Identification and characterization of colorectal cancer using Raman spectroscopy and feature selection techniques.
This study aims to detect colorectal cancer with near-infrared Raman spectroscopy and feature selection techniques. A total of 306 Raman spectra of colorectal cancer tissues and normal tissues are acquired from 44 colorectal cancer patients. Five diagnostically important Raman bands in the regions of 815-830, 935-945, 1131-1141, 1447-1457 and 1665-1675 cm(-1) related to proteins, nucleic acids and lipids of tissues are identified with the ant colony optimization (ACO) and support vector machine (SVM). The diagnostic models built with the identified Raman bands provide a diagnostic accuracy of 93.2% for identifying colorectal cancer from normal Raman spectroscopy. The study demonstrates that the Raman spectroscopy associated with ACO-SVM diagnostic algorithms has great potential to characterize and diagnose colorectal cancer.
Shaoxin
S
Li
Gong
G
Chen
Yanjiao
Y
Zhang
Zhouyi
Z
Guo
Zhiming
Z
Liu
Junfa
J
Xu
Xueqiang
X
Li
Lin
L
Lin
D000230:Adenocarcinoma / Q000175:diagnosis / Q000473:pathology; D000465:Algorithms; D015179:Colorectal Neoplasms / Q000175:diagnosis* / Q000473:pathology; D005260:Female; D006801:Humans; D021621:Imaging, Three-Dimensional; D008297:Male; D008875:Middle Aged; D012372:ROC Curve; D013059:Spectrum Analysis, Raman / Q000379:methods*; D060388:Support Vector Machine