Load distribution of articular cartilage from MR-images by neural nets

Artificial neural nets were used to determine the Young's modulus and spatial load distribution in articular cartilage by means of T2-weighted MR imaging. MR images were obtained in vitro (ex vivo?) from the joints of sheep of different ages (3 months, 9 months, 15 months, 1.5 years, 5 years, 5.5 years) and pigs (4 and 6 months) with a Bruker AMX 300 (7 T) spectrometer equipped with a micro-imaging unit. The knee of a 29-year-old male volunteer was studied in vivo under mechanical load using a clinical Siemens Vision MRT (1.5 T). The load of the cartilage is understood as a non-linear image transformation of loaded versus unloaded images. The artificial neural net was used to recognize given reference pixels of the unloaded cartilage within the image of the loaded cartilage. The Young's modulus was calculated from the local strain and the external pressure using the Hooke's law. With this method, the average Young's modulus was obtained in relationship to the biological age of the cartilage. The investigated age interval showed a progressive increase of 0.5 +/- 0.3 MPa per year. These results are consistent with published results. As shown in this pilot study, the method of neural nets allows the visualization of the spatial load distribution within the articular cartilage.