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Currently, liquid biopsy method is mainly used for tumor detection based on genomic molecular alterations in vitro. Liquid biopsy is superior to traditional tissue biopsy techniques and its diagnosis time of disease and repeated diagnosis of liquid biopsy are new breakthroughs in clinical application. Liquid biopsy method can be used to detect most human disease based on genetic biomarkers from body fluids, among which, special biomarkers in blood and cerebrospinal fluid (CSF) samples are the main research objects, and have made good achievements in preliminary clinical applications. The application of optical spectroscopy in the field of liquid biopsy has aroused great interest among researchers and demonstrated the potential of its clinical application for oncology. The aim of this study is to reveal the optical spectroscopic characteristics of the main biochemical components of CSF of brain tumor using visible resonance Raman (VRR) spectroscopy ex vivo. Tumor-associated proteins, glucose, lactate and other metabolites released to CSF can be used as markers for liquid biopsy. We studied the VRR spectra of CSF samples from 7 types of brain tumor patients. The characteristic VRR modes that were found and may be used as a combination of multiple analyte biomarkers include amyloid-β and tau protein, excess neurotransmitters such as glutamic acid derived from the exchange with interstitial fluid (ISF), DNA, glucose, lactate, etc. for optical liquid biopsy analyses. Another interesting finding was that CSF of different types of tumors showed different images similar to the crystallization of water under the optical microscope. Considering our previous study, the current study on CSF provides another proof that the VRR system can provide a complete scan region of 200 - 4000cm-1 as a clinical tool for non-invasive diagnosis of brain disease. © 2024 SPIE.
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Convolutional neural network (CNN) based deep learning is used to analyze spectral data collected by visible resonance Raman (VRR) spectroscopy to distinguish human glioma tumors from healthy brain tissues using binary classification and identify the cancer grades of the glioma tumors using multi-class classification. Classification was performed using both raw spectral data and baseline-subtracted data for comparison. The classification using both datasets yielded high accuracy, with the results obtained from baseline subtracted spectra slightly better than that obtained from raw spectra. The study showed VRR combined with deep learning provides a robust molecular diagnostic tool for accurately distinguishing glioma tumors from normal tissues and glioma tumor tissues at different cancer grades. Deep learning aided VRR technique may be used for in-situ intraoperative diagnosis of brain cancer. It may help a surgeon to identify cancer margins and even cancer grades during surgery. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.
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A VRR-LRR analyzer with handheld fiber‐optic probe is reported for the first time for diagnosis of brain GBM in vivo. The sensitivity for identification is 80% compared with histopathology examination. © OSA 2019. The Author(s).
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Laser-induced fluorescence (LIF) technique was used to generate spectral signatures of endogenous fluorophores relevant to the tissue molecular composition changes in human brain glioma tumors. The goal is to study the changes of fluorescence emission spectra from endogenous fluorophores in human brain glioma of different grades, and to find new biomarkers for prognostic optical molecular pathological diagnosis. Two hundred and thirty-seven (237) native fluorescence spectra from 61 subjects were measured using LabRAM HR Evolution micro photoluminescence (PL) system for four grades of glioma tumors in ex-vivo. The differences of four grades of glioma tumors were identified by the characteristic fluorophores fingerprints under the excitation laser wavelength at UV 325nm. To our best knowledge, this is the first report for human brain study using this technique. The fluorescence peaks of biomarkers with major contribution were found, including tryptophan, collagen, elastin, reduced nicotinamide adenine dinucleotide (NADH), flavin adenine dinucleotide (FAD) and phospholipids that play important roles in the cellular energy metabolism and glycolysis pathway. The ratios of peak intensities and the peak positions in fluorescence spectra of may be used to diagnose human brain diseases or to guide biopsy during surgical resection. © 2019 SPIE.
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