SEGMENTATION AND CORRELATION OF OPTICAL COHERENCE TOMOGRAPHY AND X-RAY IMAGES FOR BREAST CANCER DIAGNOSTICS.

Abstract

Pre-operative X-ray mammography and intraoperative X-ray specimen radiography are routinely used to identify breast cancer pathology. Recent advances in optical coherence tomography (OCT) have enabled its use for the intraoperative assessment of surgical margins during breast cancer surgery. While each modality offers distinct contrast of normal and pathological features, there is an essential need to correlate image-based features between the two modalities to take advantage of the diagnostic capabilities of each technique. We compare OCT to X-ray images of resected human breast tissue and correlate different tissue features between modalities for future use in real-time intraoperative OCT imaging. X-ray imaging (specimen radiography) is currently used during surgical breast cancer procedures to verify tumor margins, but cannot image tissue in situ. OCT has the potential to solve this problem by providing intraoperative imaging of the resected specimen as well as the in situ tumor cavity. OCT and micro-CT (X-ray) images are automatically segmented using different computational approaches, and quantitatively compared to determine the ability of these algorithms to automatically differentiate regions of adipose tissue from tumor. Furthermore, two-dimensional (2D) and three-dimensional (3D) results are compared. These correlations, combined with real-time intraoperative OCT, have the potential to identify possible regions of tumor within breast tissue which correlate to tumor regions identified previously on X-ray imaging (mammography or specimen radiography).