An MRI derived articular cartilage visualization framework

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 Outerbridge classification criteria was performed for the clinical evaluation of data by an experienced radiologist. Cartilage segmentation, T2-mapping, 2D-WearMap generation, and subregion analysis were performed semi-automatically using in-house developed algorithms. The intraclass correlation coefficient (ICC) and coefficient of variation (CV) were computed for testing the reproducibility of T2 values. One-way analysis of variance with Tukey-Kramer post hoc test was performed for evaluating the differences among the groups. The performance of individual T2 and thickness, as well as their combination using logistic regression, were evaluated with receiver operating characteristics (ROC) curve analysis. The interscan agreement based on the ICC index was 0.95 and the CV was 2.45 ± 1.33%. T2 mean of values greater than 75th percentile showed sensitivity and specificity of 94.1% and 81.3% (AUC = 0.93, cut-off value = 47.9 ms) in differentiating AS volunteers versus OA group, while sensitivity and specificity of 90.0% and 81.3% (AUC = 0.90, cut-off value = 47.9 ms) in differentiating AS volunteers versus early OA groups, respectively. In the differentiation of early OA versus advanced-OA group, ROC results of combination (T2 and thickness) showed the highest sensitivity and specificity of 85.7%, and 70.0% (AUC = 0.79, cut-off value = 0.39) compared with individual T2 and thickness features, respectively. A computer-aided quantitative evaluation of femur cartilage degeneration showed promising results and can be used to assist clinicians in diagnosing OA.

Cluster analysis of quantitative MRI T2 and T1ρ relaxation times of cartilage identifies differences between healthy and ACL-injured individuals at 3T

PURPOSE

To identify focal lesions of elevated MRI T₂ and T_1ρ relaxation times in articular cartilage of an ACL-injured group using a novel cluster analysis technique.

MATERIALS AND METHODS

Eighteen ACL-injured patients underwent 3T MRI T₂ and T_1ρ relaxometry at baseline, 6 months and 1 year and six healthy volunteers at baseline, 1 day and 1 year. Clusters of contiguous pixels above or below T₂ and T_1ρ intensity and area thresholds were identified on a projection map of the 3D femoral cartilage surface. The total area of femoral cartilage plate covered by clusters (%CA) was split into areas above (%CA+) and below (%CA-) the thresholds and the differences in %CA(+ or -) over time in the ACL-injured group were determined using the Wilcoxon signed rank test.

RESULTS

%CA+ was greater in the ACL-injured patients than the healthy volunteers at 6 months and 1 year with average %CA+ of 5.2 ± 4.0% (p = 0.0054) and 6.6 ± 3.7% (p = 0.0041) for T₂ and 6.2 ± 7.1% (p = 0.063) and 8.2 ± 6.9% (p = 0.042) for T_1ρ, respectively. %CA- at 6 months and 1 year was 3.0 ± 1.8% (p > 0.1) and 5.9 ± 5.0% (p > 0.1) for T₂ and 4.4 ± 4.9% (p > 0.1) and 4.5 ± 4.6% (p > 0.1) for T_1ρ, respectively.

CONCLUSION

With the proposed cluster analysis technique, we have quantified cartilage lesion coverage and demonstrated that the ACL-injured group had greater areas of elevated T₂ and T_1ρ relaxation times as compared to healthy volunteers.

Intra-operative assessment of fractured articular surfaces in cone beam CT image data

PURPOSE

The assessment of intra-operatively acquired volumetric data is a difficult and often time-consuming task, which demands a new set of skills from the surgeons. In the case of orthopedic surgeries such as the treatment of calcaneal fractures, the correctness of the reduction of the bone fragments can be verified with the help of C-arm CT volumetric images. For an accurate intra-operative assessment of the displaced fragments, an automatic segmentation of the articular surfaces and color-coded visualization was developed.

METHODS

Our automatic approach consists of three major steps: first, using adjusted standard planes intersecting the articular region, the joint space is localized with an intensity profile-based method. In a second step, the localized joint space is segmented on the Laplacian of Gaussian filtered volumetric image by a modified binary flood fill algorithm. Finally, a 3D surface model of the segmented joint space is analyzed and visualized with focus on critical displacements of the surface.

RESULTS

A specifically designed human cadaver study consisting of ten lower legs of ten different donors was conducted to acquire 48 realistic C-arm CT images of misaligned bone fragments (steps of varying sizes) in the posterior talar articular surface of the calcaneus. The proposed algorithmic pipeline was verified by the acquired image data and showed very good results with no false positives and an overall correct displacement assessment of 93.8%.

CONCLUSIONS

The proposed algorithmic pipeline can be easily integrated into the clinical workflow and qualifies for intra-operative usage. It showed very good results on the reference data set of the cadaver study. With the help of such an assistance system, the time-consuming process of 2D view adjustment and visual assessment of the gray value images can be greatly simplified.

Normal T2 map profile of the entire femoral cartilage using an angle/layer-dependent approach

PURPOSE

To create standard T2 map profiles from the entire femoral cartilage of healthy volunteers in order to assess regional variations using an angular and layer-dependent approach.

MATERIALS AND METHODS

Twenty healthy knees were evaluated using 3T sagittal images of a T2 mapping sequence. Manual segmentation of the entire femoral cartilage was performed slice-by-slice by two raters using MatLab. Inter- and intrarater reliabilities were calculated using intraclass correlation coefficient (ICC) and Bland-Altman analysis. T2 values were analyzed with respect to specific locations (medial condyle, trochlea, and lateral condyle), angles to B0 , and layers of cartilage (whole, deep, and superficial).

RESULTS

Inter- and intrarater reliability obtained from the entire femoral cartilage was excellent (ICC = 0.84, 0.86, respectively). The ICCs around the trochlea were lower than those of the medial and lateral condyle. Both the inter- and intrarater Bland-Altman plots indicated larger differences in pixel count are seen as the size of the angular segment becomes larger. T2 values were significantly higher in the superficial layer compared to the deep layer at each femoral compartment (P < 0.001). A magic angle effect was clearly observed, especially within the whole and deep layer over the medial and lateral femoral condyles, except for the superficial layer at the medial condyle.

CONCLUSION

The normal T2 map profiles of the entire femoral cartilage showed variations in ICCs by location and in T2 values by angles and layers. These profiles can be useful for diagnosis of early cartilage degeneration in a specific angle and layer of each condyle and trochlea.

Three-dimensional topographical variation of femoral cartilage T2 in healthy volunteer knees

OBJECTIVE

Quantitative knee cartilage T2 assessment on limited two-dimensional midsagittal or midcoronal planes may be insufficient to assess variations in normal cartilage composition. The purpose of this work was to reveal characteristic 3D distribution of T2 values in femoral cartilage in healthy volunteer knees.

MATERIALS AND METHODS

Sixteen volunteers were enrolled in this study. One knee joint in each volunteer was imaged using a 3D fast image employing steady-state acquisition cycled phases (FIESTA-C) sequence for modeling distal femoral morphology, as well as a sagittal T2 mapping of cartilage. 3D distribution of cartilage T2 values was generated for the femoral condyles. At each medial and lateral condyle, four regions of interest (ROI) were manually defined based on the cartilage covered by the 3D surface model of the medial and lateral menisci.

RESULTS

The 3D maps showed a relatively inhomogeneous distribution of cartilage T2 on the medial and lateral condyles. Cartilage T2 values in the internal half of the weight-bearing zone were significantly higher than those in all other zones on both lateral and medial condyles.

CONCLUSIONS

Analysis of 3D distribution of femoral cartilage T2 may be valuable in determining the site-specific normal range of cartilage T2 in the healthy knee joint.

Texture analysis of bone marrow in knee MRI for classification of subjects with bone marrow lesion - data from the Osteoarthritis Initiative

Visualization of bone marrow lesion (BML) can improve the diagnosis of many bone disorders that are associated with it. A quantitative approach in detecting BML could increase the accuracy and efficiency of diagnosing those bone disorders. In this paper, we investigated the feasibility of using magnetic resonance imaging (MRI)-based texture to (a) identify slices and (b) classify subjects with and without BML. A total of 58 subjects were studied; 29 of them were affected by BML. The ages of subjects ranged from 45 to 74years with a mean age of 59. Texture parameters were calculated for the weight-bearing region of distal femur. The parameters were then analyzed using Mann-Whitney U test and individual feature selection methods to identify potentially discriminantive parameters. Forward feature selection was applied to select features subset for classification. Classification results from eight classifiers were studied. Results show that 98 of the 147 parameters studied are statistically significantly different between the normal and affected marrows: parameters based on co-occurrence matrix are ranked highest in their separability. The classification of subjects achieved an area under the receiver operating characteristic curve (AUC) of 0.914, and the classification of slices achieved an AUC of 0.780. The results show that MRI-texture-based classification can effectively classify subjects/slices with and without BML.

Influence of medial meniscectomy on stress distribution of the femoral cartilage in porcine knees: a 3D reconstructed T2 mapping study

OBJECTIVE

Previous studies have shown that meniscectomy results in an increase of local load transmission and may cause degeneration of the knee cartilage. Using 3D reconstructed T2 mapping, we examined the influence on the femoral cartilage under loading after medial meniscectomy.

DESIGN

Ten porcine knees were imaged using a pressure device and a 3.0-T magnetic resonance imaging (MRI) system. Consecutive sagittal T2 maps were obtained in neutral alignment with and without compression, and under compression at 10° varus alignment. After medial meniscectomy, the aforementioned MRI was repeated. Cartilage T2 before and after meniscectomy under each condition were compared at the 12 regions of interest (ROIs) defined on the 3D weight-bearing area of the femoral cartilage.

RESULTS

Before meniscectomy, large decreases in T2 under neutral compression were mainly seen at the anterior and central ROIs of the medial cartilage, which shifted to the posterior ROIs after meniscectomy. There were significant differences in decrease in T2 ratio with loading before and after meniscectomy (9.8%/4.3% at the anterior zone, 4.0%/11.4% at the posterior zone, P < 0.05). By applying varus compression, a more remarkable decrease in the cartilage T2 in posterior ROIs after meniscectomy was achieved. (Before/after meniscectomy: 8.7%/2.5% at the anterior zone, 7.2%/18.7% at the posterior zone, P < 0.05).

CONCLUSIONS

Assuming a decrease in T2 with loading correlated with the applied pressure, a deficiency of the medial meniscus resulted in a shift of the primary area with a maximal decrease of cartilage T2 with loading posteriorly in the porcine knee joint, presumably reflecting the intraarticular environment of load transmission.

Responsiveness and reliability of MRI in knee osteoarthritis: a meta-analysis of published evidence

OBJECTIVE

To summarize literature on the responsiveness and reliability of MRI-based measures of knee osteoarthritis (OA) structural change.

METHODS

A literature search was conducted using articles published up to the time of the search, April 2009. 1338 abstracts obtained with this search were preliminarily screened for relevance and of these, 243 were selected for data extraction. For this analysis we extracted data on reliability and responsiveness for every reported synovial joint tissue as it relates to MRI measurement in knee OA. Reliability was defined by inter- and intra-reader intra-class correlation (ICC), or coefficient of variation, or kappa statistics. Responsiveness was defined as standardized response mean (SRM) - ratio of mean of change over time divided by standard deviation of change. Random-effects models were used to pool data from multiple studies.

RESULTS

The reliability analysis included data from 84 manuscripts. The inter-reader and intra-reader ICC were excellent (range 0.8-0.94) and the inter-reader and intra-reader kappa values for quantitative and semi-quantitative measures were all moderate to excellent (range 0.52-0.88). The lowest value (kappa=0.52) corresponded to semi-quantitative synovial scoring intra-reader reliability and the highest value (ICC=0.94) for semi-quantitative cartilage morphology. The responsiveness analysis included data from 42 manuscripts. The pooled SRM for quantitative measures of cartilage morphometry for the medial tibiofemoral joint was -0.86 (95% confidence intervals (CI) -1.26 to -0.46). The pooled SRM for the semi-quantitative measurement of cartilage morphology for the medial tibiofemoral joint was 0.55 (95% CI 0.47-0.64). For the quantitative analysis, SRMs are negative because the quantitative value, indicating a loss of cartilage, goes down. For the semi-quantitative analysis, SRMs indicating a loss in cartilage are positive (increase in score).

CONCLUSION

MRI has evolved substantially over the last decade and its strengths include the ability to visualize individual tissue pathologies, which can be measured reliably and with good responsiveness using both quantitative and semi-quantitative techniques.

Web-based multilayer viewing interface for knee cartilage

Many adults suffer from osteoarthritis (OA) with the majority of people over 65 showing radiographic evidence of the disease. To carry out effective diagnosis and treatment, it is necessary to understand the progression of cartilage loss and study the effectiveness of therapeutic interventions. Hence, it is important to have accurate, fast diagnosis of the disease. In this paper, we describe a Web-based user interface that enables the direct viewing of 2-D and 3-D image data from the visceral and tissue levels of the biological continuum (i.e., the continuum comprising systems, viscera, tissue, cells, proteins, and genes)--while preserving geometric integrity. This is achieved despite the fact that the data are from different modalities (i.e., magnetic resonance (MR) and light microscopy). The user interface was tested using image data acquired from a study of articular cartilage thickness in the porcine knee. The interface allows the clinician to view both MR and light microscopy images in an integrated manner-with the information linked geometrically.

Cartilage thickness visualization using 2D WearMaps and TrackBack

Osteoarthritis (OA) has a significant impact in terms of morbidity, quality of life, economic and social cost. It is the most prevalent form of arthritis - affecting a large proportion of the population, internationally. The use of Magnetic Resonance (MR) Imaging (MRI) has gained significant support. MRI allows detailed, multi-planar analysis of the joint anatomy, as well as cartilage and underlying bone status; with the ability to view articular surfaces at any angle. In this paper we describe a user interface to visualize the articular cartilage thickness using 2D WearMap derived using MR knee images. The user interface comprises an interactive function (TrackBack) which allows to the Clinician to easily and rapidly refer to the radiological information (e.g. MR images), while maintaining the geometric integrity between the WearMap and the MR image.