School of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China.
School of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China.
Spectrochim Acta A Mol Biomol Spectrosc. 2021 Feb 15;247:119083. doi: 10.1016/j.saa.2020.119083. Epub 2020 Oct 17.
Echinococcosis is a zoonotic parasitic disease transmitted by animals and distributed all over the world. There is no standardized and widely accepted treatment method, and early and accurate diagnosis is crucial for the prevention and cure of echinococcosis. Here, we explored the feasibility of using derivative Raman in combination with autofluorescence (AF) to improve the diagnosis performance of echinococcosis. The spectra of serum samples from patients with echinococcosis, as well as healthy volunteers, were recorded at 633 nm excitation. The normalized mean Raman spectra showed that there is a decrease in the relative amounts of β carotene and phenylalanine and an increase in the percentage of tryptophan, tyrosine, and glutamic acid contents in the serum of echinococcosis patients as compared to that of healthy subjects. Then, principal components analysis (PCA), combined with linear discriminant analysis (LDA), were adopted to distinguish echinococcosis patients from healthy volunteers. Based on the area under the ROC curve (AUC) value, the derivative Raman + AF spectral data set achieved the optimal results. The AUC value was improved by 0.08 for derivative Raman + AF (AUC = 0.98), compared to Raman alone. The results demonstrated that the fusion of derivative Raman and AF could effectively improve the performance of the diagnostic model, and this technique has great application potential in the clinical screening of echinococcosis.
包虫病是一种动物源性寄生虫病，分布于世界各地。目前，尚无标准化且广泛接受的治疗方法，早期、准确的诊断对于包虫病的防治至关重要。在这里，我们探索了使用衍生拉曼与自发荧光（AF）相结合以提高包虫病诊断性能的可行性。对患有包虫病的患者以及健康志愿者的血清样本在 633nm 激发下记录其光谱。归一化平均拉曼光谱显示，与健康受试者相比，包虫病患者血清中β-胡萝卜素和苯丙氨酸的相对含量降低，色氨酸、酪氨酸和谷氨酸的含量百分比增加。然后，采用主成分分析（PCA）与线性判别分析（LDA）相结合的方法，将包虫病患者与健康志愿者区分开来。基于 ROC 曲线下面积（AUC）值，衍生拉曼+AF 光谱数据集取得了最佳结果。与单独使用拉曼相比，衍生拉曼+AF 的 AUC 值提高了 0.08（AUC=0.98）。结果表明，衍生拉曼与 AF 的融合可以有效提高诊断模型的性能，该技术在包虫病的临床筛查中具有很大的应用潜力。
