Very soon the cytologists and pathologists would be able to diagnose cancer more accurately. This is possible with an automatic method which is based on vibrational micospectroscopy which can spot the presence of metastatic cancer cells without the need of undergoing staining and human input.
The research team has been led by Pro Max Diem who would support classical cytology (where visual examination is used to check the changes in the morphology of cells found from bodily fluids, exfoliation or thin needle biopsy) and classical pathology (its stained tissue sections are checked visually).
Diem, Professor of Chemistry and Chemical Biology at Northeastern University said, “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.”
The study has been sponsored by the National Cancer Institute (NCI) of the National Institutes of Health (NIH) and Prof Diem along with his team has applied quantifiable and quantitative ways to gauge cervical, urothelial or buccal exfoliated cells. When the diseases modified the chemical composition of the cell, the device is able to check the variations in cellular properties and don’t get stained.
“The method is entirely machine-based and computer-interpreted, and thus, reduces the workload in diagnostic laboratories,” added Diem. “It allows us to increase the overall accuracy and decrease the time required to render medical diagnoses.”
The researchers are also working on another grant from NCI, which are aiming an operating room-based device which will produce a diagnosis of breast cancer cells in the axillary lymph nodes within 15 minutes after the excision. The ultimate aim is to produce an instrumentation and software which can investigate lymph node sections in the operating room and can give surgeon prime diagnosis of the spread of the disease.
“We have identified three major milestones for this particular research,” said Diem. “We want to develop a rapid sample preparation methodology, refine the imaging instrumentation, and construct reliable databases and algorithms for the detection.”
Underlying the university’s importance on interdisciplinary research, Diem’s laboratory has also teamed up with the Center for Subsurface Sensing and Imaging Systems (CenSISS) at Northeastern University, which has made the professor one of the non- engineer members of the CenSISS group.