Official websites use. Share sensitive information only on official, secure websites. You do not have permission under this licence to share adapted material derived from this article or parts of it.
Osteochondral interface consists of two tissues: the calcified cartilage CC containing chondrocytes, and subchondral bone SCB containing osteocytes that interact with each other.
In this study, we propose a new method for the three-dimensional 3D segmentation of chondrocyte and osteocyte lacunae in CC and SCB from human knees, imaged using high resolution nm synchrotron radiation phase contrast micro-computed tomography SR phase contrast micro-CT.
Our approach is based on marker-controlled watershed MCW algorithm combined with a deep learning method nnU-Net. We demonstrate that incorporating nnU-Net into the MCW process improves the identification and segmentation of cell lacunae. Using this method, we analyzed a subsample of fifteen cores extracted from the central area of the medial tibial plateaus.
Several quantitative parameters lacunar volume fraction, number density, volume, anisotropy and structure model index of cell lacunae were measured to compare 10 control and 5 osteoarthritic knees. This new method may help to better understand the cellular behavior at the osteochondral interface in osteoarthritis.
