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Revealing brain pathologies with multimodal visible light optical coherence microscopy and fluorescence imaging
Antonia Lichtenegger1, Johanna Gesperger1,2, Barbara Kiesel3
1Medical University of Vienna, Center for Medical Physics and Biomedical Engineering, Vienna, Austria.
This study introduces a combined optical coherence microscopy and fluorescence imaging system for neuroimaging. The multimodal approach successfully identified Alzheimer's disease plaques and differentiated brain tumor tissues, showing promise for enhanced diagnostics.
Area of Science:
- Biomedical Optics
- Neuroimaging
- Optical Microscopy
Background:
- Current neuroimaging techniques face limitations in providing both morphological and molecular contrast.
- Multimodal imaging offers the potential for enhanced diagnostic capabilities by combining complementary information.
Purpose of the Study:
- To develop and characterize a multimodal visible light optical coherence microscopy (OCM) and fluorescence imaging (FI) system.
- To evaluate the system's efficacy in neuroimaging applications, including Alzheimer's disease models and intraoperative brain tumor biopsies.
Main Methods:
- A novel multimodal OCM and FI setup was engineered and validated using phantom measurements.
- Curcumin-stained Alzheimer's disease mouse brain slices were imaged to detect amyloid-beta plaques.
- Intraoperative human brain tumor biopsies were analyzed using OCM for structural information and FI for contrast.
Main Results:
- The OCM channel provided coregistered morphological images of brain tissue, while FI identified curcumin-stained amyloid-beta plaques.
- OCM revealed the 3D structure of brain parenchyma, and FI provided tumor-specific contrast in biopsies.
- Statistically significant differences in attenuation coefficients and fluorescence intensity were observed between 5-aminolevulinic acid (5-ALA)-positive and -negative brain tissues, correlating with histopathology.
Conclusions:
- The integrated OCM and FI system offers complementary contrast for neuroimaging applications.
- This multimodal approach shows significant potential for improved diagnostics in Alzheimer's disease and brain tumor characterization.
- The system provides valuable morphological and molecular information, aiding in the identification of pathological features in brain tissues.
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