Abstract
Multibeam scanning electron microscopy (multiSEM) provides a technical platform for seamless nano-to-mesoscale mapping of cells in human tissues and organs, which is a major new initiative of the U.S. National Institutes of Health. Such cross-length-scale imaging is expected to provide unprecedented understanding of relationships between cellular health and tissue-organ as well as organismal-scale health outcomes. For example, understanding relationships between loss in cell viability and cell network connectivity enables identification of emergent behaviors and prediction of degenerative disease onset, in organs as diverse as bone and brain, at early timepoints, providing a basis for future treatments and prevention. Developed for rapid throughput imaging of minute defects on semiconductor wafers, multiSEM has recently been adapted for imaging of human organs, their constituent tissues, and their respective cellular inhabitants. Through integration of geospatial approaches, statistical and network modelling, advances in computing and the management of immense datasets, as well as recent developments in machine learning that enable the automation of big data analyses, multiSEM and other cross- cutting imaging technologies have the potential to exert a profound impact on elucidation of disease mechanisms, translating to improvements in human health. Here we provide a protocol for acquisition and preparation of sample specimen sizes of diagnostic relevance for human anatomy and physiology. We discuss challenges and opportunities to integrate this approach with multibeam scanning electron microscopy workflows as well as multiple imaging modalities for mapping of organ and tissue structure and function.