Abstract
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.
Keywords: cartilage loading, thickness, T1rho relaxation time, T2 relaxation time, gait
Introduction
Osteoarthritis (OA) is one of the most prevalent chronic joint disorders affecting millions of people worldwide. It is a chronic degenerative disease with a multifactorial cause, which mostly affects the knee joint.1,2 Currently, no effective therapeutic interventions exist that overcome or delay the progression of OA.3 Early detection of degenerative changes in the cartilage is needed, as this would allow earlier intervention at a point where cartilage degeneration is minimal and where OA progression can be significantly delayed.
Frontal plane radiographs are used to diagnose OA, more specific with presence of osteophytes, subchondral bone sclerosis, cysts, and joint space narrowing reflecting cartilage loss, resulting in a Kellgren-Lawrence-score ≥2.4-6 However, to allow early intervention, methods that detect changes in the cartilage composition before irreversible, morphological changes occur are required. Classification of early OA is currently based on clinical scoring (i.e., presence of pain), standard radiographs (i.e., Kellgren-Lawrence-score <2) and anatomical magnetic resonance imaging (MRI) scoring, evaluating cartilage and/or meniscal degeneration and presence of bone marrow lesions; however, so far these evaluations do not account for changes in cartilage composition.6 Indeed, recently, quantitative MRI methods were developed that reflect the biochemical composition of the articular cartilage extracellular matrix.7-11 T1rho relaxation time can be used to assess relative proteoglycan content, whereas T2 relaxation time can be used as an index of collagen content and orientation.12,13 Increased T1rho relaxation time has been associated with a decreased proteoglycan concentration, which is one of the early degenerative changes in the cartilage extracellular matrix.10,14 Increased T2 relaxation time has been related to increased collagen anisotropy and collagen loss.8,15 Consequently, these sequences can be used for monitoring biochemical changes in extracellular matrix composition of the cartilage and therefore allow for an early detection of degenerative changes accompanied with OA before the onset of structural cartilage degeneration.
Insights gained from cadaveric and ex vivo studies, documented regional differences in cartilage structure and extracellular matrix composition.16-18 Cartilage homeostasis is at least partly regulated by mechanical loading and consequently local variations in loading could possibly explain the observed variation in extracellular matrix structure and composition.19,20 Biochemical analysis of cartilage explants showed that the weight-bearing regions of the cartilage had increased sulfated glycosaminoglycan (GAG) concentration compared with the non-weight-bearing region.21 Furthermore, GAG/collagen ratio was shown to be lower in the non-weight-bearing region compared to the weight-bearing region.18 Topographical variation in proteoglycan synthesis was observed in adult ovine cartilage, whereas this topographical variation was not observed in neonatal ovine cartilage. This suggests that the topographical variation in proteoglycan concentration is caused by the topographical variation in weight-bearing stress after birth as the neonatal cartilage was not exposed previously to the weight-bearing stress.17
As MRI relaxation times reflect the interaction between water and the surrounding matrix macromolecules, this topographical variability in matrix composition will be reflected in the cartilage relaxation times.12 Previously, T1rho relaxation time values were observed to be lower in the weight-bearing regions of the lateral and medial femoral condyles, suggesting increased proteoglycan content in these regions and therefore increased weight-bearing capacity of the cartilage.22,23 In contrast, T2 relaxation times were found to be heterogeneously distributed over the medial and lateral condyle and did not differ between weight-bearing and non-weight-bearing regions or was higher in the regions not covered by the meniscus.24-26 Additionally, thickness, T1rho and T2 relaxation times of the femoral cartilage were found to be related to the contact forces acting on the cartilage during walking.27 However, the aforementioned studies were based on a rather theoretical determination of the weight-bearing zone, restricting it to the position of the meniscus. Musculoskeletal modeling on the other hand has the potential to estimate the local cartilage pressures during locomotion, which allows for a more accurate description of the weight-bearing zones and local cartilage loading.
Therefore, to successfully investigate early changes in matrix composition using quantitative MRI methods, it is important to understand the topographical variation in cartilage structure, T1rho and T2 relaxation times in a healthy population. Therefore, the purpose of this study was to analyze the topographical variation of the cartilage thickness, T1rho and T2 relaxation times of the healthy femoral condyles and relate this to localized loading during walking, calculated using musculoskeletal modeling.
Methods
Subjects
Fourteen healthy volunteers (mean age 30.64 ± 6.04 years; mean weight 71.24 ± 6.89 kg; and mean height 178 ± 6.52 cm) were recruited for participation in the current study. Participants were included when they were asymptomatic and had no history of knee injury or surgery. The study was approved by the local ethics committee and written informed consent was obtained from all participants.
Medical Imaging
Imaging of the dominant leg was performed on a 3T Ingenia scanner after 1-hour standardized rest (Philips Healthcare, Best, the Netherlands). Participants were positioned in supine position with the knee in full extension and neutral rotation. The following scanning sequences were acquired: (1) A high-resolution 3-dimensional–fast spin echo (3D-FSE) acquisition used for soft tissue segmentation (repetition time [TR]/echo time [TE] = 1800/120 ms, field of view = 16 cm, matrix = 268 × 268, slice thickness = 1mm, echo train length = 85, bandwidth = 562 kHz, number of excitations (NEX) = 2, number of slices = 320, acquisition time = 5.94 minutes). (2) T1ρ relaxation time sequence (TR/TE = 5.9587/3.082 ms, time of recovery = 2000 ms, field of view = 16 cm, matrix = 292 × 256, slice thickness = 4 mm, echo train length = 64, bandwidth = 522 kHz, time of spinlock (SLT) = 0/10/20/40/60 ms, frequency of spinlock = 500 Hz, number of slices = 20, total acquisition time = 17.20 minutes). (3) T2 relaxation time sequence (TR = 4000 ms, TE = 11/22/33/44/55/66/77/8 8ms, field of view = 16 cm, matrix = 160 × 160, slice thickness = 4 mm, echo train length = 12, bandwidth = 367 kHz, number of slices = 20, acquisition time = 5.24 minutes).
Image Processing and Cartilage Segmentation
The same operator semiautomatically segmented the femoral cartilage and femur bone from the high-resolution images (3D-FSE) and 3D triangulated surfaces were created (Mimics Innovation Suite, Materialise, Leuven, Belgium). The segmented subject-specific cartilage surfaces were transformed onto the generic cartilage surface that is used in the musculoskeletal model using an advanced non-rigid deformation procedure (Mimics Innovation Suite, Materialise, Leuven, Belgium). Subsequently, cartilage thickness was calculated based on the minimal distance between the subchondral bone surface and the morphed cartilage surface for each vertex of the cartilage surface individually.28 Relaxation time maps were generated by a pixel-by-pixel based evaluation of the mono-exponential Levenberg-Marquardt fitting algorithm29:
The morphed cartilage surfaces were rigidly registered to the relaxation time maps and relaxation time values were assigned to the corresponding surface vertices ( Fig. 1 ).
Figure 1.
Methodological overview. First, subject-specific, thickness, T1rho and T2 relaxation time maps were registered on the generic mesh. Subsequently, the generic mesh was divided in angular segments with increments of 5° clockwise and counterclockwise from the vertical line (black line). Last, average thickness, T1rho and T2 relaxation times were determined in each segment separately. Furthermore, the analyses were conducted for the tibiofemoral (red lines) and trochlear cartilage (blue lines) separately.
The location-dependent profile of the thickness, T1rho and T2 relaxation times was evaluated over the cartilage surface over angular segments of 5°. To do so, a sphere was fitted onto the medial and lateral cartilage condyle vertices separately using a least-squares fitting algorithm. Next, the generic mesh was positioned in neutral postion and from the vertical line (angle 0°) the cartilage was divided in angular segments with 5° increments clockwise and counter-clockwise (i.e., negative angles are more toward posterior; Fig. 1 ). The cartilage was further subdivided in tibiofemoral and trochlear cartilage. The intercondylar notch was used to differentiate between the trochlear and tibiofemoral cartilage ( Fig. 1 ).
Subsequently, the average T1rho and T2 relaxation times and average thickness were calculated in each angular segment ( Fig. 1 ). Relaxation times between 1 and 100 ms were used to avoid outliers caused by a bad fit (0 ms) or by synovial fluid and chemical shift artifact (>100 ms).26 Additionally, the homogeneity was quantified by calculating the ratio of variability (expressed as the standard deviation) and the average thickness or relaxation times in a particular zone.
Motion Analysis
Experimental motion data were collected on the same day as the medical imaging. A 10-camera Vicon system (Vicon Oxford Metrics, 100Hz) was used to capture 3D marker positions while participants were walking at self-selected speed across the motion lab. Simultaneously, ground reaction forces were measured using force plates embedded in the ground. Markers were placed according to an extended full-body Plug-in-Gait markerset.27,30 Three trials with valid force plate contact were captured and retained for further processing.
Muscle and knee contact forces were calculated using a generic musculoskeletal model that was scaled to the subjects’ anthropometry.31 A validated customized knee joint that allows 6 degrees of freedom (DoF) tibiofemoral and patellofemoral joint kinematics was implemented in the generic lower extremity model.31,32 Lower limb muscles were represented by 44 musculotendon actuators and the major knee ligaments as well as the posterior capsule were represented by 14 bundles of nonlinear springs. An elastic foundation contact model was used to calculate the cartilage contact pressure.32,33 Uniform cartilage thickness distribution was assumed in both joints, with a combined thickness of 4 and 7 mm in the tibiofemoral and patellofemoral joint, respectively.28,34,35 Cartilage elastic modulus was set at 10 MPa and Poisson’s ratio at 0.45.36-38 The lower extremity model was implemented in SIMM with the Dynamics Pipeline (Musculographics Inc., Santa Rosa, CA) and SD/Fast (Parametric Technology Corp., Needham, MA) used to generate the multibody equations of motion. This model was found to be accurate in predicting contact forces measured using instrumented implants with a root mean square (RMS) error below 0.33 BW.39
After scaling the generic model to the subject anthropometry, joint angles were calculated using inverse kinematics. Next, muscle forces required to generate the measured joint kinematics were calculated using the concurrent optimization of muscle forces and kinematics algorithm that solves for the secondary kinematics (11 DoF), while minimizing the weighted sum of squared muscle activations and contact energy.40 This algorithm allows the kinematics in the secondary tibiofemoral and patellofemoral DoF to evolve as function of muscle, ligament and contact forces, since only the primary DoF (i.e., hip flexion, hip adduction, hip rotation, knee flexion, and ankle flexion) were prescribed to reproduce the measured values during the optimization.32,33,40 Finally, the impulse on each mesh element was calculated by integrating the resultant contact force on each element over time. The impulse on each angular segment was calculated by summing the impulses on each mesh face in each angular segment.
Statistics
The weight-bearing zone was determined as the zone on which impulse was estimated during the stance phase. The local relation over the different angular segments between the relaxation times or thickness values and impulses in the weight-bearing zone was evaluated using a Spearman rank correlation coefficient. Differences in T1rho and T2 relaxation times and thickness between weight-bearing and non-weight-bearing areas were analyzed using a Wilcoxon signed rank test. Alpha level was set at 0.05 and all statistical tests were performed in MATLAB (MATLAB 2016b, The Math Works, Inc., Natick, Massachusetts, USA).
Results
In the current cohort of healthy participants, the weight-bearing zone on the medial condyle during gait was identified between −45° posterior and 15° anterior, whereas the weight-bearing zone on the lateral condyle was observed between −45° posterior and 0° anterior ( Fig. 2 ).
Figure 2.
Angular distribution. Angle-dependent analysis of the T1rho relaxation time (upper row), T2 relaxation time (middle row) and thickness (lower row) over the medial condyle (A, D, and G), lateral condyle (B, E, and H), and trochlea (C, F, and I) in blue. Additionally, the angular distribution of the impulse during walking is shown in orange, dashed line. The weight-bearing area is indicated by the gray zone.
Thickness
The cartilage thickness of the weight-bearing zone of the lateral condyle was found to be significantly lower than the thickness of the non-weight-bearing zone ( Fig. 3C ). The thickness of the weight-bearing zone of the medial condyle was significantly correlated to the contact force impulse on the medial weight-bearing zone (R = 0.78, P = 0.0026).
Figure 3.
Comparison weight-bearing versus non-weightbearing. Differences in T1rho relaxation time (A), T2 relaxation time (B), and thickness (C) between the weight-bearing (blue) and non-weight-bearing (orange) zones. Differences in homogeneity in T1rho relaxation time (D), T2 relaxation time (E), and thickness (F) between the weight-bearing (blue) and non-weight-bearing (orange) zones. A lower value indicates a more homogeneous distribution whereas a higher value indicates a more heterogeneous distribution. *Indicates a significant difference between weight-bearing and non-weight-bearing (α < 0.05).
T1rho Relaxation Time
Topographical variation in T1rho relaxation times over the different angles is presented in Figure 2 . The T1rho relaxation time of the weight-bearing zone of the medial condyle was found to be significantly lower than the T1rho relaxation time of the non-weight-bearing zone ( Fig. 3A ). The T1rho relaxation time in the medial weight-bearing zone was negatively correlated to the impulse on the medial weight-bearing zone (R = −0.71, P = 0.008). In contrast, the T1rho relaxation time of the weight-bearing zone of the trochlea was positively correlated to the impulse on the weight-bearing zone on the trochlea (R = 0.98, P = 0.0004).
The T1rho relaxation time was found to be distributed significantly more homogeneous in the weight-bearing zones of both condyles than the non-weight-bearing zones. Whereas no difference in homogeneity was observed for the trochlea ( Fig. 3D ).
T2 Relaxation Time
Topographical variation in T2 relaxation time over the different angles is presented in Figure 2 . The T2 relaxation time of the weight-bearing zones of both condyles was found to be significantly higher than the T2 relaxation time of the non-weight-bearing zones ( Fig. 3B ). Furthermore, the T2 relaxation time of the weight-bearing zone of the trochlea was significantly higher than the T2 relaxation time of the non-weight-bearing zone of the trochlea ( Fig. 3B ). No significant correlation between T2 relaxation time and impulse on the weight-bearing zones was observed for the medial and lateral condyle. The T2 relaxation time of the weight-bearing zone of the trochlea was positively correlated with the impulse on the weight-bearing zone of the trochlea (R = 0.79, P = 0.028).
The T2 relaxation time was found to be distributed significantly more homogeneous in the weight-bearing zones of both condyles than the non-weight-bearing zones. Whereas no difference in homogeneity was observed for the trochlea ( Fig. 3E ).
Discussion
The present study evaluated the topographical variation in MRI-based measures of matrix composition and morphology of femoral cartilage of healthy adults. Cartilage thickness was used to assess cartilage morphology. T1rho mapping was used to indirectly investigate proteoglycan content and T2 mapping was used to indirectly assess collagen content and orientation. Furthermore, the relation between localized loading and these cartilage-describing parameters was evaluated. Cartilage T1rho and T2 relaxation times and thickness were found to vary over the medial and lateral condyles, whereas less variation was observed in the trochlear cartilage. Furthermore, these parameters differ in the weight-bearing zones compared with the non-weight-bearing zones.
In agreement with previous research, this study observed a location-dependent variation in cartilage thickness.41,42 Although, no differences in cartilage thickness between the weight-bearing and non-weight-bearing zones were observed, a strong correlation between localized loading on the medial condyle and the medial condyle cartilage thickness was observed. This suggests that localized loading contributes to the variation in cartilage thickness, with locations exposed to increased loading having thicker cartilage. Previously, the anterior-posterior thickness distribution was found to relate to the knee flexion extension angle at heel strike.42-44 As the authors assumed this time instant to coincide with high compressive forces, they hypothesized that the thicker cartilage was a long-term protective response to high loading.42-44 In support of this hypothesis, the current study confirmed that the weight-bearing region as a whole is adapted to the cumulative loading perceived during stance (as reflected in the impulse of the contact force). Whereas previously, it was only found to be related to the knee position at heel strike. In agreement with other studies, no relation between cartilage thickness of the lateral condyle and lateral condyle loading was observed. The absence of this relation was previously attributed to different contact mechanics compared with the medial condyle.42,43,45
In the current study, the T1rho relaxation time of the weight-bearing zone on the medial condyle was found to be lower than the non-weight-bearing zone, whereas no difference was observed between the weight-bearing and non-weight-bearing zone on the lateral condyle. This is in line with previous studies that observed lower T1rho relaxation times in the weight-bearing zones.22,46 On the other hand, in line with the present results, no difference in T1rho relaxation time between weight-bearing and non-weight-bearing zones of the lateral condyle was previously observed.47 Cartilage matrix composition was previously suggested to be affected by localized loading. Since the medial condyle receives a higher fraction of the loading during walking, this may suggest that the proteoglycan content of the lateral condyle cartilage is less adapted to mechanical loading during walking. Consequently, variation in T1rho relaxation time of the lateral condyle cartilage may be more affected by other factors such as genetics, age, or mechanical loading during other movements that engage a higher degree of knee flexion or that load the lateral condyle more.
As T1rho relaxation time is related to proteoglycan content, our results suggest that the cartilage in the weight-bearing zone of the medial condyle contains more proteoglycans. This finding agrees with previous work that observed higher GAG content in the contacting zones of the femoral condyles compared with the non-contacting zones.21,48 In line, T1rho relaxation time was found to be related to the aggregate modulus of cartilage, with higher relaxation times being related to lower aggregate modulus.23 This indicates that the cartilage in the weight-bearing zone of the medial condyle has superior biomechanical properties and therefore, better able to withstand the high compressive forces experienced during locomotion. The fact that no differences in T1rho relaxation times of the lateral condyle and trochlear cartilage were observed can possibly be attributed to the fact that the lateral condyle and trochlea are less involved in weight-bearing loading during gait. Indeed, the estimated impulse on the trochlear cartilage was lower compared with the tibiofemoral impulses. Furthermore, the trochlear cartilage may be more exposed to shear stresses by the gliding movement of the patella during the flexion-extension cycle.
The current results regarding the T2 relaxation times suggest that the collagen concentration and orientation is lower in the weight-bearing zones compared with the non-weight-bearing zones. Similar to previous studies, T2 relaxation time was found to be higher in the weight-bearing zones of both the medial and the lateral condyle as well as the trochlea.24,25,49 However, in the present study the collagen in the weight-bearing regions is distributed more homogeneously. Assuming that a homogeneous collagen orientation is the primal contributor to the cartilage resistance against shear forces and not collagen content, the current results suggest that the cartilage in the weight-bearing region has superior mechanical properties. On the other hand, a less dense collagen network with higher or equal concentration of proteoglycans would suggest an increased capacity of the extracellular matrix to sustain compressive loads experienced during walking, as this would increase the capacity to deform under compression.
When interpreting the results of the current study one should consider the use of a generic cartilage mesh to project cartilage thickness and relaxation times. This way, the effect of subject specific detail in cartilage structure and constitution may have been lost, consequently weakening the observed relation between loading and MRI-based parameters. Furthermore, the generic mesh assumes a uniformly distributed cartilage thickness in the calculation of contact pressures. As a consequence, regional variation in loading is imposed through the motion characteristics (i.e., kinematics) rather than the local variation in cartilage shape.
In conclusion, we observed a topographical variation in cartilage thickness and matrix components estimated using quantitative MRI (i.e., T1rho and T2 mapping). The topographical variation in the medial condyle cartilage thickness was found to be related to localized cartilage loading and could therefore be interpreted as a long-term protective response of the cartilage to loading. This indicates that zones, experiencing higher local loading during walking have thicker cartilage. Finally, superior weight-bearing capacities, more specific increased proteoglycan and decreased collagen content in the weight-bearing region of the medial condyle were observed compared with the non-weight-bearing region of the medial condyle.
Footnotes
Acknowledgments and Funding: The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research was supported by funding of the Katholieke Universiteit Leuven Research Council (OT/13/083).
Declaration of Conflicting Interests: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Ethical Approval: Ethical approval for this study was obtained from the university hospital Leuven ethics committee (s56093).
Informed Consent: Written informed consent was obtained from all participants before the study.
Trial Registration: Not applicable.
References
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