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Automated image analysis methods for 3‐D quantification of the neurovascular unit from multichannel confocal microscope images
Author(s) -
Lin Gang,
Bjornsson Chris S.,
Smith Karen L.,
AbdulKarim MuhammadAmri,
Turner James N.,
Shain William,
Roysam Badrinath
Publication year - 2005
Publication title -
cytometry part a
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.316
H-Index - 90
eISSN - 1552-4930
pISSN - 1552-4922
DOI - 10.1002/cyto.a.20149
Subject(s) - confocal , microscope , neurovascular bundle , confocal microscopy , confocal laser scanning microscope , microscopy , multiphoton fluorescence microscope , image processing , computer science , biomedical engineering , artificial intelligence , optics , materials science , image (mathematics) , medicine , fluorescence microscope , pathology , physics , fluorescence
Background There is a need for integrative and quantitative methods to investigate the structural and functional relations among elements of complex systems, such as the neurovascular unit (NVU), that involve multiple cell types, microvasculatures, and various genomic/proteomic/ionic functional entities. Methods Vascular casting and selective labeling enabled simultaneous three‐dimensional imaging of the microvasculature, cell nuclei, and cytoplasmic stains. Multidimensional segmentation was achieved by (i) bleed‐through removal and attenuation correction; (ii) independent segmentation and morphometry for each corrected channel; and (iii) spatially associative feature computation across channels. The combined measurements enabled cell classification based on nuclear morphometry, cytoplasmic signals, and distance from vascular elements. Specific spatial relations among the NVU elements could be quantified. Results A software system combining nuclear and vessel segmentation codes and associative features was constructed and validated. Biological variability contributed to misidentified nuclei (9.3%), undersegmentation of nuclei (3.7%), hypersegmentation of nuclei (14%), and missed nuclei (4.7%). Microvessel segmentation errors occurred rarely, mainly due to nonuniform lumen staining. Conclusions Associative features across fluorescence channels, in combination with standard features, enable integrative structural and functional analysis of the NVU. By labeling additional structural and functional entities, this method can be scaled up to larger‐scale systems biology studies that integrate spatial and molecular information. © 2005 Wiley‐Liss, Inc.