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High-definition Fourier Transform Infrared (FT-IR) Spectroscopic Imaging of Human Tissue Sections towards Improving Pathology
Published on: January 21, 2015
Modeling and quantifying biochemical changes in C6 tumor gliomas by Fourier transform infrared imaging
Abdelilah Beljebbar1, Nadia Amharref, Antoine Lévèques
1Unite MeDIAN, Universite de Reims Champagne-Ardenne, UMR CNRS 6237-MEDYC, IFR 53, UFR de Pharmacie, 51 Rue Cognacq-Jay, 51096 Reims Cedex, France. abdelilah.beljebbar@univ-reims.fr
Abstract:
The purpose of the study was to investigate molecular changes associated with glioma tissues using FT-IR microspectroscopic imaging (FT-IRM). A multivariate statistical analysis allowed one to successfully discriminate between normal, tumoral, peri-tumoral, and necrotic tissue structures. Structural changes were mainly related to qualitative and quantitative changes in lipid content, proteins, and nucleic acids that can be used as spectroscopic markers for this pathology. We have developed a spectroscopic model of glioma to quantify these chemical changes. The model constructed includes individual FT-IR spectra of normal and glioma brain constituents such as lipids, DNA, and proteins (measured on delipidized tissue). Modeling of FT-IR spectra yielded fit coefficients reflecting the chemical changes associated with a tumor. Our results demonstrate the ability of FT-IRM to assess the importance and distribution of each individual constituent and its variation in normal brain structures as well as in the different pathological states of glioma. We demonstrated that (i) cholesterol and phosphatidylethanolamine contributions are highest in corpus callosum and anterior commissure but decrease gradually towards the cortex surface as well as in the tumor, (ii) phosphatidylcholine contribution is highest in the cortex and decreases in the tumor, (iii) galactocerebroside is localized only in white, but not in gray matter, and decreases in the vital tumor region while the necrosis area shows a higher concentration of this cerebroside, (iv) DNA and oleic acid increase in the tumor as compared to gray matter. This approach could, in the future, contribute to enhance diagnostic accuracy, improve the grading, prognosis, and play a vital role in therapeutic strategy and monitoring.
Insights
Fourier-transform infrared (FT-IR) microspectroscopic imaging identified molecular changes in glioma tissues. This technique can differentiate tissue types and aid in glioma diagnosis and treatment strategies.
Area of Science:
- Biomedical Optics
- Molecular Spectroscopy
- Neuro-oncology
Background:
- Gliomas are primary brain tumors with diverse molecular profiles.
- Accurate tissue characterization is crucial for diagnosis, grading, and treatment planning.
- Fourier-transform infrared (FT-IR) microspectroscopic imaging offers label-free molecular analysis.
Purpose of the Study:
- To investigate molecular alterations in glioma tissues using FT-IR microspectroscopic imaging (FT-IRM).
- To develop a spectroscopic model for quantifying chemical changes in glioma.
- To establish FT-IRM as a tool for glioma diagnosis and prognosis.
Main Methods:
- FT-IR microspectroscopic imaging (FT-IRM) was employed to analyze normal, tumoral, peri-tumoral, and necrotic brain tissues.
- Multivariate statistical analysis was used to discriminate between tissue types.
- A spectroscopic model was developed using FT-IR spectra of brain constituents (lipids, DNA, proteins).
Main Results:
- FT-IRM successfully differentiated normal, tumoral, peri-tumoral, and necrotic tissues.
- Key molecular changes involved lipids, proteins, and nucleic acids, serving as spectroscopic markers.
- Specific changes in cholesterol, phosphatidylethanolamine, phosphatidylcholine, galactocerebroside, DNA, and oleic acid were identified in relation to tumor status and location.
Conclusions:
- FT-IRM can accurately assess the distribution and variation of molecular constituents in glioma.
- The developed spectroscopic model quantifies chemical changes associated with glioma.
- FT-IRM holds potential for enhancing diagnostic accuracy, grading, prognosis, and therapeutic monitoring of gliomas.
