Intra-operative Detection of Positive Margins in Breast Surgery

In this project, we will develop a unique OCT-Raman system based on a selective sampling approach optimised for high-resolution analysis of whole lumpectomy specimens. The aim of using OCT is not to detect the cancer but to identify the adipose tissue, such that the large adipose tissue regions are excluded from any further measurements by Raman spectroscopy. While OCT has a limited ability to distinguish between tumour and surrounding normal stroma, adipose tissue has a distinctive appearance in the OCT images due to low backscattering within adipose cells (filled with lipids and small/flattened nuclei) compared to the highly scattering benign dense tissue (stroma, ducts and lobules) and malignant tissue. Such specific patterns allow identification of normal adipose tissue from breast tissue (classification models based on reflectivity profiles) with 94% sensitivity and 93% specificity. This will reduce the task of Raman measurements, which can be focused on the smaller remaining regions to discriminate between the benign and malignant tissue. This flexible and adaptable scanning strategy will achieve a much-improved diagnosis accuracy and speed to cover all surgical margins within practical timescales.