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Quantitative pixel intensity- and color-based image analysis on minimally compressed files: implications for whole-slide imaging

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Current best practice in the quantitative analysis of microscopy images dictates that image files should be saved in a lossless format such as TIFF. Use of lossy files, including those processed with the JPEG algorithm, is highly discouraged due to effects of compression on pixel characteristics. However, with the growing popularity of whole-slide imaging (WSI) and its attendant large file sizes, compressed image files are becoming more prevelent. This prompted us to perform a color-based quantitative pixel analysis of minimally compressed WSI images. Sections from three tissues stained with one of three reagents representing the colors blue (hematoxylin), red (Oil-Red-O), and brown (immunoperoxidase) were scanned with a whole slide imager in triplicate at 20x, 40x, and 63x magnifications. The resulting files were in the form of a BigTIFF with a JPEG compression automatically applied during acquisition. Images were imported into analysis software, six regions of interest were applied to various morphological locations, and the areas assessed for the color of interest. Whereas the number of designated weakly or strongly positive pixels was variable across the triplicate scans for the individual regions of interest, the total number of positive pixels was consistent. These results suggest that total positivity for a specific color representing a histochemical or immunohistochemical stain can be adequately quantitated on compressed images, but degrees of positivity (e.g., weak vs. strong) may not be as reliable. However, it is important to assess individual whole-slide imagers, file compression level and algorithm, and analysis software for reproducibility.

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The Aperio VERSA 8 whole slide imager was purchased with funds provided through a Shared Instrumentation Grant awarded by the Dean’s Office of the Larner College of Medicine (to DJT). We thank Joan Skelly of Department of Medical Biostatisitics University of Vermont for statistical advice, and Drs. Mercedes Rincon and Marilyn Cipolla for allowing us to use their tissue slides. We also thank Leica Technical Support for discussions and assistance.

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Correspondence to Douglas J. Taatjes.

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Taatjes, D.J., Bouffard, N.A., Barrow, T. et al. Quantitative pixel intensity- and color-based image analysis on minimally compressed files: implications for whole-slide imaging. Histochem Cell Biol 152, 13–23 (2019).

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  • Whole-slide imaging
  • Image analysis
  • Image focus
  • Image compression
  • BigTiff
  • Image data