Abstract
To characterize the microstructural organization of collagen fibers in human medial menisci and the response to mechanical loading in relation to age. We combine high resolution imaging with mechanical compression to visualize the altered response of the tissue at the microscale. Menisci distribute the load in the knee and are predominantly composed of water and specifically hierarchically arranged collagen fibers. Structural and compositional changes are known to occur in the meniscus during aging and development of osteoarthritis. However, how microstructural changes due to degeneration affect mechanical performance is still largely unknown [1].
Fresh frozen 4 mm Ø plugs of human medial menisci (n=15, men, 20-85 years) with no macroscopic damage nor known diseases from the MENIX biobank at Skåne University Hospital were imaged by phase contrast synchrotron tomography at the TOMCAT beamline (Paul Scherrer Institute, CH). A rheometer was implemented into the beamline to perform in-situ stress relaxation (2 steps 15% and 30% strain) during imaging (21 keV, 2.75μm pixel size). 40s scans were acquired before and after loading, while 14 fast tomographs (5s acquisitions) were taken during relaxation. The fiber 3D orientations and structural changes during loading were determined using a structure tensor approach (adapting a script from [1]). The 3D collagen fiber orientation in menisci revealed alternating layers of fibers. Two main areas are shown: surfaces and bulk. The surface layers are a mesh of randomly oriented fibers. Within the bulk 2-3 layers of fibers are visible that alternate about 30° to each other. Structural degeneration with age is visible and is currently being quantified. During stress-relaxation all menisci show a similar behavior, with samples from older donors being characterized by larger standard deviation Furthermore, the behavior of the different layers of fibers is tracked during relaxation showing how fibers with different orientation respond to the applied loading.
Acknowledgments: We thank PSI for the beamtime at the TOMCAT beamline X02DA, and funding from Swedish Research Council (2019-00953), under the frame of ERA PerMed, and the Novo Nordisk Foundation through MathKOA (NNF21OC0065373).
