Correlation mapping: rapid method for identification of histological features and pathological classification in mid infrared spectroscopic images of lymph nodes.

In this work, a novel technique for rapid image analysis of Fourier transform infrared (FTIR) data obtained from human lymph nodes is explored. It uses the mathematical principle of orthogonality as a method to quickly and efficiently obtain tissue and pathology information from a spectral image cube. It requires less computational power and time compared to most forms of cluster analysis. The values obtained from different tissue and pathology types allows for discrimination of noncancerous from cancerous lymph nodes. It involves the calculation of the dot product between reference spectra and individual spectra from across the tissue image. These provide a measure of the correlation between individual spectra and the reference spectra, and each spectrum or pixel in the image is given a color representing the reference most closely correlating with it. The correlation maps are validated with the tissue and pathology features identified by an expert pathologist from corresponding hematoxylin and eosin stained tissue sections. Although this novel technique requires further study to properly test and validate this tool, with inclusion of more lymph node hyperspectral datasets (containing a greater variety of tissue states), it demonstrates significant clinical potential for pathology diagnosis.