Université de Reims Champagne-Ardenne, BioSpecT-EA7506, UFR de Pharmacie, 51097 Reims, France; Service d'Hépato-Gastroentérologie et de Cancérologie Digestive, Centre Hospitalier Universitaire de Reims, 51092 Reims, France.
Data_frame, 25 rue Stendhal, 44300 Nantes, France.
Spectrochim Acta A Mol Biomol Spectrosc. 2024 Jan 15;305:123433. doi: 10.1016/j.saa.2023.123433. Epub 2023 Sep 25.
Assessment of liver fibrosis is crucial to guide the therapeutic strategy in patients with chronic liver disease. We investigated the potential of serum Fourier transform infrared (FTIR) spectroscopy for assessing the degree of hepatic fibrosis in patients with chronic hepatitis C (CHC). The study was conducted on dried serum samples from 94 CHC patients at different histological stages of hepatic fibrosis: METAVIR F0 (n = 20), F1 (n = 17), F2 (n = 20), F3 (n = 20) and F4 (n = 17). Transmission FTIR spectra were acquired in the 4000-400 cm range. Wavenumbers were selected by genetic algorithm (GA) according to their diagnostic performance as assessed by a partial least squares discriminant analysis (PLS-DA) model using a training and a validation set to differentiate severe stages of fibrosis from mild or moderate ones. The GA procedure was applied 50 times on randomly selected sets. Furthermore, the best set of wavenumbers was re-tested in 1000 randomly selected validation sets. Wavenumbers selected by GA corresponded to functional groups present in lipids, proteins, and carbohydrates. This model allowed to identify patients with cirrhosis (METAVIR F4), patients with advanced fibrosis (METAVIR F3 and F4), and patients with significant fibrosis (METAVIR F2, F3 and F4), with AUROC (Area Under the Receiver Operating Characteristic) of 0.88, 0.85 and 0.85, respectively. Thus, serum FTIR spectroscopy appears to have a strong potential as a new diagnostic tool for assessing the degree of fibrosis in patients with chronic liver disease.
评估肝纤维化对于指导慢性肝病患者的治疗策略至关重要。我们研究了血清傅里叶变换红外（FTIR）光谱在评估慢性丙型肝炎（CHC）患者肝纤维化程度中的潜在应用。该研究在不同肝纤维化组织学阶段的 94 例 CHC 患者的干燥血清样本上进行：METAVIR F0（n=20）、F1（n=17）、F2（n=20）、F3（n=20）和 F4（n=17）。在 4000-400cm 范围内获得透射 FTIR 光谱。根据偏最小二乘判别分析（PLS-DA）模型的诊断性能，通过遗传算法（GA）选择波数，该模型使用训练集和验证集来区分严重纤维化阶段与轻度或中度纤维化阶段。GA 程序在随机选择的集合上应用了 50 次。此外，在 1000 个随机选择的验证集中重新测试了最佳波数集。GA 选择的波数对应于存在于脂质、蛋白质和碳水化合物中的功能基团。该模型能够识别出患有肝硬化（METAVIR F4）、晚期纤维化（METAVIR F3 和 F4）和显著纤维化（METAVIR F2、F3 和 F4）的患者，其 AUROC（接受者操作特征曲线下的面积）分别为 0.88、0.85 和 0.85。因此，血清 FTIR 光谱似乎具有作为评估慢性肝病患者纤维化程度的新诊断工具的强大潜力。
