Characterization of brain tumor tissue with 1310 nm optical coherence tomography

The separation of tumorous brain tissue and healthy brain tissue is still a big challenge in the field of neurosurgery, especially when it comes to the detection of different infiltration grades of glioblastoma multiforme at the tumor border. On the basis of a recently created labelled OCT dataset of ex vivo glioblastoma multiforme tumor samples the detection of brain tumor tissue and the identification of zones with varying degrees of infiltration of tumor cells was investigated. The identification was based on the optical properties, which were extracted by an exponential fit function. The results showed that a separation of tumorous tissue and healthy white matter based on these optical properties is possible. A support vector machine was trained on the optical properties to separate tumor from healthy white matter tissue, which achieved a sensitivity of 91% and a specificity of 76% on an independent training dataset.