title: Quantifying tumour-infiltrating lymphocyte subsets: a practical immuno-histochemical method.
abstract: BACKGROUND
  Efficient histological quantification of tumour-infiltrating T and B lymphocyte (TIL) subsets in archival tissues would greatly facilitate investigations of the role of TIL in human cancer biology. We sought to develop such a method.
  
  
  METHODS
  Ten x40 digital images of 4 micro sections of 16 ductal invasive breast carcinomas immunostained for CD3, CD4, CD8, and CD20 were acquired (a total of 640 images). The number of pixels in each image matching a partition of Lab colour space corresponding to immunostained cells were counted using the 'Color range' and 'Histogram' tools in Adobe Photoshop 7. These pixel counts were converted to cell counts per mm(2) using a calibration factor derived from one, two, three or all 10 images of each case/antibody combination.
  
  
  RESULTS
  Variations in the number of labelled pixels per immunostained cell made individual calibration for each case/antibody combination necessary. Calibration based on two fields containing the most labelled pixels gave a cell count minimally higher (+5.3%) than the count based on 10-field calibration, with 95% confidence limits -14.7 to +25.3%. As TIL density could vary up to 100-fold between cases, this accuracy and precision are acceptable.
  
  
  CONCLUSIONS
  The methodology described offers sufficient accuracy, precision and efficiency to quantify the density of TIL sub-populations in breast cancer using commonly available software, and could be adapted to batch processing of image files.
authors.affiliation: Section of Surgical Sciences and Translational Research, University of Glasgow, UK.
authors.forename: Paula M
authors.initials: PM
authors.lastname: Loughlin
authors.forename: Timothy G
authors.initials: TG
authors.lastname: Cooke
authors.forename: W David
authors.initials: WD
authors.lastname: George
authors.forename: Alison J
authors.initials: AJ
authors.lastname: Gray
authors.forename: David I
authors.initials: DI
authors.lastname: Stott
authors.forename: James J
authors.initials: JJ
authors.lastname: Going
mesh_terms: D000465:Algorithms; D018951:Antigens, CD20 / Q000032:analysis; D000951:Antigens, Neoplasm / Q000032:analysis*; D001943:Breast Neoplasms / Q000276:immunology*; D017252:CD3 Complex / Q000032:analysis; D015704:CD4 Antigens / Q000032:analysis; D016827:CD8 Antigens / Q000032:analysis; D002138:Calibration; D018270:Carcinoma, Ductal, Breast / Q000276:immunology*; D002452:Cell Count / Q000379:methods; D005260:Female; D006801:Humans; D007090:Image Interpretation, Computer-Assisted; D007150:Immunohistochemistry / Q000379:methods* / Q000592:standards; D016130:Immunophenotyping / Q000379:methods; D016131:Lymphocyte Subsets / Q000276:immunology*; D016246:Lymphocytes, Tumor-Infiltrating / Q000276:immunology*; D010865:Pilot Projects; D015203:Reproducibility of Results; D012984:Software
chemical_list: D018951:Antigens, CD20; D000951:Antigens, Neoplasm; D017252:CD3 Complex; D015704:CD4 Antigens; D016827:CD8 Antigens