Maximal safe surgical resection is a foundational principle in brain tumor surgery. To date, many intraoperative modalities have been developed to help facilitate the identification of brain tumor versus normal brain tissue so that surgical resection is maximized but limited to the boundaries of the tumor for preservation of neurological function. Of note, Raman spectroscopy has been adapted into one of these modalities because of its ability to provide rapid, non-destructive, label-free intraoperative evaluation of tumor borders and molecular classifications and help guide surgical decision-making in real time. In this review, we performed a literature review of the landmark studies incorporating Raman spectroscopy into neurosurgical care to highlight its current applications and limitations. In this modern day, Raman spectroscopy is able to detect tumor cells intraoperatively for primary glial neoplasms, meningiomas, and brain metastases with greater than 90% accuracy. For glioma surgery, a major recent advancement is the ability to detect different mutations intraoperatively, specifically IDH, 1p19q co-deletion, and ATRX, given their implications on survival and how much extent of resection should be ideally achieved. With recent advancements in artificial intelligence and their integration into stimulated Raman histology, many of these tasks can be completed in as fast as ~10 s and on average 2–3 min. Despite the incorporation of artificial intelligence, spectral data can still be heavily influenced by background noise, and its preprocessing has significant variability across platforms, which can impact the accuracy of results. Overall, Raman spectroscopy has significantly changed the intraoperative workflow of brain tumor surgery, and this review highlights the capabilities that neurosurgeons can currently take advantage of in their practice, the existing data to support it, and the areas that researchers can further optimize to improve accuracy and patient outcomes.
最大限度安全切除是脑肿瘤手术的基本原则。迄今为止，已开发出多种术中辅助技术，以帮助区分脑肿瘤与正常脑组织，从而实现最大化切除肿瘤的同时，将其限制在肿瘤边界内以保护神经功能。值得注意的是，拉曼光谱技术因其能够快速、无损、无标记地进行术中肿瘤边界评估和分子分型，并实时指导手术决策，已成为这些技术之一。本文通过文献综述，重点回顾了将拉曼光谱技术应用于神经外科护理的标志性研究，以突出其当前应用及局限性。目前，拉曼光谱技术能够在术中检测原发性胶质瘤、脑膜瘤和脑转移瘤的肿瘤细胞，准确率超过90%。对于胶质瘤手术，近年来的一个重要进展是能够在术中检测不同突变，特别是IDH、1p19q共缺失和ATRX突变，这些突变对患者生存期及理想切除范围具有重要影响。随着人工智能的最新进展及其与受激拉曼组织学的结合，许多此类任务可在约10秒至平均2-3分钟内完成。尽管结合了人工智能，光谱数据仍可能受到背景噪声的严重影响，且其预处理在不同平台间存在显著差异，这可能影响结果的准确性。总体而言，拉曼光谱技术已显著改变了脑肿瘤手术的术中工作流程，本综述重点介绍了神经外科医生目前在临床实践中可利用的技术能力、支持该技术应用的现有数据，以及研究人员可进一步优化以提高准确性和改善患者预后的领域。
The Intraoperative Utility of Raman Spectroscopy for Neurosurgical Oncology
肿瘤(癌症)患者之家