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对NousNav进行基准测试:量化一种经济实惠的开源神经导航系统的空间准确性和临床性能。

Benchmarking NousNav: quantifying the spatial accuracy and clinical performance of an affordable, open-source neuronavigation system.

作者信息

Barr Colton, Galvin Colin, Juvekar Parikshit, Torio Erickson, Horvath Samantha, Sadler Samantha, Li Annie, Bardsley Ryan, Kapur Tina, Pieper Steve, Pujol Sonia, Frisken Sarah, Fichtinger Gabor, Golby Alexandra

机构信息

Brigham and Women's Hospital, Boston, MA, USA.

Harvard Medical School, Boston, MA, USA.

出版信息

Int J Comput Assist Radiol Surg. 2025 Aug 15. doi: 10.1007/s11548-025-03494-y.

Abstract

PURPOSE

NousNav is a low-cost, open-source neuronavigation platform built to address the high costs and resource limitations that hinder access to advanced neurosurgical technologies in low-resource settings. The low-cost and accessibility of the system is made possible using consumer-grade optical tracking and open-source software packages. This study aims to assess the performance of these core enabling technologies by quantifying their spatial accuracy and comparing it to a commercial gold standard.

METHODS

A series of experiments were conducted to evaluate the capabilities of the selected hardware and registration infrastructure utilized in NousNav. Each component was tested both in a simulated bench-top environment and clinically across four brain tumor resection cases.

RESULTS

The Optitrack Duo tracker used by NousNav was found to have a mean localization error of 0.8mm (SD 0.4mm). In bench-top phantom testing, NousNav had an average target registration error of 5.0mm (SD 2.3mm) following patient registration. Clinical evaluations revealed a mean distance of 4.2mm (SD 1.5mm) between points reported by NousNav versus those obtained using a commercial neuronavigation system.

CONCLUSION

These experiments highlight the role of baseline camera tracking performance, tracked instrument calibration, and patient positioning on the spatial performance of NousNav. They also provide an essential benchmark assessment of the system to help inform future clinical use-cases and direct ongoing system development.

摘要

目的

NousNav是一个低成本的开源神经导航平台,旨在解决在资源匮乏地区阻碍获得先进神经外科技术的高成本和资源限制问题。该系统的低成本和可及性通过使用消费级光学跟踪和开源软件包得以实现。本研究旨在通过量化其空间精度并将其与商业金标准进行比较,来评估这些核心支撑技术的性能。

方法

进行了一系列实验,以评估NousNav中所选硬件和配准基础设施的能力。每个组件都在模拟台式环境和临床上针对四个脑肿瘤切除病例进行了测试。

结果

发现NousNav使用的Optitrack Duo跟踪器的平均定位误差为0.8毫米(标准差0.4毫米)。在台式体模测试中,患者配准后NousNav的平均目标配准误差为5.0毫米(标准差2.3毫米)。临床评估显示,NousNav报告的点与使用商业神经导航系统获得的点之间的平均距离为4.2毫米(标准差1.5毫米)。

结论

这些实验突出了基线相机跟踪性能、跟踪仪器校准和患者定位对NousNav空间性能的作用。它们还为该系统提供了一项重要的基准评估,以帮助指导未来的临床用例并指导正在进行的系统开发。

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