UT Faculty İmproving Surgical Outcomes For Children,Cancer Patients

Faculty and students at the Cockrell School of Engineering at The University of Texas at Austin are developing ways for cancer patients and children born with facial deformities to make more informed decisions about which reconstructive surgeries would be most aesthetically pleasing and practical based on their individual body types and personal preferences. The interdisciplinary research, which includes biomedical engineering Professor Mia K. Markey and aerospace engineering Professor K. Ravi-Chandar, pairs faculty and students with doctors and patients at The University of Texas MD Anderson Cancer Center and Dell Children's Medical Center of Central Texas.

Researchers at both medical centers are using novel 3D surface imaging technology and algorithms to address one of the most difficult questions for cancer patients and children facing reconstructive surgery: What procedure is right for me?

"With breast cancer patients, they are usually candidates for more than one kind of reconstructive surgery and the only reason to choose one over another is the patient's own preference," Markey said. "So that patient may be able to understand differences in costs or how long one procedure will require her to be in the hospital, but in terms of understanding how it will change her appearance, she wouldn't know a reason to pick one procedure over the other."

Options based off of patients' preferences

But Markey, along with a team of surgeons, doctors and psychologists at MD Anderson, aims to change that. The researchers are in the midst of several research projects – funded by the American Cancer Society and the National Institutes of Health – to develop technology for quantifying surgical outcomes and understanding patients' perceptions of changes in their appearance.

Traditionally, the area of a patient's body that will be reconstructed is measured by doctors with measuring tape. But it's hard to know upfront which measurements are important – meaning multiple measurements may be required – and the method can be uncomfortable for patients.

Markey and her team are simplifying the process, however, by using commercially available 3D surface imaging technology. The technology takes multiple photos of patients prior to their surgery and builds 3D models and measurements of the photographed area in a matter of minutes.

Such models then can be used to build simulations of what a patient would look like if he or she had a procedure. For cancer patients undergoing facial reconstructive surgery, the models would help better define cosmetic outcomes. And for breast cancer patients, who often must choose from multiple procedures, the simulations would make it easier to decide which procedure provides the most desired physical effect.

"We're trying to do this in an honest way, so that these aren't just fancy computer graphics. They provide patients with a realistic picture of what they would look like after their surgery and are constrained by what is actually surgically possible," Markey said.

The bigger goal of one of the research projects is to identify underlying commonalities among breast cancer patients – like age, feelings on body image issues, disease history, etc. – so that surgeons and doctors can provide women with reconstructive surgery options that are more tailored to their individual needs, expectations post-surgery and physical and mental characteristics.

Markey, along with Fatima Merchant, an engineering alumna and University of Houston assistant professor, and Michelle Fingeret, a clinical psychologist and an assistant professor at The University of Texas MD Anderson Cancer Center, are in the process of collecting up to 500 surveys from breast cancer patients undergoing reconstructive surgery at MD Anderson. Responses from the surveys will eventually help researchers create complex algorithms that – similarly to how Netflix and Amazon can predict what movies or products a person will like based on his or her shopping history and interests – a doctor could recommend surgical procedures based on a patient's health history and desired physical appearance post-surgery.