Noninvasive assessment of hepatic fibrosis in patients with chronic hepatitis C using serum Fourier transform infrared spectroscopy

Assessment of liver fibrosis is of paramount importance to guide the therapeutic strategy in patients with chronic hepatitis C (CHC). In this pilot study, we investigated the potential of serum Fourier transform infrared (FTIR) spectroscopy for differentiating CHC patients with extensive hepatic fibrosis from those without fibrosis. Twenty-three serum samples from CHC patients were selected according to the degree of hepatic fibrosis as evaluated by the FibroTest: 12 from patients with no hepatic fibrosis (F0) and 11 from patients with extensive fibrosis (F3-F4). The FTIR spectra (ten per sample) were acquired in the transmission mode and data homogeneity was tested by cluster analysis to exclude outliers. After selection of the most discriminant wavelengths using an ANOVA-based algorithm, the support vector machine (SVM) method was used as a supervised classification model to classify the spectra into two classes of hepatic fibrosis, F0 and F3-F4. Given the small number of samples, a leave-one-out cross-validation algorithm was used. When SVM was applied to all spectra (n = 230), the sensitivity and specificity of the classifier were 90.1% and 100%, respectively. When SVM was applied to the subset of 219 spectra, i.e., excluding the outliers, the sensitivity and specificity of the classifier were 95.2% and 100%, respectively. This pilot study strongly suggests that the serum from CHC patients exhibits infrared spectral characteristics, allowing patients with extensive fibrosis to be differentiated from those with no hepatic fibrosis.