Department of Quantum Electronics, Faculty of Physics, Lomonosov Moscow State University, Moscow, Russia.
Department of Urology, Medical Research and Education Center, Lomonosov Moscow State University, Moscow, Russia.
Lasers Surg Med. 2024 Jul;56(5):496-507. doi: 10.1002/lsm.23788. Epub 2024 Apr 22.
The aim of this work is to assess the performance of multimodal spectroscopic approach combined with single core optical fiber for detection of bladder cancer during surgery in vivo.
Multimodal approach combines diffuse reflectance spectroscopy (DRS), fluorescence spectroscopy in the visible (405 nm excitation) and near-infrared (NIR) (690 nm excitation) ranges, and high-wavenumber Raman spectroscopy. All four spectroscopic methods were combined in a single setup. For 21 patients with suspected bladder cancer or during control cystoscopy optical spectra of bladder cancer, healthy bladder wall tissue and/or scars were measured. Classification of cancerous and healthy bladder tissue was performed using machine learning methods.
Statistically significant differences in relative total haemoglobin content, oxygenation, scattering, and visible fluorescence intensity were found between tumor and normal tissues. The combination of DRS and visible fluorescence spectroscopy allowed detecting cancerous tissue with sensitivity and specificity of 78% and 91%, respectively. The addition of features extracted from NIR fluorescence and Raman spectra did not improve the quality of classification.
This study demonstrates that multimodal spectroscopic approach allows increasing sensitivity and specificity of bladder cancer detection in vivo. The developed approach does not require special probes and can be used with single-core optical fibers applied for laser surgery.
本研究旨在评估结合单芯光纤的多模态光谱方法在术中检测膀胱癌的性能。
多模态方法结合漫反射光谱(DRS)、可见(405nm 激发)和近红外(NIR)(690nm 激发)荧光光谱以及高波数拉曼光谱。所有四种光谱方法均在单个设置中组合使用。对 21 名疑似膀胱癌患者或在对照膀胱镜检查期间,对膀胱癌、健康膀胱壁组织和/或瘢痕的光学光谱进行了测量。使用机器学习方法对癌组织和健康膀胱组织进行分类。
在肿瘤和正常组织之间发现相对总血红蛋白含量、氧合、散射和可见荧光强度存在统计学显著差异。DRS 和可见荧光光谱的组合可分别以 78%和 91%的灵敏度和特异性检测癌组织。从 NIR 荧光和拉曼光谱中提取特征的添加并未提高分类质量。
本研究表明,多模态光谱方法可提高体内膀胱癌检测的灵敏度和特异性。所开发的方法不需要特殊探头,可与用于激光手术的单芯光纤一起使用。