OBJECTIVES: To implement a novel voxel-based technique to identify statistically significant local cartilage deformation and analyze in-vivo topographic knee cartilage deformation patterns using a voxel-based thickness map approach for high-flexion postures. METHODS: Sagittal 3T 3D-T1w-FLASH-WE-sequences of 10 healthy knees were acquired before and immediately after loading (kneeling/squatting/heel sitting/knee bends). After cartilage segmentation, 3D-reconstruction and 3D-registration, colour-coded deformation maps were generated by voxel-based subtraction of loaded from unloaded datasets to visualize cartilage thickness changes in all knee compartments. RESULTS: Compression areas were found bifocal at the peripheral medial/caudolateral patella, both posterior femoral condyles and both anterior/central tibiae. Local cartilage thickening were found adjacent to the compression areas. Significant local strain ranged from +13 to -15 %. Changes were most pronounced after squatting, least after knee bends. Shape and location of deformation areas varied slightly with the loading paradigm, but followed a similar pattern consistent between different individuals. CONCLUSIONS: Voxel-based deformation maps identify individual in-vivo load-specific and posture-associated strain distribution in the articular cartilage. The data facilitate understanding individual knee loading properties and contribute to improve biomechanical 3 models. They lay a base to investigate the relationship between cartilage degeneration patterns in common osteoarthritis and areas at risk of cartilage wear due to mechanical loading in work-related activities. KEY POINTS: • 3D MRI helps differentiate true knee-cartilage deformation from random measurement error • 3D MRI maps depict in vivo topographic distribution of cartilage deformation after loading • 3D MRI maps depict in vivo intensity of cartilage deformation after loading • Locating cartilage contact areas might aid differentiating common and work-related osteoarthritis.
OBJECTIVES: To implement a novel voxel-based technique to identify statistically significant local cartilage deformation and analyze in-vivo topographic knee cartilage deformation patterns using a voxel-based thickness map approach for high-flexion postures. METHODS: Sagittal 3T 3D-T1w-FLASH-WE-sequences of 10 healthy knees were acquired before and immediately after loading (kneeling/squatting/heel sitting/knee bends). After cartilage segmentation, 3D-reconstruction and 3D-registration, colour-coded deformation maps were generated by voxel-based subtraction of loaded from unloaded datasets to visualize cartilage thickness changes in all knee compartments. RESULTS: Compression areas were found bifocal at the peripheral medial/caudolateral patella, both posterior femoral condyles and both anterior/central tibiae. Local cartilage thickening were found adjacent to the compression areas. Significant local strain ranged from +13 to -15 %. Changes were most pronounced after squatting, least after knee bends. Shape and location of deformation areas varied slightly with the loading paradigm, but followed a similar pattern consistent between different individuals. CONCLUSIONS: Voxel-based deformation maps identify individual in-vivo load-specific and posture-associated strain distribution in the articular cartilage. The data facilitate understanding individual knee loading properties and contribute to improve biomechanical 3 models. They lay a base to investigate the relationship between cartilage degeneration patterns in common osteoarthritis and areas at risk of cartilage wear due to mechanical loading in work-related activities. KEY POINTS: • 3D MRI helps differentiate true knee-cartilage deformation from random measurement error • 3D MRI maps depict in vivo topographic distribution of cartilage deformation after loading • 3D MRI maps depict in vivo intensity of cartilage deformation after loading • Locating cartilage contact areas might aid differentiating common and work-related osteoarthritis.
Authors: Guoan Li; Sang Eun Park; Louis E DeFrate; Matthew E Schutzer; Lunan Ji; Thomas J Gill; Harry E Rubash Journal: Clin Biomech (Bristol, Avon) Date: 2005-08 Impact factor: 2.063
Authors: F Eckstein; B Lemberger; C Gratzke; M Hudelmaier; C Glaser; K-H Englmeier; M Reiser Journal: Ann Rheum Dis Date: 2005-02 Impact factor: 19.103
Authors: J T Bingham; R Papannagari; S K Van de Velde; C Gross; T J Gill; D T Felson; H E Rubash; G Li Journal: Rheumatology (Oxford) Date: 2008-09-05 Impact factor: 7.580
Authors: Nimit K Lad; Betty Liu; Pramodh K Ganapathy; Gangadhar M Utturkar; E Grant Sutter; Claude T Moorman; William E Garrett; Charles E Spritzer; Louis E DeFrate Journal: J Biomech Date: 2016-06-27 Impact factor: 2.712