Multimodal spectroscopic imaging : A new, powerful tool for intraoperative tumor diagnostics

Abstract

The increasing number of cancer cases requires new imaging approaches for intraoperative tumor characterization. Utilization of new optical/photonic methods in combination with artificial intelligence (AI) approaches to address urgent challenges in clinical pathology in terms of intraoperative computational spectral histopathology. Multimodal nonlinear imaging by combining the spectroscopic methods coherent anti-Stokes Raman scattering (CARS), two-photon excited autofluorescence (TPEF), fluorescence lifetime imaging microscopy (FLIM), and second harmonic generation (SHG). By using multimodal spectroscopic imaging, tissue morphochemistry, i.e., its morphology and molecular structure can be visualized in alabel-free manner. The multimodal images can be automatically analyzed using AI-based image analysis approaches. For clinical application in terms of frozen section diagnostics or in vivo use, the presented multimodal imaging approach can be translated into acompact microscope or endoscopic probe concepts. The synergistic combination of spectroscopic imaging modalities in combination with automated data analysis has great potential for fast and precise tumor diagnostics e.g., in terms of precise surgical guidance in laser or robotic surgery. Overall, intraoperative multimodal spectroscopic imaging may represent an innovative advancement for tumor diagnostics in the future, directly leading to improved patient care and significant cost savings.