Department of Otolaryngology, Massachusetts Eye and Ear, Harvard Medical School, Boston.
Division of Otolaryngology-Head and Neck Surgery, Brigham and Women's Hospital, Boston, Massachusetts.
JAMA Otolaryngol Head Neck Surg. 2024 Apr 1;150(4):318-326. doi: 10.1001/jamaoto.2024.0013.
Image guidance is an important adjunct for endoscopic sinus and skull base surgery. However, current systems require bulky external tracking equipment, and their use can interrupt efficient surgical workflow.
To evaluate a trackerless surgical navigation system using 3-dimensional (3D) endoscopy and simultaneous localization and mapping (SLAM) algorithms in the anterior skull base.
DESIGN, SETTING, AND PARTICIPANTS: This interventional deceased donor cohort study and retrospective clinical case study was conducted at a tertiary academic medical center with human deceased donor specimens and a patient with anterior skull base pathology.
Participants underwent endoscopic endonasal transsphenoidal dissection and surface model reconstruction from stereoscopic video with registration to volumetric models segmented from computed tomography (CT) and magnetic resonance imaging.
To assess the fidelity of surface model reconstruction and accuracy of surgical navigation and surface-CT model coregistration, 3 metrics were calculated: reconstruction error, registration error, and localization error.
In deceased donor models (n = 9), high-fidelity surface models of the posterior wall of the sphenoid sinus were reconstructed from stereoscopic video and coregistered to corresponding volumetric CT models. The mean (SD; range) reconstruction, registration, and localization errors were 0.60 (0.24; 0.36-0.93), 1.11 (0.49; 0.71-1.56) and 1.01 (0.17; 0.78-1.25) mm, respectively. In a clinical case study of a patient who underwent a 3D endoscopic endonasal transsphenoidal resection of a tubercular meningioma, a high-fidelity surface model of the posterior wall of the sphenoid was reconstructed from intraoperative stereoscopic video and coregistered to a volumetric preoperative fused CT magnetic resonance imaging model with a root-mean-square error of 1.38 mm.
The results of this study suggest that SLAM algorithm-based endoscopic endonasal surgery navigation is a novel, accurate, and trackerless approach to surgical navigation that uses 3D endoscopy and SLAM-based algorithms in lieu of conventional optical or electromagnetic tracking. While multiple challenges remain before clinical readiness, a SLAM algorithm-based endoscopic endonasal surgery navigation system has the potential to improve surgical efficiency, economy of motion, and safety.
图像引导是内镜鼻窦和颅底手术的重要辅助手段。然而，目前的系统需要庞大的外部跟踪设备，并且它们的使用可能会中断高效的手术流程。
评估一种无跟踪器的手术导航系统，该系统使用 3 维（3D）内窥镜和同时定位和映射（SLAM）算法在颅前底。
设计、设置和参与者：这是一项在三级学术医疗中心进行的介入性已故供体队列研究和回顾性临床病例研究，涉及已故供体标本和一名颅前底病理患者。
参与者接受了内镜经鼻蝶窦切开术，并从立体视频中进行表面模型重建，并与从计算机断层扫描（CT）和磁共振成像（MRI）分割的容积模型进行配准。
为了评估表面模型重建的保真度以及手术导航和表面-CT 模型配准的准确性，计算了 3 项指标：重建误差、注册误差和定位误差。
在已故供体模型（n=9）中，从立体视频中重建了蝶窦后壁的高精度表面模型，并与相应的容积 CT 模型进行了配准。重建、注册和定位误差的平均值（标准差；范围）分别为 0.60（0.24；0.36-0.93）、1.11（0.49；0.71-1.56）和 1.01（0.17；0.78-1.25）mm。在一名接受 3D 内镜经鼻蝶窦切除结核性脑膜瘤的临床病例研究中，从术中立体视频中重建了蝶窦后壁的高精度表面模型，并与容积术前融合 CT 磁共振成像模型进行了配准，均方根误差为 1.38mm。
这项研究的结果表明，基于 SLAM 算法的内镜经鼻手术导航是一种新颖、准确、无跟踪器的手术导航方法，它使用 3D 内窥镜和基于 SLAM 的算法代替传统的光学或电磁跟踪。虽然在临床准备之前还有许多挑战，但基于 SLAM 算法的内镜经鼻手术导航系统有可能提高手术效率、运动经济性和安全性。
