1. Raman spectroscopy with a 1064-nm wavelength laser as a potential molecular tool for prostate cancer diagnosis: a pilot study
- Author
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Jaqueline S. Soares, Felipe L. Magalhaes, Aloísio M Garcia, Eduardo Paulino, Alexei Manso Correa Machado, Ana M. de Paula, Marcelo Mamede, Ishan Barman, and Sangram K. Sahoo
- Subjects
Male ,Support Vector Machine ,Materials science ,Biopsy ,medicine.medical_treatment ,Biomedical Engineering ,Pilot Projects ,Spectrum Analysis, Raman ,01 natural sciences ,law.invention ,010309 optics ,Biomaterials ,symbols.namesake ,Prostate cancer ,Nuclear magnetic resonance ,Prostate ,law ,Nucleic Acids ,0103 physical sciences ,medicine ,Humans ,Prostatectomy ,Lasers ,010401 analytical chemistry ,Prostatic Neoplasms ,Proteins ,Reproducibility of Results ,medicine.disease ,Laser ,Lipids ,Fluorescence ,Atomic and Molecular Physics, and Optics ,0104 chemical sciences ,Electronic, Optical and Magnetic Materials ,Wavelength ,medicine.anatomical_structure ,symbols ,Neoplasm Grading ,Raman spectroscopy ,Raman scattering - Abstract
Raman spectroscopy is widely used to investigate the structure and property of the molecules from their vibrational transitions and may allow for the diagnosis of cancer in a fast, objective, and nondestructive manner. This experimental study aims to propose the use of the 1064-nm wavelength laser in a Raman spectroscopy and to evaluate its discrimination capability in prostate cancer diagnosis. Seventy-four spectra from patients who underwent radical prostatectomy were evaluated. The acquired signals were filtered, normalized, and corrected for possible oscillations in the laser intensity and fluorescence effects. Wilcoxon tests revealed significant differences between the benign and malign samples associated with the deformation vibration characteristic of nucleic acids, proteins, and lipids. A classifier based on support vector machines was able to predict the Gleason scores of the samples with 95% of accuracy, opening a perspective for the use of the 1064-nm excitatory wavelength in prostatic cancer diagnosis.
- Published
- 2018