title: Utility of multispectral imaging in automated quantitative scoring of immunohistochemistry.
abstract: BACKGROUND
  Automated scanning devices and image analysis software provide a means to overcome the limitations of manual semiquantitative scoring of immunohistochemistry. Common drawbacks to automated imaging systems include an inability to classify tissue type and an inability to segregate cytoplasmic and nuclear staining.
  
  
  METHODS
  Immunohistochemistry for the membranous marker α-catenin, the cytoplasmic marker stathmin and the nuclear marker Ki-67 was performed on tissue microarrays (TMA) of archival formalin-fixed paraffin-embedded tissue comprising 471 (α-catenin and stathmin) and 511 (Ki-67) cases of prostate adenocarcinoma. These TMA were quantitatively analysed using two commercially available automated image analysers, the Ariol SL-50 system and the Nuance system from CRi. Both systems use brightfield microscopy for automated, unbiased and standardised quantification of immunohistochemistry, while the Nuance system has spectral deconvolution capabilities.
  
  
  RESULTS
  Overall concordance between scores from both systems was excellent (r=0.90; 0.83-0.95). The software associated with the multispectral imager allowed accurate automated classification of tissue type into epithelial glandular structures and stroma, and a single-step segmentation of staining into cytoplasmic or nuclear compartments allowing independent evaluation of these areas. The Nuance system, however, was not able to distinguish reliably between tumour and non-tumour tissue. In addition, variance in the labour and time required for analysis between the two systems was also noted.
  
  
  CONCLUSIONS
  Despite limitations, this study suggests some beneficial role for the use of a multispectral imaging system in automated analysis of immunohistochemistry.
authors.affiliation: Center for Molecular Oncologic Pathology, Dana Farber Cancer Institute, Boston, Massachusetts, USA.
authors.forename: Christopher
authors.initials: C
authors.lastname: Fiore
authors.forename: Dyane
authors.initials: D
authors.lastname: Bailey
authors.forename: Niamh
authors.initials: N
authors.lastname: Conlon
authors.forename: Xiaoqiu
authors.initials: X
authors.lastname: Wu
authors.forename: Neil
authors.initials: N
authors.lastname: Martin
authors.forename: Michelangelo
authors.initials: M
authors.lastname: Fiorentino
authors.forename: Stephen
authors.initials: S
authors.lastname: Finn
authors.forename: Katja
authors.initials: K
authors.lastname: Fall
authors.forename: Swen-Olof
authors.initials: SO
authors.lastname: Andersson
authors.forename: Ove
authors.initials: O
authors.lastname: Andren
authors.forename: Massimo
authors.initials: M
authors.lastname: Loda
authors.forename: Richard
authors.initials: R
authors.lastname: Flavin
mesh_terms: D000230:Adenocarcinoma / Q000737:chemistry / Q000175:diagnosis; D000368:Aged; D000369:Aged, 80 and over; D014408:Biomarkers, Tumor / Q000032:analysis*; D002462:Cell Membrane / Q000737:chemistry / Q000473:pathology; D002467:Cell Nucleus / Q000737:chemistry / Q000473:pathology; D003593:Cytoplasm / Q000737:chemistry / Q000473:pathology; D006801:Humans; D007091:Image Processing, Computer-Assisted; D007150:Immunohistochemistry / Q000295:instrumentation* / Q000379:methods*; D019394:Ki-67 Antigen / Q000032:analysis; D008297:Male; D008875:Middle Aged; D011471:Prostatic Neoplasms / Q000737:chemistry / Q000175:diagnosis; D015203:Reproducibility of Results; D012984:Software; D050777:Stathmin / Q000032:analysis; D051178:alpha Catenin / Q000032:analysis
chemical_list: D014408:Biomarkers, Tumor; D019394:Ki-67 Antigen; C493995:STMN1 protein, human; D050777:Stathmin; D051178:alpha Catenin