Author: Dukagjin Blakaj, Zhilin Hu, Stephen Kang, Abberly Lott Limbach, Lanchun Lu, Henry Xiang, Jie Zhang 👨🔬
Affiliation: Pharostek, Department of Pediatrics, The Ohio State University, Department of Radiation Oncology, The Ohio State University Wexner Medical Center, Department of Radiology, University of Kentucky, Department of Pathology, The Ohio State University, Department of Radiation Oncology, The Ohio State University, Department of Otolaryngology, The Ohio State University 🌍
Purpose: Detect surgical margin in vivo using an original barcode-reading type portable OCT imaging system.
Methods: We developed a barcode-reading type portable optical coherence tomography (OCT) imaging device that is capable of acquiring real-time images that can be used in vivo by: (1) surgeons to assess intraoperative surgical margin to ensure comprehensive tumor resection or for radiation oncologists to prescribe prescriptions for intraoperative radiation therapy (IORT); (2) pathologists to diagnose skin cancer or other diseases; (3) radiation oncologists to examine/monitor skin reactions/damages during the course of radiation therapy for cancers of head/neck, skin, breast, etc.; and (4) basic science biomedical researchers to promptly examine and analyze skin ulcers, tissue structure changes, and experimental outcomes on a mouse or a small animal during radiation or other treatments. Using this ultra-high spatial resolution OCT imaging device (on the ~µm level), we performed IRB-approved clinical trials on the resected tissues from head and neck cancer patients immediately following surgery and assessed the surgical margin between cancerous and normal tissues. Using the OCT device, we scanned the regions of cancerous, normal, and the boundary that were labeled by the surgeon and the surgical pathologist and obtained the OCT images corresponding to these regions. We used AI to analyze OCT images to classify and identify normal tissue, cancerous tissue, and the boundary between them. The results from the AI analysis were then compared with those obtained from routine tissue staining and histological analysis.
Results: Our preliminary results indicate that OCT imaging can clearly differentiate cancerous tissues from normal tissues with the assistance of AI.
Conclusion: OCT imaging is a promising technique for real-time surgical margin detection in vivo in the operation room and AI is an effective method to assist the imaging analysis.