In this work, we introduce a multimodal imaging workflow that integrates Matrix-assisted Laser Desorption Ionization Mass Spectrometry Imaging (MALDI-MSI) combined with Immunofluorescence (IF) microscopy to enhance in tissue spatial single-cell metabolomics. The workflow allows to correlate cell populations with associated small molecule distributions by conducting on the same tissue section MSI before IF staining, addressing tissue integrity challenges and joint image analysis. To process MSI data with IF guidance, we propose an original and advanced computational strategy utilizing Receiver Operating Characteristic (ROC) analysis, allowing to identify ions specific to targeted histological regions based on IF staining. Moreover, in a non-targeted strategy, we introduce a Spatial Coherence Measure (SCM) to distinguish genuine spatial patterns from noise within ion distributions, enhancing spatial metabolomics' robustness. Then spatial clustering techniques are employed to group ions sharing similar spatial distribution to reveal histological structures, providing complementary insights into metabolite distributions. We validated our workflow mouse spleen section as this organ presents a spatially complex but well-detailed microenvironment. In conclusion, our multimodal and computational workflow opens new frontiers for diverse biomedical research applications by promoting precise spatial metabolomics in tissue sections.