Integration of 3D multimodal imaging data of a head and neck cancer and advanced feature recognition

in: Biochimica et Biophysica Acta-Proteins and Proteomics (2017)
Lotz, Judith M.; Hoffmann, Franziska; Lotz, Johannes; Trede, Dennis; Oetjen, Janina; Becker, Michael; Ernst, Günther; Maass, Peter; Alexandrov, Theodore; Guntinas-Lichius, Orlando; Thiele, Herbert; von Eggeling, Ferdinand; Heldmann, Stefan
In the last years, matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDIMSI) became an imaging technique which has the potential to characterize complex tumor tissue. The combination with other modalities and with standard histology techniques was achieved by the use of image registration methods and enhances analysis possibilities. We analyzed an oral squamous cell carcinoma with up to 162 consecutive sections with MALDI MSI, hematoxylin and eosin (H&E) staining and immunohistochemistry (IHC) against CD31.Spatial segmentation maps of the MALDIMSI data were generated by similarity-based clustering of spectra. Next, the maps were overlaid with the H&E microscopy images and the results were interpreted by an experienced pathologist. Image registration was used to fuse both modalities and to build a three-dimensional (3D) model. To visualize structures below resolution of MALDIMSI, IHC was carried out for CD31 and results were embedded additionally. The integration of 3D MALDI MSI data with H&E and IHC images allows a correlation between histological and molecular information leading to a better understanding of the functional heterogeneity of tumors.

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