ATR-FTIR and multivariate analysis as a screening tool for cervical cancer in women from northeast Brazil: a biospectroscopic approach

摘要

Cervical cancer is the fourth most frequent cancer in women worldwide and the third in Brazil. Screening methods can substantially reduce new cases of cervical cancer by identifying pre-cancerous lesions, making it possible to offer correct management and treatment. For this purpose, this work reports the use of attenuated total reflection Fourier-transforminfrared (ATR-FTIR) spectroscopy coupled with principal component analysis (PCA) and variable selection techniques, such as successive projections algorithm (SPA) and genetic algorithm (GA) associated to linear or quadratic discriminant analysis (LDA/QDA), to classify samples for negative for intraepithelial lesion or malignancy (NILM), n = 43, and squamous intraepithelial lesion (SIL), n = 40, directly from blood plasma. Furthermore, the possibility to categorize SIL subclasses according to low-grade squamous intraepithelial lesion (LSIL) and high-grade squamous intraepithelial lesion (HSIL) lesion degrees was evaluated. Application of variable selection algorithms, especially GA, considerably improved the classifications by choosing spectral variables that reflect the chemical differences between a healthy and pre-cancerous plasma sample. This method was able to correctly classify NILM vs. SIL with sensitivity and specificity for both classes varying around 77% using LDA. With QDA, the results were enhanced to sensitivity around 90% and specificity of 83%. NILM vs. LSIL presented sensitivity and specificity ranging between 67-94% and 82-94%, respectively. In addition, NILM vs. HSIL were found to have sensitivity and specificity from 76-97% to 73-100%, respectively, where QDA substantially provided better classifications. These findings highlight the potentiality of ATR-FTIR spectroscopy combined with multivariate analysis as a screening tool for pre-cancerous cervical lesions, which could contribute to reduce cervical cancer incidence.