Second harmonic generation imaging of the collagen architecture in prostate cancer tissue.

Optical microscopy has been one of the most important tools for visualizing biological samples since the seventeenth century. Recently, with the advances in femtosecond laser technology, all the nonlinear optical processes have now been included as optical microscopy methods, and second harmonic generation (SHG) microscopy has emerged as a powerful new optical imaging tool with applications in medicine and biology. Here we use SHG microscopy to obtain images of 76 prostate biopsies on histological slides. Multiple samples from the excised prostates of patients who underwent a radical prostatectomy were evaluated. The samples were collected from prostate positions as in needle biopsy procedures. The results show the collagen fiber architecture among malignant acini, and analysis of the fiber orientation in the images reveals that the collagen fibers become more aligned at higher malignancy grades. Furthermore, we find that the degree of fiber alignment correlates directly with the Gleason patterns

Raman spectroscopy with a 1064-nm wavelength laser as a potential molecular tool for prostate cancer diagnosis : a pilot study.

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