Real-time histological imaging of kidneys stained with food dyes using multiphoton microscopy

Yasuaki Nagao1, Kazushi Kimura1,2, Shujie Wang1

  • 1Department of Neural Regeneration and Cell Communication, Mie University Graduate School of Medicine, Tsu, Japan.

Insights

This study introduces a novel real-time kidney disease diagnosis method using food dyes and multiphoton microscopy (MPM) for enhanced imaging. This technique visualizes kidney structures and functions, aiding in early disease detection.

Area of Science:

  • Nephrology
  • Medical Imaging
  • Biomedical Engineering

Background:

  • Accurate and timely diagnosis of kidney diseases is crucial for effective treatment.
  • Current diagnostic methods may be invasive or lack real-time imaging capabilities.
  • Multiphoton microscopy (MPM) offers high-resolution imaging of biological tissues.

Purpose of the Study:

  • To develop a safe, real-time imaging technique for kidney disease diagnosis.
  • To evaluate the efficacy of food dyes as fluorescent agents in MPM for renal imaging.
  • To assess the potential of this technique for clinical applications in diagnosing kidney diseases.

Main Methods:

  • A two-step imaging technique involving safe staining of renal cells with food dyes (erythrosine, indigo carmine).
  • Optical sectioning of living renal tissue using multiphoton microscopy (MPM).
  • Histopathological analysis of IgA nephropathy model-mice kidneys compared to normal kidneys.

Main Results:

  • Food dyes effectively visualized renal functions and structures, including glomerular blood flow, filtration, and tissue morphology.
  • MPM imaging with food dyes revealed distinct histopathological differences in IgA nephropathy model-mice kidneys.
  • Enhanced image quality was achieved, facilitating clearer visualization of renal tissues.

Conclusions:

  • Food dyes can serve as safe and effective fluorescent agents for MPM-based renal imaging.
  • This technique provides real-time visualization of kidney structures and functions, aiding in disease diagnosis.
  • The developed method shows significant potential for clinical application in real-time kidney disease diagnosis.

Related Concept Videos