Statistical analysis of FTIR spectra of cervical tissues and diagnostic algorithms for cervical cancer

Benjamin Appiah; Vengadesan Nammalvar; Rebekah Drezek

doi:10.1117/12.764271

22 February 2008 Statistical analysis of FTIR spectra of cervical tissues and diagnostic algorithms for cervical cancer

Benjamin Appiah, Vengadesan Nammalvar, Rebekah Drezek

Proceedings Volume 6863, Optical Diagnostics and Sensing VIII; 68630V (2008) https://doi.org/10.1117/12.764271
Event: SPIE BiOS, 2008, San Jose, California, United States

Abstract

We have analyzed infrared spectra of microtome sections of frozen cervical tissues from the malignant (cancer) and normal histopathological groups. Intensity ratios of the different bands throughout the fingerprint region in the mid-IR are compared for the above groups. The bands are evaluated to show that the peak absorbances for the different groups exhibit statistically significant differences. Among the significant changes observed is the increase in the peak intensity of the 1400 cm^-1 band of the normal tissue group. Also, the contribution of the 1240 cm^-1 band which is ^*due to the phosphatediester group of nucleic acids was greater for the malignant tissue group compared to normal tissues. Partial-Least Squares (PLS) factors are used to further analyze the tissues to access the more subtle differences between the cancer and normal groups and to help determine the spectral bands that are most useful for cancer diagnosis. Also, we utilized Linear Discriminant Analysis (LDA) as well as the supervised learning method of Support Vector Machines (SVM) to study our tissue samples and develop diagnostic algorithms. PLS was used to decompose the spectra to reduce the spectral variables. The PLS components were then used as variables in SVM procedures to construct algorithms that produce specificity and sensitivity values greater than 90%.

Citation Download Citation

Benjamin Appiah, Vengadesan Nammalvar, and Rebekah Drezek "Statistical analysis of FTIR spectra of cervical tissues and diagnostic algorithms for cervical cancer", Proc. SPIE 6863, Optical Diagnostics and Sensing VIII, 68630V (22 February 2008); https://doi.org/10.1117/12.764271

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KEYWORDS

Tissues

Cancer

Statistical analysis

FT-IR spectroscopy

Cervical cancer

Algorithm development

Absorption

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