学术文献库

The initial detection and identification of suspicious lesions and the precise delineation of tumour mar-gins are essential for successful tumour resection, with progression-free survival linked to rates of complete resection. However, post-surgical positive margin rates remain high for many cancers and despite numerous advances in intraoperative imaging and diagnostic technologies, there exists no single modality that can adequately perform both tumoural detection and delineation. Here, we demonstrate a multimodal computer vision-based diagnostic system capable of both the gross detection and identification of suspicious lesions and the precise delineation of disease margins. We first show that through visual tracking of a spectroscopic probe, we enable real-time tumour margin delineation both for ex vivo human tumour biopsies and for an in vivo tumour xenograft mouse model. We then demonstrate that the combination of Raman spectroscopic diagnoses with protoporphyrin IX (PPIX) fluorescence imaging enables fluorescence-guided Raman spectroscopic margin delineation. Our fluorescence-guided Raman spectroscopic system achieves superior margin delineation accuracy to fluorescence imaging alone, demonstrating the potential for our system to achieve improved clinical outcomes for tumour resection surgeries.