Imaging Dense Biological Samples

Optical microscopy has played a key role in biomedical discoveries with clinical impact. Significant challenges remain, however, for applications that require rapid, non-invasive imaging over large volumes. This is particularly true when deep, cellular-resolution imaging into optically dense biological media is needed. It is currently impossible, for example, to image the dynamic biophysical interactions associated with three-dimensional collective cell migration. This is equally true for imaging neural network activity in the intact mouse model brain beyond the depth of a millimeter. Such imaging would immediately accelerate clinically relevant discoveries.

With this CAREER award, Steven G. Adie, Biomedical Engineering, is addressing these imaging limitations by developing new ways of splitting up and sharing the work of image formation between state-of-the-art computational and hardware approaches. The current options for the deepest microscopic imaging in biological samples are optical coherence microscopy (OCM) and three-photon microscopy (3PM).

Adie is synergistically combining hardware adaptive optics and computational adaptive optics that will reduce distortions and dramatically improve the speed and imaging depth range of volumetric OCM and 3PM. For the latter, Adie’s group is collaborating with the lab of Chris Xu, Applied and Engineering Physics.

Adie’s team will demonstrate these methods and hybrid approach by imaging biological phenomena that cannot be studied with existing methods, thereby launching new avenues of investigation. This includes studies on cell migration and the intercell coordination of cell traction forces. Adie’s lab will investigate the connection between behavior and spatiotemporal patterns of neural network activity deep in the intact mouse model brain.

Cornell Researchers

Funding Received

$500 Thousand spanning 5 years