This study presents a single-cell metabolic imaging platform that enables high-resolution and high-specificity imaging of lipid metabolism in human-derived model systems. The platform uses an azide-tagged infrared (IR) probe to selectively detect newly synthesized lipids in cells and tissues, while fluorescence imaging allows for cell-type identification. The IR probe, combined with optical photothermal infrared (OPTiR) microscopy, provides sub-micrometer resolution and enables the visualization of lipid metabolism in various human-derived 2D and 3D culture systems, including neuroglioma, hiPSCs, hiPSC-derived microglia, and hiPSC-derived brain organoids. The platform was tested using azide-PA, a fatty acid tagged with an azide group, to track lipid metabolism. The results showed that newly synthesized lipids were visualized with high resolution, and the platform was able to distinguish between different cell types, such as neurons and astrocytes in brain organoids. The study also demonstrated that lipid metabolism was significantly upregulated in progranulin-knockdown human induced pluripotent stem cells and their differentiated microglia cells. Additionally, the platform was able to detect differences in lipid metabolism between hiPSC-derived microglia cells and hiPSCs, and the impact of progranulin deficiency on lipid metabolism. The study highlights the potential of the platform for cell-type specific metabolic imaging and the suitability of human-derived model systems for studying human-relevant metabolic alterations. The platform's ability to provide high-resolution and high-specificity imaging of lipid metabolism in human-derived models offers new insights into the mechanisms of metabolic-related diseases, including neurodegenerative disorders. The study also discusses the limitations of current metabolic imaging techniques and the advantages of the proposed platform in overcoming these limitations. The results suggest that the platform can be adapted to study the metabolism of other molecules, such as cholesterol, and that further improvements in imaging speed and spatial resolution are needed to fully explore its potential in biomedical research.This study presents a single-cell metabolic imaging platform that enables high-resolution and high-specificity imaging of lipid metabolism in human-derived model systems. The platform uses an azide-tagged infrared (IR) probe to selectively detect newly synthesized lipids in cells and tissues, while fluorescence imaging allows for cell-type identification. The IR probe, combined with optical photothermal infrared (OPTiR) microscopy, provides sub-micrometer resolution and enables the visualization of lipid metabolism in various human-derived 2D and 3D culture systems, including neuroglioma, hiPSCs, hiPSC-derived microglia, and hiPSC-derived brain organoids. The platform was tested using azide-PA, a fatty acid tagged with an azide group, to track lipid metabolism. The results showed that newly synthesized lipids were visualized with high resolution, and the platform was able to distinguish between different cell types, such as neurons and astrocytes in brain organoids. The study also demonstrated that lipid metabolism was significantly upregulated in progranulin-knockdown human induced pluripotent stem cells and their differentiated microglia cells. Additionally, the platform was able to detect differences in lipid metabolism between hiPSC-derived microglia cells and hiPSCs, and the impact of progranulin deficiency on lipid metabolism. The study highlights the potential of the platform for cell-type specific metabolic imaging and the suitability of human-derived model systems for studying human-relevant metabolic alterations. The platform's ability to provide high-resolution and high-specificity imaging of lipid metabolism in human-derived models offers new insights into the mechanisms of metabolic-related diseases, including neurodegenerative disorders. The study also discusses the limitations of current metabolic imaging techniques and the advantages of the proposed platform in overcoming these limitations. The results suggest that the platform can be adapted to study the metabolism of other molecules, such as cholesterol, and that further improvements in imaging speed and spatial resolution are needed to fully explore its potential in biomedical research.