit from a procedure -- bypass procedure -- to improve blood flow down to the legs?" Taylor says after examining a patient's 3D model on the computer. The yellow on the model shows the potential bypass path. When blood flow is simulated, it's revealed that two of the vessels going into the legs were clotted off -- the surgery would not have been successful.

"What it will mean for the patient is fewer operations -- conceivably more successful operations," Taylor says. And it will help keep hearts beating -- longer.

The computer model is being tested right now, retrospectively, on patients who are already planning to have surgery. So far results show it will be successful in predicting the outcome of cardiovascular surgeries.

BACKGROUND: A professor at Stanford University is applying his engineering expertise to take some of the guesswork out of predicting surgical outcomes by making a new computer model of the cardiovascular system. Charles Taylor spent 10 years taking detailed information gleaned from diagnostic imaging tools like CT scans and MRI to build his computing modeling program.

THE PROBLEM: People are unique on the inside as well as on the outside, and this can make it difficult for surgeons to predict how any given person will respond to surgery. Currently the only tools available are statistics and educated guesses.

HOW THE MODEL WORKS: The new model incorporates imaging data into a Web-based tool that includes 3D views and surgical sketchpads. Millions of complex equations involving how blood flows through the body and individual physiology are used to demonstrate what might happen under various "what if" scenarios. Taylor has also taken into account the flexibility of veins and arteries. The model is currently being tested by taking data before and after surgery and determining how well the model predicted what actually occurred. Taylor recently reported that in large-animal studies, the model can predict blood flow after an aortic graft within 10 percent.