Correlated multimodal imaging in life sciences: lessons learnt

Abstract

Correlated Multimodal Imaging (CMI) gathers information about the same specimen with two or more modalities that–combined–create a composite and complementary view of the sample (including insights into structure, function, dynamics and molecular composition). CMI allows one to reach beyond what is possible with a single modality and describe biomedical processes within their overall spatio-temporal context and gain a mechanistic understanding of cells, tissues, and organisms in health and disease by untangling their molecular mechanisms within their native environment. The field of CMI has grown substantially over the last decade and previously unanswerable biological questions have been solved by applying novel CMI workflows. To disseminate these workflows and comprehensively share the scattered knowledge present within the CMI community, an initiative was started to bring together imaging, image analysis, and biomedical scientists and work towards an open community that promotes and disseminates the field of CMI. This community project was funded for the last 4 years by an EU COST Action called COMULIS (COrrelated MUltimodal imaging in the LIfe Sciences). In this review we share some of the showcases and lessons learnt from the action. We also briefly look ahead at how we anticipate building on this initial initiative.