Quantitative histochemical analysis of human artery using Raman spectroscopy

Area of Science:

• Biomedical Engineering
• Analytical Chemistry
• Spectroscopy

Background:

• Atherosclerosis involves changes in arterial composition, including proteins, lipids, and calcium.
• Accurate quantitative analysis of these components is crucial for understanding disease progression.
• Current methods may lack the specificity or quantitative precision needed for complex tissue analysis.

Purpose of the Study:

• To develop and validate a quantitative method using near infrared Raman spectroscopy for analyzing human artery histochemical composition.
• To determine the relative contributions of key biomolecules (collagen, elastin, cholesterol lipids, calcium hydroxyapatite) to Raman spectra.
• To establish a linear model for extracting quantitative component concentrations from complex tissue spectra.

Main Methods:

• Near infrared Raman spectroscopy was employed to collect spectral data from normal and atherosclerotic human aorta.
• Raman scattering cross-sections for collagen, elastin, cholesterol lipids, and calcium hydroxyapatite were determined.
• A linear model was developed based on spectral contributions and component concentrations.
• The model's precision and accuracy were evaluated using mixtures of known compositions and actual atherosclerotic aorta samples.

Main Results:

• Raman spectra of aorta are primarily influenced by collagen, elastin, cholesterol lipids, and calcium hydroxyapatite.
• The Raman signal demonstrated a linear relationship with component concentration, even in scattering media.
• The developed linear model accurately extracted quantitative contributions of individual components.
• Model predictions showed agreement with measured values within experimental uncertainties for known mixtures.
• Quantitative analysis of atherosclerotic aorta revealed variations in the relative concentrations of biological constituents.

Conclusions:

• Near infrared Raman spectroscopy provides a precise and accurate method for the quantitative histochemical analysis of human artery.
• The developed linear modeling approach effectively deconvolutes complex Raman spectra of biological tissues.
• This technique offers valuable insights into the biochemical changes associated with atherosclerosis, aiding disease understanding and potentially diagnosis.