Spectroscopy-based imaging techniques can provide useful biochemical information about tissue samples. Here, we employ Raman and Fourier transform infrared (IR) imaging to characterize composition and constitution of atherosclerotic plaques of rabbits, fed with a high cholesterol diet. The results were compared with conventional light microscopy after staining with hematoxylin eosin, and elastica van Gieson. The spectral unmixing algorithm vertex component analysis was applied for data analysis and image reconstruction. IR microscopy allowed for differentiation between lipids and proteins in plaques of full aortic cross sections. Raman microscopy further discriminated cholesterol esters, cholesterol and triglycerides. FTIR and Raman images were recorded at a resolution near 20 micrometer per pixel for a large field of view. High resolution Raman images at 1 micrometer per pixel revealed structural details at selected regions of interest. The intima-media and the lipid-protein ratio were determined in five specimens for quantitation. These results correlate well with histopathology. The described method is a promising tool for easy and fast molecular imaging of atherosclerosis.

Visualization as well as characterization of inner arterial plaque depositions is of vital diagnostic interest, especially for the early recognition of vulnerable plaques. Established clinical techniques provide valuable visual information but cannot deliver information about the chemical composition of individual plaques. Here, we employ Raman-probe spectroscopy to characterize the plaque compositions of arterial walls on a rabbit model in vivo, using a miniaturized filtered probe with one excitation and 12 collection fibers integrated in a 1 mm sleeve. Rabbits were treated with a cholesterol-enriched diet. The methodology can improve the efficiency of animal experiments and shows great potential for applications in cardiovascular research. In order to further characterize the plaque depositions visually, coherent anti-Stokes Raman scattering (CARS) microscopy images have been acquired and are compared with the Raman-probe results.

The heterogeneity of high‐grade glioma recurrences remains an ongoing challenge for the interdisciplinary neurooncology team. Response to re‐irradiation (re‐RT) is heterogeneous, and survival data depend on prognostic factors such as tumor volume, primary histology, age, the possibility of reresection, or time between primary diagnosis and initial RT and re‐RT. In the present pooled analysis, we gathered data from radiooncology centers of the DKTK Consortium and used it to validate the established prognostic score by Combs et al. and its modification by Kessel et al. Data consisted of a large independent, multicenter cohort of 565 high‐grade glioma patients treated with re‐RT from 1997 to 2016 and a median dose of 36 Gy. Primary RT was between 1986 and 2015 with a median dose of 60 Gy. Median age was 54 years; median follow‐up was 7.1 months. Median OS after re‐RT was 7.5, 9.5, and 13.8 months for WHO IV, III, and I/II gliomas, respectively. All six prognostic factors were tested for their significance on OS. Aside from the time from primary RT to re‐RT (P = 0.074) and the reresection status (P = 0.101), all factors (primary histology, age, KPS, and tumor volume) were significant. Both the original and new score showed a highly significant influence on survival with P < 0.001. Both prognostic scores successfully predict survival after re‐RT and can easily be applied in the routine clinical workflow. Now, further prognostic features need to be found to even improve treatment decisions regarding neurooncological interventions for recurrent glioma patients.