IEEE Trans Biomed Eng. 2022 Dec;69(12):3645-3656. doi: 10.1109/TBME.2022.3175072. Epub 2022 Nov 23.
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.
We developed an automatic processing pipeline to enable characterization of the intraparenchymal microvascular network in human brain samples.
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.
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.
连续切片光学相干断层扫描（OCT）可实现数立方厘米人类脑组织样本的精确体积重建。我们旨在利用固有光学对比度，从 OCT 数据中以三维方式识别离体人脑的解剖特征，如脑实质内血管和轴突纤维束。
我们开发了一种自动处理管道，以实现对人脑样本中脑实质微血管网络的特征描述。
我们通过过滤策略、图形表示和三维微血管网络几何性质的特征描述，证明了自动提取直径达 20μm 的血管的能力。我们还展示了将这种处理策略扩展到从体积 OCT 图像中提取轴突纤维束的能力。
该方法为离体人脑正常和病变组织中体积微血管网络以及轴突束特性的定量描述提供了一种可行的工具。
