Abstract
Background Three-dimensional (3D) multivariate Fourier Transform Infrared (FTIR) image maps of tissue sections are presented. A villoglandular adenocarcinoma from a cervical biopsy with a number of interesting anatomical features was used as a model system to demonstrate the efficacy of the technique.
Methods Four FTIR images recorded using a focal plane array detector of adjacent tissue sections were stitched together using a MATLAB® routine and placed in a single data matrix for multivariate analysis using Cytospec™. Unsupervised Hierarchical Cluster Analysis (UHCA) was performed simultaneously on all 4 sections and 4 clusters plotted. The four UHCA maps were then stacked together and interpolated with a box function using SCIRun software.
Results The resultant 3D-images can be rotated in three-dimensions, sliced and made semi-transparent to view the internal structure of the tissue block. A number of anatomical and histopathological features including connective tissue, red blood cells, inflammatory exudate and glandular cells could be identified in the cluster maps and correlated with Hematoxylin & Eosin stained sections. The mean extracted spectra from individual clusters provide macromolecular information on tissue components.
Conclusion 3D-multivariate imaging provides a new avenue to study the shape and penetration of important anatomical and histopathological features based on the underlying macromolecular chemistry and therefore has clear potential in biology and medicine.
| Original language | English |
|---|---|
| Title of host publication | Spectroscopy |
| Subtitle of host publication | New Uses and Implications |
| Publisher | Apple Academic Press, Inc. |
| Chapter | 13 |
| Pages | 249-263 |
| Number of pages | 15 |
| ISBN (Electronic) | 9781466562318 |
| ISBN (Print) | 9781926692821 |
| Publication status | Published - 19 Apr 2016 |