Communication of medical images to diverse audiences using multimodal imaging

Abstract

AbstractA study has been completed examining design issues concerning the interpretation of and dissemination of multimodal medical imaging data sets to diverse audiences. To create a model data set mouse fibrosarcoma tissue was visualised via magnetic resonance imaging (MRI), Matrix-Assisted Laser Desorption/Ionisation-Mass Spectrometry (MALDI-MSI) and histology. MRI images were acquired using the 0.25T Esaote GScan; MALDI images were acquired using a Q-Star Pulsar I mass spectrometer. Histological staining of the same tissue sections used for MALDI-MSI was then carried out. Areas assigned to hemosiderin deposits due to haemorrhaging could be visualised via MRI. In the MALDI-MSI data obtained the distribution sphingomyelin species could be used to identify regions of viable tumour. Mathematical ‘up sampling’ using hierarchical clustering-based segmentation provided a sophisticated image enhancement tool for both MRI and MALDI-MS and assisted in the correlation of images.