CH-overtone regions as diagnostic markers for near-infrared spectroscopic diagnosis of primary cancers in human pancreas and colorectal tissue.
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.
Kondepati
Venkata Radhakrishna
VR
Institute for Instrumental Analysis and Bioanalysis, Mannheim University of Applied Sciences, Windeckstrasse 110, 68163 Mannheim, Germany.
Oszinda
Thomas
T
Heise
H Michael
HM
Luig
Klaus
K
Mueller
Ralf
R
Schroeder
Olaf
O
Keese
Michael
M
Backhaus
Juergen
J
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*
D014408:Biomarkers, Tumor; D002244:Carbon; D006859:Hydrogen