A grid matrix-based Raman spectroscopic method to characterize different cell milieu in biopsied axillary sentinel lymph nodes of breast cancer patients. Issue 1 (January 2016)

• Record Type: Journal Article
• Authors: Som, Dipasree; Tak, Megha; Setia, Mohit; Patil, Asawari; Sengupta, Amit; Chilakapati, C.; Srivastava, Anurag; Parmar, Vani; Nair, Nita; Sarin, Rajiv; Badwe, R.
• Is Part Of: Lasers in medical science. Volume 31:Issue 1(2016)
• Page Start: 95
• Page End: 111
• Publication Date: 2016-01
• Subjects: Axillary lymph node -- Raman spectroscopy -- Grid matrix -- Histopathology -- Cross-correlation -- Peak-to-peak ratio; Lasers in medicine -- Periodicals; 610.28
• DOI: 10.1007/s10103-015-1830-6
• Languages: English
• ISSNs: 0268-8921

Abstract

Abstract Raman spectroscopy which is based upon inelastic scattering of photons has a potential to emerge as a noninvasive bedside in vivo or ex vivo molecular diagnostic tool. There is a need to improve the sensitivity and predictability of Raman spectroscopy. We developed a grid matrix-based tissue mapping protocol to acquire cellular-specific spectra that also involved digital microscopy for localizing malignant and lymphocytic cells in sentinel lymph node biopsy sample. Biosignals acquired from specific cellular milieu were subjected to an advanced supervised analytical method, i.e., cross-correlation and peak-to-peak ratio in addition to PCA and PC-LDA. We observed decreased spectral intensity as well as shift in the spectral peaks of amides and lipid bands in the completely metastatic (cancer cells) lymph nodes with high cellular density. Spectral library of normal lymphocytes and metastatic cancer cells created using the cellular specific mapping technique can be utilized to create an automated smart diagnostic tool for bench side screening of sampled lymph nodes. Spectral library of normal lymphocytes and metastatic cancer cells created using the cellular specific mapping technique can be utilized to develop an automated smart diagnostic tool for bench side screening of sampled lymph nodes supported by ongoing global research in developing better technology and signal and big data processing algorithms.