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Cell counting in human endobronchial biopsies - disagreement of 2D versus 3D morphometry

: Bratu, Vlad A.; Erpenbeck, Veit J.; Fehrenbach, Antonia; Rausch, Tanja; Rittinghausen, Susanne; Krug, Norbert; Hohlfeld, Jens M.; Fehrenbach, Heinz

Postprint urn:nbn:de:0011-n-2926674 (5.2 MByte PDF)
MD5 Fingerprint: ca11d15615020e51ab95c81c41ca004c
Erstellt am: 11.6.2014

PLoS one. Online journal 9 (2014), Nr.3, Art. e92510, 12 S.
ISSN: 1932-6203
Zeitschriftenaufsatz, Elektronische Publikation
Fraunhofer ITEM ()

Inflammatory cell numbers are important endpoints in clinical studies relying on endobronchial biopsies. Assumption-based bidimensional (2D) counting methods are widely used, although theoretically design-based stereologic three-dimensional (3D) methods alone offer an unbiased quantitative tool. We assessed the method agreement between 2D and 3D counting designs in practice when applied to identical samples in parallel.
Biopsies from segmental bronchi were collected from healthy non-smokers (n = 7) and smokers (n = 7), embedded and sectioned exhaustively. Systematic uniform random samples were immunohistochemically stained for macrophages (CD68) and T-lymphocytes (CD3), respectively. In identical fields of view, cell numbers per volume unit (NV) were assessed using the physical disector (3D), and profiles per area unit (NA) were counted (2D). For CD68+ cells, profiles with and without nucleus were separately recorded. In order to enable a direct comparison of the two methods, the zero-dimensional CD68+/CD3+-ratio was calculated for each approach. Method agreement was tested by Bland-Altmann analysis.
In both groups, mean CD68+/CD3+ ratios for NV and NA were significantly different (non-smokers: 0.39 and 0.68, p<0.05; smokers: 0.49 and 1.68, p<0.05). When counting only nucleated CD68+ profiles, mean ratios obtained by 2D and 3D counting were similar, but the regression-based Bland-Altmann analysis indicated a bias of the 2D ratios proportional to their magnitude. This magnitude dependent deviation differed between the two groups.
2D counts of cell and nuclear profiles introduce a variable size-dependent bias throughout the measurement range. Because the deviation between the 3D and 2D data was different in the two groups, it precludes establishing a 'universal conversion formula'.