Increasing the speed of tumour diagnosis during surgery with selective scanning Raman microscopy

One of the main challenges in cancer surgery is ensuring that all tumour cells are removed during surgery, while sparing as much healthy tissue as possible. Histopathology, the gold-standard technique for cancer diagnosis, is often impractical for intra-operative use because of the time-consuming tissue preparation procedures (sectioning and staining). Raman micro-spectroscopy is a powerful technique that can discriminate between tumours and healthy tissues with high accuracy, based entirely on intrinsic chemical differences. However, raster-scanning Raman micro-spectroscopy is a slow imaging technique that typically requires data acquisition times as long as several days for typical tissue samples obtained during surgery (1 × 1 cm2) – in particular when high signal-to-noise ratio spectra are required to ensure accurate diagnosis. In this paper we present two techniques based on selective sampling Raman micro-spectroscopy that can overcome these limitations. In selective sampling, information regarding the spatial features of the tissue, either measured by an alternative optical technique or estimated in real-time from the Raman spectra, can be used to drastically reduce the number of Raman spectra required for diagnosis. These sampling strategies allowed diagnosis of basal cell carcinoma in skin tissue samples excised during Mohs micrographic surgery faster than frozen section histopathology, and two orders of magnitude faster than previous techniques based on raster-scanning Raman microscopy. Further development of these techniques may help during cancer surgery by providing a fast and objective way for surgeons to ensure the complete removal of tumour cells while sparing as much healthy tissue as possible.