Optical Molecular Signatures of IDH Genotype for Classification of Human Glioma Using Visible Resonance Raman Spectroscopy - Zhang, Liang; Zhou, Yan; Wu, Binlin; Zhang, Shengjia; Zhu, Ke; Liu, C.; Alfano, Robert; Yu, Xinguang (Journal of Biophotonics, 2026)
Keywords: Biomarker; Gene; Genotype; Glioma; IDH mutation; IDH1; Isocitrate dehydrogenase; Mutation; Raman spectroscopy; Resonance Raman spectroscopy; dept.phy; glioma; optical molecular biopsy; visible resonance Raman spectroscopy

Human brain meningioma tumor detection using visible resonance Raman spectroscopy - Zhang, Liang; Zhou, Yan; Zhang, Shengjia; Wu, Binlin; Zhu, Ke; Liu, Cheng-hui; Yu, Xinguang; Alfano, Robert R. (Advanced biomedical and clinical diagnostic and surgical guidance systems XIX, 2021)
0 citations (Crossref) [2023-10-31]
Keywords: Brain; Brain neoplasms; Detection and diagnosis; Diagnosis; Healthy tissues; Margin status; Remote control; Resonance Raman; Resonance Raman spectroscopy; Surgery; Tumor boundary; Tumor detection; Tumors; dept.phy

Intraoperative detection of human meningioma using a handheld visible resonance Raman analyzer. - Zhang, Liang; Zhou, Yan; Wu, Binlin; Zhang, Shengjia; Zhu, Ke; Liu, Cheng-hui; Yu, Xinguang; Alfano, Robert R. (Lasers in medical science, 2021)
8 citations (Crossref) [2023-10-31] https://pubmed.ncbi.nlm.nih.gov/34365551/
Keywords: dept.phy; peer-reviewed

A handheld visible resonance raman analyzer used in intraoperative detection of human glioma - Zhang, Liang; Zhou, Yan; Wu, Binlin; Zhang, Shengjia; Zhu, Ke; Liu, Cheng-Hui; Yu, Xinguang; Alfano, Robert R. (Cancers, 2023)
There is still a lack of reliable intraoperative tools for glioma diagnosis and to guide the maximal safe resection of glioma. We report continuing work on the optical biopsy method to detect glioma grades and assess glioma boundaries intraoperatively using the VRR-LRRTM Raman analyzer, which is based on the visible resonance Raman spectroscopy (VRR) technique. A total of 2220 VRR spectra were collected during surgeries from 63 unprocessed fresh glioma tissues using the VRR-LRRTM Raman analyzer. After the VRR spectral analysis, we found differences in the native molecules in the fingerprint region and in the high-wavenumber region, and differences between normal (control) and different grades of glioma tissues. A principal component analysis–support vector machine (PCA-SVM) machine learning method was used to distinguish glioma tissues from normal tissues and different glioma grades. The accuracy in identifying glioma from normal tissue was over 80%, compared with the gold standard of histopathology reports of glioma. The VRR-LRRTM Raman analyzer may be a new label-free, real-time optical molecular pathology tool aiding in the intraoperative detection of glioma and identification of tumor boundaries, thus helping to guide maximal safe glioma removal and adjacent healthy tissue preservation.
0 citations (Crossref) [2023-10-31] Number: 6
Keywords: dept.phy; glioma; human brain; intraoperative; optical biopsy; optical molecular pathology; peer-reviewed; portable optical-fiber-probe Raman analyzer; visible resonance Raman (VRR)

Glioma tumors classified using visible resonance raman spectroscopy and machine learning - Wu, Binlin; Zhou, Yan; Zhang, Liang; Zhang, Shengjia; Yu, Xinguang; Wang, Eric; Zhu, Ke; Liu, Cheng-hui; Alfano, Robert R. (Frontiers in Optics, 2020)
Machine learning algorithms were used to classify and analyze spectral data collected by visible resonance Raman spectroscopy to distinguish normal human brain tissue and glioma tumor tissues at different grades and show promising results. © OSA 2020 © 2020 The Author(s)
0 citations (Crossref) [2023-10-31]
Keywords: dept.phy; ⛔ No DOI found

Human blood biomarkers for glioma and meningioma detection by a portable visible resonance Raman analyzer - Zhang, Liang; Zhou, Yan; Zhang, Shengjia; Wu, Binlin; Zhu, Ke; Zhang, Chunyuan; Liu, Cheng-hui; Yu, Xinguang; Alfano, Robert R. (Optical biopsy XIX: Toward real-time spectroscopic imaging and diagnosis, 2021)
Recent reports pointed out that 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. We report a preliminary investigation on the visible resonance Raman (VRR) spectra of human brain blood liquid collected from the scalp and around the meningeal tumor during surgery and a set of venous blood samples from healthy people and glioma grade III patients using a portable VRR-LRRTM, HR800, HR-Evolution and WITec300 Raman systems in vivo and ex vivo. The biochemical fingerprints and molecular biomarkers were found. These findings indicate that if VRR spectroscopy technology is combined with polymerase chain reaction (PCR) or genetic molecular biomarker methods (VRR-PCR), it will greatly increase the possibility for its clinical application. © 2021 SPIE.
1 citations (Crossref) [2023-10-31]
Keywords: Biomarkers; Biopsy; Blood; Clinical application; Healthy people; Molecular biomarker; Optical spectroscopy; Polymerase chain reaction; Raman systems; Resonance Raman; Spectroscopy; Spectroscopy technology; Tumors; Venous bloods; dept.phy

Human glioma tumors detection by a portable visible resonance Raman analyzer with a hand-held optical fiber probe - Zhou, Yan; Zhang, Shengjia; Wu, Binlin; Yu, Xinguang; Cheng, Gangge; Zhu, Ke; Zhao, Mingyue; Zheng, Jichun; Zhang, Liang; Zhang, Mingqian; Liang, Qijun; Go, Yun Ii; et al. (Biomedical Vibrational Spectroscopy 2020: Advances in Research and Industry, 2020)
Based on Visible Resonance Raman (VRR) method, we have developed a novel label-free portable VRR LRR2000 Raman analyzer with a portable fiber-optic probe and used it for the classification of human gliomas ex vivo and for the analysis of changes in tumor chemical compositions in molecular level. The purpose of this study was to examine the performance of the LRR2000 Raman analyzer as an optical biopsy tool for detecting human brain tumors compared to the commercial laboratory HR800 and WITec300 micro confocal Raman spectroscopy instruments. As of 2018, a total 1,938 VRR spectra were collected using LRR2000, HR800 and WITec300 Raman system, ex vivo. Identification of the four grades of glioma tumors and control tissues was performed based on the characteristic native molecular fingerprints. LRR2000 demonstrated consistent diagnostic results with HR800 and WITec300 Raman systems. LRR2000 showed the advantages of high speed, convenience and low cost compared to the two confocal micro Raman systems. Using artificial intelligence (AI)-based analysis of part of the data, the cross-validated accuracy for identifying glioma tumors is ~90% compared with gold standard histopathology examination.
3 citations (Crossref) [2023-10-31]
Keywords: Biopsy; Brain; Chemical analysis; Handhelds; Histology; Human brain; Industrial research; Molecular biology; Optical biopsies; Optical fibers; Optical molecular Pathology; Palmprint recognition; Principal component analysis; Principle component analysis; Probes; Resonance; Resonance Raman; Spectroscopy; Spectrum analysis; Support vector machines; Tissue engineering; Tumors; Vibrational spectroscopy; dept.phy; glioma tumor; handheld LRR2000 analyzer; human brain tissues; optical biopsy; principle component analysis(PCA); support vector machine (SVM); visible resonance Raman (VRR)