Combined spatial frequency spectroscopy analysis with visible resonance Raman for optical biopsy of human brain metastases of lung cancers

被引:12
作者
Zhou, Yan [1 ]
Liu, Cheng-Hui [2 ]
Pu, Yang [2 ]
Wu, Binlin [3 ,4 ]
Thien An Nguyen [2 ]
Cheng, Gangge [1 ]
Zhou, Lixin [5 ]
Zhu, Ke [6 ]
Chen, Jun [7 ]
Li, Qingbo [8 ]
Alfano, Robert R. [2 ]
机构
[1] PLA, Air Force Med Ctr, 30 Fuchenglu, Beijing 100142, Peoples R China
[2] CUNY City Coll, Dept Phys, Inst Ultrafast Spect & Lasers, New York, NY 10031 USA
[3] Southern Connecticut State Univ, Dept Phys, 501 Crescent St, New Haven, CT 06515 USA
[4] Southern Connecticut State Univ, CSCU Ctr Nanotechnol, 501 Crescent St, New Haven, CT 06515 USA
[5] Beijing Canc Hosp, 52 Fuchenglu, Beijing 100142, Peoples R China
[6] Chinese Acad Sci, Inst Phys, Beijing 100190, Peoples R China
[7] Tianjin Med Univ, Dept Cardiol, Gen Hosp, Tianjin 300052, Peoples R China
[8] Beihang Univ, Xueyuan Rd 37, Beijing 100191, Peoples R China
关键词
Spatial frequency spectroscopy analysis (SFSA); visible resonance Raman (VRR); human brain; metastatic lung cancer; photomicrograph image; support vector machine (SVM); BREAST-CANCER; FLUORESCENCE; TRYPTOPHAN; SPECTRA; TISSUE; TUMOR; ENHANCEMENT; CAROTENOIDS; KYNURENINE; PROGNOSIS;
D O I
10.1142/S179354581950010X
中图分类号
O43 [光学];
学科分类号
070207 ; 0803 ;
摘要
The purpose of this study is to examine optical spatial frequency spectroscopy analysis (SFSA) combined with visible resonance Raman (VRR) spectroscopic method, for the first time, to discriminate human brain metastases of lung cancers adenocarcinoma (ADC) and squamous cell carcinoma (SCC) from normal tissues. A total of 31 label-free micrographic images of three types of brain tissues were obtained using a confocal micro-Raman spectroscopic system. VRR spectra of the corresponding samples were synchronously collected using excitation wavelength of 532 nm from the same sites of the tissues. Using SFSA method, the difference in the randomness of spatial frequency structures in the micrograph images was analyzed using Gaussian function fitting. The standard deviations, sigma calculated from the spatial frequencies of the micrograph images were then analyzed using support vector machine (SVM) classifier. The key VRR biomolecular fingerprints of carotenoids, tryptophan, amide II, lipids and proteins (methylene/methyl groups) were also analyzed using SVM classifier. All three types of brain tissues were identified with high accuracy in the two approaches with high correlation. The results show that SFSA-VRR can potentially be a dual-modal method to provide new criteria for identifying the three types of human brain tissues, which are on-site, real-time and label-free and may improve the accuracy of brain biopsy.
引用
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页数:12
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