This study tries to demonstrate that attenuated total reflectance-fourier transform infrared (ATR-FTIR) microspectroscopy in combination with chemometric methods can reliably distinguish malignant colon tissues from healthy ones. It is important to explore a noninvasive and rapid method for detection of colon cancer biopsies. Initially, principal component analysis was applied to examine the degree of separation between tissue samples. Soft independent modeling of class analogy (SIMCA) was also employed to evaluate the prediction accuracy of ATR-FTIR microspectroscopy for the diagnosis of colon cancer. There were significant differences in the fourier transform infrared spectra of normal and cancerous colon biopsies in the 1,800-900 cm(-1) spectral region. The SIMCA results demonstrated that the accuracy, specificity, and sensitivity of the proposed diagnostic method were 93.3, 100, and 88.2%, respectively, which could help satisfy clinical diagnostic requirements.

Attenuated Total Reflectance Fourier Transform Infrared (ATR-FTIR) microspectroscopy was applied for detection of colon cancer according to the spectral features of colon tissues. Supervised classification models can be trained to identify the tissue type based on the spectroscopic fingerprint. A total of 78 colon tissues were used in spectroscopy studies. Major spectral differences were observed in 1,740-900 cm(-1) spectral region. Several chemometric methods such as analysis of variance (ANOVA), cluster analysis (CA) and linear discriminate analysis (LDA) were applied for classification of IR spectra. Utilizing the chemometric techniques, clear and reproducible differences were observed between the spectra of normal and cancer cases, suggesting that infrared microspectroscopy in conjunction with spectral data processing would be useful for diagnostic classification. Using LDA technique, the spectra were classified into cancer and normal tissue classes with an accuracy of 95.8%. The sensitivity and specificity was 100 and 93.1%, respectively.

Attenuated total reflectance-Fourier transform infrared (ATR-FTIR) spectroscopy was applied to discriminate the blood samples obtained from healthy people and those with basal cell carcinoma, demonstrating high accuracy while soft independent modeling class analogy (SIMCA) chemometric technique is benefited. It was aimed to classify the normal case and cancer case blood samples through the use of ATR-FTIR spectroscopy as a rapid method while the sample preparation is so easy in comparison with the common pathologic methods. A total of 72 blood samples, including 32 cancer and 40 normal cases, were analyzed in 1,800-900 cm(-1) spectral region. Results showed 97.6% of accuracy being compared with the current clinical methods. Research results were exemplified with comparable data of other classification methods such as principal component analysis (PCA) and Cluster analysis. The residual errors in prediction (REP) of calibration model for normal and cancerous groups in SIMCA method were 0.00362 and 0.00343, respectively.

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