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Quantification of differences in bone texture from plain radiographs in knees with and without osteoarthritis.

Hirvasniemi, J; Thevenot, J; Immonen, V; Liikavainio, T; Pulkkinen, P; Jämsä, T; Arokoski, J; Saarakkala, S.
Osteoarthritis Cartilage; 22(10): 1724-31, 2014 Oct.
Artigo em Inglês | MEDLINE | ID: mdl-25278081


To quantify differences in bone texture between subjects with different stages of knee osteoarthritis (OA) and age- and gender-matched controls from plain radiographs using advanced image analysis methods.


Altogether 203 knees were imaged using constant X-ray parameters and graded according to Kellgren-Lawrence (KL) grading scale (KL0 n = 110, KL1 n = 28, KL2 n = 27, KL3 n = 31, KL4 n = 7). Bone density-related and structure-related parameters were calculated from medial and lateral tibial subchondral bone plate and trabecular bone and from femur. Density-related parameters were derived from grayscale values and structure-related parameters from Laplacian- and local binary patterns (LBP)-based images.


Reproducibilities of structure-related parameters were better than bone density-related parameters. Bone density-related parameters were significantly (P < 0.05) higher in KL2-4 groups than in control group (KL0) in medial tibial subchondral bone plate and trabecular bone. LBP-based structure parameters differed significantly between KL0 and KL2-4 groups in medial subchondral bone plate, between KL0 and KL1-4 groups in medial and lateral trabecular bone, and between KL0 and KL1-4/KL2-4 in medial and lateral femur. Laplacian-based parameters differed significantly between KL0 and KL2-4 groups in medial side regions-of-interest (ROIs).


Our results indicate that the changes in bone texture in knee OA can be quantitatively evaluated from plain radiographs using advanced image analysis. Based on the results, increased bone density can be directly estimated if the X-ray imaging conditions are constant between patients. However, structural analysis of bone was more reproducible than direct evaluation of grayscale values, and is therefore better suited for quantitative analysis when imaging conditions are variable.
Selo DaSilva