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Updated: Jul 19, 2026
High-definition Fourier Transform Infrared (FT-IR) Spectroscopic Imaging of Human Tissue Sections towards Improving Pathology
Published on: January 21, 2015
A three-dimensional multivariate image processing technique for the analysis of FTIR spectroscopic images of multiple
Bayden R Wood1, Keith R Bambery, Corey J Evans
1Centre for Biospectroscopy and School of Chemistry, Monash University, 3800 Victoria, Australia. bayden.wood@sci.monash.edu.au
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.
