Label-free investigation of infected acute pyelonephritis tissue by FTIR microspectroscopy with unsupervised and

Jingzhu Shao1, Xiangyu Zhao1, Ping Tang1

  • 1Center for Biophotonics, Institute of Medical Robotics, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China.

Insights

Fourier transform infrared (FTIR) microspectroscopy effectively differentiates acute pyelonephritis (AP) kidney tissue from healthy tissue. This label-free method analyzes molecular and morphological changes, achieving high accuracy in classifying infected tissues.

Area of Science:

  • Biomedical Optics
  • Spectroscopy
  • Pathology

Background:

  • Acute pyelonephritis (AP) is a severe urinary tract infection (UTI) impacting many patients globally.
  • Current diagnostic methods for AP include urinalysis, imaging, and histology.
  • Fourier transform infrared (FTIR) microspectroscopy offers a label-free approach for analyzing tissue morphology and molecular composition.

Purpose of the Study:

  • To investigate the utility of FTIR microspectroscopy for analyzing renal tissue in a rat model of AP.
  • To differentiate normal kidney tissues (cortex and medulla) from infected AP tissues using FTIR spectral data.
  • To assess the accuracy of unsupervised and supervised machine learning methods for classifying renal tissues based on FTIR spectra.

Main Methods:

  • FTIR microspectroscopy was used to collect spectral data from rat kidney tissues.
  • Unsupervised methods (integration, clustering, PCA) were applied to create infrared histological maps.
  • Supervised analysis using Support Vector Machines (SVM) was employed for tissue classification.
  • Synchrotron-based FTIR was utilized for high-resolution imaging of specific kidney structures.

Main Results:

  • Infrared histological maps successfully differentiated renal tissue types compared to H&E staining.
  • Analysis revealed decreased amide II and increased nucleic acids and lipids in infected AP tissues.
  • PCA effectively separated infected from normal tissues.
  • SVM models achieved a classification accuracy of 96.11% for differentiating tissue types.
  • High-resolution maps of glomerulus and necrotic cell mass were generated using synchrotron FTIR.

Conclusions:

  • FTIR microspectroscopy is a powerful tool for investigating AP tissue.
  • This technique enables differentiation of infected renal tissue from normal tissue in a model system.
  • FTIR offers a label-free, molecularly informative approach to AP diagnostics.

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