A bedside feasibility study with optical coherence tomography for real-time tumor-located of lung cancer

Background: Instant histological diagnosis is an important procedure during surgery for histology-unknown lung tumors. Through such a brief diagnosis, accurate decision-making excision of the target, especially in lung cancer, is crucial for the cure of the disease. There is still a limited advancement in this kind of microscopic diagnostic technology during these years.Methods: We design a spectral domain optical coherence tomography (SD-OCT) system and perform the real-time scanning of targeting tumor intraoperatively. The images got from this novel system are compared with the results by the frozen section and permanent pathological process. Characteristics and weaknesses of OCT-captured images for lung tumors are analyzed and presented.Results: A total of 6 ex vivo lung specimens from 3 patients, diagnosed with invasive adenocarcinoma (IA), were enrolled in this study. Depending on appropriate signal processing methods, the normal and cancerous regions showed different features of OCT images. This proposed optical method can provide an instant micrometer level scope of tissue images. By comparing OCT images of the cross-section and en-face, intensity clefs and dark stripes can be observed below the surface of the cancerous part. We inferred that these are very classic features of tumors. The corresponding regions can be identified on OCT-scanned images as well as those from the H&E stain results.Conclusions: From the results of this study, an optical imaging method by building an instantly on-site support through this novel modality was possible and feasible. Furthermore, we expect that future deep learning ability of OCT-captured images could be carried out to avoid time-consuming and resource-consuming status and improve current diagnostic efficiency.