Image-guided surgery enables skilled physicians to perform difficult operations. But the images used for guidance are generally taken before surgery begins. How do surgeons account for changes that take place in tissue while the surgery is ongoing—changes brought on by the pressure of an instrument, a shift due to an incision or other factors?
That is the primary work of Michael Miga, director of Vanderbilt’s Biomedical Modeling Laboratory and associate professor of biomedical engineering. Miga and his colleagues produce computational modeling techniques that mimic these effects and are then used to compensate for tissue changes during surgery.
Miga’s computer modeling techniques so far have chiefly focused on brain, liver and kidney surgery. His lab is developing a novel computational framework that interacts with current operating room systems. It uses software and computer and measurement equipment to make calculations that modify the images for deformations during surgery.
This is important in brain operations, for example, as certain drugs shrink the brain during surgery, or when tissue is retracted during removal of a tumor. The computer modeling would cost-effectively augment the image-guided surgery techniques already in place and account for the tumor’s new location.
Miga says that unlike the brain, which is largely held in position by the skull, other organs are more flexible and can move during surgery.
Each organ has unique characteristics and different surgical approaches, requiring that the engineers apply separate research methods, new approaches to computation and different algorithmic design. Research done by Miga using laser-range scanning to capture the liver shape for image-guided liver surgery has already been incorporated into a new product that has received FDA approval. It is available in the marketplace and is being tested clinically (see Engineering Vanderbilt, spring 2009). Miga is currently focused on using the changes measured by the laser-range scanner to incorporate deformation correction into the product. It is expected to be the first of its kind available commercially.
Computer modeling also affects medical imaging. With breast cancer detection, current imaging modalities cannot document a tissue’s stiffness, an important biomarker of disease. Miga and his team are researching ways to use new noninvasive imaging methods to detect changes in tissue stiffness.
Using similar methods, but in a very different context, Miga also focuses on bone fractures. In this work, models and algorithms attempt to determine how well a fracture is healing by looking at the stiffness of the tissue at the fracture site.
“The common thread is that these are all mathematical model-based analysis approaches with a characterization, or interventional, aspect,” Miga says. “Strewn throughout each research project is the integration of computer models, soft tissue mechanics and analysis, with a central focus at translating the information to direct therapy or characterize tissue changes in an active way.”