Researchers at the University of California, Davis have developed imaging and analysis methods to detect and characterize the spatial distribution of collagen and other macromolecules on hematoxylin and eosin (H&E)-stained slides without the need for additional staining or expensive optics.
Excess collagen deposition plays a major role in organ dysfunction and is most commonly associated with cancer and liver and kidney pathologies. Reliable detection and reproducible quantitation of collagen is important in the diagnosis and clinical management of such pathologies. Current methods to detect and quantify collagen abundance and organization, especially on conventional histology preparations (i.e., formalin-fixed, paraffin-embedded and sectioned tissue specimens mounted on glass slides) have varying degrees of reliability, cost, and ease of use. There is a need for a simple, inexpensive, easy-to-use method for detection and characterization of collagen in whole H&E-stained tissue sections, as well as other tissue macromolecules (such as elastin).
Researchers at the University of California, Davis have developed a combined imaging and analysis method for detecting the spatial distribution of collagen and other structural molecules on standard H&E-stained slides. The method combines feature extraction with image processing and quantitative metrics to identify, display and characterize collagen and/or structural macromolecule-related tissue components. This method removes the need for additional stains or expensive optics, such as those involved with second-harmonic generation imaging systems. A prototype has already been developed and successfully tested on a number of H&E slides from a variety of specimen types including healthy and cancerous human breast, cervical and pancreatic tissue. It can capture individual fields and scan entire specimens on slides ("whole-slide imaging").
collagen, structural proteins, histology, elastin, whole slide imaging, hematoxylin and eosin stain, H&E, histochemical stain, immunohistochemical stains, spatial distribution, morphometry, prognostics, renal, hepatic, cancer, cirrhosis, transplantation