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

• Main Authors: Yan Zhou, Cheng-Hui Liu, Yang Pu, Binlin Wu, Thien An Nguyen, Gangge Cheng, Lixin Zhou, Ke Zhu, Jun Chen, Qingbo Li, Robert R. Alfano
• Format: Article
• Language: English
• Published: World Scientific Publishing 2019-03-01
• Series: Journal of Innovative Optical Health Sciences
• Subjects: Spatial frequency spectroscopy analysis (SFSA); visible resonance Raman (VRR); human brain; metastatic lung cancer; photomicrograph image; support vector machine (SVM)
• Online Access: http://www.worldscientific.com/doi/pdf/10.1142/S179354581950010X

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 532nm 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, σ 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.