Blockface histology with optical coherence tomography: A comparison with Nissl staining

• DOI: 10.1016/j.neuroimage.2013.08.072
• Publication Date: 2013-09-13T18:17:44Z
• Authors: Caroline Magnain; Jean C. Augustinack; Martin Reuter; Christian Wachinger; Matthew P. Frosch; Timothy Ragan; Taner Akkin; Van J. Wedeen; David A. Boas; Bruce Fischl
• Keywords: Aged, 80 and over; Brain Chemistry; Male; Neurons; 0301 basic medicine; Aniline Compounds; Staining and Labeling; Brain; Reproducibility of Results; Middle Aged; Image Enhancement; Sensitivity and Specificity; 03 medical and health sciences; 0302 clinical medicine; Subtraction Technique; Image Interpretation, Computer-Assisted; Humans; Female; 10. No inequality; Tomography, Optical Coherence; Aged

Spectral domain optical coherence tomography (SD-OCT) is a high resolution imaging technique that generates excellent contrast based on intrinsic optical properties of the tissue, such as neurons and fibers. The SD-OCT data acquisition is performed directly on the tissue block, diminishing the need for cutting, mounting and staining. We utilized SD-OCT to visualize the laminar structure of the isocortex and compared cortical cytoarchitecture with the gold standard Nissl staining, both qualitatively and quantitatively. In histological processing, distortions routinely affect registration to the blockface image and prevent accurate 3D reconstruction of regions of tissue. We compared blockface registration to SD-OCT and Nissl, respectively, and found that SD-OCT-blockface registration was significantly more accurate than Nissl-blockface registration. Two independent observers manually labeled cortical laminae (e.g. III, IV and V) in SD-OCT images and Nissl stained sections. Our results show that OCT images exhibit sufficient contrast in the cortex to reliably differentiate the cortical layers. Furthermore, the modalities were compared with regard to cortical laminar organization and showed good agreement. Taken together, these SD-OCT results suggest that SD-OCT contains information comparable to standard histological stains such as Nissl in terms of distinguishing cortical layers and architectonic areas. Given these data, we propose that SD-OCT can be used to reliably generate 3D reconstructions of multiple cubic centimeters of cortex that can be used to accurately and semi-automatically perform standard histological analyses.