An important factor in fighting cancer is the speed at which the disease can be identified, diagnosed and treated.
The current standard involves a patient feeling ill or a physician seeing signs of a tumor. These indicators lead to more precise diagnoses via blood tests, x-rays or MRI imaging. But once the disease is far enough along to be noticeable, the cancer has often spread.
In the future, though, it may be possible to diagnose cancer much earlier using more sensitive body scans, new types of biomarker tests, and even nano-sensors working in the bloodstream.
Experimenting with these techniques in cancer patients or healthy individuals is difficult and potentially unethical. But scientists can test these technologies virtually using supercomputers to simulate the dynamics of cells and tissues.
BUILDING A BETTER BREAST CANCER EARLY DETECTION SYSTEM
Manual breast exams and mammograms are currently the most effective and widely used techniques for early detection of breast cancer. Unfortunately, manual breast exams are limited in their ability to detect tumors since they only produce local information about the site where the force is applied.
Mammograms (breast x-rays), on the other hand, are more accurate, but expose patients to radiation. Importantly, they do not quantify tissue stiffness, an identifying characteristic of breast tumors. They also produce many false positives, resulting in painful biopsies.
Lorraine Olson, a professor of mechanical engineering at Rose-Hulman Institute of Technology, is collaborating with colleagues Robert Throne of Electrical and Computer Engineering and Adam Nolte of Chemical Engineering to develop an electro-mechanical device that gently indents breast tissue in various locations and records the tissue surface deflections. This data is then converted into detailed 3-D maps of breast tissue stiffness, which can then be used to identify suspicious (stiffer) sites for further testing.
"The research takes an approach to early detection of breast cancer that utilizes a fundamental mechanical difference between cancerous and noncancerous tissue," Olson said. "Although this stiffness difference is the basis of manual breast exams, it has not been systematically investigated from an engineering point of view."
Olson and her team's approach to determining the relationship between stiffness and interior mapping involves a combination of finite element methods -- a numerical method for solving problems in engineering and mathematical physics -- and genetic algorithms -- a method for solving optimization problems based on natural selection.
