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全斯托克斯偏振激光诱导击穿光谱法检测浸润性胶质瘤边界组织

Full-Stokes polarization laser-induced breakdown spectroscopy detection of infiltrative glioma boundary tissue.

作者信息

Teng Geer, Wang Qianqian, Hao Qun, Fan Axin, Yang Haifeng, Xu Xiangjun, Chen Guoyan, Wei Kai, Zhao Zhifang, Khan M Nouman, Idrees Bushra Sana, Bao Mengyu, Luo Tianzhong, Zheng Yongyue, Lu Bingheng

机构信息

School of Optics and Photonics, Beijing Institute of Technology, Beijing, 100081, China.

Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, OX3 7LD, United Kingdom.

出版信息

Biomed Opt Express. 2023 Jun 20;14(7):3469-3490. doi: 10.1364/BOE.492983. eCollection 2023 Jul 1.

Abstract

The glioma boundary is difficult to identify during surgery due to the infiltrative characteristics of tumor cells. In order to ensure a full resection rate and increase the postoperative survival of patients, it is often necessary to make an expansion range resection, which may have harmful effects on the quality of the patient's survival. A full-Stokes laser-induced breakdown spectroscopy (FSLIBS) theory with a corresponding system is proposed to combine the elemental composition information and polarization information for glioma boundary detection. To verify the elemental content of brain tissues and provide an analytical basis, inductively coupled plasma mass spectrometry (ICP-MS) and LIBS are also applied to analyze the healthy, boundary, and glioma tissues. Totally, 42 fresh tissue samples are analyzed, and the Ca, Na, K elemental lines and CN, C molecular fragmental bands are proved to take an important role in the different tissue identification. The FSLIBS provides complete polarization information and elemental information than conventional LIBS elemental analysis. The Stokes parameter spectra can significantly reduce the under-fitting phenomenon of artificial intelligence identification models. Meanwhile, the FSLIBS spectral features within glioma samples are relatively more stable than boundary and healthy tissues. Other tissues may be affected obviously by individual differences in lesion positions and patients. In the future, the FSLIBS may be used for the precise identification of glioma boundaries based on polarization and elemental characterizing ability.

摘要

由于肿瘤细胞的浸润特性,胶质瘤边界在手术过程中难以识别。为了确保全切率并提高患者术后生存率,通常需要进行扩大范围切除,这可能会对患者的生存质量产生有害影响。提出了一种全斯托克斯激光诱导击穿光谱(FSLIBS)理论及相应系统,将元素组成信息和偏振信息结合用于胶质瘤边界检测。为了验证脑组织的元素含量并提供分析依据,还应用电感耦合等离子体质谱(ICP-MS)和激光诱导击穿光谱(LIBS)对健康组织、边界组织和胶质瘤组织进行分析。总共分析了42个新鲜组织样本,证明Ca、Na、K元素谱线以及CN、C分子碎片带在不同组织识别中起重要作用。与传统的LIBS元素分析相比,FSLIBS提供了完整的偏振信息和元素信息。斯托克斯参量光谱可以显著减少人工智能识别模型的欠拟合现象。同时,胶质瘤样本内的FSLIBS光谱特征比边界组织和健康组织相对更稳定。其他组织可能会受到病变位置和患者个体差异的明显影响。未来,FSLIBS可能基于偏振和元素表征能力用于胶质瘤边界的精确识别。

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