Correlation and Difference Between Raman Spectral Characteristic and Feature Evaluation for Leukocytes and Tumor Cells. Issue 12 (December 2021)

• Record Type: Journal Article
• Authors: Dai, Yixin; Li, Wenxue; Wang, Liu; Luo, Chuan; Huang, Qing; Pang, Lin
• Is Part Of: Applied spectroscopy. Volume 75:Issue 12(2021)
• Page Start: 1516
• Page End: 1525
• Publication Date: 2021-12
• Subjects: Correlation -- feature evaluation -- leukocytes -- Raman spectroscopy -- spectral characteristic -- tumor cells; Spectrum analysis -- Periodicals; 543.505
• DOI: 10.1177/00037028211050663
• Languages: English
• ISSNs: 0003-7028

Abstract

Tumor detection supported by Raman spectroscopy is becoming increasingly popular, yet the relevance of spectral variation and feature selection retains unclear. Here we determined the correlation and difference between spectral characteristic and feature evaluation for leukocytes and tumor cells. Some peaks were found to show noticeable spectral differences, and their intensity distributions were investigated, finding using log-normal distribution to describe Raman intensity pattern may be more appropriate. Further the importance of all Raman features was calculated, where some other peak features occupied the top status. By surveying the intensity variation and feature evaluation for those peaks, we concluded the peak with the highest importance does not correspond to the peak location with the most noticeable intensity difference in spectra. Moreover, the peak intensity ratio of I1517 /I719 associated with protein to nucleic acid level presented the maximum separation, thus, it can be recognized as a special indicator to develop an alternative cancer detection. It is inspiring to introduce advanced statistical models into bio-spectroscopic fields but those intrinsic spectral variations rather than classification performance should be valued. Our explorations can provide possibilities to reveal the essences within tumor carcinogenesis based on Raman spectroscopy, further overwhelming the obstacles during the translation into clinical applications. Graphical Abstract