The Gross Room’s Digital Makeover - Scorecard - MDSpire
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The Gross Room’s Digital Makeover

  • By

  • Jessica Allerton

  • October 22, 2026

  • 8 min

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Clinical Scorecard: The Gross Room’s Digital Makeover

At a Glance

CategoryDetail
ConditionDigital technologies and workflows for specimen grossing
Key MechanismsThe article groups digital grossing technologies into intake (documenting specimens), integration (connecting information), and intelligence (applying computational tools and AI). Examples discussed include annotated photography, specimen radiography, three-dimensional imaging, voice recognition, adaptive templates, and computational tools.
Target PopulationPathologists, pathologists’ assistants, and laboratory teams involved in specimen grossing
Care SettingGrossing laboratories; the source does not specify particular institution types.

Key Highlights

  • Gross specimens vary in size, shape, orientation, texture, and clinical context, making digitization more complex than digitizing standardized glass slides.
  • Digital grossing technologies include annotated photography, specimen radiography, three-dimensional imaging, voice recognition, and adaptive templates.
  • Interoperability can keep images, measurements, annotations, and sampling details linked to specimens throughout the pathology workflow.
  • Computational tools may support reproducible measurement and automate repetitive tasks, while professionals retain responsibility for decisions requiring judgment.
  • Successful adoption should begin with a defined laboratory problem; cost and leadership support are among the factors discussed.

Guideline-Based Recommendations

Diagnosis

  • The interview notes that much of the information needed for staging comes from the gross specimen.

Management

  • The interview suggests identifying which aspects of grossing technology could improve and introducing tools without disrupting professional judgment.
  • The interview describes interoperability as keeping images, measurements, annotations, sampling details, and other observations linked to the specimen and accessible throughout the workflow.
  • The interview frames computational tools as support for the person making decisions, not as replacements for professional judgment.

Monitoring & Follow-up

  • The interview describes digital imaging as a potential way to make measurements more reproducible and quantify features that are difficult to estimate consistently.
  • The interview discusses structured information linked to specimen images and computational tools for repetitive tasks as possible workflow improvements.

Risks

  • The source describes variability in specimen size, shape, orientation, texture, and clinical context as a challenge for digitization.
  • The source warns that information can be trapped in standalone cameras or workstations rather than remaining accessible across the workflow.
  • The source cautions against replacing professional judgment with an algorithm.

Patient & Prescribing Data

Not specified; the article discusses laboratory workflows and specimen examination rather than patient treatment.

No prescribing or treatment regimen is provided. The article notes that some visually estimated gross-specimen percentages may influence treatment.

Clinical Best Practices

  • Consider structured information linked directly to specimen images, as discussed in the interview.
  • The interview identifies measurement, documentation, specimen identification, tracking, calculations, photography, and dictation as repetitive tasks that technology might support.
  • The interview emphasizes providing better information to the professional making the decision rather than replacing professional judgment.
  • Consider interoperability so specimen information remains accessible throughout the pathology workflow.

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Original Source(s)

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