catalyst

Research, Scholarship and Creative Achievement at UTSA

Engineering a Cure

Engineering a Cure

Mechanical engineer tackles cancer from a different angle


Yusheng Feng used to work on mathematical modeling of nano-thin films in semiconductors, but now the mathematician and mechanical engineer is using his expertise in a whole new way—searching for better cancer treatments.

A career in industry left Feng craving problems to solve. Now an associate professor of mechanical engineering at UTSA, he’s found plenty. His projects all involve computer simulation and mathematical modeling applied in a range of areas—from treatments for prostate and liver cancer and drug delivery using nanoparticles to bioheat transfer (i.e., temperature variations within tumors and surrounding tissues that affect the way cancer treatments work).

“When I came back to academia, I wanted to find some interesting areas to work in [that have] more open questions,” he says.

Cancer, with its roots in biology, offers the research challenges Feng sought. “Using mathematics as a tool, I believe that the big breakthrough will be in biological areas this century as opposed to physics in the last century.”

Feng, who joined UTSA’s faculty in 2007, received a competitive career grant supporting biomedical research from the National Institutes of Health the same year. He is on the core faculty of the joint bioengineering Ph.D. program of UTSA and the University of Texas Health Science Center at San Antonio, and he also directs UTSA’s Computational Bioengineering and Nanomechanics Lab.

But it was in 2004 that he received his first biomedical research opportunity. Two years into his job as an assistant professor of mathematics at Concordia University and research fellow at the University of Texas at Austin, he became involved in a collaborative, multidisciplinary research project between UT and M.D. Anderson Cancer Center. The project, which studied real-time surgical control for image-guided laser treatment of prostate cancer, was part of the Dynamic Data Driven Application System (DDDAS) initiative sponsored by the National Science Foundation. Feng was one of three original researchers who produced preliminary results that led to the research effort.

Feng’s role in that project was to create the computer simulation and mathematical models that guided the laser, using magnetic resonance thermal imaging (MRTI) while monitoring the temperature of the tumor and other tissues during a procedure and making adjustments based on constant feedback from the imaging device. The DDDAS project, which Feng called a success, wrapped up in 2009, and lessons learned from that study continue to inform other areas of his research, he says.

“Commonly used treatment of cancer is either surgery, chemo or radiation,” says Feng. “But now you may use a laser to treat cancer,” in a process called ablation, which surgically removes tissue.

A key issue is optimizing the laser treatment in order to “minimize damage outside and maximize the damage inside” a tumor, Feng explains. To that end, computer simulation gives surgeons a more precise plan for using lasers.

“[Surgeons] have to use computers for treatment planning and surgical control,” he says. “So that’s where I come in, to do the optimization simulation to tell them OK, turn it on.

J. Tinsley Oden, who was the principal investigator of the DDDAS project, says the relatively recent advent of computational modeling has enormous implications for science and medicine.

“We can sort of look into the future,” says Oden, who is considered the father of the field of computational mechanics. He is an associate vice president for research at UT Austin and founder and director of the Institute for Computational Engineering and Sciences.

Researchers intent on finding new and better ways to treat cancer increasingly collaborate in teams drawn from a range of academic disciplines. As such, Feng plays a key role in forming the kind of partnerships among academic disciplines that are essential to marshaling the full power of computational modeling, Oden says.

“Mathematics, physics, chemistry, medicine, biomedicine, biology—specialists from these disciplines have learned the importance and benefits of collaboration,” Oden says. Feng “is in the middle of all of it.”

Feng, trained in computational mechanics and applied mathematics, is building on knowledge gained from the prostate cancer project with another research project focused on liver cancer in which he is collaborating with a researcher at the University of Colorado Denver. In this project, the heat source is radio frequency (RF) rather than a laser, and the diagnostic imaging is done by ultrasound instead of magnetic resonance imaging (MRI). Using RF and ultrasound is much less expensive, Feng says, but it is more challenging to optimize the surgical process.

The key to a successful surgery for prostate and liver cancer using either laser or RF is to control bioheat transfer in tumors. Temperatures vary among normal tissue, tumors, arteries and veins, for example, which affects the laser or RF’s potency. Feng is working on equations that account for these temperature changes, which no models currently capture accurately.

Some forms of cancer—those with cells spread over a larger area—require a different treatment approach.

“Usually, the impact area [of the laser itself] is very small,” Feng says. “Sometimes the tumor is bigger than that. That’s where the nanoparticles will be used to enhance the treatment effect.”

Yet another of Feng’s projects involves silicon nanoparticles with a gold shell that are injected into tumors.

“You can tune the thickness and diameters of the nanoparticles and then you get the maximum heat absorption,” he says.

Other nanotechnology projects are in the works, including a collaboration with Boston University that uses nanotubes to deliver drugs under magnetic influence. Feng’s task is to create computer models to simulate the drug delivery process.

The goal behind the various cancer research projects Feng and his collaborators are involved in is to find ways to treat cancer effectively while doing as little damage as possible to healthy tissue.

“Chemotherapy is very toxic; it’s like you give a poison to the body everywhere,” Feng says. “And the radiation therapy can only target a large area in current practice. It doesn’t matter if it’s good or bad. It just kills [all the cells].”

As a result, side effects abound, he explains, including hair loss during chemotherapy, which targets fast-growing cells.

“The idea of patient-specific and targeted medicine can be viewed as ‘This is the organ, that’s the part you want to treat.’ You can spare the healthy part and only treat the sick part,” he says.

It is possible to design treatment specific to a patient and formulate a more accurate prognosis by taking a patient’s information and using it to create predictive models, Feng says.

“Cancer is a terrible disease,” Feng says. “Hopefully, people like me can use our analytical skills to contribute [to] cancer research. I am glad to see that mathematics and computer simulation are now gaining more and more acceptance in the medical field.”

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