Challenges and advances in optical 3D mesoscale imaging.

ABSTRACT

Optical mesoscale imaging is a rapidly developing field that allows the visualisation of larger samples than is possible with standard light microscopy, and fills a gap between cell and organism resolution. It spans from advanced fluorescence imaging of micrometric cell clusters to centimetre-size complete organisms. However, with larger volume specimens, new problems arise. Imaging deeper into tissues at high resolution poses challenges ranging from optical distortions to shadowing from opaque structures. This manuscript discusses the latest developments in mesoscale imaging and highlights limitations, namely labelling, clearing, absorption, scattering, and also sample handling. We then focus on approaches that seek to turn mesoscale imaging into a more quantitative technique, analogous to quantitative tomography in medical imaging, highlighting a future role for digital and physical phantoms as well as artificial intelligence.

RESUMEN

This review discusses the state of the art of an emerging field called mesoscale imaging. Mesoscale imaging refers to the trend towards imaging ever-larger samples that exceed the classic microscopy domain and is also referred to as 'mesoscopic imaging'. In optical imaging, this refers to objects between the microscopic and macroscopic scale that are imaged with subcellular resolution; in practice, this implies the imaging of objects from millimetre up to cm size with µm or nm resolution. As such, the mesoscopy field spans the boundary between classic 'biological' imaging and preclinical 'biomedical' imaging, typically utilising lower magnification objective lenses with a bigger field of view. We discuss the types of samples currently imaged with examples, and highlight how this type of imaging fills the gap between microscopic and macroscopic imaging, allowing further insight into the organisation of tissues in an organism. We also discuss the challenges of imaging such large samples, from sample handling to labelling and optical phenomena that stand in the way of quantitative imaging. Finally, we put the current state of the art into context within the neighbouring fields and outline future developments, such as the use of 'phantom' test samples and artificial intelligence for image analysis that will underpin the quality of mesoscale imaging.