COLUMBUS, Ohio -- An Ohio State University mathematician and his colleagues are finding ways to tell the difference between healthy cells and abnormal cells, such as cancer cells, based on the way the cells look and move.
They are creating mathematical equations that describe the shape and motion of single cells for laboratory analysis.
Though this research is in its early stages, it represents an entirely new way of identifying cell abnormalities, including cancer. It could one day be useful in gauging future stages of a disease -- for example, by detecting whether cancer cells are aggressive and likely to spread throughout the body, or metastasize.
In a paper published online in the Bulletin of Mathematical Biology, researchers describe a mathematical model which analyzes image sequences of single, live cells to determine abnormalities manifested in their shape and behavior. A brain tumor cell was one of the cell types they analyzed in the study.
Huseyin Coskun, visiting assistant professor of mathematics at Ohio State and leader of the project, described their novel approach as a first step toward developing mathematical tools for diagnosing cell abnormalities and for giving potential prognoses.
Because the technique would allow doctors to view how cancer cells behave under different physical or chemical conditions, it could also be used to test different treatment strategies for each individual patient -- such as determining the most efficient dose of chemotherapeutic agents or radiation -- or even to test entirely new treatments.
In addition, Coskun sees his technique as a tool for also pathologists, who typically look at photographs of biopsied cells to identify cancer and judge how advanced the cancer may be.
"A pathologist can diagnose cancer, but as far as predicting the future, they don't have many tools at their disposal -- particularly if a cancer is in its early stages," Cos
|Contact: Huseyin Coskun|
Ohio State University