Hans Blaauwgeers

181 Pattern recognition in pulmonary AdC; a modified classification To test both hypotheses, morphometry was performed on cases from two cohorts of resection specimen with a primary pulmonary adenocarcinoma of a pathologic tumour diameter ≦ 3 cm. CK7 stained slides were digitized and the point counting method performed according to Weibel321 (see for methodology Figure 4). Figure 4 and methodology according to Weibel321 . A rectangle of 14,7x12,5 cm containing 63 dots of 1x1 mm, all within equal distance, was designed and printed on a plastic sheet, see photo. The overhead sheet with dots was superimposed on the screen showing the digital tumour image. The dots were projected on top of either “air”, “cell”, “nucleus” or “stroma”. Four tumour areas on CK7 were chosen for each case: two different areas with a prominent amount of “air” (or the largest “air” spaces present) and two severely iatrogenic collapsed areas with minimal “air”. Each area was counted at the same (20x) magnification. The number of dots in the air spaces, on the cells (both nucleus and cytoplasm) and in the stroma were recorded. Dots on alveolar macrophages or cellular debris floating in the alveolar space were regarded as “air” spaces dots. Dots that fall on structures that were not clearly recognizable, because of technical artifacts as one of the three components (cells/stroma/air) were not assigned. The relative fractions of a) air, b) cells (including dots on nuclei) and c) stroma were calculated. The relative fractions of a) air, b) tumour cells and c) stroma were calculated. Subsequently, the minimum and maximum apicobasal tumour cell height was measured in microns with a ruler available in the software (Philips IntelliSite Pathology solution, Image management system 3.3 (1.4). For the latter measurement, only cells with clearly discernible profiles were selected, while for instance areas of tangential cutting with 14

RkJQdWJsaXNoZXIy MTk4NDMw