Significance: In neurosurgery, it is essential to differentiate between tumor and healthy brain regions to maximize tumor resection while minimizing damage to vital healthy brain tissue. However, conventional intraoperative imaging tools used to guide neurosurgery are often unable to distinguish tumor margins, particularly in infiltrative tumor regions and low-grade gliomas. Aim: The aim of this work is to assess the feasibility of a label-free molecular imaging tool called stimulated Raman scattering-spectroscopic optical coherence tomography (SRS-SOCT) to differentiate between healthy brain tissue and tumor based on (1) structural biomarkers derived from the decay rate of signals as a function of depth and (2) molecular biomarkers based on relative differences in lipid and protein composition extracted from the SRS signals. Approach: SRS-SOCT combines the molecular sensitivity of SRS (based on vibrational spectroscopy) with the spatial and spectral multiplexing capabilities of SOCT to enable fast, spatially and spectrally resolved molecular imaging. SRS-SOCT is applied to image a 9L gliosarcoma rat tumor model, a well-characterized model that recapitulates human high-grade gliomas, including high proliferative capability, high vascularization, and infiltration at the margin. Structural and biochemical signatures acquired from SRS-SOCT are extracted to identify healthy and tumor tissues. Results: Data show that SRS-SOCT provides light-scattering-based signatures that correlate with the presence of tumors, similar to conventional OCT. Further, nonlinear phase changes from the SRS interaction, as measured with SRS-SOCT, provide an additional measure to clearly separate tumor tissue from healthy brain regions. We also show that the nonlinear phase signals in SRS-SOCT provide a signal-to-noise advantage over the nonlinear amplitude signals for identifying tumors. Conclusions: SRS-SOCT can distinguish both spatial and spectral features that identify tumor regions in the 9L gliosarcoma rat model. This tool provides fast, label-free, nondestructive, and spatially resolved molecular information that, with future development, can potentially assist in identifying tumor margins in neurosurgery.

中文翻译：

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使用受激拉曼散射光谱光学相干断层扫描对 9L 胶质肉瘤大鼠模型中的脑肿瘤进行无标记检测

意义：在神经外科中，区分肿瘤和健康大脑区域至关重要，以最大限度地切除肿瘤，同时最大限度地减少对重要健康脑组织的损害。然而，用于指导神经外科手术的常规术中成像工具通常无法区分肿瘤边缘，尤其是在浸润性肿瘤区域和低级别胶质瘤中。目的：这项工作的目的是评估一种称为受激拉曼散射光谱光学相干断层扫描 (SRS-SOCT) 的无标记分子成像工具的可行性，该工具基于 (1) 衍生的结构生物标志物区分健康脑组织和肿瘤。从作为深度函数的信号衰减率和 (2) 基于从 SRS 信号中提取的脂质和蛋白质组成的相对差异的分子生物标志物。方法：SRS-SOCT 将 SRS（基于振动光谱）的分子灵敏度与 SOCT 的空间和光谱复用能力相结合，以实现快速、空间和光谱解析的分子成像。应用 SRS-SOCT 对 9L 胶质肉瘤大鼠肿瘤模型进行成像，这是一种表征良好的模型，可重现人类高级别胶质瘤，包括高增殖能力、高血管化和边缘浸润。提取从 SRS-SOCT 获得的结构和生化特征以识别健康和肿瘤组织。结果：数据显示，SRS-SOCT 提供了与肿瘤存在相关的基于光散射的特征，类似于传统的 OCT。此外，SRS 相互作用产生的非线性相位变化，如用 SRS-SOCT 测量的，提供一种额外的措施来清楚地将肿瘤组织与健康的大脑区域分开。我们还表明，SRS-SOCT 中的非线性相位信号在识别肿瘤方面提供了优于非线性幅度信号的信噪比优势。结论：SRS-SOCT 可以区分识别 9L 胶质肉瘤大鼠模型中肿瘤区域的空间和光谱特征。该工具提供快速、无标记、无损和空间解析的分子信息，随着未来的发展，这些信息可能有助于识别神经外科中的肿瘤边缘。SRS-SOCT 可以区分识别 9L 胶质肉瘤大鼠模型中肿瘤区域的空间和光谱特征。该工具提供快速、无标记、无损和空间解析的分子信息，随着未来的发展，这些信息可能有助于识别神经外科中的肿瘤边缘。SRS-SOCT 可以区分识别 9L 胶质肉瘤大鼠模型中肿瘤区域的空间和光谱特征。该工具提供快速、无标记、无损和空间解析的分子信息，随着未来的发展，这些信息可能有助于识别神经外科中的肿瘤边缘。