T2 values of articular cartilage in clinically relevant subregions of the asymptomatic knee

A reproducibility study of knee cartilage volume and thickness values derived by fully automatic segmentation based on three-dimensional dual-echo in steady state data from 1.5 T and 3 T magnetic resonance imaging

OBJECTIVE

To evaluate the repeatability of cartilage volume and thickness values at 1.5 T MRI using a fully automatic cartilage segmentation method and reproducibility of the method between 1.5 T and 3 T data.

METHODS

The study included 20 knee joints from 10 healthy subjects with each subject having undergone double-knee MRI. All knees were scanned at 1.5 T and 3 T MR scanners using a three-dimensional (3D) high-resolution dual-echo in steady state (DESS) sequence. Cartilage volume and thickness of 21 subregions were quantified using a fully automatic cartilage segmentation research application (MR Chondral Health, version 3.0, Siemens Healthcare, Erlangen, Germany). The volume and thickness values derived from fully automatically computed segmentation masks were analyzed for the scan-rescan data from the same volunteers. The accuracy of the automatic segmentation of the cartilage in 1.5 T images was evaluated by the dice similarity coefficient (DSC) and Hausdorff distance (HD) using the manually corrected segmentation as a reference. The volume and thickness values calculated from 1.5 T and 3 T were also compared.

RESULTS

No statistically significant differences were found for cartilage thickness or volume across all subregions between the scan-rescanned data at 1.5 T (P > 0.05). The mean DSC between the fully automatic and manually corrected knee cartilage segmentation contours at 1.5 T was 0.9946. The average value of HD was 2.41 mm. Overall, there was no statistically significant difference in the cartilage volume or thickness in most-subregions between the two field strengths (P > 0.05) except for the medial region of femur and tibia. Bland-Altman plot and intraclass correlation coefficient (ICC) showed high consistency between results obtained based on same and different scanning sequences.

CONCLUSION

The cartilage segmentation software had high repeatability for DESS images obtained from the same device. In addition, the overall reproducibility of the images obtained from equipment of two different field strengths was satisfactory.

CartiMorph: A framework for automated knee articular cartilage morphometrics

We introduce CartiMorph, a framework for automated knee articular cartilage morphometrics. It takes an image as input and generates quantitative metrics for cartilage subregions, including the percentage of full-thickness cartilage loss (FCL), mean thickness, surface area, and volume. CartiMorph leverages the power of deep learning models for hierarchical image feature representation. Deep learning models were trained and validated for tissue segmentation, template construction, and template-to-image registration. We established methods for surface-normal-based cartilage thickness mapping, FCL estimation, and rule-based cartilage parcellation. Our cartilage thickness map showed less error in thin and peripheral regions. We evaluated the effectiveness of the adopted segmentation model by comparing the quantitative metrics obtained from model segmentation and those from manual segmentation. The root-mean-squared deviation of the FCL measurements was less than 8%, and strong correlations were observed for the mean thickness (Pearson's correlation coefficient ρ∈[0.82,0.97]), surface area (ρ∈[0.82,0.98]) and volume (ρ∈[0.89,0.98]) measurements. We compared our FCL measurements with those from a previous study and found that our measurements deviated less from the ground truths. We observed superior performance of the proposed rule-based cartilage parcellation method compared with the atlas-based approach. CartiMorph has the potential to promote imaging biomarkers discovery for knee osteoarthritis.

Subject-specific biomechanical analysis to estimate locations susceptible to osteoarthritis-Finite element modeling and MRI follow-up of ACL reconstructed patients

The aims of this case-control study were to: (1) Identify cartilage locations and volumes at risk of osteoarthritis (OA) using subject-specific finite element (FE) models; (2) Quantify the relationships between the simulated biomechanical parameters and T₂ and T_1ρ relaxation times of magnetic resonance imaging (MRI). We created subject-specific FE models for seven patients with anterior cruciate ligament (ACL) reconstruction and six controls based on a previous proof-of-concept study. We identified locations and cartilage volumes susceptible to OA, based on maximum principal stresses and absolute maximum shear strains in cartilage exceeding thresholds of 7 MPa and 32%, respectively. The locations and volumes susceptible to OA were compared qualitatively and quantitatively against 2-year longitudinal changes in T₂ and T_1ρ relaxation times. The degeneration volumes predicted by the FE models, based on excessive maximum principal stresses, were significantly correlated (r = 0.711, p < 0.001) with the degeneration volumes determined from T₂ relaxation times. There was also a significant correlation between the predicted stress values and changes in T₂ relaxation time (r = 0.649, p < 0.001). Absolute maximum shear strains and changes in T_1ρ relaxation time were not significantly correlated. Five out of seven patients with ACL reconstruction showed excessive maximum principal stresses in either one or both tibial cartilage compartments, in agreement with follow-up information from MRI. Expectedly, for controls, the FE models and follow-up information showed no degenerative signs. Our results suggest that the presented modelling methodology could be applied to prospectively identify ACL reconstructed patients at risk of biomechanically driven OA, particularly by the analysis of maximum principal stresses of cartilage.

Analysis of Knee Joint Injury Caused by Physical Training of Freshmen Students Based on 3T MRI and Automatic Cartilage Segmentation Technology: A Prospective Study

Background

The differential effects of various exercises on knee joint injury have not been well documented. Improper physical training can cause irreversible damage to the knee joint. MRI is generally used to precisely analyze morphological and biochemical changes in the knee cartilage. We compared the effects of long-walking and regular daily physical training on acute and chronic knee joint injuries as well as cartilage structure in freshmen students.

Methods

A total of 23 young male college freshmen were recruited to participate in an 8-day 240 km long distance walk and a one-year daily training. 3D-DESSwe, 2D T2 mapping, DIXON, and T1WI of the right knee joint were performed using the MAGNETOM Spectra 3T MR scanner. The injury of meniscus, bone marrow edema, ligaments and joint effusion is graded. Cartilage volume, thickness and T2 values of 21 sub-regions of the knee cartilage were estimated using automatic cartilage segmentation prototype software. Friedman's test and Wilcoxon paired rank-sum test were used to compare quantitative indices of knee cartilage in three groups.

Results

The injury to the medial meniscus and anterior cruciate ligament of the knee joint, joint effusion, and bone marrow edema was significantly higher in the long-walking group compared to the baseline and daily groups. Furthermore, injury to the lateral meniscus was significantly worse in the long-walking group compared to the baseline group but was significantly better in the daily group compared to the baseline group. No significant changes to the posterior cruciate ligament were observed among the three groups. Knee cartilage volume was significantly increased, mainly in the stress surface of the femur, patella, and the lateral area of the tibial plateau. Regular daily training did not significantly change the thickness of the knee cartilage. Conversely, knee cartilage thickness decreased in the long-walking group, especially in the medial and lateral areas of the femur and tibial plateau. Moreover, no significant changes were observed in the knee cartilage volume of the long-walking group. Both long-walking and daily groups showed reduced T2 values of the knee joint compared to the baseline.

Conclusion

Among freshmen students and the training of this experimental intensity, our results show that regular daily training does not cause high-level injury to the knee joint, but improve the knee joint function adaptability by increasing cartilage volume. Moreover, knee injury caused by short-term long walking can be reversible.

Clinical validation of the use of prototype software for automatic cartilage segmentation to quantify knee cartilage in volunteers

Background

The cartilage segmentation algorithms make it possible to accurately evaluate the morphology and degeneration of cartilage. There are some factors (location of cartilage subregions, hydrarthrosis and cartilage degeneration) that may influence the accuracy of segmentation. It is valuable to evaluate and compare the accuracy and clinical value of volume and mean T2* values generated directly from automatic knee cartilage segmentation with those from manually corrected results using prototype software.

Method

Thirty-two volunteers were recruited, all of whom underwent right knee magnetic resonance imaging examinations. Morphological images were obtained using a three-dimensional (3D) high-resolution Double-Echo in Steady-State (DESS) sequence, and biochemical images were obtained using a two-dimensional T2* mapping sequence. Cartilage score criteria ranged from 0 to 2 and were obtained using the Whole-Organ Magnetic Resonance Imaging Score (WORMS). The femoral, patellar, and tibial cartilages were automatically segmented and divided into subregions using the post-processing prototype software. Afterwards, all the subregions were carefully checked and manual corrections were done where needed. The dice coefficient correlations for each subregion by the automatic segmentation were calculated.

Results

Cartilage volume after applying the manual correction was significantly lower than automatic segmentation (P < 0.05). The percentages of the cartilage volume change for each subregion after manual correction were all smaller than 5%. In all the subregions, the mean T2* relaxation time within manual corrected subregions was significantly lower than in regions after automatic segmentation (P < 0.05). The average time for the automatic segmentation of the whole knee was around 6 min, while the average time for manual correction of the whole knee was around 27 min.

Conclusions

Automatic segmentation of cartilage volume has a high dice coefficient correlation and it can provide accurate quantitative information about cartilage efficiently without individual bias.

Advances in knowledge: Magnetic resonance imaging is the most promising method to detect structural changes in cartilage tissue. Unfortunately, due to the structure and morphology of the cartilages obtaining accurate segmentations can be problematic. There are some factors (location of cartilage subregions, hydrarthrosis and cartilage degeneration) that may influence segmentation accuracy. We therefore assessed the factors that influence segmentations error.

Quantitative MRI evaluation of articular cartilage in patients with meniscus tear

PURPOSE

The aim of this study was to assess quantitatively articular cartilage volume, thickness, and T2 value alterations in meniscus tear patients.

MATERIALS AND METHODS

The study included 32 patients with meniscus tears (17 females, 15 males; mean age: 40.16 ± 11.85 years) and 24 healthy controls (12 females; 12 males; mean age: 36 ± 9.14 years). All subjects were examined by 3 T magnetic resonance imaging (MRI) with 3D dual-echo steady-state (DESS) and T2 mapping images. All patients underwent diagnostic arthroscopy and treatment. Cartilage thickness, cartilage volume and T2 values of 21 subregions of knee cartilage were measured using the prototype KneeCaP software (version 2.1; Siemens Healthcare, Erlangen, Germany). Mann-Whitney-U tests were utilized to determine if there were any significant differences among subregional articular cartilage volume, thickness and T2 value between patients with meniscus tear and the control group.

RESULTS

The articular cartilage T2 values in all subregions of the femur and tibia in the meniscus tear group were significantly higher (p< 0.05) than in the healthy control group. The cartilage thickness of the femoral condyle medial, femur trochlea, femur condyle lateral central, tibia plateau medial anterior and patella facet medial inferior in the meniscus tear group were slightly higher than in the control group (p< 0.05). In the femur trochlea medial, patella facet medial inferior, tibia plateau lateral posterior and tibia plateau lateral central, there were significant differences in relative cartilage volume percentage between the meniscus tear group and the healthy control group (p< 0.05). Nineteen patients had no cartilage abnormalities (Grade 0) in the meniscus tear group, as confirmed by arthroscopic surgery, and their T2 values in most subregions were significantly higher (p< 0.05) than those of the healthy control group.

CONCLUSION

The difference in articular cartilage indexes between patients with meniscus tears and healthy people without such tears can be detected by using quantitative MRI. Quantitative T2 values enable early and sensitive detection of early cartilage lesions.

Reproducibility of an Automated Quantitative MRI Assessment of Low-Grade Knee Articular Cartilage Lesions

OBJECTIVE

The goal of this study was to assess the reproducibility of an automated knee cartilage segmentation of 21 cartilage regions with a model-based algorithm and to compare the results with manual segmentation.

DESIGN

Thirteen patients with low-grade femoral cartilage defects were included in the study and were scanned twice on a 7-T magnetic resonance imaging (MRI) scanner 8 days apart. A 3-dimensional double-echo steady-state (3D-DESS) sequence was used to acquire MR images for automated cartilage segmentation, and T2-mapping was performed using a 3D triple-echo steady-state (3D-TESS) sequence. Cartilage volume, thickness, and T2 and texture features were automatically extracted from each knee for each of the 21 subregions. DESS was used for manual cartilage segmentation and compared with automated segmentation using the Dice coefficient. The reproducibility of each variable was expressed using standard error of measurement (SEM) and smallest detectable change (SDC).

RESULTS

The Dice coefficient for the similarity between manual and automated segmentation ranged from 0.83 to 0.88 in different cartilage regions. Test-retest analysis of automated cartilage segmentation and automated quantitative parameter extraction revealed excellent reproducibility for volume measurement (mean SDC for all subregions of 85.6 mm³), for thickness detection (SDC = 0.16 mm) and also for T2 values (SDC = 2.38 ms) and most gray-level co-occurrence matrix features (SDC = 0.1 a.u.).

CONCLUSIONS

The proposed technique of automated knee cartilage evaluation based on the segmentation of 3D MR images and correlation with T2 mapping provides highly reproducible results and significantly reduces the segmentation effort required for the analysis of knee articular cartilage in longitudinal studies.

Micro- and Macroscale Assessment of Posterior Cruciate Ligament Functionality Based on Advanced MRI Techniques

T2 mapping assesses tissue ultrastructure and composition, yet the association of imaging features and tissue functionality is oftentimes unclear. This study aimed to elucidate this association for the posterior cruciate ligament (PCL) across the micro- and macroscale and as a function of loading. Ten human cadaveric knee joints were imaged using a clinical 3.0T scanner and high-resolution morphologic and T2 mapping sequences. Emulating the posterior drawer test, the joints were imaged in the unloaded (δ0) and loaded (δ1) configurations. For the entire PCL, its subregions, and its osseous insertion sites, loading-induced changes were parameterized as summary statistics and texture variables, i.e., entropy, homogeneity, contrast, and variance. Histology confirmed structural integrity. Statistical analysis was based on parametric and non-parametric tests. Mean PCL length (37.8 ± 1.8 mm [δ0]; 44.0 ± 1.6 mm [δ1] [p < 0.01]), mean T2 (35.5 ± 2.0 ms [δ0]; 37.9 ± 1.3 ms [δ1] [p = 0.01]), and mean contrast values (4.0 ± 0.6 [δ0]; 4.9 ± 0.9 [δ1] [p = 0.01]) increased significantly under loading. Other texture features or ligamentous, osseous, and meniscal structures remained unaltered. Beyond providing normative T2 values across various scales and configurations, this study suggests that ligaments can be imaged morphologically and functionally based on joint loading and advanced MRI acquisition and post-processing techniques to assess ligament integrity and functionality in variable diagnostic contexts.

Review of Quantitative Knee Articular Cartilage MR Imaging

Osteoarthritis (OA) is one of the most prevalent disorders in today’s society, resulting in significant socio-economic costs and morbidity. MRI is widely used as a non-invasive imaging tool for OA of the knee. However, conventional knee MRI has limitations to detect subtle early cartilage degeneration before morphological changes are visually apparent. Novel MRI pulse sequences for cartilage assessment have recently received increased attention due to newly developed compositional MRI techniques, including: T2 mapping, T1rho mapping, delayed gadolinium-enhanced MRI of cartilage (dGEMRIC), sodium MRI, diffusion-weighted imaging (DWI)/ diffusion tensor imaging (DTI), ultrashort TE (uTE), and glycosaminoglycan specific chemical exchange saturation transfer (gagCEST) imaging. In this article, we will first review these quantitative assessments. Then, we will discuss the variations of quantitative values of knee articular cartilage with cartilage layer (depth)- and angle (regional)-dependent approaches. Multiple MRI sequence techniques can discern qualitative differences in knee cartilage. Normal articular hyaline cartilage has a zonal variation in T2 relaxation times with increasing T2 values from the subchondral bone to the articular surface. T1rho values were also higher in the superficial layer than in the deep layer in most locations in the medial and lateral femoral condyles, including the weight-bearing portion. Magic angle effect on T2 mapping is clearly observed in the both medial and lateral femoral condyles, especially within the deep layers. One of the limitations for clinical use of these compositional assessments is a long scan time. Recent new approaches with compressed sensing (CS) and MR fingerprinting (MRF) have potential to provide accurate and fast quantitative cartilage assessments.

Is T2 mapping reliable in evaluation of native and repair cartilage tissue of the knee?

PURPOSE

To evaluate the effect of imaging plane and experience of observers on the reliability of T2 mapping of native and repair cartilage tissue of the knee.

METHODS

Fifteen consecutive patients from two randomised controlled trials (RCTs) were included in this cross-sectional study. Patients with an isolated knee cartilage lesion were randomised to receive either debridement or microfracture (RCT 1) or debridement or autologous chondrocyte implantation (RCT 2). T2 mapping was performed in coronal and sagittal planes two years postoperatively. A musculoskeletal radiologist, a resident of radiology and two orthopaedic surgeons measured the T2 values independently. Intraclass Correlation Coefficient (ICC) with 95% Confidence Intervals was used to calculate the inter- and intraobserver agreement.

RESULTS

Mean age for the patients was 36.8 ± 11 years, 8 (53%) were men. The overall interobserver agreement varied from poor to good with ICCs in the range of 0.27- 0.76 for native cartilage and 0.00 - 0.90 for repair tissue. The lowest agreement was achieved for evaluations of repair cartilage tissue. The estimated ICCs suggested higher inter- and intraobserver agreement for radiologists. On medial femoral condyles, T2 values were higher for native cartilage on coronal images (p < 0.001) and for repair tissue on sagittal images (p < 0.001).

CONCLUSIONS

The reliability of T2 mapping of articular cartilage is influenced by the imaging plane and the experience of the observers. This influence may be more profound for repair cartilage tissue. This is important to consider when using T2 mapping to measure outcomes after cartilage repair surgery.

TRIAL REGISTRATION

ClinicalTrials.gov, NCT02637505 and NCT02636881 , registered December 2015.

LEVEL OF EVIDENCE

II, based on prospective data from two RCTs.

Longitudinal Femoral Cartilage T2 Relaxation Time and Thickness Changes with Fast Sequential Radiographic Progression of Medial Knee Osteoarthritis-Data from the Osteoarthritis Initiative (OAI)

This study tested for longitudinal changes in femoral cartilage T2 relaxation time and thickness in fast-progressing medial femorotibial osteoarthritis (OA). From the Osteoarthritis Initiative (OAI) database, nineteen knees fulfilled the inclusion criteria, which included medial femorotibial OA and sequential progression from Kellgren–Lawrence grade (KL) 1 to KL2 to KL3 within five years. Median T2 value and mean thickness were calculated for six condylar volumes of interest (VOIs; medial/lateral anterior, central, posterior) and six sub-VOIs (medial/lateral anterior external, central, internal). T2 value and thickness changes between severity timepoints were tested using repeated statistics. T2 values increased between KL1 and KL2 and between KL1 and KL3 in the medial compartment (p ≤ 0.02), whereas both increases and decreases were observed between the same timepoints in the lateral compartment (p ≤ 0.02). Cartilage thickness decreased in VOI/subVOIs of the medial compartment from KL1 to KL2 and KL3 (p ≤ 0.014). Cartilage T2 value and thickness changes varied spatially over the femoral condyles. While all T2 changes occurred in the early radiographic stages of OA, thickness changes occurred primarily in the later stages. These data therefore support the use of T2 relaxation time analyses in methods of detecting disease-related change during early OA, a valuable period for therapeutic interventions.

Quantitative T2 mapping of the glenohumeral joint cartilage in asymptomatic shoulders and shoulders with increasing severity of rotator cuff pathology

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Glenohumeral cartilage T2 values were correlated to increasing rotator cuff pathology severity.

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Massive tear versus lesser injury differences were most evident in superior humeral cartilage.

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Sagittal T2 mapping best captures superior humeral head cartilage change in massive tear patients.

Purpose

To examine the relationship between glenohumeral cartilage T2 mapping values and rotator cuff pathology.

Method

Fifty-nine subjects (age 48.2 ± 13.5 years, 15 asymptomatic volunteers and 10 tendinosis, 13 partial-thickness tear, 8 full-thickness tear, and 13 massive tear patients) underwent glenohumeral cartilage T2 mapping. The humeral head cartilage was segmented in the sagittal and coronal planes. The glenoid cartilage was segmented in the coronal plane. Group means for each region were calculated and compared between the groups.

Results

Massive tear group T2 values were significantly higher than the asymptomatic group values for the humeral head cartilage included in the sagittal (45 ± 7 versus 32 ± 4 ms, p <  .001) and coronal (44 ± 6 versus 38 ± 1 ms, p =  0.01) plane images. Mean T2 was also significantly higher for massive than full-thickness tears (45 ± 7 versus 38 ± 5 ms, p =  0.02), massive than partial-thickness tears (45 ± 7 versus 34 ± 4 ms, p <  0.001), and massive tears than tendinosis (45 ± 7 versus 35 ± 4 ms, p =  0.001) in the sagittal-images humeral head region and significantly higher for massive tears than asymptomatic shoulders (44 ± 6 versus 38 ± 1 ms, p =  0.01) in the coronal-images humeral head region.

Conclusion

Humeral head cartilage T2 values were significantly positively correlated with rotator cuff pathology severity. Massive rotator cuff tear patients demonstrated significantly higher superior humeral head cartilage T2 mapping values relative to subjects with no/lesser degrees of rotator cuff pathology.

Identification of locations susceptible to osteoarthritis in patients with anterior cruciate ligament reconstruction: Combining knee joint computational modelling with follow-up T1ρ and T2 imaging

BACKGROUND

Finite element modelling can be used to evaluate altered loading conditions and failure locations in knee joint tissues. One limitation of this modelling approach has been experimental comparison. The aims of this proof-of-concept study were: 1) identify areas susceptible to osteoarthritis progression in anterior cruciate ligament reconstructed patients using finite element modelling; 2) compare the identified areas against changes in T₂ and T_1ρ values between 1-year and 3-year follow-up timepoints.

METHODS

Two patient-specific finite element models of knee joints with anterior cruciate ligament reconstruction were created. The knee geometry was based on clinical magnetic resonance imaging and joint loading was obtained via motion capture. We evaluated biomechanical parameters linked with cartilage degeneration and compared the identified risk areas against T₂ and T_1ρ maps.

FINDINGS

The risk areas identified by the finite element models matched the follow-up magnetic resonance imaging findings. For Patient 1, excessive values of maximum principal stresses and shear strains were observed in the posterior side of the lateral tibial and femoral cartilage. For Patient 2, high values of maximum principal stresses and shear strains of cartilage were observed in the posterior side of the medial joint compartment. For both patients, increased T₂ and T_1ρ values between the follow-up times were observed in the same areas.

INTERPRETATION

Finite element models with patient-specific geometries and motions and relatively simple material models of tissues were able to identify areas susceptible to post-traumatic knee osteoarthritis. We suggest that the methodology presented here may be applied in large cohort studies.

T2 distribution profiles are a good way to show cartilage regional variabilities and cartilage insufficiency

OBJECTIVE

To use T2 relaxation time distribution profiles to assess inter-group regional differences along articular surfaces and to evaluate the feasibility of this analysis for comparison of cartilage insufficiency.

MATERIALS AND METHODS

Twelve pairs matched according to age and gender (12 healthy volunteers and 12 patients after anterior cruciate ligament reconstruction (ACLR)) underwent 3-T MRI. T2 maps were calculated from six time echo images of the mid-sagittal slice in the lateral and medial compartment. The femoral and tibial cartilage was analyzed by measuring T2 distribution profiles along the articular surfaces.

RESULTS

T2 distribution profiles were generated along the length of the articular surface in the femorotibial compartments. Differences in the T2 distribution profiles between the tibial and femoral cartilage as well as between the cartilage of the femoral condyles were identified in healthy individuals. T2 distribution profiles clearly demonstrated cartilage insufficiency in the weight-bearing areas for subjects in the ACLR group.

CONCLUSIONS

T2 distribution profiles can identify regional differences in femoral and tibial cartilage. The T2 distribution profile pattern is preserved with cartilage insufficiency, however, with important differences in T2 values for the ACLR group in weight-bearing areas.

Comprehensive description of T2 value spatial variations in non-osteoarthritic femoral cartilage using three-dimensional registration of morphological and relaxometry data

PURPOSE

The aim of this study was to develop and assess a method of quantifying cartilage T2 relaxation times in a series of volumes of interest (VOIs) covering the entire cartilage of the femoral condyles. Subsequently, the method was used to test for T2 spatial variations in non-osteoarthritic (OA) knees.

METHODS

Ten non-OA subjects (five female, average 30 years) were enrolled after informed consent. Three-dimensional bone and cartilage models were created by double echo steady state (DESS) morphological magnetic resonance image (MRI) segmentation, and the models were semi-manually registered with multi-slice, multi-echo (MSME) T2 MRI. Mean T2 values were calculated for 12 VOIs derived from cartilage thickness literature and their respective superficial and deep layers.

RESULTS

Analyses showed that intra- and inter-rater reliabilities of the presented method were "good" to "excellent" in more than 90% of the VOIs. Additionally, several spatial differences in T2 values were observed, including, for the medial condyle, higher T2 values in the anterior and central VOIs versus in the posterior VOI (p < .05). T2 values were also generally higher in the superficial versus deep layers (p < .05).

CONCLUSIONS

The presented MRI T2 analysis method is reliable and provides a comprehensive quantification of spatial heterogeneity of healthy cartilage compositional properties. This method can be further applied to better understand knee OA pathophysiology and potentially define clinically relevant diagnostic features of the disease.

Topographical Variation of Human Femoral Articular Cartilage Thickness, T1rho and T2 Relaxation Times Is Related to Local Loading during Walking

OBJECTIVE

Early detection of degenerative changes in the cartilage matrix composition is essential for evaluating early interventions that slow down osteoarthritis (OA) initiation. T1rho and T2 relaxation times were found to be effective for detecting early changes in proteoglycan and collagen content. To use these magnetic resonance imaging (MRI) methods, it is important to document the topographical variation in cartilage thickness, T1rho and T2 relaxation times in a healthy population. As OA is partially mechanically driven, the relation between these MRI-based parameters and localized mechanical loading during walking was investigated.

DESIGN

MR images were acquired in 14 healthy adults and cartilage thickness and T1rho and T2 relaxation times were determined. Experimental gait data was collected and processed using musculoskeletal modeling to identify weight-bearing zones and estimate the contact force impulse during gait. Variation of the cartilage properties (i.e., thickness, T1rho, and T2) over the femoral cartilage was analyzed and compared between the weight-bearing and non-weight-bearing zone of the medial and lateral condyle as well as the trochlea.

RESULTS

Medial condyle cartilage thickness was correlated to the contact force impulse ( r = 0.78). Lower T1rho, indicating increased proteoglycan content, was found in the medial weight-bearing zone. T2 was higher in all weight-bearing zones compared with the non-weight-bearing zones, indicating lower relative collagen content.

CONCLUSIONS

The current results suggest that medial condyle cartilage is adapted as a long-term protective response to localized loading during a frequently performed task and that the weight-bearing zone of the medial condyle has superior weight bearing capacities compared with the non-weight-bearing zones.

Systematic review and meta-analysis of the reliability and discriminative validity of cartilage compositional MRI in knee osteoarthritis

OBJECTIVE

To assess reliability and discriminative validity of cartilage compositional magnetic resonance imaging (MRI) in knee osteoarthritis (OA).

DESIGN

The study was carried out per PRISMA recommendations. We searched MEDLINE and EMBASE (1974 - present) for eligible studies. We performed qualitative synthesis of reliability data. Where data from at least two discrimination studies were available, we estimated pooled standardized mean difference (SMD) between subjects with and without OA. Discrimination analyses compared controls and subjects with mild OA (Kellgren-Lawrence (KL) grade 1-2), severe OA (KL grade 3-4) and OA not otherwise specified (NOS) where not possible to stratify. We assessed quality of the evidence using Quality Appraisal of Diagnostic Reliability (QAREL) and Quality Assessment of Diagnostic Accuracy (QUADAS-2) tools.

RESULTS

Fifty-eight studies were included in the reliability analysis and 26 studies were included in the discrimination analysis, with data from a total of 2,007 knees. Intra-observer, inter-observer and test-retest reliability of compositional techniques were excellent with most intraclass correlation coefficients >0.8 and coefficients of variation <10%. T1rho and T2 relaxometry were significant discriminators between subjects with mild OA and controls, and between subjects with OA (NOS) and controls (P < 0.001). T1rho showed best discrimination for mild OA (SMD [95% CI] = 0.73 [0.40 to 1.06], P < 0.001) and OA (NOS) (0.60 [0.41 to 0.80], P < 0.001). Quality of evidence was moderate for both parts of the review.

CONCLUSIONS

Cartilage compositional MRI techniques are reliable and, in the case of T1rho and T2 relaxometry, can discriminate between subjects with OA and controls.

Quantitative mapping of glenohumeral cartilage in asymptomatic subjects using 3 T magnetic resonance imaging

OBJECTIVE

The purpose of this study was to develop quantitative T2 mapping methodology in asymptomatic shoulders for the entire mappable region of the glenohumeral cartilage in the coronal and sagittal planes, to assess the feasibility and limitations of the development of a diagnostic tool for future application in symptomatic patients.

MATERIALS AND METHODS

Twenty-one asymptomatic volunteers underwent sagittal and coronal glenohumeral T2 mapping, as the spherical geometry of the humeral head obviates the need to evaluate the entire glenohumeral cartilage in a single plane. The humeral head cartilage orthogonal to the mapping plane was manually segmented in the sagittal and coronal planes, whereas the glenoid cartilage was segmented in the coronal plane. Cartilage T2 summary statistics were calculated and coverage in each mapping plane was qualitatively assessed.

RESULTS

The mean ± standard deviation of the glenoid cartilage T2 was 38 ± 2 ms. The coronal and sagittal mapping planes captured different regions of the humeral head with some overlap: inferior-medial to superior-lateral versus superior/superior-lateral to anterior-lateral and posterior-lateral respectively. The mean humeral head cartilage T2 in the coronal plane was 41 ± 3 ms, which was significantly different (p < 0.05) from the sagittal plane mean of 34 ± 2 ms.

CONCLUSION

This study measured characteristic glenoid and humeral head cartilage T2 values over the area mappable with two planes. Importantly, this study demonstrated that two-dimensional mapping in a single plane or two combined planes cannot capture the entirety of the semi-spherical humeral head cartilage. This highlights the need for three-dimensional T2 mapping techniques in the shoulder.

Assessing patterns of T2/T1rho change in grade 1 cartilage lesions of the distal femur using an angle/layer dependent approach

PURPOSE

To assess changes in the patterns of T2 and T1rho values within grade 1 cartilage lesions of osteoarthritis (OA) patients compared to healthy controls.

MATERIALS AND METHODS

Twenty healthy knees and 25 OA knees were examined on a 3 T scanner. Areas of signal heterogeneity within the cartilage of the distal femur were identified using fat suppressed proton density-weighted imagines. T2 and T1rho values in each OA patient with grade 1 lesions were compared to average T2 and T1rho values of the corresponding areas in healthy subjects.

RESULTS

A total of 28 areas including grade 1 lesion were identified. Compared to normal cartilage, the majority of grade 1 cartilage lesions demonstrated either no significant change or a statistically significant increase in both T2 values (18/28, 64%) and T1rho values (23/28, 82%). Compared to T2, T1rho demonstrated a greater proportion of statistically significantly higher values in OA patients than those from the normal controls. However, T2 and T1rho values in grade 1 lesions can be decreased, or demonstrate mixed patterns compared to those in healthy cartilage.

CONCLUSION

Our results suggest that early degenerative cartilage lesions can demonstrate various patterns of T2 and T1rho changes.

MRI T2 Mapping of Knee Articular Cartilage Using Different Acquisition Sequences and Calculation Methods at 1.5 Tesla

OBJECTIVE

This study aims to determine how magnetic resonance imaging (MRI) acquisition techniques and calculation methods affect T2 values of knee cartilage at 1.5 tesla and to identify sequences that can be used for high-resolution T2 mapping in short scanning times.

MATERIALS AND METHODS

This study was performed on phantom and 29 patients who underwent MRI of the knee joint at 1.5 tesla. The protocol includes T2 mapping sequences based on Single-Echo Spin Echo (SESE), Multi-Echo Spin Echo (MESE), Fast Spin Echo (FSE) and Turbo Gradient Spin Echo (TGSE). The T2 relaxation times were quantified and evaluated using three calculation methods (MapIt, Syngo Offline and mono-exponential fit). signal-to-noise ratios (SNR) were measured in all sequences. All statistical analyses were performed using the t-test.

RESULTS

The average T2 values in phantom were 41.7 ± 13.8 ms for SESE, 43.2 ± 14.4 ms for MESE, 42.4 ± 14.1 ms for FSE and 44 ± 14.5 ms for TGSE. In the patient study, the mean differences were 6.5 ± 8.2 ms, 7.8 ± 7.6 ms and 8.4 ± 14.2 ms for MESE, FSE and TGSE compared to SESE, respectively; these statistical results were not significantly different (p > 0.05). The comparison between the three calculation methods showed no significant difference (p > 0.05). The t-test showed no significant difference between SNR values for all sequences.

CONCLUSION

T2 values depend not only on the sequence type but also on the calculation method. None of the sequences revealed significant differences compared to the SESE reference sequence. TGSE with its short scanning time can be used for high-resolution T2 mapping.

Quantifiable Imaging Biomarkers for Evaluation of the Posterior Cruciate Ligament Using 3-T Magnetic Resonance Imaging: A Feasibility Study

Background:

Quantitative magnetic resonance imaging (MRI) techniques, such as T2 and T2 star (T2*) mapping, have been used to evaluate ligamentous tissue in vitro and to identify significant changes in structural integrity of a healing ligament. These studies lay the foundation for a clinical study that uses quantitative mapping to evaluate ligaments in vivo, particularly the posterior cruciate ligament (PCL). To establish quantitative mapping as a clinical tool for identifying and evaluating chronic or acute PCL injuries, T2 and T2* values first must be determined for an asymptomatic population.

Purpose:

To quantify T2 and T2* mapping properties, including texture variables (entropy, variance, contrast, homogeneity), of the PCL in an asymptomatic population. It was hypothesized that biomarker values would be consistent throughout the ligament, as measured across 3 clinically relevant subregions (proximal, middle, and distal thirds) in the asymptomatic cohort.

Study Design:

Cross-sectional study; Level of evidence, 4.

Methods:

Unilateral knee MRI scans were acquired for 25 asymptomatic subjects with a 3.0-T MRI system using T2 and T2* mapping sequences in the sagittal plane. The PCL was manually segmented and divided into thirds (proximal, middle, and distal). Summary statistics for T2 and T2* values were calculated. Intra- and interrater reliability was assessed across 3 raters to 2 time points.

Results:

The asymptomatic PCL cohort had mean T2 values of 36.7, 29.2, and 29.6 ms in the distal, middle, and proximal regions, respectively. The distal PCL exhibited significantly higher mean, variance, and contrast and lower homogeneity of T2 values than the middle and proximal subregions (P < .05). T2* results exhibited substantial positive skew and were therefore presented as median and quartile (Q) values. Median T2* values were 7.3 ms (Q1-Q3, 6.8-8.9 ms), 7.3 ms (Q1-Q3, 7.0-8.5 ms), and 7.3 ms (Q1-Q3, 6.4-8.2 ms) in the distal, middle, and proximal subregions, respectively.

Conclusion:

This is the first study to identify T2 and T2* mapping values, and their texture variables, for the asymptomatic PCL. The distal third of the PCL had significantly greater T2 values than the proximal or middle thirds.

Clinical Relevance:

T2 and T2* values of the asymptomatic PCL can provide a baseline for comparison with acute and chronic PCL injuries in future studies.

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.