Poster R7 - Epidural needle guidance using a forward-view polarization-sensitive optical coherence tomography probe

Introduction: Accurate guidance of the epidural needle is important for ensuring the safety and efficacy of epidural anesthesia. Within this study, we proposed an endoscopic system built on polarization-sensitive optical coherence tomography (PS-OCT). To evaluate its viability, we performed experiments on ex-vivo human epidural specimens. Throughout the experimental process, we captured and analyzed various layers of spinal tissue that the epidural needle goes through during the surgery, including subcutaneous fat, supraspinous ligament, interspinous ligament, ligamentum flavum, epidural space, dura, and the spinal cord. Each of these tissue layers had distinctive OCT imaging patterns. Furthermore, we employed deep learning techniques for automated tissue recognition.

Materials and

Methods: Epidural anesthesia is a widely utilized approach for pain relief during surgeries. The pivotal stage in this process is the precise and secure injection of anesthetic medications to the epidural space through a specialized needle. Inaccurate placement can result in failed anesthesia and potential harm to the spinal cord and surrounding tissues, leading to severe complications. Current needle-guidance techniques exhibit an up to 20% failure rate, underscoring the need for improved methodologies. In our earlier research, we introduced an optical coherence tomography (OCT) endoscope to assist in guiding the epidural needle. Nonetheless, accurately classifying distinct tissue types using structural OCT imaging alone remained an area for advancement. To address this limitation, we applied polarization-sensitive OCT (PS-OCT) to enhance the differentiation of spinal tissues. Notably, PS-OCT proves potential in discerning spinal structures such as ligaments and nerves, given their highly organized and directional micro-structures, leading to strong polarization contrast. For this project, we designed a specialized PS-OCT probe and conducted comprehensive evaluations on human epidural tissues.

Results, Conclusions, and Discussions: Utilizing the PS-OCT probe, we successfully imaged different spinal tissues, including subcutaneous fat, supraspinous ligament, interspinous ligament, ligamentum flavum, epidural space, dura, and the spinal cord. Our findings showed the superior tissue recognition achieved through PS-OCT in comparison to conventional intensity OCT. Furthermore, to optimize usability, we used deep learning methodologies for automated tissue identification. Leveraging the rich imaging data provided by PS-OCT, our deep learning models exhibited heightened precision in recognizing diverse tissue types.

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