Device for Assessing Knee Joint Dynamics During Magnetic Resonance Imaging.

Background: Knee assessment with and without load using magnetic resonance imaging (MRI) can provide information on knee joint dynamics and improve the diagnosis of knee joint diseases. Performing such studies on a routine MRI-scanner require a load-exerting device during scanning. There is a need for more studies on developing loading devices and evaluating their clinical potential.

Model for in-vivo estimation of stiffness of tibiofemoral joint using MR imaging and FEM analysis.

Background: Appropriate structural and material properties are essential for finite-element-modeling (FEM). In knee FEM, structural information could extract through 3D-imaging, but the individual subject's tissue material properties are inaccessible.

Purpose: The current study's purpose was to develop a methodology to estimate the subject-specific stiffness of the tibiofemoral joint using finite-element-analysis (FEA) and MRI data of knee joint with and without load.

A semi-automatic framework based upon quantitative analysis of MR-images for classification of femur cartilage into asymptomatic, early OA, and advanced-OA groups.

To develop a semi-automatic framework for quantitative analysis of biochemical properties and thickness of femur cartilage using magnetic resonance (MR) images and evaluate its potential for femur cartilage classification into asymptomatic (AS), early osteoarthritis (OA), and advanced OA groups. In this study, knee joint MRI data (fat suppressed-proton density-weighted and multi-echo T2-weighted images) of eight AS-volunteers (data acquired twice) and 34 OA patients including 20 early OA (16 Grade-I and 4 Grade-II), 14 advanced-OA (Grade-III) were acquired at 3.0T MR scanner.

Modified radial-search algorithm for segmentation of tibiofemoral cartilage in MR images of patients with subchondral lesion.

Purpose: The quantitative analysis of weight-bearing articular cartilage superficial to subchondral abnormality is important in osteoarthritis (OA) progression studies. The current study aimed to address the challenges of a semi-automatic segmentation of tibiofemoral cartilage in MR images of OA patient with and without subchondral bone abnormalities (SBA).

Methods: In this study, knee MRI data [fat-suppressed proton density-weighted, multi-echo T2-weighted (CartiGram) images] of 29 OA patients, acquired at 3.