Raman Spectroscopy in Colorectal Cancer Diagnostics: Comparison of PCA-LDA and PLS-DA Models

Wenjing Liu,Chuanbo Jing,Zhaotian Sun,Jinyu Chen

doi:10.1155/2016/1603609

Abstract

Raman spectra of human colorectal tissue samples were employed to diagnose colorectal cancer. High-quality Raman spectra were acquired from normal and cancerous colorectal tissues from 81 patients. Subtle Raman variations, such as for peaks at 1134 cm−1 (protein, C-C/C-N stretching) and 1297 cm−1 (lipid, C-H2 twisting), were observed between normal and cancerous colorectal tissues. The average peak intensity at 1134 and 1297 cm−1 was increased from approximately 235 and 72 in the normal group, respectively, to 315 and 273 in the cancer group. The variations of Raman spectra reflected the changes of cell molecules during canceration. The multivariate statistical methods of principal component analysis-linear discriminant analysis (PCA-LDA) and partial least-squares-discriminant analysis (PLS-DA), together with leave-one-patient-out cross-validation, were employed to build the discrimination model. PCA-LDA was used to evaluate the capability of this approach for classifying colorectal cancer, resulting in a diagnostic accuracy of 79.2%. Further PLS-DA modeling yielded a diagnostic accuracy of 84.3% for colorectal cancer detection. Thus, the PLS-DA model is preferable between the two to discriminate cancerous from normal tissues. Our results demonstrate that Raman spectroscopy can be used with an optimized multivariate data analysis model as a sensitive diagnostic alternative to identify pathological changes in the colon at the molecular level.

Highlights

Colorectal cancer has high morbidity and mortality rates and is the third most commonly diagnosed cancer as well as the third leading cause of cancer death for both males and females in the United States [1]
The gold standard for cancer diagnostics is histopathology, which is based on the visual investigation of tissue biopsies
This study evaluated and compared two statistical models for colorectal tissue classification

Summary

Introduction

Colorectal cancer has high morbidity and mortality rates and is the third most commonly diagnosed cancer as well as the third leading cause of cancer death for both males and females in the United States [1] Detecting this cancer is a crucial and foremost step toward improving the survival rate of patients with colorectal cancer. Though colonoscopic screening has significantly increased the survival rate of patients with colorectal cancer, it remains a challenge to distinguish adenomas and early adenocarcinomas from benign hyperplastic polyps using colonoscopy [2]. This difficulty is due mainly to the fact that conventional white light reflectance colonoscopy deeply relies on subjective visual assessment of colorectal polyps [3]. It is of great necessity to develop an objective and sensitive technique that can assist clinicians in the differential diagnosis of benign and malignant cysts

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Conclusion