Molecular spectral imaging system for quantitative immunohistochemical analysis of early diabetic retinopathy

  • Qingli Li*
  • , Jingfa Zhang
  • , Yiting Wang
  • , Guoteng Xu
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

10 Scopus citations

Abstract

A molecular spectral imaging system has been developed based on microscopy and spectral imaging technology. The system is capable of acquiring molecular spectral images from 400 nm to 800 nm with 2 nm wavelength increments. The basic principles, instrumental systems, and system calibration method as well as its applications for the calculation of the stain-uptake by tissues are introduced. As a case study, the system is used for determining the pathogenesis of diabetic retinopathy and evaluating the therapeutic effects of erythropoietin. Some molecular spectral images of retinal sections of normal, diabetic, and treated rats were collected and analyzed. The typical transmittance curves of positive spots stained for albumin and advanced glycation end products are retrieved from molecular spectral data with the spectral response calibration algorithm. To explore and evaluate the protective effect of erythropoietin (EPO) on retinal albumin leakage of streptozotocininduced diabetic rats, an algorithm based on Beer-Lambert's law is presented. The algorithm can assess the uptake by histologic retinal sections of stains used in quantitative pathology to label albumin leakage and advanced glycation end products formation. Experimental results show that the system is helpful for the ophthalmologist to reveal the pathogenesis of diabetic retinopathy and explore the protective effect of erythropoietin on retinal cells of diabetic rats. It also highlights the potential of molecular spectral imaging technology to provide more effective and reliable diagnostic criteria in pathology.

Original languageEnglish
Pages (from-to)1336-1342
Number of pages7
JournalApplied Spectroscopy
Volume63
Issue number12
DOIs
StatePublished - Dec 2009

Keywords

  • Diabetic retinopathy
  • Molecular spectral imaging
  • Quantitative pathology

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