Articular cartilage cushions the bones inside an articulation during motion. When a degenerative disease like arthritis erodes this protective layer, the joint may stop functioning properly.
Unfortunately, depending on the size of the joint we analyze, articular cartilage may be difficult to image in vivo. To generate wrist-cartilage images like the ones shown in the right column (bones shown in blue, cartilage in tan), bones may need to be extracted from the joint, immersed in contrast dye for 24 hours, then microsliced.
We developed a non-invasive method for estimating individual-specific cartilage maps directly from in vivo kinematic data and bone surfaces. The left-column images show cartilage maps estimated non-invasively, through our method. Note the excellent correlation with the maps estimated invasively, shown in the right-hand column.
We also present a novel algorithm for computing cartilage surface deformations. Our proposed cartilage model, a meshless incompressible height-field captures the physical properties important for estimating the shape, contact area, and deformation magnitude of cartilage at each articulation. This cartilage model can serve as an effective building block for a future forward-dynamic predictive model of the human wrist. [see the paper for details]