Use of FT-IR spectroscopy combined with SVM as a screening tool to identify invasive ductal carcinoma in breast cancer

Abstract This study proposes a rapid, noninvasive method for screening invasive ductal carcinoma (IDC) and noninvasive ductal carcinoma (non-IDC) using serum Fourier transform infrared (FT-IR) spectroscopy combined with multivariate statistical methods. Serum samples from 114 healthy patients, 74 IDC patients, and 41 non-IDC patients were examined in this experiment. Tentative assignments of the FT-IR peaks in the measured serum spectra suggested specific biomolecular changes between the groups. Principal component analysis was used for feature extraction to reduce spectral dimension and improve the diagnostic model rate. Linear, polynomial, and radial basis function kernels were used to build support vector machine models for the extracted features. Polynomial kernel achieves the best results with an accuracy of 95.7 %, and sensitivity and specificity of 91.7 % and 100 %, respectively. The results of the study indicate that serum FT-IR spectroscopy combined with multivariate statistical analysis has considerable potential for screening IDC in breast cancer. This technology can be used to develop a portable, rapid screening device for discriminating healthy patients and those with IDC and non-IDC.