使用增强现实系统对前哨淋巴结进行定位：一项尸体可行性研究。

Localization of sentinel lymph nodes using augmented-reality system: a cadaveric feasibility study.

作者信息

Duan Heying, Yang Yue, Niu Wally L, Anders David, Dreisbach Andrew M, Holley Dawn, Franc Benjamin L, Perkins Steffi L, Leuze Christoph, Daniel Bruce L, Baik Fred M

机构信息

Department of Radiology, Division of Nuclear Medicine and Molecular Imaging, Stanford University, 300 Pasteur Drive, H2200, Stanford, CA, 94305, USA.

Department of Radiology, Division of Body Imaging, Stanford University, 1201 Welch Road, Stanford, CA, 94305, USA.

出版信息

Eur J Nucl Med Mol Imaging. 2025 Mar 24. doi: 10.1007/s00259-025-07216-z.

DOI:10.1007/s00259-025-07216-z

PMID:40123008

Abstract

PURPOSE

Sentinel lymph node biopsy (SLNB) helps stage melanoma. Pre-surgical single-photon emission computed tomography/computed tomography (SPECT/CT) visualizes draining lymph nodes, but intraoperative gamma probe detection only estimates SLN location. This study evaluates augmented reality (AR) for projecting pre-surgical SLN imaging onto patients to aid precise localization and extraction.

METHODS

Molecular sieves (8 mm) incubated in fluorine-18 simulated lymph nodes and were implanted in the head and neck region of cadavers. Positron emission tomography/magnetic resonance imaging (PET/MRI) replaced SPECT/CT due to institutional restriction on cadavers. Virtual PET/MRI renderings were projected using the HoloLens 2 and custom software. Five cadavers underwent surgeries with standard, AR, and AR with head movement compensation methods.

RESULTS

AR achieved a mean surface localization error of 2.5±2.0 mm (range, 0-8 mm) and a depth error of 2.3±1.7 mm (range, 1-7 mm), both within PET voxel resolution. For more challenging level V nodes, the mean surface error slightly increased to 2.9 mm. Compared to manual surface marking, which had an average error of 18.6±13.0 mm (range, 6-62 mm), the AR system significantly reduced errors both in the head-straight and rotated positions (p <.001). Additionally, the AR system reduced the task completion time by 74% (35.1/47.4 s), with an average time of 12.3 s compared to 47.4 s for manual methods.

CONCLUSION

The AR system demonstrated high accuracy and efficiency in SLN localization, integrating head-movement compensation and 3D visualization to improve precision and reduce operating room time.

CLINICAL TRIAL NUMBER

Not applicable.

摘要

目的

前哨淋巴结活检（SLNB）有助于黑色素瘤分期。术前单光子发射计算机断层扫描/计算机断层扫描（SPECT/CT）可显示引流淋巴结，但术中γ探针检测只能估计前哨淋巴结位置。本研究评估增强现实（AR）技术，将术前前哨淋巴结成像投射到患者身上，以辅助精确定位和提取。

方法

将在氟-18模拟淋巴结中孵育的分子筛（8毫米）植入尸体的头颈部区域。由于机构对尸体的限制，正电子发射断层扫描/磁共振成像（PET/MRI）取代了SPECT/CT。使用HoloLens 2和定制软件投射虚拟PET/MRI渲染图。五具尸体接受了标准、AR以及带有头部运动补偿方法的AR手术。

结果

AR实现的平均表面定位误差为2.5±2.0毫米（范围为0 - 8毫米），深度误差为2.3±1.7毫米（范围为1 - 7毫米），均在PET体素分辨率范围内。对于更具挑战性的V级淋巴结，平均表面误差略有增加至2.9毫米。与平均误差为18.6±13.0毫米（范围为6 - 62毫米）的手动表面标记相比，AR系统在头部直立和旋转位置均显著降低了误差（p <.001）。此外，AR系统将任务完成时间减少了74%（35.1/47.4秒），平均时间为12.3秒，而手动方法为47.4秒。