Sentinel Lymph Node Biopsy (SLNB) is an increasingly standard procedure to help oncologists accurately stage cancers.
It is performed as an alternative to full axillary lymph node dissection in breast cancer patients, reducing the risk of longterm
health problems associated with lymph node removal. Intraoperative analysis is currently performed using touchprint
cytology, which can introduce significant delay into the procedure. Spectral imaging is forming a multi-plane image
where reflected intensities from a number of spectral bands are recorded at each pixel in the spatial plane. We investigate
the possibility of using spectral imaging to assess sentinel lymph nodes of breast cancer patients with a view to
eventually developing an optical technique that could significantly reduce the time required to perform this procedure.
We investigate previously reported spectra of normal and metastatic tissue in the visible and near infrared region, using
them as the basis of dummy spectral images. We analyse these images using the spectral angle map (SAM), a tool
routinely used in other fields where spectral imaging is prevalent. We simulate random noise in these images in order to
determine whether the SAM can discriminate between normal and metastatic pixels as the quality of the images
deteriorates. We show that even in cases where noise levels are up to 20% of the maximum signal, the spectral angle
map can distinguish healthy pixels from metastatic. We believe that this makes spectral imaging a good candidate for
further study in the development of an optical SLNB.