Rapid overlapping-volume acquisition and reconstruction (ROVAR): automated 3D tiling for high-resolution, large...

Area of Science:

• Microscopy and imaging science
• Cell biology
• Biomedical engineering

Background:

• Fluorescence microscopy provides critical subcellular detail on cellular morphology and protein localization.
• High-resolution multiphoton microscopy is limited by small field-of-view, hindering large-scale tissue analysis.
• Imaging intact, unfixed organs in vivo and in situ presents significant technical challenges.

Purpose of the Study:

• To develop an automated system for rapid, large-scale 3D data acquisition from tissue surfaces using multiphoton microscopy.
• To overcome field-of-view limitations while maintaining micrometer resolution.
• To enable efficient imaging of intact, unfixed organs without coverglass.

Main Methods:

• An automated system was created to rapidly acquire overlapping image stacks from multiple fields-of-view along nonplanar tissue surfaces.
• Image acquisition was optimized to capture data only within the optimal signal-to-background ratio range, from the surface to maximal imaging depth.
• Overlapping 3D volumes were automatically collected and reconstructed into a single, large-scale 3D volume of the tissue surface.

Main Results:

• The system successfully generated large-scale (millimeter range) 3D volumes of tissue surfaces at micrometer resolution.
• Data acquisition was significantly faster and required less operator intervention compared to conventional methods.
• The system demonstrated its efficacy by acquiring high-resolution data from intact, unfixed organs both in vivo and in situ without a coverglass.

Conclusions:

• The automated 3D microscopy system enables efficient, high-resolution, large-scale imaging of tissue surfaces.
• This approach overcomes previous limitations in field-of-view and operator workload for multiphoton microscopy.
• The technology is valuable for studying cellular morphology and function in intact biological tissues, advancing cellular and tissue imaging capabilities.