Journal of Pathology Informatics Journal of Pathology Informatics
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ORIGINAL ARTICLE
Year : 2011  |  Volume : 2  |  Issue : 1  |  Page : 47

Image microarrays (IMA): Digital pathology's missing tool


1 Department of Pathology, University of Michigan, M4233A Medical Science I, 1301 Catherine, Ann Arbor, Michigan 48109-0602, USA
2 Department of Pathology, Division of Pathology Informatics, University of Pittsburgh Medical Center, UPMC Shadyside Hospital, Suite 201, 5150 Centre Avenue, Pittsburgh, PA 15232, USA
3 National Institutes of Health, National Cancer Institute, Laboratory of Pathology, Advanced Technology Center, 8717 Grovemont Circle, Gaithersburg, MD 20877, USA
4 MGH Pathology Imaging and Communication, Technology (PICT) Center, 101 Merrimac Street, Boston, MA 02114-4719, USA
5 Department of Biomedical Engineering, Rutgers The State University of New Jersey, 599 Taylor Road, Piscataway, NJ, USA
6 Department of Pathology and Laboratory Medicine, Perlman School of Medicine at the University of Pennsylvanaia, Division of Surgical Pathology, 6 Founders, Hospital of the University of Pennsylvania, 3400 Spruce Street, Philadelphia, PA 19104, USA
7 Weill Cornell Medical College, 575 Lexington Avenue, # 312, New York, NY 10022, USA
8 National Institutes of Health, National Cancer Institute, Medical Oncology 10 Center Drive, Bethesda, MD, 20892, USA

Correspondence Address:
Ulysses J Balis
Department of Pathology, University of Michigan, M4233A Medical Science I, 1301 Catherine, Ann Arbor, Michigan 48109-0602
USA
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/2153-3539.86829

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Introduction: The increasing availability of whole slide imaging (WSI) data sets (digital slides) from glass slides offers new opportunities for the development of computer-aided diagnostic (CAD) algorithms. With the all-digital pathology workflow that these data sets will enable in the near future, literally millions of digital slides will be generated and stored. Consequently, the field in general and pathologists, specifically, will need tools to help extract actionable information from this new and vast collective repository. Methods: To address this limitation, we designed and implemented a tool (dCORE) to enable the systematic capture of image tiles with constrained size and resolution that contain desired histopathologic features. Results: In this communication, we describe a user-friendly tool that will enable pathologists to mine digital slides archives to create image microarrays (IMAs). IMAs are to digital slides as tissue microarrays (TMAs) are to cell blocks. Thus, a single digital slide could be transformed into an array of hundreds to thousands of high quality digital images, with each containing key diagnostic morphologies and appropriate controls. Current manual digital image cut-and-paste methods that allow for the creation of a grid of images (such as an IMA) of matching resolutions are tedious. Conclusion: The ability to create IMAs representing hundreds to thousands of vetted morphologic features has numerous applications in education, proficiency testing, consensus case review, and research. Lastly, in a manner analogous to the way conventional TMA technology has significantly accelerated in situ studies of tissue specimens use of IMAs has similar potential to significantly accelerate CAD algorithm development.


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