Abstract：
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.
摘要：
心脏粘液瘤（CM）的症状主要发生在肿瘤生长时，诊断取决于临床表现。不幸的是,没有证据表明特定的血液检查对CM诊断有用.拉曼光谱（RS）已成为一种有前途的辅助诊断工具，因为它能够同时检测多个分子特征而无需标记。这项研究的目的是确定CM的光谱标记，最常见的良性心脏肿瘤之一，起病隐匿且进展迅速。在这项研究中,根据血清拉曼光谱进行初步分析，以获得CM患者（CM组）和健康对照组（正常组）之间的光谱差异。构建了主成分分析-线性判别分析（PCA-LDA），以根据获得的光谱信息突出显示各组间生化成分分布的差异。主成分分析与基于三个不同核函数（线性，多项式,和高斯径向基函数(RBF))来解决所有研究组之间的光谱变化。结果显示，CM患者血清苯丙氨酸和类胡萝卜素水平低于正常组，和增加的脂肪酸水平。所得拉曼数据用于多变量分析以确定可用于CM诊断的拉曼范围。此外，基于多变量曲线分辨率-交替最小二乘（MCR-ALS）方法，在讨论部分中进一步介绍了对获得的光谱结果的化学解释。这些结果表明，RS可以作为CM诊断的辅助和有希望的工具，指纹区域的振动可以用作所研究疾病的光谱标记。
