Abstract
The demand for accurate and reproducible phenotyping of a disease trait increases with the rising number of biobanks and genome wide association studies. Detailed analysis of histology is a powerful way of phenotyping human tissues. Nonetheless, purely visual assessment of histological slides is time-consuming and liable to sampling variation and optical illusions and thereby observer variation, and external validation may be cumbersome. Therefore, within our own biobank, computerized quantification of digitized histological slides is often preferred as a more precise and reproducible, and sometimes more sensitive approach. Relatively few free toolkits are, however, available for fully digitized microscopic slides, usually known as whole slides images. In order to comply with this need, we developed the slideToolkit as a fast method to handle large quantities of low contrast whole slides images using advanced cell detecting algorithms. The slideToolkit has been developed for modern personal computers and high-performance clusters (HPCs) and is available as an open-source project on github.com. We here illustrate the power of slideToolkit by a repeated measurement of 303 digital slides containing CD3 stained (DAB) abdominal aortic aneurysm tissue from a tissue biobank. Our workflow consists of four consecutive steps. In the first step (acquisition), whole slide images are collected and converted to TIFF files. In the second step (preparation), files are organized. The third step (tiles), creates multiple manageable tiles to count. In the fourth step (analysis), tissue is analyzed and results are stored in a data set. Using this method, two consecutive measurements of 303 slides showed an intraclass correlation of 0.99. In conclusion, slideToolkit provides a free, powerful and versatile collection of tools for automated feature analysis of whole slide images to create reproducible and meaningful phenotypic data sets.
Highlights
Biobanking has become a significant corner stone in pathogenetic studies of multiple diseases and is an important resource for identifying mechanisms of many complex diseases. [1] It is evident that adequate and reproducible histological characterization of large amounts of collected of tissue is key, especially when used for association studies, such as genome wide association studies
Acquisition, Preparation & Tiles We collected a total of 303 unique digital slides containing CD3 stained abdominal aortic aneurysm (AAA) tissue
Analyse & Data One digital slide failed the conversion to tiles in both runs for unknown reasons
Summary
Biobanking has become a significant corner stone in pathogenetic studies of multiple diseases and is an important resource for identifying mechanisms of many complex diseases. [1] It is evident that adequate and reproducible histological characterization of large amounts of collected of tissue is key, especially when used for association studies, such as genome wide association studies. In our Athero-Express biobank study, for instance, over 3000 patients have been included, which has resulted in .20.000 immunohistochemically stained cross-sectional slides using different types of antibodies that call for sufficient and consistent phenotyping. We applied manual semi-quantitative scoring methods or case-by-case quantitative scoring of immunohistochemically stained cross-sections. Manual or case-by-case phenotyping of histological slides is a time-consuming process liable to observer variability, and fast, unbiased and reproducible computerized phenotyping is indispensable. Interactive morphometric techniques on live video images [3] and image analysis on sampled digital [4] have been applied, which has improved reproducibility, but this was still time consuming. A computeraided method (analySIS FIVE, Olympos soft imaging solutions) to score inflammatory cells and smooth muscle cells quantitatively was previously implemented to improve reproducibility that performed well. A computeraided method (analySIS FIVE, Olympos soft imaging solutions) to score inflammatory cells and smooth muscle cells quantitatively was previously implemented to improve reproducibility that performed well. [5] this method requires the user to manually set color thresholds for the positively stained areas within subjectively selected regions of interest
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
