Texas Tech University researchers have recently developed a deep-learning system and microscope that quickly and accurately analyze cancer cells to determine their type and evaluate metastatic potential. By accurately classifying metastatic cancer cells, this innovation promises to be a major breakthrough in oncology and help medical practitioners predict progression of the disease and determine the best courses of treatment.
Typically, these analysis techniques would require advanced instruments and time-consuming techniques. The research team devised a less expensive and complicated process that does not require additional chemicals or biological solutions and only needs a single microscope and some computing power. The classification model boasts an accuracy higher than 94% and does not require labeling using chemical markers or nanoparticles.
In a workflow, images of the cells were obtained and fed into the neural network model. This model converted the data into a probability. When the probability was lower than 0.5, the cancer cell was categorized in one type and above that cutoff, it was classified as another.
Currently, the data set only covers single cancer cells, but the researchers are looking to broaden the model to include both single cells and cell clusters, as recent studies suggest that clustered cells may be more associated with cancer metastasis than single cells.
Wei Li, a co-author of the study and Associate Professor of Chemical Engineering at Texas Tech University expressed the importance of this research in that it enables the identification of cell subpopulations, which are crucial in finding ways to fight cancer metastasis.
Texas Tech University is a public research university located in Lubbock, Texas and is among one of the most prestigious research universities in the United States. The university hosts 11 colleges and schools, offers more than 150 undergraduate and postgraduate programs in fields ranging from business to humanities and offers a number of highly esteemed research centers.
Wei Li is a researcher and the Associate Professor of Chemical Engineering at Texas Tech University. She received her B.S. degree in Chemical Engineering from Harbin Institute of Technology, China and obtained her Ph.D. in Chemical and Petroleum Engineering from the University of Pittsburgh. She joined Texas Tech University in 2012 and her research focuses on complex fluids, soft matter, and cancer biology.
