Volumetric Characterization of Microvasculature in Ex Vivo Human Brain Samples By Serial Sectioning Optical Coherence Tomography
Jiarui Yang, Shuaibin Chang, Anderson Chen, Sreekanth Kura, Grace A. Rosen, Nicole Saltiel, Bertrand R. Huber, Divya Varadarajan, Yaël Balbastre, Caroline Magnain, Shih‐Chi Chen, Bruce Fischl, Ann C. McKee, David A. Boas, Hui Wang
Abstract
OBJECTIVE: Serial sectioning optical coherence tomography (OCT) enables accurate volumetric reconstruction of several cubic centimeters of human brain samples. We aimed to identify anatomical features of the ex vivo human brain, such as intraparenchymal blood vessels and axonal fiber bundles, from the OCT data in 3D, using intrinsic optical contrast. METHODS: We developed an automatic processing pipeline to enable characterization of the intraparenchymal microvascular network in human brain samples. RESULTS: We demonstrated the automatic extraction of the vessels down to a 20 μm in diameter using a filtering strategy followed by a graphing representation and characterization of the geometrical properties of microvascular network in 3D. We also showed the ability to extend this processing strategy to extract axonal fiber bundles from the volumetric OCT image. CONCLUSION: This method provides a viable tool for quantitative characterization of volumetric microvascular network as well as the axonal bundle properties in normal and pathological tissues of the ex vivo human brain.