Magnetic resonance imaging (MRI) of articular cartilage in knee osteoarthritis (OA): morphological assessment

Factors that may mediate the relationship between physical activity and the risk for developing knee osteoarthritis

Studies investigating the effect of physical activity on risk for developing osteoarthritis at weight-bearing joints have reported conflicting results. We examine evidence to suggest that this may be due to the existence of subgroups of individuals who differ in their response to physical activity, as well as methodological issues associated with the assessment of knee joint structure and physical activity. Recommendations for future studies of physical activity and the development of knee osteoarthritis are discussed.

Cartilage thickness: factors influencing multidetector CT measurements in a phantom study

PURPOSE

To prospectively assess in a phantom the reconstruction errors and detection limits of cartilage thickness measurements obtained with multidetector computed tomographic (CT) arthrography, as a function of contrast agent concentration, scanning direction, spatial resolution, joint spacing, and tube current, with known measurements as the reference standard.

MATERIALS AND METHODS

A phantom with nine chambers was constructed. Each chamber had a nylon cylinder encased by sleeves of aluminum and polycarbonate to simulate trabecular bone, cortical bone, and cartilage. Varying simulated cartilage thicknesses and 10 joint space widths were assessed. On 3 days, the phantom was scanned with and without contrast agent administration and with the chamber axes both perpendicular and parallel to the scanner axis. Images were reconstructed at 1.0- and 0.5-mm intervals. Contrast agent concentration and tube current were varied. The simulated cartilage thickness was determined by using image segmentation. Root mean squared errors and mean residual errors were used to characterize the measurements. The reproducibility of the CT scanner and image segmentation results was determined.

RESULTS

Simulated cartilage greater than 1.0 mm in thickness was reconstructed with less than 10% error when either no contrast agent or a low concentration (25%) of contrast agent was used. Error increased as contrast agent concentration increased. Decreasing the simulated joint space width to 0.5 mm caused slight increases in error; however, error increased substantially at joint spaces narrower than 0.5 mm. Errors in measurements derived from anisotropic CT data were greater than errors in measurements derived from isotropic data. Altering the tube current did not substantially affect reconstruction errors.

CONCLUSION

The study revealed lower boundaries and the repeatability of simulated cartilage thickness measurements obtained by using multidetector CT arthrography and yielded data pertinent to choosing the contrast agent concentration, joint space width, scanning direction, and spatial resolution to reduce reconstruction errors.

Validation of phalanx bone three-dimensional surface segmentation from computed tomography images using laser scanning

OBJECTIVE

To examine the validity of manually defined bony regions of interest from computed tomography (CT) scans.

MATERIALS AND METHODS

Segmentation measurements were performed on the coronal reformatted CT images of the three phalanx bones of the index finger from five cadaveric specimens. Two smoothing algorithms (image-based and Laplacian surface-based) were evaluated to determine their ability to represent accurately the anatomic surface. The resulting surfaces were compared with laser surface scans of the corresponding cadaveric specimen.

RESULTS

The average relative overlap between two tracers was 0.91 for all bones. The overall mean difference between the manual unsmoothed surface and the laser surface scan was 0.20 mm. Both image-based and Laplacian surface-based smoothing were compared; the overall mean difference for image-based smoothing was 0.21 mm and 0.20 mm for Laplacian smoothing.

CONCLUSIONS

This study showed that manual segmentation of high-contrast, coronal, reformatted, CT datasets can accurately represent the true surface geometry of bones. Additionally, smoothing techniques did not significantly alter the surface representations. This validation technique should be extended to other bones, image segmentation and spatial filtering techniques.

Non-invasive in vivo quantification of the medial tibial cartilage thickness progression in an osteoarthritis rabbit model with quantitative 3D high resolution micro-MRI

OBJECTIVE

To develop a quantitative non-invasive in vivo three-dimensional (3D) high resolution (HR) micro-magnetic resonance imaging (microMRI) protocol to measure the medial tibial cartilage thickness (MT.ThC) in the normal rabbit and in the anterior cruciate ligament transection (ACLT) rabbit model of osteoarthritis and quantify the progression of MT.ThC.

METHODS

The left knee of 10 control and 40 operated rabbits was imaged in vivo with a 7T microMRI system at 3 and 5 months after ACLT. A 3D fast low angle short (FLASH) fat-suppressed MRI protocol was implemented leading to 44x176 microm(3) spatial resolution and to 44 microm(3) isotropic voxel after cubic interpolation. Semi-automatic MT.ThC measurements were made in 3D, in four different locations, in vivo and longitudinally in both groups. At 5 months, gross macroscopy, visual analogical evaluation of the cartilage and histology were compared to the MR-based MT.ThC.

RESULTS

At 3 and 5 months, the MT.ThC measured in the minimum interbone distance area was the thinnest MR-based MT.ThC. It was significantly lower in the operated group and among the four evaluated MT.ThC, it was the most discriminative between the normal and the operated groups (P<0.05). The MT.ThC measured in the minimum interbone distance area was also the most sensitive to change in the operated group (66.4% MT.ThC loss, P=0.003) while no significant changes were observed in the control group.

CONCLUSION

Quantitative 3D HR microMRI allowed for non-invasive longitudinal MT.ThC measurements in four different locations in both the normal and the operated rabbits. We concluded the MT.ThC measured in the minimum interbone distance area reflected the severity of the disease and was the most effective to measure the progression of the medial tibial cartilage destruction.

Two year longitudinal change and test-retest-precision of knee cartilage morphology in a pilot study for the osteoarthritis initiative

OBJECTIVE

Fast low angle shot (FLASH) and double echo steady state (DESS) magnetic resonance imaging (MRI) acquisitions were recently cross-calibrated for quantification of cartilage morphology at 3T. In this pilot study for the osteoarthritis (OA) initiative we compare their test-retest-precision and sensitivity to longitudinal change.

METHOD

Nine participants with mild to moderate clinical OA were imaged twice each at baseline, year 1 (Y1) and year 2 (Y2). Coronal 1.5mm FLASH and sagittal 0.7mm DESS sequences were acquired; 1.5mm coronal multiplanar reformats (MPR) were obtained from the DESS. Patellar, femoral and tibial cartilage plates were quantified in a paired fashion, with blinding to time point.

RESULTS

In the weight-bearing femorotibial joint, average precision errors across plates were 1.8% for FLASH, 2.6% for DESS, and 3.0% for MPR-DESS. Volume loss at Y1 was not significant; at Y2 the average change across the femorotibial cartilage plates was -1.7% for FLASH, -2.8% for DESS, and -0.3% for MPR-DESS. Volume change in the lateral tibia (-5.5%; P<0.03), and in the medial (-2.9%; P<0.04) and lateral femorotibial compartments (-3.8%; P<0.03) were significant for DESS.

CONCLUSIONS

FLASH, DESS and MPR-DESS all displayed adequate test-retest precision. Although the comparison between protocols is limited by the small number of participants and by the relatively small longitudinal change in cartilage morphology in this pilot study, the data suggest that significant change can be detected with MRI in a small sample of OA subjects over 2 years.

Primal/dual linear programming and statistical atlases for cartilage segmentation

In this paper we propose a novel approach for automatic segmentation of cartilage using a statistical atlas and efficient primal/dual linear programming. To this end, a novel statistical atlas construction is considered from registered training examples. Segmentation is then solved through registration which aims at deforming the atlas such that the conditional posterior of the learned (atlas) density is maximized with respect to the image. Such a task is reformulated using a discrete set of deformations and segmentation becomes equivalent to finding the set of local deformations which optimally match the model to the image. We evaluate our method on 56 MRI data sets (28 used for the model and 28 used for evaluation) and obtain a fully automatic segmentation of patella cartilage volume with an overlap ratio of 0.84 with a sensitivity and specificity of 94.06% and 99.92%, respectively.

The long-term consequence of anterior cruciate ligament and meniscus injuries: osteoarthritis

The objectives of this study are to review the long-term consequences of injuries to the anterior cruciate ligament and menisci, the pathogenic mechanisms, and the causes of the considerable variability in outcome. Injuries of the anterior cruciate ligament and menisci are common in both athletes and the general population. At 10 to 20 years after the diagnosis, on average, 50% of those with a diagnosed anterior cruciate ligament or meniscus tear have osteoarthritis with associated pain and functional impairment: the young patient with an old knee. These individuals make up a substantial proportion of the overall osteoarthritis population. There is a lack of evidence to support a protective role of repair or reconstructive surgery of the anterior cruciate ligament or meniscus against osteoarthritis development. A consistent finding in a review of the literature is the often poor reporting of critical study variables, precluding data pooling or a meta-analysis. Osteoarthritis development in the injured joints is caused by intra-articular pathogenic processes initiated at the time of injury, combined with long-term changes in dynamic joint loading. Variation in outcome is reinforced by additional variables associated with the individual such as age, sex, genetics, obesity, muscle strength, activity, and reinjury. A better understanding of these variables may improve future prevention and treatment strategies. In evaluating medical treatment, we now expect large randomized clinical trials complemented by postmarketing monitoring. We should strive toward a comparable level of quality of evidence in surgical treatment of knee injuries. In instances in which a randomized clinical trial is not feasible, natural history and other observational cohort studies need to be as carefully designed and reported as the classic randomized clinical trial, to yield useful information.

Osteoarthritic cartilage is more homogeneous than healthy cartilage: identification of a superior region of interest colocalized with a major risk factor for osteoarthritis

RATIONALE AND OBJECTIVES

Cartilage loss as determined by magnetic resonance imaging (MRI) or joint space narrowing as determined by x-ray is the result of cartilage erosion. However, metabolic processes within the cartilage that later result in cartilage loss may be a more sensitive assessment method for early changes. Recently, it was shown that cartilage homogeneity visualized by MRI representing the biochemical changes undergoing in the cartilage is a potential marker for early detection of knee osteoarthritis (OA) and is also able to significantly separate groups of healthy subjects from those with OA. The purpose of this study was twofold. First, we wished to evaluate whether the results on cartilage homogeneity from the previous study can be reproduced using an independent population. Second, based on the homogeneity framework, we present an automatic technique that partitions the region of interest in the cartilage that contributes most to discrimination between healthy and OA subjects and allows for identification of the most implicated areas in early OA. These findings may allow further investigation of whether cartilage homogeneity reveals a predisposition for OA or whether it evolves as a consequence to disease and thereby can be used as a progression biomarker.

MATERIALS AND METHODS

A total of 283 right and left knees from 159 subjects aged 21 to 81 years were scanned using a Turbo 3D T1 sequence on a 0.18-T MRI Esaote scanner. The medial compartment of the tibial cartilage sheet was segmented using a fully automatic voxel classification scheme based on supervised learning. From the segmented cartilage sheet, homogeneity was quantified by measuring entropy from the distribution of signal intensities inside the compartment. Each knee was examined by radiography, and the knees were categorized by the Kellgren and Lawrence (KL) Index. Next, based on a gradient descent optimization technique, the cartilage region that contributed to the maximum statistical significance of homogeneity in separating healthy subjects from the diseased was partitioned. The generalizability of the region was evaluated by testing for overfitting. Three different regularization techniques were evaluated for reducing overfitting errors.

RESULTS

The P values for separating the different groups based on cartilage homogeneity were 2 x 10(-5) (KL 0 versus KL 1) and 1 x 10(-7) (KL 0 versus KL >0). Using the automatic gradient descent technique, the partitioned region was toward the peripheral part of the cartilage sheet. Using this region, the P values for separating the different groups based on homogeneity were 5 x 10(-9) (KL 0 versus KL 1) and 1 x 10(-15) (KL 0 versus KL >0). The precision of homogeneity for the partitioned region assessed as a test-retest root-mean-square coefficient of variation was 3.3%. Bootstrapping proved to be an effective regularization tool in reducing overfitting errors.

CONCLUSION

The validation study supported the use of cartilage homogeneity as a tool for the early detection of knee OA and for separating groups of healthy subjects from those who have disease. Our automatic, unbiased partitioning algorithm based on a general statistical framework outlined the cartilage region of interest that best separated healthy from OA conditions on the basis of homogeneity discrimination. We have shown that OA affects certain areas of the cartilage more distinctly, and these areas are located more toward the peripheral region of the cartilage. We propose that this region corresponds anatomically to cartilage covered by the meniscus in healthy subjects. This finding may provide valuable clues in the early detection and monitoring of OA and thus may improve treatment efficacy.

Separation of healthy and early osteoarthritis by automatic quantification of cartilage homogeneity

OBJECTIVE

Cartilage loss as determined either by magnetic resonance imaging (MRI) or by joint space narrowing in X-rays is the result of cartilage erosion. However, metabolic processes within the cartilage that later result in cartilage loss may be a more accurate assessment method for early changes. Early biological processes of cartilage destruction are among other things, a combination of proteoglycan turnover, as a result of altered charge distributions, and local alterations in water content (edema). As water distribution is detectable by MRI, the aim of this study was to investigate cartilage homogeneity visualized by MRI related to water distribution, as a potential very early marker for early detection of knee osteoarthritis (OA).

DESIGN

One hundred and fourteen right and left knees from 71 subjects aged 22-79 years were scanned using a Turbo 3D T(1) sequence on a 0.18T MRI Esaote scanner. The medial compartment of the tibial cartilage sheet was segmented using a fully automatic voxel classification scheme based on supervised learning. From the segmented cartilage sheet, homogeneity was quantified by measuring entropy from the distribution of signal intensities inside the compartment. For each knee an X-ray was acquired and the knees were categorized by the Kellgren and Lawrence (KL) index and the joint space width (JSW) was measured. The P-values for separating the groups by each of JSW, cartilage volume, cartilage mean intensity, and cartilage homogeneity were calculated using the unpaired t-test.

RESULTS

The P-value for separating the group diagnosed as KL 0 from the group being KL 1 based on JSW, volume and mean signal intensity the values were P=0.9, P=0.4 and P=0.0009, respectively. In contrast, the P-value for homogeneity was P=0.0004. The precision of the measures assessed, as a test-retest root mean square coefficient of variation (RMS-CV%) was 3.9% for JSW, 7.4% for volume, 3.9% for mean signal intensity and 3.0% for homogeneity quantification.

CONCLUSION

These data demonstrate that the distribution of components of the articular matrix precedes erosion, as measured by cartilage homogeneity related to water concentration. We show that homogeneity was able to separate early OA from healthy individuals in contrast to traditional volume and JSW quantifications. These data suggest that cartilage homogeneity quantification may be able to quantify early biochemical changes in articular cartilage prior to cartilage loss and thereby provide better identification of patients for OA trials who may respond better to medicinal intervention of some treatments. In addition, this study supports the feasibility of using low-field MRI in clinical studies.

Averaged and depth-dependent anisotropy of articular cartilage by microscopic imaging

OBJECTIVES

To identify the common connections among the averaged and depth-dependent anisotropic properties of articular cartilage by performing a meta-analysis of several published multidisciplinary imaging results. The imaging techniques involved include microscopic magnetic resonance imaging (microMRI), polarized light microscopy (PLM), Fourier-transform infrared imaging (FTIRI), and transmission electron microscopy (TEM).

METHODS

Several physical properties of cartilage are incorporated in this meta-analysis. These tissue properties include T(2) anisotropy from microMRI, angle and retardance from PLM, infrared anisotropy from FTIRI, and image morphology from TEM. Because the specimens in these studies all came from the same type of canine humeral joints, it is possible to correlate these multidisciplinary tissue properties using a common platform.

RESULTS

An ellipse model was used to identify the connections among these tissue properties in terms of the anisotropy of articular cartilage, in each histological zone as well as for the entire noncalcified tissue. It was found that many aspects of these tissue properties can be interpreted beyond their usual meanings as measured, based on 3 features of an ellipse: the concentration, the orientation, and the anisotropy.

CONCLUSIONS

The ellipse model is a useful graphical concept in cartilage imaging since it helps to bring together the measured physical/morphological/chemical quantities in these imaging tools and the anisotropic structure of articular cartilage. Two possible mechanisms for the angular transition of collagen fibrils in cartilage are discussed.

Imaging of knee osteoarthritis: data beyond the beauty

PURPOSE OF REVIEW

MRI has revolutionized osteoarthritis research by providing semi-quantitative and quantitative imaging endpoints on most articular tissues. With the first image data of the Osteoarthritis Initiative now becoming publicly available, this article reviews recent developments in quantitative imaging of osteoarthritis.

RECENT FINDINGS

Although radiography remains the standard for regulatory studies on disease modifying osteoarthritis drugs, there is no consensus on the optimal positioning and acquisition protocol. With MRI, semi-quantitative scoring systems for evaluation of multiple articular tissue changes have been developed and are currently investigated in the context of correlation with symptoms and of predicting structural progression of osteoarthritis. Most efforts on quantitative measurement of imaging endpoints have focused on cartilage morphology and composition, with higher field strength (3T), newer sequences, and new measurement endpoints being a driver of current innovation.

SUMMARY

The semi-quantitative and quantitative tools for analysis of articular structure are now available and permit comprehensive analysis of morphological and compositional tissue changes in osteoarthritis. These changes will need to be related to clinical outcomes (e.g. how a patient feels or functions) with current epidemiological studies, such as the Osteoarthritis Initiatives, providing the opportunity for clinical validation of these imaging biomarkers.

Automatic morphometric cartilage quantification in the medial tibial plateau from MRI for osteoarthritis grading

OBJECTIVE

To evaluate whether a novel, fully automatic, morphometric cartilage quantification framework is suitable for assessing level of knee osteoarthritis (OA) in clinical trials.

METHOD

The population was designed with a normal population and groups with varying degree of OA of both sexes and at ages from 21 to 78. Posterior-anterior X-rays were acquired in semi-flexed, load-bearing position. The radiographic signs of OA were evaluated based on the Kellgren and Lawrence score (KL) and the joint space width (JSW) was measured. Turbo 3D T1 magnetic resonance imaging (MRI) scans were acquired with resolution 0.7x0.7x0.8mm(3) from a 0.18T scanner. The morphometric cartilage quantification from MRI resulted in volume, surface area, thickness and surface curvature for the medial tibial cartilage compartment. These quantifications were evaluated against JSW with respect to precision and ability to separate healthy subjects from OA subjects.

RESULTS

The automatic, morphometric cartilage quantifications allowed fairly precise measurements with scan-rescan coefficient of variations (CVs) in the range from 3.4% to 6.3%. All quantifications, including JSW, allowed separation of the groups of healthy and OA subjects. However, for separation of the healthy from the borderline cases (KL 0 vs KL 1), only the Cartilage Curvature quantification allowed statistically significant separation (P<0.01).

CONCLUSION

The novel morphometric framework shows promise for use in clinical trials. The ability of the Cartilage Curvature quantification to detect the early stages of OA and the effectiveness of the focal thickness Q10 measure are particularly noteworthy. Furthermore, these results may indirectly support that low-field MRI may be a low-cost option for clinical trials.

Automatic segmentation of the bone and extraction of the bone-cartilage interface from magnetic resonance images of the knee

The accurate segmentation of the articular cartilages from magnetic resonance (MR) images of the knee is important for clinical studies and drug trials into conditions like osteoarthritis. Currently, segmentations are obtained using time-consuming manual or semi-automatic algorithms which have high inter- and intra-observer variabilities. This paper presents an important step towards obtaining automatic and accurate segmentations of the cartilages, namely an approach to automatically segment the bones and extract the bone-cartilage interfaces (BCI) in the knee. The segmentation is performed using three-dimensional active shape models, which are initialized using an affine registration to an atlas. The BCI are then extracted using image information and prior knowledge about the likelihood of each point belonging to the interface. The accuracy and robustness of the approach was experimentally validated using an MR database of fat suppressed spoiled gradient recall images. The (femur, tibia, patella) bone segmentation had a median Dice similarity coefficient of (0.96, 0.96, 0.89) and an average point-to-surface error of 0.16 mm on the BCI. The extracted BCI had a median surface overlap of 0.94 with the real interface, demonstrating its usefulness for subsequent cartilage segmentation or quantitative analysis.

Automatic segmentation of articular cartilage in magnetic resonance images of the knee

To perform cartilage quantitative analysis requires the accurate segmentation of each individual cartilage. In this paper we present a model based scheme that can automatically and accurately segment each individual cartilage in healthy knees from a clinical MR sequence (fat suppressed spoiled gradient recall). This scheme consists of three stages; the automatic segmentation of the bones, the extraction of the bone-cartilage interfaces (BCI) and segmentation of the cartilages. The bone segmentation is performed using three-dimensional active shape models. The BCI is extracted using image information and prior knowledge about the likelihood of each point belonging to the interface. A cartilage thickness model then provides constraints and regularizes the cartilage segmentation performed from the BCI. The accuracy and robustness of the approach was experimentally validated, with (patellar, tibial and femoral) cartilage segmentations having a median DSC of (0.870, 0.855, 0.870), performing significantly better than non-rigid registration (0.787, 0.814, 0.795). The total cartilage segmentation had an average DSC of (0.891), close to the (0.896) obtained using a semi-automatic watershed algorithm. The error in quantitative volume and thickness measures was (8.29, 4.94, 5.56)% and (0.19, 0.33, 0.10) mm respectively.

Impact of coil design on the contrast-to-noise ratio, precision, and consistency of quantitative cartilage morphometry at 3 Tesla: A pilot study for the osteoarthritis initiative

Phased-array (PA) coils generally provide higher signal-to-noise ratios (SNRs) than quadrature knee coils. In this pilot study for the Osteoarthritis Initiative (OAI) we compared these two types of coils in terms of contrast-to-noise ratio (CNR), precision, and consistency of quantitative femorotibial cartilage measurements. Test-retest measurements were acquired using coronal fast low-angle shot with water excitation (FLASHwe) and coronal multiplanar reconstruction (MPR) of sagittal double-echo steady state with water excitation (DESSwe) at 3T. The precision errors for cartilage volume and thickness were <or=2.6% for the quadrature coil and <or=2.3% for the PA coil with FLASHwe, and <or=2.3%/<or=2.5% with DESSwe. The precision for aggregate medial and lateral cartilage measures was significantly higher than that for single plates, independently of coil and sequence. The PA coil measurements did not always fully agree with the quadrature coil measurements, and some differences were significant. The higher CNR of the PA coil did not translate directly into improved precision of cartilage measurement; however, summing up cartilage plates within the medial and lateral compartment reduced precision errors.

Quantitative imaging of cartilage morphology at 3.0 Tesla in the presence of gadopentate dimeglumine (Gd-DTPA)

MRI-based cartilage morphometry was previously validated in the absence of gadopentate dimeglumine (Gd-DTPA). However, Gd-DTPA is required for compositional (proteoglycan) imaging using delayed gadolinium-enhanced MRI of cartilage (dGEMRIC). Therefore, the effect of Gd-DTPA on cartilage morphometry was studied. A total of 165 female participants (67 with and 98 without osteoarthritis [OA]) were imaged at 3.0 Tesla before and 2 hr after intravenous Gd-DTPA injection. Flip angles in post-Gd-DTPA scans varied between 12 degrees and 35 degrees . Cartilage volume and thickness of post- vs. pre-Gd-DTPA scans showed intraclass correlation coefficients (ICCs) of 0.85 > or = r > or = 0.95, mean differences between -2.1% and +1.1%, and standard deviations (SDs) of differences between 4.7% and 9.2%. Mixed-effect models found no consistent impact of flip angle and OA status on post- vs. pre-Gd-DTPA differences. Accurate morphological measurements of cartilage can be obtained after Gd-DTPA injection, allowing compositional and morphological imaging to be combined into one session.

MR measurement of articular cartilage thickness distribution in the hip

OBJECTIVE

To develop a method to determine the distribution of articular cartilage in the hip and to evaluate the potential of the method in a study of normal weight-bearing effects in asymptomatic young volunteers.

DESIGN

Six volunteers were scanned after periods of standing and lying supine, using 3D gradient-echo magnetic resonance imaging (MRI). The protocol was repeated for two successive weeks to determine reproducibility. The femoral and acetabular cartilage layers were segmented as a single unit and thickness distribution maps were calculated using a spherical bone model as a frame of reference. Thickness maps were combined over the population using the bone model and post-weight-bearing and post-resting maps were compared.

RESULTS

Mean thickness values were compared using an analysis of variance and a significant increase in cartilage thickness of 0.05 mm (P=0.02) was observed. The reproducibility of the method, assessed using test-retest coefficient of variation was 2.5%.

CONCLUSIONS

The technique is reproducible, sensitive to sub-millimetre changes in thickness and may be useful in monitoring changes due to disease progression in patients with arthritis of the hip.

Imaging osteoarthritis: Magnetic resonance imaging versus x-ray

Until recently, imaging evaluation of osteoarthritis has relied primarily on conventional radiography. Using radiography in clinical practice or clinical research, however, has been fraught with difficulty. Techniques for reproducibly acquiring serial radiographs of joints have improved considerably over the past several years. However, the greatest promise for advancing knowledge about osteoarthritis and its treatment lies in MRI and its unique ability to examine the joint as a whole organ. In contrast to conventional radiography, MRI can directly visualize the articular cartilage, synovium, menisci, and other intra-articular structures important to the functional integrity of joints. There have been considerable advances in MRI of articular cartilage in particular over the past several years. However, much of this has come from small cross-sectional studies. Larger, longitudinal studies are ongoing, and publications are just emerging. This paper reviews the current status of x-ray and MRI in osteoarthritis and points to where changes might be anticipated in the future.