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A system for sharing routine surgical pathology specimens across institutions: the Shared Pathology Informatics

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A new Web-based system enables pathologists to efficiently search and retrieve pathology specimens from multiple institutions, accelerating cancer research. This informatics tool facilitates finding relevant paraffin blocks for studies.

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Area of Science:

  • Pathology Informatics
  • Biomedical Informatics
  • Cancer Research Informatics

Background:

  • Pathology specimens are crucial for research but difficult to access across institutions.
  • Existing systems lack efficient methods for searching and retrieving paraffin blocks.
  • The National Cancer Institute's Shared Pathology Informatics Network (SPIN) program aimed to address this gap.

Purpose of the Study:

  • To develop a novel Web-enabled system for indexing and retrieving pathology specimens across multiple institutions.
  • To create a prototype system for identifying paraffin blocks relevant to cancer research.
  • To overcome challenges in data sharing while maintaining local control and privacy.

Main Methods:

  • Development of a Web-based informatics system with local data control.
  • Creation of an eXtensible Markup Language (XML) schema for specimen data.
  • Implementation of deidentification methods for pathology reports.
  • Utilizing the Unified Medical Language System (UMLS) for automated data coding.
  • Establishing robust confidentiality and consent hierarchies.

Main Results:

  • The prototype system allows Web-based querying of millions of pathology reports from six institutions.
  • Search and retrieval of relevant pathology reports and paraffin blocks are achieved in seconds to minutes.
  • Researchers can identify and request specific paraffin blocks from participating institutions.

Conclusions:

  • The developed system successfully enables efficient, multi-institutional access to pathology specimens.
  • This informatics solution has significant potential to expand annotated tissue availability for cancer and other disease research.
  • Future integration with clinical and outcome data will further enhance its research utility.