EXPRESS: High-Resolution Fourier Transform Infrared (FT-IR) Spectroscopic Imaging for Detection of Lung Structures and Cancer-Related Abnormalities in a Murine Model

2021 ◽  
pp. 000370282110255
Author(s):  
Karolina Augustyniak ◽  
Karolina Chrabaszcz ◽  
Marta Smeda ◽  
Marta Stojak ◽  
Katarzyna M. Marzec ◽  
...  

Label-free molecular imaging is a promising utility to study tissues in terms of the identification of their compartments as well as chemical features and alterations induced by disease. The aim of this work was to assess if higher magnification of optics in the FTIR microscope coupled with the focal plane detector (FPA) resulted in better resolution of lung structures and if the histopathological features correlated with clustering of spectral images. FTIR spectroscopic imaging was performed on paraffinized lung tissue sections from mice with optics providing a total magnification of 61× and 36×. Then, IR images were subjected to unsupervised cluster analysis and, subsequently, cluster maps were compared with hematoxylin and eosin staining of the same tissue section. Based on these results, we observed minute features such as cellular compartments in single alveoli and bronchiole, blood cells and megakaryocytes in a vessel as well as atelectasis of the lung. In the case of the latter, differences in composition were also noted between the tissue from the non-cancerous and cancerous specimen. This study demonstrated the ability of high-definition FTIR imaging to evaluate the chemical features of well-resolved lung structures that could complement the histological examination widely used in animal models of disease.

2019 ◽  
Vol 73 (5) ◽  
pp. 556-564 ◽  
Author(s):  
Mahsa Lotfollahi ◽  
Sebastian Berisha ◽  
Davar Daeinejad ◽  
David Mayerich

Histological stains, such as hematoxylin and eosin (H&E), are routinely used in clinical diagnosis and research. While these labels offer a high degree of specificity, throughput is limited by the need for multiple samples. Traditional histology stains, such as immunohistochemical labels, also rely only on protein expression and cannot quantify small molecules and metabolites that may aid in diagnosis. Finally, chemical stains and dyes permanently alter the tissue, making downstream analysis impossible. Fourier transform infrared (FT-IR) spectroscopic imaging has shown promise for label-free characterization of important tissue phenotypes and can bypass the need for many chemical labels. Fourier transform infrared classification commonly leverages supervised learning, requiring human annotation that is tedious and prone to errors. One alternative is digital staining, which leverages machine learning to map IR spectra to a corresponding chemical stain. This replaces human annotation with computer-aided alignment. Previous work relies on alignment of adjacent serial tissue sections. Since the tissue samples are not identical at the cellular level, this technique cannot be applied to high-definition FT-IR images. In this paper, we demonstrate that cellular-level mapping can be accomplished using identical samples for both FT-IR and chemical labels. In addition, higher-resolution results can be achieved using a deep convolutional neural network that integrates spatial and spectral features.


2012 ◽  
Vol 403 (3) ◽  
pp. 727-735 ◽  
Author(s):  
Gerald Steiner ◽  
Luisa Mackenroth ◽  
Kathrin D. Geiger ◽  
Allison Stelling ◽  
Thomas Pinzer ◽  
...  

2010 ◽  
Vol 66 (a1) ◽  
pp. s294-s295
Author(s):  
Naomi E. Chayen ◽  
Lata Govada ◽  
K. L. Andrew Chan ◽  
Roslyn M. Bill ◽  
Sergei G. Kazarian

TECHNOLOGY ◽  
2015 ◽  
Vol 03 (01) ◽  
pp. 27-31 ◽  
Author(s):  
David Mayerich ◽  
Michael J. Walsh ◽  
Andre Kadjacsy-Balla ◽  
Partha S. Ray ◽  
Stephen M. Hewitt ◽  
...  

Dyes such as hematoxylin and eosin (H&E) and immunohistochemical stains have been increasingly used to visualize tissue composition in research and clinical practice. We present an alternative approach to obtain the same information using stain-free chemical imaging. Relying on Fourier transform infrared (FT-IR) spectroscopic imaging and computation, stainless computed histopathology can enable a rapid, digital, quantitative and non-perturbing visualization of morphology and multiple molecular epitopes simultaneously in a variety of research and clinical pathology applications.


1998 ◽  
Author(s):  
N. A. Wright ◽  
R. A. Crocombe ◽  
D. L. Drapcho ◽  
W. J. McCarthy

Sign in / Sign up

Export Citation Format

Share Document