Non-destructive diagnostic testing of cardiac myxoma by serum confocal Raman microspectroscopy combined with multivariate analysis

• Published in: Analytical methods Vol. 15; no. 21; pp. 2578 - 2587
• Main Authors: Chen, Qiang, Shi, Tao, Du, Dan, Wang, Bo, Zhao, Sha, Gao, Yang, Wang, Shuang, Zhang, Zhanqin
• Format: Journal Article
• Language: English
• Published: England Royal Society of Chemistry 01.06.2023
• Subjects: Algorithms; Diagnosis; Diagnostic Techniques and Procedures; Diagnostic tests; Discriminant Analysis; Fatty acids; Heart; Heart Neoplasms; Humans; Kernel functions; Labeling; Multivariate Analysis; Myxoma; Nondestructive testing; Phenylalanine; Polynomials; Principal components analysis; Radial basis function; Raman spectra; Raman spectroscopy; Respiratory Tract Neoplasms; Serum levels; Signs and symptoms; Spectrum analysis; Spectrum Analysis, Raman; Support vector machines; Tumors; Vibrations
• ISSN: 1759-9660; 1759-9679; 1759-9679
• DOI: 10.1039/d3ay00180f

The symptoms of cardiac myxoma (CM) mainly occur when the tumor is growing, and the diagnosis is determined by clinical presentation. Unfortunately, there is no evidence that specific blood tests are useful in CM diagnosis. Raman spectroscopy (RS) has emerged as a promising auxiliary diagnostic tool because of its ability to simultaneously detect multiple molecular features without labelling. The objective of this study was to identify spectral markers for CM, one of the most common benign cardiac tumors with insidious onset and rapid progression. In this study, a preliminary analysis was conducted based on serum Raman spectra to obtain the spectral differences between CM patients (CM group) and healthy control subjects (normal group). Principal component analysis-linear discriminant analysis (PCA-LDA) was constructed to highlight the differences in the distribution of biochemical components among the groups according to the obtained spectral information. Principal component analysis was combined with a support vector machine model (PCA-SVM) based on three different kernel functions (linear, polynomial, and Gaussian radial basis function (RBF)) to resolve spectral variations between all study groups. The results showed that CM patients had lower serum levels of phenylalanine and carotenoid than those in the normal group, and increased levels of fatty acids. The resulting Raman data was used in a multivariate analysis to determine the Raman range that could be used for CM diagnosis. Also, the chemical interpretation of the spectral results obtained is further presented in the discussion section based on the multivariate curve resolution-alternating least squares (MCR-ALS) method. These results suggest that RS can be used as an adjunct and promising tool for CM diagnosis, and that vibrations in the fingerprint region can be used as spectral markers for the disease under study. An adjunct and promising tool for cardiac myxoma diagnosis is performed by Raman spectroscopy analysis combined with multivariate algorithms.