Journal of Pathology Informatics Journal of Pathology Informatics
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SYMPOSIUM - 2ND NORDIC SYMPOSIUM ON DIGITAL PATHOLOGY
Year : 2015  |  Volume : 6  |  Issue : 1  |  Page : 8

RandomSpot: A web-based tool for systematic random sampling of virtual slides


1 Section of Pathology and Tumour Biology, Leeds Institute of Cancer and Pathology, University of Leeds, England, UK
2 Section of Pathology and Tumour Biology, Leeds Institute of Cancer and Pathology, University of Leeds, England, UK; Department of Pathology, Maastricht University Medical Center, Maastricht, Netherlands
3 Section of Pathology and Tumour Biology, Leeds Institute of Cancer and Pathology, University of Leeds; Department of Histopathology, St. James's University Hospital, Leeds Teaching Hospitals NHS Trust, Leeds, England, UK

Correspondence Address:
Alexander I Wright
Section of Pathology and Tumour Biology, Leeds Institute of Cancer and Pathology, University of Leeds, England, UK

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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/2153-3539.151906

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This paper describes work presented at the Nordic Symposium on Digital Pathology 2014, Linköping, Sweden. Systematic random sampling (SRS) is a stereological tool, which provides a framework to quickly build an accurate estimation of the distribution of objects or classes within an image, whilst minimizing the number of observations required. RandomSpot is a web-based tool for SRS in stereology, which systematically places equidistant points within a given region of interest on a virtual slide. Each point can then be visually inspected by a pathologist in order to generate an unbiased sample of the distribution of classes within the tissue. Further measurements can then be derived from the distribution, such as the ratio of tumor to stroma. RandomSpot replicates the fundamental principle of traditional light microscope grid-shaped graticules, with the added benefits associated with virtual slides, such as facilitated collaboration and automated navigation between points. Once the sample points have been added to the region(s) of interest, users can download the annotations and view them locally using their virtual slide viewing software. Since its introduction, RandomSpot has been used extensively for international collaborative projects, clinical trials and independent research projects. So far, the system has been used to generate over 21,000 sample sets, and has been used to generate data for use in multiple publications, identifying significant new prognostic markers in colorectal, upper gastro-intestinal and breast cancer. Data generated using RandomSpot also has significant value for training image analysis algorithms using sample point coordinates and pathologist classifications.


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