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Diagnosing Osteomyelitis: A Histology Guide for Pathologists.

Amelia B Sybenga1, Daniel C Jupiter2, V O Speights3

  • 1Clinical Fellow, Department of Pathology, Microbiology and Immunology, Vanderbilt University Medical Center, Nashville, TN.

The Journal of Foot and Ankle Surgery : Official Publication of the American College of Foot and Ankle Surgeons
|November 23, 2019
PubMed
Summary
This summary is machine-generated.

A new algorithmic tool improves osteomyelitis (OM) diagnosis by categorizing cases into five types based on histopathology. This method enhances diagnostic accuracy and identifies previously undiagnosed OM cases, potentially predicting complications.

Keywords:
diagnosisdiagnosticshistopathologyinfectioninvolucrumneutrophilosteomyelitisperiosteal reaction

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Area of Science:

  • Histopathology
  • Medical Diagnostics
  • Skeletal System Diseases

Background:

  • Osteomyelitis (OM) diagnosis relies on histopathology and bone culture, but interpathologist agreement is low (30%) due to undefined criteria.
  • Existing literature reveals a histologic progression of OM from acute to chronic phases, suggesting potential for subcategorization.
  • Lack of standardized diagnostic criteria hinders accurate and consistent osteomyelitis diagnosis.

Purpose of the Study:

  • To develop and validate an algorithmic histopathologic tool for classifying osteomyelitis (OM).
  • To define five distinct categories of OM: acute, acute and chronic, chronic, chronic active, and chronic inactive.
  • To assess the association of a histopathologic load score (Jupiter score) with OM categories.

Main Methods:

  • Developed a 15-criterion algorithmic tool with associated scores for OM histopathology.
  • Reviewed 462 slides from 263 patients with suspected OM, applying the algorithm for diagnosis.
  • Calculated a total histopathologic load score (Jupiter score) for each case.

Main Results:

  • The algorithm-derived diagnoses aligned with original clinical diagnoses and identified new OM cases.
  • Newly diagnosed OM cases showed a higher likelihood of subsequent clinical complications.
  • The study assessed the correlation between histopathologic load scores and the defined OM categories.

Conclusions:

  • An algorithmic histopathologic tool can standardize osteomyelitis diagnosis and improve accuracy.
  • The defined OM categories and Jupiter score offer a more nuanced understanding of the disease.
  • This approach may aid in predicting clinical outcomes and guiding treatment strategies for osteomyelitis.