AI Article Synopsis

  • The human eye can see around 10,000 colors, making color important for interpreting images, especially since biological samples are usually transparent and hard to see with regular microscopes.
  • The study introduces a technique called histoplasmonics, which uses special microscope slides to create colorful images of biological samples without using stains that could change their properties.
  • This method effectively distinguishes between different types of breast tissue and could transform laboratory practices in tissue diagnostics, suggesting further improvements in digital pathology are possible.

Article Abstract

The human eye can distinguish as many as 10,000 different colours but is far less sensitive to variations in intensity, meaning that colour is highly desirable when interpreting images. However, most biological samples are essentially transparent, and nearly invisible when viewed using a standard optical microscope. It is therefore highly desirable to be able to produce coloured images without needing to add any stains or dyes, which can alter the sample properties. Here we demonstrate that colorimetric histology images can be generated using full-sized plasmonically active microscope slides. These slides translate subtle changes in the dielectric constant into striking colour contrast when samples are placed upon them. We demonstrate the biomedical potential of this technique, which we term histoplasmonics, by distinguishing neoplastic cells from normal breast epithelium during the earliest stages of tumorigenesis in the mouse MMTV-PyMT mammary tumour model. We then apply this method to human diagnostic tissue and validate its utility in distinguishing normal epithelium, usual ductal hyperplasia, and early-stage breast cancer (ductal carcinoma in situ). The colorimetric output of the image pixels is compared to conventional histopathology. The results we report here support the hypothesis that histoplasmonics can be used as a novel alternative or adjunct to general staining. The widespread availability of this technique and its incorporation into standard laboratory workflows may prove transformative for applications extending well beyond tissue diagnostics. This work also highlights opportunities for improvements to digital pathology that have yet to be explored.

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http://dx.doi.org/10.1038/s41586-021-03835-2DOI Listing

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