Improvement of tissue analysis and classification using optical coherence tomography combined with Raman spectroscopy

Optical coherence tomography (OCT) is an optical imaging technique that is capable of performing high-resolution (approaching the histopathology level) and real-time imaging of tissues without use of contrast agents. Based on these advantages, the pathological features of tumors (in micro scale) can be identified during resection surgery. However, the accuracy of tumor margin prediction still needs to be enhanced for assisting the judgment of surgeons. In this regard, we present a two-dimensional computational method for advanced tissue analysis and characterization based on optical coherence tomography (OCT) and Raman spectroscopy (RS). The method combines the slope of OCT intensity signal and the Principal component (PC) of RS, and relies on the tissue optical attenuation and chemical ingredients for the classification of tissue types. Our pilot experiments were performed on mouse kidney, liver and small intestine. Results demonstrate the improvement of the tissue differentiation compared with the analysis only based on the OCT detection. This combined OCT/RS method is potentially useful as a novel optical biopsy technique for cancer detection.