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Author Notes:

Corresponding author: Emory University, 1639 Pierce Dr. NE, Woodruff Memorial Research Building Rm. 6105, Atlanta, GA, USA. Tel.: +1 404-712-9206. David Gutman, dgutman@emory.edu

Conception and design: D.A. Gutman, M. Khalilia, J. Beezley, L.A.D. Cooper

Development of methodology: D.A. Gutman, M. Khalilia, S. Lee, L.A.D. Cooper

Acquisition of data (provided animals, acquired and managed patients, provided facilities, etc.): D.A. Gutman, M. Khalilia, M. Nalisnik, L.A.D. Cooper

Analysis and interpretation of data (e.g., statistical analysis, biostatistics, computational analysis): D.A. Gutman, M. Nalisnik, D.R. Chittajallu, L.A.D. Cooper

Writing, review, and/or revision of the manuscript: D.A. Gutman, M. Khalilia, D.R. Chittajallu, L.A.D. Cooper

Administrative, technical, or material support (i.e., reporting or organizing data, constructing databases): D.A. Gutman, M. Khalilia, M. Nalisnik, Z. Mullen, J. Beezley, D. Manthey, L.A.D. Cooper

Study supervision: L.A.D. Cooper

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

Subjects:

Research Funding:

Funding statement: this work is supported by the National Cancer Institute Informatics Technology for Cancer Research grant number U24-CA194362-02.

Keywords:

  • Science & Technology
  • Life Sciences & Biomedicine
  • Oncology

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

Tools:

Journal Title:

Cancer Research

Volume:

Volume 77, Number 21

Publisher:

, Pages E75-E78

Type of Work:

Article | Post-print: After Peer Review

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.

Copyright information:

© 2017 American Association for Cancer Research.

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