title: [Study on bladder cancer tissues with Raman spectroscopy].
abstract: The scope of this research lies in diagnosis of bladder cancer through Raman spectra. The spectra of bladder cancer and normal bladder were measured by using laser confocal Raman micro-spectroscopy. Principal component analysis/support vector machines was applied to the spectral dataset to construct diagnostic algorithms, then to detect the accuracy of these algorithms to determine histological diagnosis by leave-one-out cross validation from its Raman spectrum. It was showed that the peak intensity of nucleic acid (782, 1 583 cm(-1)) in bladder cancer and protein (1 061, 1 295, 2 849, 2 881 cm(-1)) in normal bladder increased significantly. Additionally, Principal component analysis (PCA) and support vector machines (SVM) provided an effective tool for differentiating the bladder cancer from normal bladder tissue. Excellent sensitivity (86.7%), specificity (87.5%), positive predictive value (92.9%), and negative predictive value (72. 8%) for the diagnosis of bladder cancer were obtained by leave-one-out cross validation. It was concluded that Raman spectroscopy can be used to accurately identify bladder cancer in vitro, and it suggests the promising potential application of PCA/SVM-based Raman spectroscopy for the diagnosis of bladder cancer.
authors.affiliation: Department of Urology, No. 1 Affiliated Hospital of Xi' an Jiaotong University, Key Laboratory of Environment and Genes Related to Disease, Ministry of Education, Xi'an 710061, China. tuodi1986@msn.com
authors.forename: Lei
authors.initials: L
authors.lastname: Wang
authors.forename: Jin-hai
authors.initials: JH
authors.lastname: Fan
authors.forename: Zhen-feng
authors.initials: ZF
authors.lastname: Guan
authors.forename: You
authors.initials: Y
authors.lastname: Liu
authors.forename: Jin
authors.initials: J
authors.lastname: Zeng
authors.forename: Da-lin
authors.initials: DL
authors.lastname: He
authors.forename: Li-qing
authors.initials: LQ
authors.lastname: Huang
authors.forename: Xin-yang
authors.initials: XY
authors.lastname: Wang
authors.forename: Hui-ling
authors.initials: HL
authors.lastname: Gong
mesh_terms: D000465:Algorithms; D006801:Humans; D011237:Predictive Value of Tests; D025341:Principal Component Analysis; D012680:Sensitivity and Specificity; D013059:Spectrum Analysis, Raman; D060388:Support Vector Machine; D001749:Urinary Bladder Neoplasms / Q000175:diagnosis* / Q000473:pathology*