Detection of prostate cancer by Raman spectroscopy: A multivariate study on patients with normal and altered PSA values
This study aimed to identify the differences in the Raman spectra of serum samples with normal and altered PSA values and correlate these differences by using multivariate techniques (principal component analysis - PCA and partial least squares regression – PLS). A total of 321 spectra were collected from 108 subjects. Two hundred and seventy were obtained from 91 non-altered PSA samples and 51 spectra from 17 samples with altered PSA. Each spectrum acquired was standardized to the area under the curve (1-norm). Discriminating and quantitative models employing PCA and PLS were developed. The PCA analyses showed 85.7% predictive power (87.41% sensitivity and 76.47% specificity). The PLS test showed a near-perfect sensitivity (98.51%) and an intermediate specificity (62.75%). The quantitative model through PLS regression showed a good correlation between PSA values and the spectral features (r = 0.605). This preliminary study suggests that Raman spectroscopy could be efficiently used for screening patients with altered PSA as well as for follow-up of the treatment of the prostate cancer by using initially the PLS to identify the possible presence of the prostate cancer and later on use de PCA to confirm the diagnosis.Graphical Abstract
Source: Journal of Photochemistry and Photobiology B: Biology - Category: Speech-Language Pathology Source Type: research
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