Digital Transplantation Pathology: Combining Whole Slide Imaging, Multiplex Staining and Automated Image Analysis

Authors

  • K. Isse,

    1. Department of Pathology, Division of Transplantation, University of Pittsburgh Medical Center, Pittsburgh, PA
    2. Department of Pathology, Tomas E. Starzl Transplantation Institute, University of Pittsburgh, Pittsburgh, PA
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  • A. Lesniak,

    1. Department of Pathology, Division of Transplantation, University of Pittsburgh Medical Center, Pittsburgh, PA
    2. Department of Pathology, Tomas E. Starzl Transplantation Institute, University of Pittsburgh, Pittsburgh, PA
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  • K. Grama,

    1. Department of Electrical & Computer Engineering, University of Houston, Houston, TX
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  • B. Roysam,

    1. Department of Electrical & Computer Engineering, University of Houston, Houston, TX
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  • M. I. Minervini,

    1. Department of Electrical & Computer Engineering, University of Houston, Houston, TX
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  • A. J. Demetris

    Corresponding author
    1. Department of Pathology, Division of Transplantation, University of Pittsburgh Medical Center, Pittsburgh, PA
    2. Department of Pathology, Tomas E. Starzl Transplantation Institute, University of Pittsburgh, Pittsburgh, PA
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Anthony J. Demetris, demetrisaj@upmc.edu

Abstract

Conventional histopathology is the gold standard for allograft monitoring, but its value proposition is increasingly questioned. “-Omics” analysis of tissues, peripheral blood and fluids and targeted serologic studies provide mechanistic insights into allograft injury not currently provided by conventional histology. Microscopic biopsy analysis, however, provides valuable and unique information: (a) spatial-temporal relationships; (b) rare events/cells; (c) complex structural context; and (d) integration into a “systems” model. Nevertheless, except for immunostaining, no transformative advancements have “modernized” routine microscopy in over 100 years. Pathologists now team with hardware and software engineers to exploit remarkable developments in digital imaging, nanoparticle multiplex staining, and computational image analysis software to bridge the traditional histology—global “-omic” analyses gap. Included are side-by-side comparisons, objective biopsy finding quantification, multiplexing, automated image analysis, and electronic data and resource sharing. Current utilization for teaching, quality assurance, conferencing, consultations, research and clinical trials is evolving toward implementation for low-volume, high-complexity clinical services like transplantation pathology. Cost, complexities of implementation, fluid/evolving standards, and unsettled medical/legal and regulatory issues remain as challenges. Regardless, challenges will be overcome and these technologies will enable transplant pathologists to increase information extraction from tissue specimens and contribute to cross-platform biomarker discovery for improved outcomes.

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