System and method for cancer detection

Abstract

Nuclear Factor I/B (Nfib), a protein important to lung maturation in human embryos, is an oncogene in SCLC. This novel bioinformatics image-processing tool analyzes digital images of biopsies stained for Nfib. First, the model was trained to determine whether the biopsy was cancerous or not, then it was trained to predict the whether the biopsy represented limited stage SCLC or extensive stage SCLC. The factors considered were the amount of positive Nfib staining, amount of negative Nfib staining, amount of “non-tissue” areas on the slide, and the intensity of the staining itself. Overall this tool is highly accurate with 95.11% accuracy. Doctors can directly use this tool to accurately predict stage of SCLC in less than one minute. This system application can allow doctors to better guide their patients' treatments of SCLC.

1 . System and method to diagnose small cell lung cancer and the stage (limited vs. extensive) of that cancer. 
     
     
         2 . Similar procedures can be implemented to diagnose other cancers that express biomarkers in differing quantities between healthy and cancerous cells due to the functional roles of these biomarkers. This invention is a reliable method to diagnose cancers based off of biomarker-specific staining and thus, this method holds true as long as there is a qualitative difference in biomarker staining between the tissues that are healthy and those that are cancerous.