Automatic quantification of tibio-femoral contact area and congruity

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We present methods to quantify the medial tibio- femoral (MTF) joint contact area (CA) and congruity index (CI) from low-field magnetic resonance imaging (MRI). Firstly, based on the segmented MTF cartilage compartments, we computed the contact area using the Euclidian distance transformation. The CA was defined as the area of the tibial superior surface and the femoral inferior surface that are less than a voxel width apart. Furthermore, the CI is computed point-by-point by assessing the first- and second-order general surface features over the contact area. Mathematically, it is the inverse distance between the local normal vectors (first-order features) scaled by the local normal curvatures (second-order features) along the local direction of principal knee motion in a local reference coordinate system formed by the directions of principal curvature and the surface normal vector. The abilities of the CA and the CI for diagnosing osteoarthritis (OA) at different levels (disease severity was assessed using the Kellgren and Lawrence Index, KL) were cross-validated on 288 knees at baseline. Longitudinal analysis was performed on 245 knees. The precision quantified on 31 scan-rescan pairs (RMS CV) for CA was 13.7% and for CI 7.5%. The CA increased with onset of the disease and then decreased with OA progression. The CI was highest in healthy and decreased with the onset of OA and further with disease progression. The CI showed an AUC of 0.69 (p ; 0. For separating KL ; 1 knees, the AUC for CI was 0.73 (p
Original languageEnglish
JournalI E E E Transactions on Medical Imaging
Issue number7
Pages (from-to)1404-1412
Number of pages9
Publication statusPublished - 2012

    Research areas

  • biomedical MRI, bone, diseases, medical disorders, orthopaedics, MRI, OA progression, automatic quantification, congruity index, contact area, disease progression, euclidian distance transformation, femoral inferior surface, first-order general surface features, local normal curvatures, local reference coordinate system, longitudinal analysis, low-field magnetic resonance imaging, medial tibiofemoral joint contact area, osteoarthritis, principal curvature, principal knee motion, scan-rescan pairs, second-order general surface features, segmented MTF cartilage compartments, surface normal vector, tibial superior surface, voxel width, Biomechanics, Equations, Indexes, Joints, Magnetic resonance imaging, Mathematical model, Vectors, Congruity, knee osteoarthritis, magnetic resonance imaging, normal curvature, Adult, Aged, Aged, 80 and over, Algorithms, Cartilage, Articular, Case-Control Studies, Disease Progression, Femur, Humans, Knee Joint, Magnetic Resonance Imaging, Middle Aged, Osteoarthritis, Knee, Reproducibility of Results, Tibia

ID: 45437512