Multinuclear MR and multilevel data processing: an insight into morphologic assessment of in vivo knee articular cartilage.

RATIONALE AND OBJECTIVES: Quantitative assessment of knee articular cartilage (AC) morphology using magnetic resonance (MR) imaging requires an accurate segmentation and 3D reconstruction. However, automatic AC segmentation and 3D reconstruction from hydrogen-based MR images alone is challenging because of inhomogeneous intensities, shape irregularity, and low contrast existing in the cartilage region. Thus, the objective of this research was to provide an insight into morphologic assessment of AC using multilevel data processing of multinuclear ((23)Na and (1)H) MR knee images. MATERIALS AND METHODS: A dual-tuned ((23)Na and (1)H) radio-frequency coil with 1.5-T MR scanner is used to scan four human subjects using two separate MR pulse sequences for the respective sodium and proton imaging of the knee. Postprocessing is performed using customized routines written in MATLAB. MR data were fused to improve contrast of the cartilage region that is further used for automatic segmentation. Marching cubes algorithm is applied on the segmented AC slices for 3D volume rendering and volume is then calculated using the divergence theorem. RESULTS: Fusion of multinuclear MR images results in an improved contrast (factor >3) in the cartilage region. Sensitivity (80.21%) and specificity (99.64%) analysis performed by comparing manually segmented AC shows a good performance of the automated AC segmentation. The average cartilage volume (23.19 ± 1.38 cm(3); coefficient of variation [COV] -0.059) measured from 3D AC models of four data sets shows a marked improvement over average cartilage volume (23.24 cm(3); COV -0.19) reported earlier. CONCLUSIONS: This study confirms the use of multinuclear MR data for cartilage morphology (volume) assessment that can be used in clinical settings.

Non-invasive and in vivo assessment of osteoarthritic articular cartilage: a review on MRI investigations.

Early detection of knee osteoarthritis (OA) is of great interest to orthopaedic surgeons, rheumatologists, radiologists, and researchers because it would allow physicians to provide patients with treatments and advice to slow the onset or progression of the disease. Early detection can be achieved by identifying early changes in selected features of degenerative articular cartilage (AC) using non-invasive imaging modalities. Magnetic resonance imaging (MRI) is becoming the standard for assessment of OA. The aim of this paper was to review the influence of MRI on the selection, detection, and measurement of AC features associated with early OA. Our review of the literature indicates that the changes associated with early OA are in cartilage thickness, cartilage volume, cartilage water content, and proteoglycan content that can be accurately, consistently, and non-invasively measured using MRI. Choosing an MR pulse sequence that provides the capability to assess cartilage physiology and morphology in a single acquisition and advanced multi-nuclei MRI is desirable. The results of the review indicate that using an ultra-high magnetic strength, MR imager does not affect early OA detection. In conclusion, MRI is currently the most suitable modality for early detection of knee OA, and future research should focus on the quantitative evaluation of early OA features using advances in MR hardware, software, and data processing with sophisticated image/pattern recognition techniques.

Fusion of multinuclear magnetic resonance images of knee for the assessment of articular cartilage.

The onset of osteoarthritis (OA), a most common knee joint disease, can be characterized by the degeneration of articular cartilage (AC). Degenerative changes in AC have been assessed by the morphological and physiological measurements using non-invasive modality such as Magnetic Resonance Imaging (MRI) to obtain MRI images of the knee. However, visualization and quantification of AC from MR images is difficult due to the low visibility contrast of AC compared to surrounding tissues, low and varying signal intensities in cartilage region and variable intensities in different slices of single dataset. In this work, we present a method to fuse multinuclear ((23)Na and (1)H) MR images acquired in the same plane without changing the position of the human knee as well as the Radio Frequency (RF) coil. This work is performed towards our hypothesis that fusion of sodium and proton images will provide an enhanced image that can be used for an accurate assessment of cartilage morphology. Our result shows that merging of sodium knee MR image with proton knee MR image resulting in enhanced contrast information in the cartilage region and resolves low visibility and varying intensities issue with 2D/3D proton MR. We conclude that the proposed method can further be utilized for the accurate assessment of cartilage morphology.