Asthma is one of the major non-communicable diseases, with upwards of 500 million cases worldwide. It is characterized by chronic inflammation and remodeling in the lung that is mediated by a combination of immune and structural cells. These different cell populations (eg, mast cells) synthesize multiple lipid mediators (eg, eicosanoids) that impact the etiology and progression of the disease. Targeting these biochemical pathways constitute the primary means of asthma management. Lipid mediators are oxygenated products of fatty acids (eg, arachidonic acid) that regulate inflammation via autocrine and paracrine signaling. While in situ levels can be transitorily elevated, circulating concentrations are relatively low. While bulk analysis has aided our understanding, there is a need to map the spatial heterogeneity and determine the cellular neighborhoods that release and biosynthesize lipid mediators within the lung. However, spatial technologies generally focus on mapping abundant molecules (eg, phospholipids), and seldom map these low abundant functional mediators. To image the heterogeneity of lipid mediators in the lung, we have harnessed the sensitivity of a new technology called desorption electrospray ionization-multiple reaction monitoring (DESI-MRM). This method increases the sensitivity and specificity of the analysis, enabling detection of the low abundant lipid mediators. Our workflow demonstrated the first routine imaging of lipid mediators with a spatial resolution of 25 µm. We have combined DESI-MRM with targeted spatial transcriptomics (SCRINSHOT) to identify cell types associated with lipid mediator production. These approach enables multi-modal analysis of lipid mediator synthetic pathways in the airways. To perform our data analysis and infer the roles of lipid mediators during different phases of inflammation, we have overlayed other imaging modalities. We correlate lipid mediator concentrations with tissue type annotations from H&E stains (eg, airways smooth muscle and epithelium) and cellular neighborhoods from spatial transcriptomics (eg, fibroblast and mast cells) to provide a broader biological context. Importantly we have shown that these techniques can be performed on the same human lung cryosections after DESI-MRM acquisition to increase their relevance. Given the novelty of the DESI-MRM data type, there is a lack of existing tools and it has been necessary to develop open-source software to analyse these data. We developed quantMSImageR, which is an R-based package able to quantify lipid mediator concentrations, statistically compare lipid mediator distributions and generate average data matrices and tiff images for downstream analysis with existing tools. To probe the results from the multimodal imaging work, we have worked with NBIS to develop extensions to spatialData and tissUUmaps to parse our data modalities into these popular open-source environments. While these initial efforts have been successful, we are now limited in our ability to perform the data analysis locally and require additional computational resources. These analytical and computational developments enable us to understand which cellular neighborhoods in which tissues contribute to lipid mediator biosynthesis. These experiments pave the way for better understanding the roles of lipid mediators in the onset and progression of asthma and will assist identification of new therapeutic targets.