Subchondral tibial bone texture predicts the incidence of radiographic knee osteoarthritis: data from the Osteoarthritis Initiative

• Published in: Osteoarthritis and cartilage Vol. 25; no. 12; pp. 2047 - 2054
• Main Authors: Janvier, T., Jennane, R., Toumi, H., Lespessailles, E.
• Format: Journal Article
• Language: English
• Published: England Elsevier Ltd 01.12.2017; Elsevier
• Subjects: Aged; Area Under Curve; Artificial Intelligence; Bioengineering; Case-Control Studies; Computer Science; Computer Vision and Pattern Recognition; Disease Progression; Female; Fractal analysis; Human health and pathology; Humans; Imaging; Incidence; Knee osteoarthritis; Life Sciences; Logistic Models; Male; Middle Aged; Osteoarthritis, Knee - diagnostic imaging; Osteoarthritis, Knee - epidemiology; Osteophyte - diagnostic imaging; Osteophyte - epidemiology; Radiographs; Rhumatology and musculoskeletal system; ROC Curve; Subchondral bone; Tibia - diagnostic imaging; Trabecular bone texture; Trabecular bone texture; Knee osteoarthritis; Subchondral bone; Fractal analysis; Radiographs
• ISSN: 1063-4584; 1522-9653; 1522-9653
• DOI: 10.1016/j.joca.2017.09.004

To evaluate whether trabecular bone texture (TBT) parameters measured on computed radiographs (CR) could predict the onset of radiographic knee osteoarthritis (OA). Subjects from the Osteoarthritis Initiative (OAI) with no sign of radiographic OA at baseline were included. Cases that developed either a global radiographic OA defined by the Kellgren–Lawrence (KL) scale, a joint space narrowing (JSN) or tibial osteophytes (TOS) were compared with the controls with no changes after 48 months of follow-up. Baseline bilateral fixed flexion CR were analyzed using a fractal method to characterize the local variations. The prediction was explored using logistic regression models evaluated by the area under the receiver operating characteristic curves (AUC). From the 344 knees, 79 (23%) developed radiographic OA after 48 months, 44 (13%) developed progressive JSN and 59 (17%) developed osteophytes. Neither age, gender and BMI, nor their combination predicted poorer KL (AUC 0.57), JSN or TOS (AUC 0.59) scores. The inclusion of the TBT parameters in the models improved the global prediction results for KL (AUC 0.69), JSN (AUC 0.73) and TOS (AUC 0.71) scores. Several differences were found between the models predictive of three different outcomes (KL, JSN and TOS), indicating different underlying mechanisms. These results suggest that TBT parameters assessed when radiographic signs are not yet apparent on radiographs may be useful in predicting the onset of radiological tibiofemoral OA as well as identifying at-risk patients for future clinical trials.