Distinction of cervical cancer biopsies by use of infrared microspectroscopy and probabilistic neural networks

Abstract

Fourier-transform infrared spectroscopy has shown alterations of spectral characteristics of cells and tissues as a result of carcinogenesis. The research reported here focuses on the diagnosis of cancer in formalin-fixed biopsied tissue for which immunochemistry is not possible and when PAP-smear results are to be confirmed. The data from two groups of patients (a control group and a group of patients diagnosed with cervical cancer) were analyzed. It was found that the glucose/phosphate ratio decreases (by 23-49%) and the RNA/DNA ratio increases (by 38-150%) in carcinogenic compared with normal tissue. Fourier-transform microspectroscopy was used to examine these tissues. This type of study in larger populations may help to set standards or classes with which to use treated biopsied tissue to predict the possibility of cancer. Probabilistic neural networks and statistical tests as parts of these biopsies predict the possibility of cancer with a high degree of accuracy (> 95%).

Review of multidimensional data processing approaches for Raman and infrared spectroscopy

“…ANN is a very powerful tool and can represent extremely complex structures in the data as it can approximate many patterns locally using different hidden layers. ANN is also used to solve classification problems in the field of vibrational spectroscopy [76,77]. Support Vector Machines identify the decision boundaries (hyperplanes) between the classes in an optimal way i.e.…”

Chemometrics of Cells and Tissues Using IR Spectroscopy - Relevance in Biomedical Research

“…Similarly, minute changes can occur between the different stages of cancer or malignancy which are difficult to detect even with histochemical analyses. Under these circumstances, FTIR becomes handy as it distinguishes among different grades of premalignant and malignant tissues based on markers like carbohydrates which may not be easily stained in normal laboratory practices (Mark et al 2005). Observation of metabolite variation along tissues reflecting the dynamic nature through FTIR spectroscopy has been one of the most important findings (Chiriboga et al 1998a, Sahu et al 2010 that has implications for cancer diagnosis.…”

Nucleic acids absorbance in Mid IR and its effect on diagnostic variates during cell division: A case study with lymphoblastic cells

“…The differences in the absorbance spectra (elucidated through biomarkers in the Mid-IR region) between normal and abnormal tissues have been shown to be a possible criterion for the detection of different forms of cancer, [6][7][8] among which those dependent on nucleic acid absorbance are prominent. Previous works have identified important variates (biomarkers) in the region between 900 and 1300 cm 21 , which were expected to originate from DNA (phosphates), for utilization in distinction of cancer and normal cells and tissues. 8,9 The nucleic acids predominantly absorb in the wavenumber region from 900 to 1300 cm 21 .…”

“…Previous works have identified important variates (biomarkers) in the region between 900 and 1300 cm 21 , which were expected to originate from DNA (phosphates), for utilization in distinction of cancer and normal cells and tissues. 8,9 The nucleic acids predominantly absorb in the wavenumber region from 900 to 1300 cm 21 . 10,11 Absorbance at wavenumbers 1020 and 1230 cm 21 are known to arise primarily because of the phosphates of DNA and those at 1121 and 1244 cm 21 arise mainly because of the phosphates of…”

“…8,9 The nucleic acids predominantly absorb in the wavenumber region from 900 to 1300 cm 21 . 10,11 Absorbance at wavenumbers 1020 and 1230 cm 21 are known to arise primarily because of the phosphates of DNA and those at 1121 and 1244 cm 21 arise mainly because of the phosphates of…”