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Expanding multimodal microscopy by high spectral resolution coherent anti-stokes raman scattering imaging for clinical disease diagnostics

: Meyer, Tobias; Chemnitz, Mario; Baumgartl, Martin; Gottschall, Thomas; Pascher, Torbjörn; Matthäus, Christian; Romeike, Bernd F.M.; Brehm, Bernhard R.; Limpert, Jens; Tünnermann, Andreas; Schmitt, Michael; Dietzek, Benjamin; Popp, Jürgen


Analytical chemistry 85 (2013), Nr.14, S.6703-6715
ISSN: 0003-2700
ISSN: 1520-6882
Fraunhofer IOF ()

Over the past years fast label-free nonlinear imaging modalities providing molecular contrast of endogenous disease markers with subcellular spatial resolution have been emerged. However, applications of these imaging modalities in clinical settings are still at the very beginning. This is because single nonlinear imaging modalities such as second-harmonic generation (SHG) and two-photon excited fluorescence (TPEF) have only limited value for diagnosing diseases due to the small number of endogenous markers. Coherent anti-Stokes Raman scattering (CARS) microscopy on the other hand can potentially be added to SHG and TPEF to visualize a much broader range of marker molecules. However, CARS requires a second synchronized laser source and the detection of a certain wavenumber range of the vibrational spectrum to differentiate multiple molecules, which results in increased experimental complexity and often inefficient excitation of SHG and TPEF signals. Here we report the application of a novel near-infrared (NIR) fiber laser of 1 MHz repetition rate, 65 ps pulse duration, and 1 cm-1 spectral resolution to realize an efficient but experimentally simple SGH/TPEF/multiplex CARS multimodal imaging approach for a label-free characterization of composition of complex tissue samples. This is demonstrated for arterial tissue specimens demonstrating differentiation of elastic fibers, triglycerides, collagen, myelin, cellular cytoplasm, and lipid droplets by analyzing the CARS spectra within the C-H stretching region only. A novel image analysis approach for multispectral CARS data based on colocalization allows correlating spectrally distinct pixels to morphologic structures. Transfer of this highly precise but compact and simple to use imaging approach into clinical settings is expected in the near future.