Three-Dimensional Microscopy by Milling with Ultraviolet Excitation

Sci Rep. 2019 Oct 10;9(1):14578. doi: 10.1038/s41598-019-50870-1.

Abstract

Analysis of three-dimensional biological samples is critical to understanding tissue function and the mechanisms of disease. Many chronic conditions, like neurodegenerative diseases and cancers, correlate with complex tissue changes that are difficult to explore using two-dimensional histology. While three-dimensional techniques such as confocal and light-sheet microscopy are well-established, they are time consuming, require expensive instrumentation, and are limited to small tissue volumes. Three-dimensional microscopy is therefore impractical in clinical settings and often limited to core facilities at major research institutions. There would be a tremendous benefit to providing clinicians and researchers with the ability to routinely image large three-dimensional tissue volumes at cellular resolution. In this paper, we propose an imaging methodology that enables fast and inexpensive three-dimensional imaging that can be readily integrated into current histology pipelines. This method relies on block-face imaging of paraffin-embedded samples using deep-ultraviolet excitation. The imaged surface is then ablated to reveal the next tissue section for imaging. The final image stack is then aligned and reconstructed to provide tissue models that exceed the depth and resolution achievable with modern three-dimensional imaging systems.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Animals
  • Brain / diagnostic imaging
  • Cerebral Cortex / diagnostic imaging
  • Humans
  • Image Processing, Computer-Assisted / methods
  • Imaging, Three-Dimensional / methods*
  • Liver / diagnostic imaging
  • Lung / diagnostic imaging
  • Mice
  • Microcirculation
  • Microscopy / methods*
  • Microscopy, Confocal / methods
  • Microscopy, Ultraviolet / methods
  • Microtomy / methods
  • Monte Carlo Method
  • Pattern Recognition, Automated
  • Ultraviolet Rays*