手术中实时更新CT影像，帮医生看清鼻窦切除的进展。
Virtual Intraoperative CT (viCT): Sequential Anatomic Updates for Modeling Tissue Resection Throughout Endoscopic Sinus Surgery
- 用单目内镜视频生成三维重建，逐步更新术前CT模型。
- 与真实解剖对比，表面误差小于0.32毫米，匹配度达88%。
- 无需额外设备，适合需要精准导航的鼻窦手术医生。
不完全切除是慢性鼻窦炎患者术后复发和二次手术的常见原因。现有术中导航系统多依赖静态术前CT（pCT），无法反映组织切除过程中的解剖变化。本文提出虚拟术中CT（viCT）方法，通过单目内镜视频结合深度监督的NeRF框架生成逐阶段的度量尺度三维重建，并在3D Slicer中基于解剖对应关系进行刚性配准，将重建结果体素化至pCT网格。利用射线追踪的体素占据比较，删除过时区域并重映保留结构与更新边界，实现动态解剖可视化。在4例尸体标本、4个手术阶段的可行性研究中，通过体积重叠率（DSC=0.88±0.05，Jaccard=0.79±0.07）和表面距离指标（HD95=0.69±0.28 mm，Chamfer=0.09±0.05 mm，MSD=0.11±0.05 mm，RMSD=0.32±0.10 mm）评估，viCT更新结果与真实CT高度一致。结论：viCT可在无需额外硬件条件下实现鼻窦手术中的实时解剖更新，未来将优化自动配准、临床验证及实时性能。
原文摘要 · Abstract (English)
Purpose: Incomplete dissection is a common cause of persistent disease and revision endoscopic sinus surgery (ESS) in chronic rhinosinusitis. Current image-guided surgery systems typically reference static preoperative CT (pCT), and do not model evolving resection boundaries. We present Virtual Intraoperative CT (viCT), a method for sequentially updating pCT throughout ESS using intraoperative 3D reconstructions from monocular endoscopic video to enable visualization of evolving anatomy in CT format. Methods: Monocular endoscopic video is processed using a depth-supervised NeRF framework with virtual stereo synthesis to generate metrically scaled 3D reconstructions at multiple surgical intervals. Reconstructions undergo rigid, landmark-based registration in 3D Slicer guided by anatomical correspondences, and are then voxelized into the pCT grid. viCT volumes were generated using a ray-based occupancy comparison between pCT and reconstruction to delete outdated voxels and remap preserved anatomy and updated boundaries. Performance is evaluated in a cadaveric feasibility study of four specimens across four ESS stages using volumetric overlap (DSC, Jaccard) and surface metrics (HD95, Chamfer, MSD, RMSD), and qualitative comparisons to ground-truth CT. Results: viCT updates show agreement with ground-truth anatomy across surgical stages, with submillimeter mean surface errors. Dice Similarity Coefficient (DSC) = 0.88 +/- 0.05 and Jaccard Index = 0.79 +/- 0.07, and Hausdorff Distance 95% (HD95) = 0.69 +/- 0.28 mm, Chamfer Distance = 0.09 +/- 0.05 mm, Mean Surface Distance (MSD) = 0.11 +/- 0.05 mm, and Root Mean Square Distance (RMSD) = 0.32 +/- 0.10 mm. Conclusion: viCT enables CT-format anatomic updating in an ESS setting without ancillary hardware. Future work will focus on fully automating registration, validation in live cases, and optimizing runtime for real-time deployment.
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