Endoscopic OCT for epidural anesthesia

Epidural anesthesia is a method used to ease the pain of the patients. It is widely used in delivery and many other surgeries. However, there is a failure rate of around 20% due to the lack of needle guidance. Sometimes the needle is punctured too much, leading to some severe complications. Optical coherence tomography (OCT) is a novel technique widely used in medical imaging. It can provide imaging results of subsurface tissue with very high resolution (~several micrometers) in real time. In order to help the epidural anesthesia guidance, we built an OCT endoscope system to help image and recognize the tissue type in front of the needle during the puncture. We fabricated a gradient-index (GRIN) rod lens in front of the OCT scanner to expand the imaging distance, and make it possible to image the inner tissue of samples. To mimic the whole puncture process of the practical surgery, porcine back bones were utilized in our experiments and we inserted our OCT endoscope into five different tissue types: fat; interspinous ligament; ligamentum flavum; epidural space and spinal cord. OCT images of these types were obtained. We then used deep-learning models to automatically classify the different tissue types. The dataset contains two folders: Epidural: fat, flavum, ligament and spinal cord tissues Epidural_new_class: epidural space category (or Empty category)