Purpose

A real-time intra-operative imaging modality is required to update the navigation systems during neurosurgery, since precise localization and safe maximal resection of gliomas are of utmost clinical importance. Different intra-operative imaging modalities have been proposed to delineate the resection borders, each with advantages and disadvantages. This preliminary study was designed to simulate the photoacoustic imaging (PAI) to illustrate the brain tumor margin vessels for safe maximal resection of glioma.

Methods

In this study, light emitting diode (LED)-based PAI was selected because of its lower cost, compact size and ease of use. We developed a simulation framework based on multi-wavelength LED-based PAI to further facilitate PAI during neurosurgery. This framework considers a multilayer model of the tumoral and normal brain tissue. The simulation of the optical fluence and absorption map in tissue at different depths was computed by Monte Carlo. Then, the propagation of initial photoacoustic pressure was simulated by using k-wave toolbox.

Results

To evaluate the LED-based PAI, we used three evaluation criteria: signal-to-noise ratio (SNR), contrast ratio (CR) and full width of half maximum (FWHM). Results showed that by using proper wavelengths, the vessels were recovered with the same axial and lateral FWHM. Furthermore, by increasing the wavelength from 532 to 1064 nm, SNR and CR were increased in the deep region. The results showed that vessels with larger diameters at same wavelength have a higher CR with average improvement 28%.

Conclusion

Multi-wavelength LED-based PAI provides detailed images of the blood vessels which are crucial for detection of the residual glioma: The longer wavelengths like 1064 nm can be used for the deeper tumor margins, and the shorter wavelengths like 532 nm for tumor margins closer to the surface. LED-based PAI may be considered as a promising intra-operative imaging modality to delineate tumor margins.

中文翻译：

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基于多波长LED的光声成像评估可最大程度地安全切除神经胶质瘤：概念验证。

目的

由于神经胶质瘤的精确定位和最大安全切除在临床上至关重要，因此在神经外科手术期间需要实时术中成像方式来更新导航系统。已经提出了不同的术中成像方式来描述切除边界，每种边界都有优点和缺点。这项初步研究旨在模拟光声成像（PAI），以说明脑肿瘤边缘血管对神经胶质瘤的安全最大切除。

方法

在这项研究中，选择了基于发光二极管（LED）的PAI，因为其成本较低，尺寸紧凑且易于使用。我们开发了基于基于多波长LED的PAI的仿真框架，以进一步促进神经外科手术期间的PAI。该框架考虑了肿瘤和正常脑组织的多层模型。蒙特卡罗计算了不同深度组织中的光通量和吸收图。然后，使用k波工具箱模拟了初始光声压力的传播。

结果

为了评估基于LED的PAI，我们使用了三个评估标准：信噪比（SNR），对比度（CR）和半高全宽（FWHM）。结果表明，通过使用适当的波长，可以用相同的轴向和横向FWHM恢复血管。此外，通过将波长从532 nm增加到1064 nm，深区的SNR和CR得以提高。结果表明，在相同波长下直径较大的血管具有较高的CR，平均改善率为28％。

结论

基于多波长LED的PAI可提供对残留神经胶质瘤的检测至关重要的详细血管图像：较长的波长（如1064 nm）可用于更深的肿瘤边缘，而较短的波长（如532 nm）可用于更近的肿瘤边缘。到表面。基于LED的PAI可以被视为有希望的术中影像学方法，以描绘肿瘤的边缘。