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. 2017 Nov 1;77(21):e75-e78.
doi: 10.1158/0008-5472.CAN-17-0629.

The Digital Slide Archive: A Software Platform for Management, Integration, and Analysis of Histology for Cancer Research

David A Gutman  1   2   3 , Mohammed Khalilia  4 , Sanghoon Lee  4 , Michael Nalisnik  2 , Zach Mullen  5 , Jonathan Beezley  5 , Deepak R Chittajallu  5 , David Manthey  5 , Lee A D Cooper  2   3   6
Affiliations

The Digital Slide Archive: A Software Platform for Management, Integration, and Analysis of Histology for Cancer Research

David A Gutman et al. Cancer Res. .

Abstract

Tissue-based cancer studies can generate large amounts of histology data in the form of glass slides. These slides contain important diagnostic, prognostic, and biological information and can be digitized into expansive and high-resolution whole-slide images using slide-scanning devices. Effectively utilizing digital pathology data in cancer research requires the ability to manage, visualize, share, and perform quantitative analysis on these large amounts of image data, tasks that are often complex and difficult for investigators with the current state of commercial digital pathology software. In this article, we describe the Digital Slide Archive (DSA), an open-source web-based platform for digital pathology. DSA allows investigators to manage large collections of histologic images and integrate them with clinical and genomic metadata. The open-source model enables DSA to be extended to provide additional capabilities. Cancer Res; 77(21); e75-78. ©2017 AACR.

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Conflict of interest statement

Competing interests statement: the authors have no competing interests to declare.

Figures

Figure 1
Figure 1. Overview of the DSA Interface
a: Girder view showing list of specimens for a given patient (case) b: Girder view showing access control widget for a given patient (case) c: DSA viewer showing a selected case from GBM and its corresponding Aperio annotation
Figure 1
Figure 1. Overview of the DSA Interface
a: Girder view showing list of specimens for a given patient (case) b: Girder view showing access control widget for a given patient (case) c: DSA viewer showing a selected case from GBM and its corresponding Aperio annotation
Figure 1
Figure 1. Overview of the DSA Interface
a: Girder view showing list of specimens for a given patient (case) b: Girder view showing access control widget for a given patient (case) c: DSA viewer showing a selected case from GBM and its corresponding Aperio annotation
See this image and copyright information in PMC

References

    1. Chang H, Han J, Borowsky A, Loss L, Gray JW, Spellman PT, et al. Invariant delineation of nuclear architecture in glioblastoma multiforme for clinical and molecular association. IEEE Trans Med Imaging. 2013;32:670–682. - PMC - PubMed
    1. Wang C, Pécot T, Zynger DL, Machiraju R, Shapiro CL, Huang K. Identifying survival associated morphological features of triple negative breast cancer using multiple datasets. J Am Med Inform Assoc. 2013;20:680–687. - PMC - PubMed
    1. Cooper LAD, Kong J, Gutman DA, Dunn WD, Nalisnik M, Brat DJ. Novel genotype-phenotype associations in human cancers enabled by advanced molecular platforms and computational analysis of whole slide images. Lab Invest. 2015;95:366–376. - PMC - PubMed
    1. Kong J, Cooper LAD, Wang F, Gao J, Teodoro G, Scarpace L, et al. Machine-based morphologic analysis of glioblastoma using whole-slide pathology images uncovers clinically relevant molecular correlates. PLoS One. 2013;8:e81049. - PMC - PubMed
    1. Heng YJ, Lester SC, Tse GM, Factor RE, Allison KH, Collins LC, et al. The molecular basis of breast cancer pathological phenotypes. J Pathol. 2017;241:375–391. - PMC - PubMed

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