title: CH-overtone regions as diagnostic markers for near-infrared spectroscopic diagnosis of primary cancers in human pancreas and colorectal tissue.
abstract: We have investigated the application of near-infrared spectroscopy for detection of human primary pancreatic and colorectal cancers. Spectra from cancerous and normal tissue were collected from a total of 37 surgically resected pancreatic and colorectal patient tissue specimens using a fibre-optic probe. Major spectral differences were observed in the CH-stretching first (6,000-5,400 cm(-1)) and second overtone (9,000-7,900 cm(-1)) regions. By use of artificial neural networks, linear discriminant analysis, and cluster analysis as pattern-recognition methods the spectra were classified into cancerous and normal tissue groups with accuracy up to 89%. We also explored differences between the spectra obtained from colorectal and pancreatic tissue. Spectral data from cancerous and normal tissue were classified organ-specifically into four groups with accuracy between 80 and 83%. Our results indicate that CH-overtone regions, besides serving as diagnostic markers for NIR spectroscopic diagnosis of primary human pancreas and colorectal cancers, are also useful for elucidating differences between the spectra obtained from colorectal and pancreatic cancerous tissue.
authors.affiliation: Institute for Instrumental Analysis and Bioanalysis, Mannheim University of Applied Sciences, Windeckstrasse 110, 68163 Mannheim, Germany.
authors.forename: Venkata Radhakrishna
authors.initials: VR
authors.lastname: Kondepati
authors.forename: Thomas
authors.initials: T
authors.lastname: Oszinda
authors.forename: H Michael
authors.initials: HM
authors.lastname: Heise
authors.forename: Klaus
authors.initials: K
authors.lastname: Luig
authors.forename: Ralf
authors.initials: R
authors.lastname: Mueller
authors.forename: Olaf
authors.initials: O
authors.lastname: Schroeder
authors.forename: Michael
authors.initials: M
authors.lastname: Keese
authors.forename: Juergen
authors.initials: J
authors.lastname: Backhaus
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D001185:Artificial Intelligence; D014408:Biomarkers, Tumor / Q000032:analysis*; D002244:Carbon / Q000032:analysis*; D015179:Colorectal Neoplasms / Q000175:diagnosis* / Q000378:metabolism*; D003936:Diagnosis, Computer-Assisted / Q000379:methods; D005260:Female; D006801:Humans; D006859:Hydrogen / Q000032:analysis*; D008297:Male; D008875:Middle Aged; D010190:Pancreatic Neoplasms / Q000175:diagnosis* / Q000378:metabolism*; D010363:Pattern Recognition, Automated / Q000379:methods; D013055:Spectrophotometry, Infrared / Q000379:methods*
chemical_list: D014408:Biomarkers, Tumor; D002244:Carbon; D006859:Hydrogen