Deep-tissue chemical imaging is essential for many biomedical applications. Here, we present a shortwave infrared photothermal (SWIP) microscope for millimeter-deep vibrational imaging with micron lateral resolution. By pumping the overtone transition of carbon-hydrogen bonds and probing the subsequent photothermal lens with shortwave infrared light, SWIP can obtain chemical contrast from one-micron polymer particles located at 800-μm depth in a highly scattering phantom. We demonstrated that SWIP can resolve intracellular lipids across an intact tumor spheroid and the layered structure in thick liver, skin, brain, and breast tissues. SWIP microscopy fills a gap in vibrational imaging with sub-cellular resolution and millimeter-level penetration, which heralds broad potential for life science and clinical applications.
Deep-tissue chemical imaging is essential for many biomedical applications. Here, we present a shortwave infrared photothermal (SWIP) microscope for millimeter-deep vibrational imaging with micron-resolution and nanoparticle detection sensitivity. By using short-wave infrared light for overtone excitation of CH bonds and photothermal probing, our modality can reach millimeter deep into scattering phantom and tissue. With a fast digitization method, we showed that in our setting the photothermal signal amplitude is 100 times larger than photoacoustic thus enabling higher sensitivity. SWIP can resolve intracellular lipids in tumor spheroid and layered structure in the liver, skin, and brain tissue.
Stimulated Raman scattering (SRS) imaging of fresh tissue is an emerging approach to render label-free pathology and diagnosis based on the chemical contrasts of native biomolecules. However, the contrast of cell nuclei is often too weak to perform reliable segmentation and quantification. To advance the development of label-free digital pathology with SRS, we explored three deep learning-based techniques with multicolor and hyperspectral SRS imaging data, including U-Net, Mask R-CNN, and Autoencoder. Our results show that a combination of machine learning and SRS imaging is a promising pathway to transforming the methodology of SRS label-free pathology for real clinical use.
Glioblastoma (GBM) is one of the most aggressive cancer types in nervous system. Due to the limited effectiveness of current treatments, prognosis remains poor for GBM patients. Altered lipid metabolism is a hallmark of GBM. Previous studies show that increased lipid droplets (LDs) could protect cancer cells from chemotherapy and other extracellular stresses. In this study, we apply stimulated Raman scattering (SRS) microscopy to image LDs to monitor uptake of palmitic acid (PA) by U-87 glioma cells. We observe that uptake of free PA rapidly upregulates adipogenesis in glioma cells. We find that glioma cells exhibit distinctive time-dependent and dose-dependent patterns in PA uptake and adipogenesis. Uptake of extra PA significantly decreases the unsaturation degree of LDs. The decreased unsaturation degree and other lipotoxicity effects lead to clear cell death upon PA treatment at a high concentration. The results indicate that inhibition of adipogenesis may have therapeutic effects for GBM utilizing the lipotoxicity effects induced by free fatty acids. This work demonstrates that SRS microscopy for label-free imaging of LDs distribution and their composition is a promising tool for lipid metabolism studies in cancer.
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