gms | German Medical Science

Objective: Tumor specific characteristics of tissue like cell density, pleomorphism, mitosis and necrosis are tightly linked with the chemistry and morphology and can be studied with methods of optical spectroscopy (like fluorescence-, absorption- and vibrational spectroscopy). In an in vitro study financed by the Baden-Württemberg Stiftung, we proved the concept that the new developed method is able to distinguish and characterize gliomas of different WHO grades.

Method: With the help of a reasonable composed set of reference samples, different marker-free spectroscopic methods were tested for their suitability to classify tumors. The sample sets were analyzed with the help of UV/VIS-, Raman, light scattering and autofluorescence spectroscopy to determine the leading optical markers to be used for a characterization according to their WHO grade. To extract the important information out of the spectra, a principal component analysis (PCA) was applied. Tumor classification was performed by linear discrimination analysis and correlated to the histological classification according to the WHO grading.

Results: Tumor grades can be detected by combined spectroscopic methods in fixated cross sections of glioma tissue. Different methods are complementary. UV/VIS- and light scattering spectroscopy (dark field) supplement each other with their complementary information of chemistry and morphology. Infrared- and Raman spectroscopy are also generally suitable, but should be seen as a backup technology due to their longer measurement times and the much higher costs, as long the tumor typification in a larger sample set can't be achieved using only UV/VIS and light scattering spectroscopy. Two dimensional autofluorescence spectroscopy also appears to be promising.

Conclusions: The integration of spectroscopic characterization methods can be used to speed up and to increase the validation of the pathological findings ex situ. Added to an imaging platform, multimodal optical spectroscopy can be a promising approach to characterize tumor in situ and distinguish it from normal tissue.