title: [Histopathological particle algorithm. Particle identification in the synovia and the SLIM].
abstract: BACKGROUND
  In the histopathological diagnostics of synovitis and the synovium-like interface membrane (SLIM) the identification of crystals and crystal-like deposits and the associated inflammatory reactions play an important role. The multitude of endogenous crystals, the range of implant materials and material combinations, and the variability in the formation process of different particles explain the high morphological particle heterogeneity which complicates the diagnostic identification of diagnostic particles.
  
  
  METHODS
  A simple histopathological particle algorithm has been designed which allows methodological particle identification based on (1) conventional transmitted light microscopy with a guide to particle size, shape and color, (2) optical polarization criteria and (3) enzyme histochemical properties (oil red staining and Prussian blue reaction). These methods, the importance for particle identification and the differential diagnostics from non-prosthetic materials are summarized in the so-called histopathological particle algorithm.
  
  
  RESULTS
  A total of 35 cases of synovitis and SLIM were analyzed and validated according to these criteria. Based on these criteria and a dichotomous differentiation the complete spectrum of particles in the SLIM and synovia can be defined histopathologically.
  
  
  CONCLUSIONS
  For histopathological diagnosis a particle score for synovitis and SLIM is recommended to evaluate (1) the predominant type of prothetic wear debris with differentiation between microparticles, and macroparticles, (2) the presence of non-prosthesis material particles and (3) the quantification of particle-association necrosis and lymphocytosis. An open, continuously updated web-based particle algorithm would be helpful to address the issue of particle heterogeneity and include all new particle materials generated in a rapidly changing field.
authors.affiliation: MVZ-Zentrum für Histologie, Zytologie und Molekulare Diagnostik, Max-Planck-Str. 5, 54296, Trier, Deutschland, krenn@patho-trier.de.
authors.forename: V
authors.initials: V
authors.lastname: Krenn
authors.forename: P
authors.initials: P
authors.lastname: Thomas
authors.forename: M
authors.initials: M
authors.lastname: Thomsen
authors.forename: J P
authors.initials: JP
authors.lastname: Kretzer
authors.forename: S
authors.initials: S
authors.lastname: Usbeck
authors.forename: L
authors.initials: L
authors.lastname: Scheuber
authors.forename: G
authors.initials: G
authors.lastname: Perino
authors.forename: W
authors.initials: W
authors.lastname: Rüther
authors.forename: R
authors.initials: R
authors.lastname: v Welser
authors.forename: F
authors.initials: F
authors.lastname: Hopf
authors.forename: M
authors.initials: M
authors.lastname: Huber
mesh_terms: D000368:Aged; D000465:Algorithms; D005260:Female; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013583:Synovial Membrane / Q000473:pathology*; D013585:Synovitis / Q000473:pathology*