Recently, phasor approach has emerged as a powerful tool for extracting fluorescence lifetime and has been utilized as a biochemical component analyzing tool without complicated fitting algorithms. In this study, we propose the new method to obtain phasors from directly sampled waveforms. With deconvolution using optically obtained instrumental response function (IRF), fluorescence lifetime can be successfully measured with high precision (~ 40 psec). Cells under the various metabolic conditions were imaged through label-free fluorescence lifetime imaging microscopy with targeting nicotinamide adenine dinucleotide (NADH) and their phasors exhibited distinct clusters on phasor plots corresponding to different culturing conditions.
Photoactivation is a promising theranostic tool to image and stabilize the atherosclerotic plaque by apoptosis induction in macrophages or other vascular cells; however, lack of effective drugs and mechanistic understanding hinder its clinical application for cardiovascular disease. Here, we developed the macrophage targeted photosensitizer delivery strategy and demonstrated that imaging assisted light activation reduced inflammation and burden of atherosclerotic plaques. Mechanistically, targeted photoactivation induced autophagy and increased MerTK expression in carotid atheroma as early as 1 day, and had 2-fold increase in macrophage-associated apoptotic cells, indicating efferocytosis enhancement. This multifunctional photoactivatable theranostic strategy could confer a promising tool for high-risk plaques.
We developed a high-precision multispectral fluorescence lifetime imaging microscopy (FLIM) for label-free immune-histologic imaging of atherosclerotic plaques. With images of fluorescence lifetimes and intensity ratios between different channels, we could characterize various plaque components of coronary arteries that are related to immunohistochemistry results. Correlative FLIM-immunohistochemistry validation revealed significant associations between plaque components and multispectral FLIM parameters. The machine learning algorithm, trained with co-registered FLIM-immunohistochemistry datasets, allowed automated visualization of multiple atherosclerotic components from FLIM image of an unstained section. We anticipate that the multispectral FLIM can be widely used to assess biochemical components of various biological tissues, including atherosclerotic plaques.
Intravascular optical coherence tomography-fluorescence lifetime imaging (OCT-FLIm) provides co-registered structural and biochemical information of atherosclerotic plaques in a label-free manner. For intuitive image interpretation of OCT-FLIm, herein, we present a machine learning classifier where key biochemical components (lipids, lipids+macrophages, macrophages, fibrotic, and normal) related to plaque destabilization are characterized based on the combination of multispectral FLIm parameters and convolutional OCT features. Using dataset from in vivo atheromatous swine models, the classification accuracy was >92% for each plaque component according the five-fold cross validation. This highly translatable imaging strategy will open a new avenue for clinical intracoronary assessment of high-risk plaques.
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