Cascaded Neural Networks Assist Just about Re-Stain Tissue Samples | Analysis & Know-how | Sep 2022


LOS ANGELES, Sept. 19, 2022 — Utilizing a cascaded deep neural community construction, a UCLA analysis group led by professor Aydogan Ozcan developed a computational method for chemical-free re-staining of tissue specimens. The AI-powered method to digital stain switch supplied high-quality digital photographs of various stains utilizing current, histochemically stained slides. It’s a repeatable course of that saves time and prices, reduces waste, and preserves the biopsied tissue in order that it may be used for added testing.

To diagnose illness, pathologists visually examine tissue specimens taken from the affected person. They might use several types of stains to carry distinction to and spotlight numerous histological options of the tissue. The histochemical staining procedures are often irreversible, making it troublesome to acquire a number of stains on the identical skinny part of tissue.

The Ozcan-led workforce constructed a digital stain switch framework utilizing a cascade of two deep neural networks and demonstrated the power of the framework to digitally remodel hematoxylin- and eosin- (H&E) stained tissue photographs into different varieties of histological stains. Through the coaching course of, the cascaded deep neural community construction first discovered to make use of digital staining to remodel autofluorescence microscopy photographs into H&E, after which discovered to execute a stain switch from H&E to the area of one other stain in a cascaded method.

By implementing a cascaded construction in the course of the coaching part, the researchers enabled the mannequin to instantly exploit histochemically stained picture information on each H&E and the opposite stain of curiosity — on this case, the periodic acid-Schiff (PAS) stain. The cascaded coaching technique helped to mitigate the problem of paired information acquisition when utilizing histochemically stained slides and improved the picture high quality and colour accuracy of the digital stain switch from H&E to a special stain.

A tissue slide could be stained as soon as, with one sort of stain. Washing away the prevailing stain and placing a brand new chemical stain as a substitute is troublesome and never typically practiced in medical settings. Earlier strategies of digital stain switch have been stymied by this problem, which additionally made buying paired photographs of various stain sorts problematic.
A virtual tissue re-staining method saves biopsied tissue for more advanced diagnostic tests to be performed, eliminating the need for a second, potentially unnecessary biopsy. The virtual tissue re-staining method could be applied to other types of stains used in histology, and the method for virtual stain transfer could lead to new opportunities in digital pathology and tissue-based diagnostics. This image depicts the virtual re-staining of tissue using cascaded deep neural networks. Courtesy of the Ozcan Lab at UCLA.


A digital tissue re-staining technique saves biopsied tissue for extra superior diagnostic checks to be carried out, eliminating the necessity for a second, probably pointless biopsy. The digital tissue re-staining technique may very well be utilized to different varieties of stains utilized in histology, and the tactic for digital stain switch may result in new alternatives in digital pathology and tissue-based diagnostics. This picture depicts the digital re-staining of tissue utilizing cascaded deep neural networks. Courtesy of the Ozcan Lab at UCLA.


The Ozcan workforce validated the efficiency of its cascaded deep neural community method utilizing kidney needle core biopsy tissue sections. The researchers demonstrated the profitable switch of H&E-stained tissue photographs right into a digital PAS stain.

In giving clinicians the choice to just about re-stain tissue, the tactic for digital stain switch may result in new alternatives in digital pathology and tissue-based diagnostics. Moreover, the digital re-staining technique may very well be utilized to different varieties of stains utilized in histology.

The analysis was printed in ACS Photonics (www.doi.org/10.1021/acsphotonics.2c00932).



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