Washington, May 11 : Cancer diagnosis will soon become more accurate and less straining for cytologists and pathologists, thanks to researchers who have developed an automatic method based on vibrational microspectroscopy that identifies the presence of metastatic cancer cells without the need for staining and human input.
Research team led by Professor Max Diem will support classical cytology (where visually inspection is used to detect changes in the morphology of cells obtained from bodily fluids, exfoliation or thin needle biopsy) and classical pathology (where stained tissue sections are examined visually).
"The idea behind the methodology is to examine the chemical composition of cells, as opposed to relying solely on the morphology. Abnormalities in exfoliated cells, for instance in Pap smears, can be difficult to discern visually, however, by looking at the biochemical composition of the cell with the help of vibrational spectroscopy, we can detect specific cellular changes indicating cancer," said Diem, Professor of Chemistry and Chemical Biology at Northeastern University.
This novel method makes use of a quantifiable and quantitative approach to measure cervical, urothelial or buccal exfoliated cells. With the disease changing the chemical composition of the cell, the instrument is able to detect variations in cellular properties without the need to stain the slides and inspect them visually.
"The method is entirely machine-based and computer-interpreted, and thus, reduces the workload in diagnostic laboratories. It allows us to increase the overall accuracy and decrease the time required to render medical diagnoses," added Diem.
In another study, researchers are developing an operating room-based instrument that will produce a diagnosis of breast cancer cells in the axillary lymph nodes within 15 minutes after excision. They are aiming to produce instrumentation and software that can analyze lymph node sections in the operating room, and provide the surgeon with an objective diagnosis of the spread of disease.
"We have identified three major milestones for this particular research. We want to develop a rapid sample preparation methodology, refine the imaging instrumentation, and construct reliable databases and algorithms for the detection," said Diem.