Standalone ultrasound-based highly visualized volumetric spine imaging for surgical navigation - Xinben Hu; Tianjian Liu; Zhengyuan Zhang; Xuan Xiao; Lin Chen; Gao Wei; Yunjiang Wang; Keji Yang; Haoran Jin; Yongjian Zhu (Scientific Reports)
Abstract Current navigation systems employing intraoperative CT have been applied in spinal interventions for accurate and visualized guidance. The consequential issue of radiation doses and surgical workflow disruption spotlighted ultrasound (US) as an alternative imaging modality. However, the challenge of anatomy interpretation left US-based navigation inadequate in visualization, resulting in the necessity of registration of preoperative images. Here we report a standalone ultrasound image-guided system (SUIGS) leveraging a purpose-made network to automatically extract bone features and reconstruct them into highly visualized volumetric images for spinal navigation. We showed the SUIGS highly visualized the bone markers with an imaging accuracy of 1.19 ± 0.85 mm in scanning tests on human volunteers. Through extensive testing on data from hospitalized patients containing atypical cases (spinal deformity, obesity), we confirmed that SUIGS generalizes across different individuals with a 100% success rate in aligning with preoperative CT. Furthermore, SUIGS yielded comparable results to three-dimensional fluoroscopy guidance in intraoperative intraspinal tumor localization and reduced the procedure to 8 min. This study explored and broadened the clinical application of standalone US navigation by providing intraoperative high-visualized volumetric spinal imaging, which is expected to increase the likelihood of surgeons adopting it in practice to reduce the occurrence of wrong-site surgery.