Reichert David, Wadiura Lisa I, Erkkilae Mikael T, Gesperger Johanna, Lang Alexandra, Roetzer-Pejrimovsky Thomas, Makolli Jessica, Woehrer Adelheid, Wilzbach Marco, Hauger Christoph, Kiesel Barbara, Andreana Marco, Unterhuber Angelika, Drexler Wolfgang, Widhalm Georg, Leitgeb Rainer A
Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Vienna, Austria.
Christian Doppler Laboratory for Innovative Optical Imaging and its Translation to Medicine (OPTRAMED), Medical University of Vienna, Vienna, Austria.
Front Oncol. 2023 Feb 20;13:1105648. doi: 10.3389/fonc.2023.1105648. eCollection 2023.
Modern techniques for improved tumor visualization have the aim to maximize the extent of resection during brain tumor surgery and thus improve patient prognosis. Optical imaging of autofluorescence is a powerful and non-invasive tool to monitor metabolic changes and transformation in brain tumors. Cellular redox ratios can be retrieved from fluorescence emitted by the coenzymes reduced nicotinamide adenine dinucleotide (phosphate) (NAD(P)H) and flavin adenine dinucleotide (FAD). Recent studies point out that the influence of flavin mononucleotide (FMN) has been underestimated.
Fluorescence lifetime imaging and fluorescence spectroscopy were performed through a modified surgical microscope. We acquired 361 flavin fluorescence lifetime (500-580 nm) and fluorescence spectra (430-740 nm) data points on freshly excised different brain tumors: low-grade gliomas (N=17), high-grade gliomas (N=42), meningiomas (N=23), metastases (N=26) and specimens from the non-tumorous brain (N=3).
Protein-bound FMN fluorescence in brain tumors did increase with a shift toward a more glycolytic metabolism (). This increased the average flavin fluorescence lifetime in tumor entities with respect to the non-tumorous brain. Further, these metrics were characteristic for the different tumor entities and showed promise for machine learning based brain tumor classification.
Our results shed light on FMN fluorescence in metabolic imaging and outline the potential for supporting the neurosurgeon in visualizing and classifying brain tumor tissue during surgery.
现代用于改善肿瘤可视化的技术旨在在脑肿瘤手术期间最大化切除范围,从而改善患者预后。自发荧光光学成像是一种强大的非侵入性工具,可用于监测脑肿瘤中的代谢变化和转变。细胞氧化还原比率可从辅酶还原型烟酰胺腺嘌呤二核苷酸(磷酸)(NAD(P)H)和黄素腺嘌呤二核苷酸(FAD)发出的荧光中获取。最近的研究指出,黄素单核苷酸(FMN)的影响一直被低估。
通过改良的手术显微镜进行荧光寿命成像和荧光光谱分析。我们在新鲜切除的不同脑肿瘤上获取了361个黄素荧光寿命(500 - 580 nm)和荧光光谱(430 - 740 nm)数据点:低级别胶质瘤(N = 17)、高级别胶质瘤(N = 42)、脑膜瘤(N = 23)、转移瘤(N = 26)以及非肿瘤性脑标本(N = 3)。
脑肿瘤中与蛋白质结合的FMN荧光确实随着向更糖酵解代谢的转变而增加()。这使得肿瘤实体中的黄素平均荧光寿命相对于非肿瘤性脑有所增加。此外,这些指标对于不同的肿瘤实体具有特征性,并且显示出基于机器学习的脑肿瘤分类的潜力。
我们的结果揭示了代谢成像中FMN荧光的情况,并概述了在手术期间支持神经外科医生可视化和分类脑肿瘤组织的潜力。