While research shows that removal of cancerous tumors is most successful when surgeons remove a layer of healthy tissue around tumors, it can be difficult to know where healthy tissue begins. Fluorescent molecules that “light up” cancer cells that remain during tumor resection, but this does not provide information on the depth of cancer cells, and the needed equipment for the method is large and expensive and, therefore, not accessible in many medical facilities.
A research team from Washington University of Medicine in St. Louis, Missouri, led by Dr. Christine M. O’Brien, developed a solution to these challenges—an imaging system that both uses fluorescent molecules to determine tumor cell depth and is inexpensive and portable. The results offer great potential for better accuracy in future tumor removal as well as availability to low-resource medical centers.
“Multiple research groups have contributed to the development of mathematical relationships that link fluorophore depth to ratiometric fluorescence measurements,” said O’Brien. “Our group built upon prior work in this field to develop a low-cost, simple system that can quickly determine the depth of tumor cells using probes.
“The surge of near-infrared contrast agents being developed for use in medicine encouraged us to build upon prior work and to create a system that works in the near-infrared and that is also low-cost and simple to use.”
Her team developed the new system by using two different near-infrared (NIR) fluorescent wavelengths to excite a single fluorescent dye during tumor resection. The wavelengths penetrate different depths in the tissue, which allows detection of cancer cells 1-2 cm below the surface, and the different light wavelengths of the two allow comparison that helps predict tumor depth. O’Brien’s team first tested the system on layered synthetic materials and slices of chicken before testing breast tumors grown in mice. The imaging takes only five minutes but has an average error of only 0.34 mm.
The researchers see potential not only in the success rate of cancerous cell removal during resection, but also note the potential for eliminating the long wait for pathology results on the success of tumor removal. They are continuing to develop improve upon the system and currently are working to speed data processing and add more automation.