We here employed a multidimensional MSI strategy using a novel MALDI trapped ion mobility time of flight instrument to delineate plaque pathology associated lipid species with increased identification confidence. This is achieved through the ion mobility dimension of the used instrument that expands the molecular coverage of the MSI analyses at reasonable analysis times and most importantly increases molecular specificity through additional molecular parameters, i.e. mass accuracy and collisional cross section. Herein, we investigated plaque associated lipid regulation in transgenic AD mice (tgAPPswe) from two perspectives, including plaque morphology and age. For this we multiplexed the MSI analyses with complemental structure sensitive amyloid staining performed on the same section and followed plaque pathology and plaque polymorphism in tgAPPSwe mice at different age (18 and 23 months). In TIMS, in addition to the m/z dimension, additional data are generated across the ion mobility dimension for each mass window leading consequently to very large data file sizes. To approach these complex, highly dimensional data in an unbiased way, we performed multistage image data processing and image segmentation analysis (Figure ). Following data processing, we performed principal component analysis (PCA) of the data for image segmentation (Figure and . This allowed us to obtain PCA images containing plaque specific single ion information that we subsequently used for image segmentation. In detail, binary maps were generated for classification of plaque structures into four regions of interest including 1) plaques and 2) background as well as 3) plaque core and 4) plaque periphery. Binary maps were generated through a combination of thresholding and active contours segmentation to annotate the different ROI in an unbiased way across all single plaques within each tissue sample and mouse, respectively (Figure ).