Winner of the 1st Prize at the 2018 Engineering PhD Summit on Data Driven Engineering in the Life Sciences
Breast cancer is diagnosed via histopathology, a process that involves biopsy, tissue staining followed by manual examination by a pathologist. This is susceptible to under-diagnosis, over-diagnosis and low concordance rates across pathology labs. To overcome this, a combinatory and quantitative diagnostic approach utilizing imaging coupled to pattern recognition tools is developed for holistic patient analysis. The proposed approach integrates both the spatially resolved and quantitative information of biological samples. The major goal of this project is to establish the feasibility of mid-infrared (IR) chemical imaging technology for automated cellular identification, recognition of disease and characterization of both the tumor its microenvironment. This study provides rapid, objective and automated diagnostic and prognostic information. This will address the long recurring need of reducing pathologic inter-observer variability, thereby impacting surgical treatment and patient outcomes.
View Shachi’s winning presentation: