Conor C Horgan1,2,3, Mads S Bergholt1,2,3, May Zaw Thin4, Anika Nagelkerke1,2,3, Robert Kennedy5, Tammy L Kalber4, Daniel J Stuckey4, Molly M Stevens1,2,3. 1. Imperial College London, Department of Materials, London, United Kingdom. 2. Imperial College London, Department of Bioengineering, London, United Kingdom. 3. Imperial College London, Institute of Biomedical Engineering, London, United Kingdom. 4. University College London, Centre for Advanced Biomedical Imaging, London, United Kingdom. 5. King's College London, Guy's and St Thomas' NHS Foundation Trust, Oral/Head and Neck Pathology Labor, United Kingdom.
Abstract
SIGNIFICANCE: Tumor detection and margin delineation are essential for successful tumor resection. However, postsurgical positive margin rates remain high for many cancers. Raman spectroscopy has shown promise as a highly accurate clinical spectroscopic diagnostic modality, but its margin delineation capabilities are severely limited by the need for pointwise application. AIM: We aim to extend Raman spectroscopic diagnostics and develop a multimodal computer vision-based diagnostic system capable of both the detection and identification of suspicious lesions and the precise delineation of disease margins. APPROACH: We first apply visual tracking of a Raman spectroscopic probe to achieve real-time tumor margin delineation. We then combine this system with protoporphyrin IX fluorescence imaging to achieve fluorescence-guided Raman spectroscopic margin delineation. RESULTS: Our system enables real-time Raman spectroscopic tumor margin delineation for both ex vivo human tumor biopsies and an in vivo tumor xenograft mouse model. We then further demonstrate that the addition of protoporphyrin IX fluorescence imaging enables fluorescence-guided Raman spectroscopic margin delineation in a tissue phantom model. CONCLUSIONS: Our image-guided Raman spectroscopic probe-tracking system enables tumor margin delineation and is compatible with both white light and fluorescence image guidance, demonstrating the potential for our system to be developed toward clinical tumor resection surgeries.
SIGNIFICANCE: Tumor detection and margin delineation are essential for successful tumor resection. However, postsurgical positive margin rates remain high for many cancers. Raman spectroscopy has shown promise as a highly accurate clinical spectroscopic diagnostic modality, but its margin delineation capabilities are severely limited by the need for pointwise application. AIM: We aim to extend Raman spectroscopic diagnostics and develop a multimodal computer vision-based diagnostic system capable of both the detection and identification of suspicious lesions and the precise delineation of disease margins. APPROACH: We first apply visual tracking of a Raman spectroscopic probe to achieve real-time tumor margin delineation. We then combine this system with protoporphyrin IX fluorescence imaging to achieve fluorescence-guided Raman spectroscopic margin delineation. RESULTS: Our system enables real-time Raman spectroscopic tumor margin delineation for both ex vivo humantumor biopsies and an in vivo tumor xenograft mouse model. We then further demonstrate that the addition of protoporphyrin IX fluorescence imaging enables fluorescence-guided Raman spectroscopic margin delineation in a tissue phantom model. CONCLUSIONS: Our image-guided Raman spectroscopic probe-tracking system enables tumor margin delineation and is compatible with both white light and fluorescence image guidance, demonstrating the potential for our system to be developed toward clinical tumor resection surgeries.
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