Distinction of cervical cancer biopsies by use of infrared microspectroscopy and probabilistic neural networks
| Autor: | Shaul Mordechai, Jed Goldstein, Hugo Guterman, Shmuel Argov, R. Jagannathan, Ranjit Sahu, K. Kantarovich, Shlomo Mark, A. Podshyvalov |
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| Rok vydání: | 2005 |
| Předmět: |
Pathology
medicine.medical_specialty Spectrophotometry Infrared Biopsy Materials Science (miscellaneous) Normal tissue Uterine Cervical Neoplasms medicine.disease_cause Models Biological Sensitivity and Specificity Industrial and Manufacturing Engineering Phosphates Optics Immunochemistry Biomarkers Tumor medicine Humans Diagnosis Computer-Assisted RNA Neoplasm Business and International Management Carcinogen Cervical cancer Models Statistical medicine.diagnostic_test business.industry Reproducibility of Results Cancer Signal Processing Computer-Assisted DNA Neoplasm medicine.disease Glucose Female Neural Networks Computer Carcinogenesis Infrared microscopy business Algorithms |
| Zdroj: | Applied Optics. 44:3725 |
| ISSN: | 1539-4522 0003-6935 |
| Popis: | 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%). |
| Databáze: | OpenAIRE |
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