Tuck Michael, Grélard Florent, Blanc Landry, Desbenoit Nicolas
Univ. Bordeaux, CNRS, CBMN, UMR 5248, Pessac, France.
Front Chem. 2022 May 9;10:904688. doi: 10.3389/fchem.2022.904688. eCollection 2022.
Multimodal imaging is a powerful strategy for combining information from multiple images. It involves several fields in the acquisition, processing and interpretation of images. As multimodal imaging is a vast subject area with various combinations of imaging techniques, it has been extensively reviewed. Here we focus on Matrix-assisted Laser Desorption Ionization Mass Spectrometry Imaging (MALDI-MSI) coupling other imaging modalities in multimodal approaches. While MALDI-MS images convey a substantial amount of chemical information, they are not readily informative about the morphological nature of the tissue. By providing a supplementary modality, MALDI-MS images can be more informative and better reflect the nature of the tissue. In this mini review, we emphasize the analytical and computational strategies to address multimodal MALDI-MSI.
多模态成像作为一种强大的策略，可用于整合来自多幅图像的信息。它涉及图像采集、处理和解读的多个领域。由于多模态成像作为一个广阔的学科领域，存在多种成像技术的组合方式，因此已有大量综述。在此，我们聚焦于在多模态方法中，基质辅助激光解吸电离质谱成像（MALDI-MSI）与其他成像模态的耦合。虽然MALDI-MS图像传达了大量化学信息，但它们对于组织的形态学特征并不具有直观的信息性。通过提供一种补充模态，MALDI-MS图像可以包含更多信息，并能更好地反映组织的本质。在本微型综述中，我们着重介绍用于处理多模态MALDI-MSI的分析和计算策略。
