Precision, Reliability, and Responsiveness of a Novel Automated Quantification Tool for Cartilage Thickness: Data from the Osteoarthritis Initiative.

Objective: Accurate automated segmentation of cartilage should provide rapid reliable outcomes for both epidemiological studies and clinical trials. We aimed to assess the precision and responsiveness of cartilage thickness measured with careful manual segmentation or a novel automated technique.

Methods: Agreement of automated segmentation was assessed against 2 manual segmentation datasets: 379 magnetic resonance images manually segmented in-house (training set), and 582 from the Osteoarthritis Initiative with data available at 0, 1, and 2 years (biomarkers set).

Osteoarthritic bone marrow lesions almost exclusively colocate with denuded cartilage: a 3D study using data from the Osteoarthritis Initiative.

Objectives: The aetiology of bone marrow lesions (BMLs) in knee osteoarthritis (OA) is poorly understood. We employed three-dimensional (3D) active appearance modelling (AAM) to study the spatial distribution of BMLs in an OA cohort and compare this with the distribution of denuded cartilage.

Methods: Participants were selected from the Osteoarthritis Initiative progressor cohort with Kellgren-Lawrence scores ≥2, medial joint space narrowing and osteophytes.

A novel method for bone area measurement provides new insights into osteoarthritis and its progression.

Background: Modern image analysis enables the accurate quantification of knee osteoarthritis (OA) bone using MRI. We hypothesised that three-dimensional changes in bone would be characteristic of OA and provide a responsive measure of progression.

Methods: 1312 participants with radiographic knee OA, and 885 non-OA controls with MRIs at baseline, 1, 2 and 4 years were selected from the NIH Osteoarthritis Initiative.

Magnetic resonance imaging-based three-dimensional bone shape of the knee predicts onset of knee osteoarthritis: data from the osteoarthritis initiative.

Objective: To examine whether magnetic resonance imaging (MRI)-based 3-dimensional (3-D) bone shape predicts the onset of radiographic knee osteoarthritis (OA).

Methods: We conducted a case-control study using data from the Osteoarthritis Initiative by identifying knees that developed incident tibiofemoral radiographic knee OA (case knees) during followup, and matching them each to 2 random control knees. Using knee MRIs, we performed active appearance modeling of the femur, tibia, and patella and linear discriminant analysis to identify vectors that best classified knees with OA versus those without OA.