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Keywords:

  • adaptation;
  • biomechanics;
  • cartilage;
  • morphology;
  • magentic resonance imaging

Abstract

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methodological background of qMRI of cartilage
  5. Short-term effects of exercise on articular cartilage (deformational behaviour)
  6. Long-term effects of exercise on articular cartilage (functional adaptation)
  7. Conclusion
  8. References

The effects of exercise on articular hyaline articular cartilage have traditionally been examined in animal models, but until recently little information has been available on human cartilage. Magnetic resonance imaging now permits cartilage morphology and composition to be analysed quantitatively in vivo. This review briefly describes the methodological background of quantitative cartilage imaging and summarizes work on short-term (deformational behaviour) and long-term (functional adaptation) effects of exercise on human articular cartilage. Current findings suggest that human cartilage deforms very little in vivo during physiological activities and recovers from deformation within 90 min after loading. Whereas cartilage deformation appears to become less with increasing age, sex and physical training status do not seem to affect in vivo deformational behaviour. There is now good evidence that cartilage undergoes some type of atrophy (thinning) under reduced loading conditions, such as with postoperative immobilization and paraplegia. However, increased loading (as encountered by elite athletes) does not appear to be associated with increased average cartilage thickness. Findings in twins, however, suggest a strong genetic contribution to cartilage morphology. Potential reasons for the inability of cartilage to adapt to mechanical stimuli include a lack of evolutionary pressure and a decoupling of mechanical competence and tissue mass.


Introduction

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methodological background of qMRI of cartilage
  5. Short-term effects of exercise on articular cartilage (deformational behaviour)
  6. Long-term effects of exercise on articular cartilage (functional adaptation)
  7. Conclusion
  8. References

Diarthrodial (synovial) joints represent important organs of the musculoskeletal system. They enable individuals to maintain posture within the gravitational field, to position their body relative to their surroundings, to move, and to manipulate objects around them. When performing these tasks, joints commonly encounter forces of several times the body weight (Bergmann et al. 1993). Diarthrodial joints are composed of various structures and tissues which, from a functional point of view, act in concert. Joints are made in a manner to deal effectively with the mechanical loads encountered over many years of life, ideally without suffering damage (Mow et al. 2003; Ateshian & Mow, 2005).

Hyaline articular cartilage provides the bearing surface of synovial joints. This review will focus on the morphology and function of this tissue, which – for the sake of brevity – will simply be addressed as ‘cartilage’ throughout the remainder of the text. Cartilage is unique as it is an avascular, aneural tissue, in which cells survive for a lifetime, without intercellular connections (Hunziker et al. 2002). In particular, adult articular cartilage has no other known function than maintaining mechanical competence. Owing to its sophisticated composition, its high water content and its ability to withstand hydrostatic pressurization (Ateshian et al. 1994; Mow et al. 2003), cartilage is capable of transferring enormous forces relatively evenly from one subchondral bone plate to the other (Mow et al. 1984, 1993). Under physiological conditions, cartilage also provides an almost frictionless gliding surface and is thus capable of transferring these loads during motion (Ateshian & Mow, 2005). In order to be able to meet these complex mechanical demands without undergoing wear and tear, articular cartilage displays unique morphological and biomechanical properties (Mow et al. 1984, 1993; Buckwalter & Mankin, 1998b; Hunziker et al. 2002). These properties are yet unmatched by any artificial material, despite considerable efforts by engineers and biologists (Buckwalter & Mankin, 1998a; Hunziker, 2002).

Due to a lack of non-invasive methods that allow human articular cartilage to be studied directly in vivo, little has been known until recently about the variability of normal cartilage morphology between subjects and the factors which determine this. Even less is known about the deformational behaviour of cartilage under load in the intact joint in vivo. However, with quantitative magnetic resonance imaging (qMRI) having become available, data on these topics have begun to emerge.

This review will primarily focus on whether articular cartilage is mechano-adaptive. In contrast to that of many other tissues, the morphology of articular cartilage (i.e. its thickness) is determined relatively late in postnatal life, during adolescence, when endochondral ossification is complete. We do not know which specific factors prohibit the calcification front from advancing to the joint surface and are responsible for the fact that a layer of cartilage is maintained at the joint surface. Given the limited number of genes available to guide the emergence and maintenance of the morphology of various tissues and functional systems in general, it is tempting to hypothesize that environmental factors, specifically mechanics, play a pivotal role in this process. The ability of tissues to emerge and maintain their structure in accordance with specific environmental requirements has been termed ‘functional adaptation’ (Lamarck, 1809; Darwin, 1872; Roux, 1881; Wolff, 1892; Pauwels, 1980; Carter et al. 1991; Huiskes et al. 2000). Processes of functional adaptation have been regarded as occurring during the development of the central nervous system (e.g. the visual cortex), internal organs (e.g. the kidney) and in tissues with primarily mechanical functions, such as muscle and bone (Wolff, 1892; Pauwels, 1980; Carter et al. 1991; Keller et al. 1992; Booth, 1994; Huiskes et al. 2000). Physical exercise has been shown to increase bone and muscle mass (e.g. body building), whereas states of inactivity or microgravity have been associated with tissue atrophy (Keller et al. 1992; Booth, 1994). In bone, functional adaptation to mechanics has been mathematically characterized as a cell-mediated process in which osteocytes act as mechanical sensors and orchestrate the function of other (bone-forming and bone-resorbing) cells through biochemical signalling (Huiskes et al. 2000). The biosynthetic activity of chondrocytes has also been shown experimentally to be regulated by mechanical stimuli (Kim et al. 1995; Waldman et al. 2003). Based on these in vitro findings, mathematical models have been developed that explain the variable thickness of cartilage between joints based on differences in mechanical loading magnitude (Carter & Wong, 1988a,b, 2003; Carter et al. 1991; Wong & Carter, 2003). To date, however, there has been little experimental evidence to support this theory on a systemic level.

For this reason, the primary objective of this review is to address the question of whether (and to what extent) articular cartilage is subject to deformation under physiological loading conditions, and what magnitude of mechanical signals is encountered by the cartilage matrix (and thus the chondrocytes) during activities of daily life. The second objective to be addressed is whether cartilage tissue can adapt to mechanical stimuli by altering its morphology (specifically its thickness) and composition (proteoglycan, collagen and interstitial water content) to the specific mechanical conditions on a systemic level. Because most of the recent experiments on these questions have been performed using MRI, we will also briefly review methodological aspects of this imaging modality in the context of quantitative cartilage analysis.

Methodological background of qMRI of cartilage

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methodological background of qMRI of cartilage
  5. Short-term effects of exercise on articular cartilage (deformational behaviour)
  6. Long-term effects of exercise on articular cartilage (functional adaptation)
  7. Conclusion
  8. References

MR pulse sequences for quantitative analysis of cartilage morphology

An MRI pulse sequence suitable for measuring cartilage morphology quantitatively must provide a high signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) for accurate delineation of the subchondral bone interface and articular surface, and no significant artefacts must be present. Measurements should be obtained at relatively short imaging times, in order to avoid motion artefacts and to be able to measure cartilage deformation directly after exercise (Tieschky et al. 1997). Because cartilage layers exhibit a mean thickness of only 1.3–2.5 mm throughout the human knee (Eckstein et al. 2001a; Hudelmaier et al. 2001) and even less so in other joints (Peterfy et al. 1995; Springer et al. 1998; Graichen et al. 2000, 2003; Al Ali et al. 2002), a high spatial resolution is required so that a sufficient number of image points (pixels) are available to characterize the thickness of the tissue throughout the joint surface, including areas with thin cartilage coverage. Increasing the resolution by a factor of two in three dimensions requires acquisition times to be increased by a factor of 64, if the SNR is to be kept constant. Although there is no current consensus on the optimal resolution for imaging cartilage morphology, a 1.5-mm section thickness and 0.3-mm in-plane resolution has been commonly used at a field strength of 1.5 T. The specific MR pulse sequences that has been most frequently employed for cartilage imaging is a T1-weighted spoiled gradient echo sequence [FLASH = fast low angle shot (Frahm et al. 1986) or SPGR = spoiled gradient recalled acquisition at steady state]. This sequence (Fig. 1a,b) is available on most clinical MRI systems and has been implemented either with frequency-selective spectral fat-suppression by a prepulse (Recht et al. 1993; Peterfy et al. 1994; Eckstein et al. 1996a; Cicuttini et al. 2000) or with frequency-selective water excitation (Hardy et al. 1998; Graichen et al. 2000; Burgkart et al. 2001; Glaser et al. 2001). Both techniques achieve effective fat-saturation, which is required to provide a sufficient dynamic range of the image contrast between the cartilage and its surrounding tissues, and to eliminate artefacts at the subchondral bone interface. New 3.0-T whole-body MR scanners now make it possible to perform quantitative cartilage imaging at higher field strength (Gold et al. 2004a,b; Eckstein et al. 2005a,b; Kornaat et al. 2005). A recent study has shown that measurements at 3.0 T are consistent with those at 1.5 T, and that the precision (reproducibility) of the measurements is slightly improved when exploiting the higher field strength to obtain a higher spatial resolution (1-mm slice thickness) at 3.0 T compared with 1.5 mm at 1.5 T (Eckstein et al. 2005a).

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Figure 1. (a) Coronal MR imaging (slice thickness 1.5 mm, in-plane resolution 0.31 mm × 0.31 mm) acquired with a T1-weighted spoiled gradient echo sequence (FLASH = fast low angle shot; or SPGR = spoiled gradient recalled acquisition at steady state) with frequency-selective water excitation. (b) Segmentation showing the medial tibial cartilage in blue, the medial femoral condyle in yellow, the lateral tibia cartilage in green, and the lateral femoral cartilage in red. (c) Sagittal dGEMRIC image kindly provided by Dr Deborah Burstein, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA.

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One of the great advantages of MRI (e.g. in comparison with histology) is that consecutive slices are contiguous and spatially aligned, so that three-dimensional (3D) parameters can be obtained that characterize cartilage morphology appropriately (Fig. 2). These parameters include cartilage volume, cartilage thickness (mean, maximum, standard deviation), cartilage surface area (or subchondral bone interface area) as a measure of bone size, cartilage surface curvature (joint incongruity) and others (Fig. 2). When reporting cartilage volume, one must keep in mind that this parameter depends on both the cartilage thickness and the cartilage surface area, and that only under conditions where the cartilage surface (or chondro-osseous interface area) is constant, do volume or thickness changes over time correspond. In cross-sectional studies, it is important to report cartilage thickness directly, or to normalize cartilage volume to the joint surface/bone interface area, in order to provide meaningful results. It has been shown, for instance, that gender differences in joint surface areas are substantially larger than those for cartilage thickness (Faber et al. 2001), a finding that is not evident from measuring cartilage volume alone. Also, it has been shown that cartilage thickness and cartilage surface areas are not closely associated in healthy individuals (Eckstein et al. 2001b); in other words, subjects in whom the articular cartilage occupies a larger surface area do not necessarily have thick cartilage and vice versa. Thus, one of these parameters cannot be estimated from the other – both must be measured as separate entities.

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Figure 2. (a) Three-dimensional reconstruction of femoral and tibial cartilage from segmentations of contiguous MR images; (b) distribution pattern of cartilage thickness in the femur, determined independent of the original section orientation. The blue colour shows areas of thick cartilage, orange and red show areas of thin cartilage.

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In order to derive quantitative data from a 3D, contiguous image set, an anatomical structure (the articular cartilage) must first be labelled, distinguishing it from its immediate relations (segmentation –Fig. 1b). Owing to the relatively low contrast in some areas of the joint surface (joint contact areas, the vicinity of synovial folds, tendons and ligaments, repair tissue, etc.), fully automated segmentation of cartilage is impractical from MR images. Various semi-automated image analysis techniques have been developed to date, each requiring different degrees of user interaction. Verification (and some degree of correction) by an experienced user is generally necessary on a section-by-section basis. The inability of current computer software reliably to identify structures in images that are evident to the experienced human eye may seem surprising. However, if one considers the great difficulties involved in automated speech recognition by computers, despite the tremendous efforts made by industry, one may appreciate the complexity of automated recognition in intricate image pattern identification. For these reasons, and because many slices must be acquired of one joint surface to obtain sufficient spatial resolution, cartilage segmentation is a time-consuming process currently requiring several hours of human interaction per knee data set.

After segmentation, computation of the cartilage volume is straightforward, by simple numerical integration of the number of voxels attributed to the cartilage during the segmentation process (Fig. 2). More sophisticated algorithms are then used to determine the cartilage thickness (Fig. 2) and joint surface area, which must account for out-of-plane deviations of these parameters. Computations should therefore be made in three dimensions, independent of the original section orientation. Extraction of cartilage surfaces also allows for the determination of geometric topography and curvature characteristics of diarthrodial joints (Ateshian et al. 1991). Mathematical descriptions of joint surfaces and articular cartilage layers can also be applied to derive computer models of human joints, by which the contact areas and surface stresses in joints may be estimated (Cohen et al. 1999, 2001) but these methods have not been yet applied to the study of the effects of exercise on cartilage and joint morphology.

Because these ‘global’ parameters (volume and mean thickness for an entire cartilage plate) may be relatively insensitive to regional/focal changes that affect only small portions of the surface, several investigators have presented techniques for displaying regional cartilage thickness patterns (Eckstein et al. 1995, 1996a,b, 1998a; Sittek et al. 1996; Cohen et al. 1999, 2003; McGibbon & Trahan, 2003) (Fig. 2). Changes over time (or differences between subjects) in regional cartilage thickness are, however, difficult to detect from subjective comparison of such thickness patterns, because only a limited number of thickness intervals can be displayed. In order to track local/regional thickness changes over time, registration techniques have therefore been proposed (Kshirsagar et al. 1998; Stammberger et al. 2000; Waterton et al. 2000; Lynch et al. 2001; Cohen et al. 2003; Raynauld et al. 2003). With these methods, the bone interface or other anatomical landmarks from two data sets are matched so that the thickness distribution can be compared on a point-by-point basis. Stammberger et al. (2000) reported a local mismatch of cartilage thickness for joint repositioning in the range of 0.5–1 mm. These local errors are relatively large in comparison with the absolute cartilage thickness in knee joint surfaces, but this is not surprising given that an anatomically complex structure is reconstructed and registered with data obtained from a limited number of sectional images.

Validation and reproducibility (precision) of quantitative analysis of cartilage morphology

The validity (accuracy) of qMRI of cartilage has been addressed in numerous studies over recent years and these have been carried out in unselected cadaver joints, amputated joints (Peterfy et al. 1994; Cicuttini et al. 1999) or knee joint of patients undergoing total knee arthroplasty (TKA) (Peterfy et al. 1994; Cicuttini et al. 1999; Burgkart et al. 2001; Graichen et al. 2004). TKA provides a unique opportunity for validating quantitative measurements, as patients can be imaged prior to surgery in vivo, and the tissue can be removed and analysed after the operation. Validation studies have been carried out in comparison with various reference methods, namely water displacement of surgically retrieved tissue (either direct or by employing Archimedes’ principle), anatomical sections obtained with high-precision band saws, computer tomography arthrography, A-mode ultrasound (not to be confused with clinical B-mode ultrasound), and stereophotogrammetry. Most of these comparative studies have reported close agreement between methods of measuring cartilage volume, with random errors (absolute pairwise over- or underestimation) vs. the respective reference method of about 5–10%. Validation studies have also been performed in other joints with thinner cartilage, such as the metacarpophalageal joint (Peterfy et al. 1995), the hip (McGibbon et al. 1998), the elbow (Graichen et al. 2000) and the shoulder (Graichen et al. 2003).

Precision errors are random errors that occur when repeated measurements of a parameter are taken under constant conditions. Highly reproducible techniques are required to resolve small changes (i.e. cartilage deformation) with statistical confidence. For qMRI of cartilage morphology, the precision depends on factors associated with image acquisition, and factors associated with image analysis. Differences in joint positioning are less critical than for projectional techniques (such as radiography), because the technique is 3D and the relevant quantitative measures are obtained from reconstructions of serial images rather than from projection onto one image plane. The lowest precision errors (CV%∼1%) have been observed for axial protocols of the patella (Eckstein et al. 2000b). Higher precision errors, by contrast, have been reported for analyses of the femoral condyles in sagittal scans (Eckstein et al. 2002b), whereas analysis of the total femur has usually been comparable with other joint surfaces of the knee. Precision errors of computations of the mean cartilage thickness throughout joint surfaces have been reported to be similar to those of cartilage volume (Stammberger et al. 1999; Hyhlik-Dürr et al. 2000; Burgkart et al. 2001; Eckstein et al. 2002b) as have those for quantification of cartilage surface areas (Hohe et al. 2002; Eckstein et al. 2002b).

MR protocols for compositional cartilage imaging

In addition to measuring cartilage morphology, there have been great efforts in using MRI to determine the composition of cartilage, namely the glycosaminoglycan (GAG) content, collagen content and orientation, and the interstitial water content. Attempts to determine the concentration of GAG include imaging of fixed charge density by using an intravenous injection of the charged clinical MRI contrast agent Gd(DTPA)2–. If Gd(DTPA)2– is allowed to penetrate into cartilage, a process that has been estimated to last for about 90 min after injection, it distributes inversely with the GAG concentration (Fig. 1c). Because full penetration is required, the technique has been termed delayed gadolinium enhanced MRI of cartilage (dGEMRIC) (Gray et al. 2004). When tissue is placed in a magnetic field, magnetic moments of the protons are aligned, resulting in a net magnetic moment. This equilibrium is then disturbed by transmitting another magnetic field at the same frequency as the rotations of the protons for a very short time. The return to equilibrium of the magnetic moments after this pulse is strongly affected by molecular interactions of the nuclei with their surroundings and can be exploited for imaging cartilage composition (Burstein & Gray, 2003). Two time constants are relevant in this context, the longitudinal (T1) and transverse relaxation time (T2). When probing T1 in cartilage in the presence of fully penetrated Gd(DTPA)2– (dGEMRIC), one can estimate the GAG content of the tissue (Fig. 1c). dGEMRIC has been validated in basic science and clinical studies through comparison with biochemical and histological measures of GAG (Bashir et al. 1997, 1999; Tiderius et al. 2003; Williams et al. 2004). Another technique that has been successfully explored is T2 mapping (Mosher & Dardzinski, 2004). T2 can be obtained without the presence of a contrast agent, but cannot be attributed to a single constituent of cartilage composition. T2 has been shown to provide a quantitative measure of cartilage interstitial fluid and its interaction with the solid components of the extracellular cartilage matrix, in particular with collagen content and orientation, whereas there is little to no sensitivity to changes in GAG concentration (Mosher & Dardzinski, 2004). Spatially resolved cartilage T2 maps have been shown to be correlated with the regional water content of the deep and mid zones of cartilage (Lusse et al. 2000) but recent data suggest that collagen fibre anisotropy is the dominant factor related to regional differences in T2. T2 of the superficial zone of cartilage was shown to change with aging (Mosher et al. 2004).

Short-term effects of exercise on articular cartilage (deformational behaviour)

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methodological background of qMRI of cartilage
  5. Short-term effects of exercise on articular cartilage (deformational behaviour)
  6. Long-term effects of exercise on articular cartilage (functional adaptation)
  7. Conclusion
  8. References

Although the mechanical properties of articular cartilage have been thoroughly studied under in vitro conditions (Mow et al. 1993, 2003), until recently there have been little data on the magnitude of the in situ cartilage deformation in intact joints, and there have been no data for in vivo loading conditions. This information cannot be extrapolated from in vitro studies, because the magnitude of the joint loads during normal (particularly dynamic) exercise is unknown. Moreover, the effect of boundary conditions (e.g. non-linear contact conditions between incongruous joint surfaces, presence of the synovial fluid) is difficult to take into account. In vivo data on the deformation of articular cartilage are necessary, however, in a number of areas. (1) Cartilage deformational behaviour depends on the biochemical composition of the tissue and may potentially represent a more sensitive surrogate marker of early osteoarthritis than morphological endpoints such as cartilage volume, thickness or joint space narrowing (Burstein et al. 2000). (2) Knowing the magnitude of strain in the target tissue is important when designing cartilage transplants. Artificial cartilage can then be designed in a way to be able to withstand these strains ex vivo so that cartilage transplants can be expected to meet mechanical requirements in vivo. (3) The magnitude of in vivo deformation of articular cartilage is related to the magnitude of mechanical stimulation experienced by the chondrocytes, which is known to affect their biosynthetic activity (Sah et al. 1989; Urban, 1994; Kim et al. 1995). Knowledge of cartilage deformation in vivo may thus serve as an important guideline of how to stimulate cells optimally in tissue culture and cartilage transplants, and also how to use mechanical signals to stimulate cartilage in situ.

In vitro studies of the intact femoro-patellar joint

Cartilage deformation during loading cannot be readily investigated with MRI, because it is difficult to apply relevant loads to the joint of a living person within the MRI scanner, and to keep the joint in a constant position relative to the coil at the same time. Note that, given an in-plane resolution of 300 µm, even very tiny movements of the limb make it impossible to obtain an accurate measure of cartilage thickness. To overcome this limitation, one group (Herberhold et al. 1998) constructed a non-metallic compression apparatus capable of generating loads of up to 1500 N (Fig. 3) for studying patellofemoral compression in a clinical MRI scanner. The time-dependent deformation of the patellofemoral cartilage was studied in situ over a 4-h period under continuous static loading with 150% body weight, with the joint capsule being kept fully intact (Herberhold et al. 1999). Analysis of cartilage deformation in the central 2D slice revealed a mean reduction of 44 ± 15% of the initial thickness in the patella, and a cartilage thickness change of 30 ± 10% in the femoral trochlea after 3.5 h of static loading with 150% body weight (Figs 3 and 4a). The deformation of the patellar cartilage exceeded that of the trochlea, this being consistent with the differences in cartilage mechanical properties reported between the patella and femoral trochlear (Froimson et al. 1997). The maximal cartilage deformation observed was 57 ± 15% in the patella and 44 ± 7% in the trochlea (Herberhold et al. 1999). Cartilage thickness decreased in an approximately exponential manner and cartilage deformation ceased in the central slice after 3.5 h (equilibrium). Interestingly, however, only a small fraction of the final (3.5 h) deformation was reached during the first 1 min of static loading (3% cartilage thickness change in the patella and 1.3% in the trochlea), and the deformation was still of little magnitude after ∼8 min of loading (11% cartilage thickness change in the patella and 9% in the trochlea; Fig. 4b). This revealed that only about 4–7% of the final (near equilibrium) deformation is reached with the first 1 min of loading, and that only 25–30% of this final deformation is reached during the first 8 min of load application.

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Figure 3. The non-metallic compression apparatus that fits into the extremity coil of a clinical MRI scanner is capable of generating loads of up to 1500 N using a pneumatic pressure piston, and can accommodate a human patellofemoral joint at a 60° flexion angle. The patella and pressure piston are guided between Delrin trays, so that the cartilage deformation could be monitored using a fast two-dimensional MR imaging sequence with an acquisition time of < 1 min. Images on the right show the status of the femoropatellar cartilage before compression (t = 0 min) and after 120 min and 240 min of compression, respectively.

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Figure 4. In situ compression of patellofemoral cartilage using the compression device shown in Fig. 3. (a) Graph showing the mean reduction of thickness in a central axial 2D slice through the patellofemoral contact zone over 3.5 h of static loading with 150% body weight; (b) only a small fraction of the final thickness is reached during the first few minutes of static loading; (c) patellar cartilage volume (measured over the entire patella) was reduced by approximately 30% after 3.5 h of loading.

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The patellar cartilage volume (as measured over the entire patella, but not in the central 2D slice) was reduced by 8 ± 5% after 14 min and by 29 ± 3.2% after 3.5 h of loading (Fig. 4c). After 3.5 h, deformation had not yet ceased and equilibrium had not yet been reached, because the load-bearing area continued to increase proximally and distally from the site of central contact, in which equilibrium had been reached (see above). Given an interstitial water content of cartilage of about 80%, these data suggest that more than 50% of the interstitial fluid was displaced from the patellar cartilage matrix during 3.5 h of static compression. Based on the assumptions that the solid matrix is incompressible (Mow et al. 2003), that all volume changes are due to fluid flow and that during compression the fluid flow will occur throughout the articular surface into the joint cavity, the rate of interstitial fluid loss from the matrix was estimated to be 1.3 (± 0.5) mm3 min−1 per cm2 surface area (fluid flux = 0.217 ± 0.083 µm s−1) for the first 14 min of loading, and 0.22 (± 0.04) mm3 (min cm2)−1 (0.037 ± 0.007 µm s−1) in the terminal phase of the experiment (> 120 min). Note that these values provide only a mean throughout the joint surface and that the flux is assumed to be highly variable throughout it during the compression experiment. Also, the thickness changes were found to be highly inhomogeneous throughout the joint surface and load-bearing area, with the maximal deformation (the lateral patellar facet) being identical to the site of the maximal cartilage thickness. An experiment using pressure-sensitive FUJI film, conducted in the same specimens after imaging, showed pressure maxima of 3.6 ± 1.3 MPa, in the lateral patellar facet, the pressure distribution being very similar to the pattern of cartilage deformation.

In one of the specimens imaging was continued after the 3.5-h experiment and after removal of the load. The cartilage displayed almost full recovery (98%) after approximately 4 h. The rate of fluid re-uptake by the cartilage matrix was 0.9 mm3 (min cm2)−1 (0.15 µm s−1) within the first 14 min of recovery, and 0.14 mm3 (min cm2)−1 (0.023 µm s−1) in the terminal phase of the recovery period.

It may appear surprising that cartilage deforms so little for the first few minutes under high loads. However, the primary function of cartilage is not to absorb energy through deformation (a function that is performed by the muscles, the tendons and the joint as an organ), but to distribute the load equally to the subchondral bone plate and to provide minimal friction during motion. This function can be compared with the inflated tyre of a bike, which should not deform, in order to avoid damage to the wheel (the subchondral bone) and to provide minimum resistance during rolling. The energy absorption, by contrast, is provided by a spring (the joint, with its tendons and muscles), and energy absorption is warranted by controlled joint movement and negative acceleration in it. It may be argued that deformation is higher when high-impact loading occurs, but it should be remembered that cartilage consists of 80–90% interstitial fluid, which is incompressible, and which has little time to escape from the load-bearing area in high-impact loading. This can be appreciated when landing on one's front or back on water after a jump from a 10-m tower. Given that the water has little time to escape under these high-impact conditions, little energy absorption is provided, and this even more so in the cartilage, in which the fluid is bound to the matrix.

In vivo deformation of the patellar cartilage

In order to determine in vivo cartilage deformation shortly after exercise, we have quantified the cartilage volume of healthy volunteers after 1 h of physical rest (no weight-bearing in the scanner) and then 3–7 min after 50 knee bends (Eckstein et al. 1998b). Note that so far it has been impossible to determine cartilage deformation reliably during loading in vivo for the reasons mentioned in the first paragraph, and that it also cannot be determined immediately after the exercise, as some time is required to reposition the patient in the magnet, to obtain a preliminary view for slice position and alignment, and actually to acquire the 3D image data. After the knee bends we observed a reduction in cartilage volume (compression) in the patella of 2.4–8.6% (mean = 6.0%) (Fig. 5) (Eckstein et al. 1998b). Note that this is the mean deformation across the entire patellar cartilage and that a certain amount of inhomogeneity may be present, with some areas encountering higher and some lower deformation (see below). When asking the same subjects to perform 100 knee bends (Eckstein et al. 1999), the level of deformation was of 2.4–8.5% (mean = 5.0%) and was not significantly different from that after 50 knee bends (Fig. 5). We then examined the time required for recovery of the cartilage under non-weight-bearing conditions (Eckstein et al. 1999). A period of 45 min was required to compensate approximately 50% of the deformation observed after knee bends and a period of 90 min to attain the pre-exercise volume before the knee bends (Eckstein et al. 1999) (Fig. 5). The fluid re-uptake appeared to be almost linear throughout the observation period, and the average fluid flux during the recovery period was estimated to be approximately 0.027 µm s−1. This compares well with the values observed during terminal recovery after long-term static loading (Eckstein et al. 1999) (see above). We demonstrated further that multiple sets of 50 knee bends, with intervals of 15 min of rest in between, maintained the level of deformation measured after the first set of knee bends (around 5–6%), but did not lead to further cartilage deformation beyond this value (Eckstein et al. 1999) (Fig. 5).

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Figure 5. Patellar cartilage deformation after six sets of 50 knee bends at 15-min intervals (top), and during recovery after 100 knee bends (bottom).

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Liess et al. (2002) studied 20 healthy volunteers after performing 60 knee bends. MR images of the patellar cartilage were acquired immediately following exercise and then after 45 min of rest. Within 45 min of loading, patellar cartilage volume increased by 5.4 ± 1.5%. At the same time, T2 maps of the patellar cartilage were acquired. During the 45-min recovery period, T2 increased by 2.6 ± 1.0% (P < 0.05). The authors concluded that small physiological changes in the water content of patellar cartilage and concomitant changes of the macromolecular composition of the cartilage occurred following exercise.

When comparing static (90° squatting for 20 s) with dynamic loading (30 deep knee bends to 120°), differences were found both in the magnitude and in the pattern of cartilage deformation throughout the joint surface (Eckstein et al. 2000a). The reduction in cartilage thickness after 30 knee bends (5.9 ± 2.1%) was not less than after 50 or 100 knee bends, with the range being 2.9–9.6%. After static loading, we also observed a significant reduction of the patellar cartilage volume of 4.7 ± 1.6% (range 2.4–6.5%). The maximal deformation was observed in the central aspect of the lateral facet, which is also the site of maximal cartilage thickness (Fig. 6). The cartilage volume changes recorded after dynamic loading were significantly higher than those after static loading (P < 0.05), probably because the patellar joint surface area involved in load-bearing is much higher for dynamic exercise with a wide range of knee angles being taken, and the correlation coefficient for deformation after the two activities was r = 0.69 (P < 0.05). In a recent paper we compared several activities (Eckstein et al. 2005c), including (1) 30 deep knee bends, (2) static loading (see above), (3) normal walking at ground level for 5 min, (4) running 200 m and walking up and down 54 steps over a total time of 4 min, and (5) cycling for 10 min on a training bike at a frequency of 80 Hz (Fig. 6). The cartilage deformation of the patella was 5.9 ± 2.1% after the 30 knee bends, 2.8 ± 0.8% after walking, 5.0 ± 1.3% after running and 4.5 ± 1.6% after cycling (Fig. 6), with all changes being significant at P < 0.01. In order to investigate the pattern of cartilage deformation throughout the patella as well, we employed the matching algorithm described by Stammberger et al. (2000). Cartilage thickness difference maps for the 12 volunteers were displayed using grey value coding. Averages of the deformation patterns of the 12 volunteers (for each activity) were then derived, in order to reduce the noise. They were then recoded in colour intervals, in order to visualize better the effects of short-term exercise throughout the patellar surface (Fig. 6). During squatting and walking, changes were confined to limited regions of the patellar surface, consistent with the contact areas involved for these activities (Hehne, 1990). Activities where there was a larger range of knee motion (running including stairs, cycling, knee bends) involved a more widespread area of deformation. When measuring patellar cartilage of volunteers in the evening after a day of normal activity (no period of rest prior to imaging) and then after spending the night sleeping (and without weight-bearing) in the MRI unit, Sitoci et al. (2003) found that cartilage volume increased significantly, but only by 2.2% overnight. This finding is consistent with that of a 3% deformation observed when walking after a period of non-load-bearing. In summary, these data demonstrate that during normal daily activity (walking etc.), the patellar cartilage is at a state of approximately 2–3% average compression vs. non-weight-bearing conditions, and that intense exercise may add another 2–3% of average compression on top of those encountered during normal daily activity vs. non-weight-bearing conditions (Fig. 7).

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Figure 6. In vivo deformation patterns of patellar cartilage after different physiological activities (see text). A posterior view onto the right patellar cartilage surface (proximal pole of the patella on top, medial side on the left): average of differences in cartilage thickness before and after various activities averaged over 12 volunteers. Red and orange colours show areas of high deformation, blue colour areas of little deformation.

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Figure 7. Scheme showing the state of patellar cartilage deformation (cartilage thickness change) during normal daily activity and the physiological window of cartilage deformation between non-weight-bearing conditions and heavy exercise, such as deep knee bends.

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In vivo deformation of femorotibial cartilage

Femorotibial cartilage deformation is more challenging to investigate compared with the patella, because the cartilages are thinner and the precision errors (CV 2–3%) are higher than for patellar cartilage. Waterton et al. (2000) studied volunteers in the morning and then after a day of mainly standing activity. They reported no change in overall femoral cartilage volume and thickness but cartilage thinning in the femorotibial contact zones. They observed an increase in thickness in areas of the femoral condyles and trochlea that were supposedly not involved in loading during standing, and they hypothesized that this resulted from negative intra-articular pressure during joint extension by the quadriceps muscles. It was alternatively suggested that interstitial fluid was displaced from load-bearing to non-load-bearing areas within the cartilage. To investigate femorotibial cartilage deformation after more intense activities, we acquired two coronal scans after a period of 60 min of physical rest in a first session (in order to reduce the precision error involved), and then one coronal scan after 30 knee bends in 12 healthy subjects (Eckstein et al. 2005c). Other activities investigated in the same volunteers included 12 knee bends performed on one leg only, 2 min of static loading of the femorotibial joint of one leg at 15° flexion, and ten jumps from a chair (40 cm height) onto one leg (Fig. 8). No significant change in cartilage volume was observed in femorotibial cartilage after two-legged knee bends (except for the lateral tibia) or one-legged knee bends (Eckstein et al. 2005c). Significant changes were observed in the medial and lateral tibial cartilage after impact loading (jumps from 40 cm height), but not in the medial or lateral femoral condyle (Fig. 8). Changes with borderline significance were found in the medial tibial and lateral femoral condyles after the static loading exercise (Eckstein et al. 2005c).

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Figure 8. Graphs showing the magnitude of tibiofemoral cartilage deformation (change in mean thickness) and level of significance after various types of activities: MT = medial tibia; cMF = central medial femur (condyle); LT = lateral tibia; cLF = central lateral femur (condyle).

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When investigating seven female runners after performing a full distance marathon under competitive conditions (Boston marathon 2005), no significant deformation of tibiofemoral or patellofemoral cartilage was observed 90 min after the race (Kunz et al. 2005). These findings do not exclude the possibility that some deformation may have been present immediately after the race, but these data show that no prolonged deformation occurs after a very intense activity involving several thousand load cycles. In the same sample, Williams et al. (2005) found a decrease of the dGEMRIC index in the medial and lateral femoral condyles 1 day after the race (up to 18%), followed by a return towards pre-race values at 1 week and recovery to near pre-race values by 6 weeks post-race. The tibial cartilage, by contrast, displayed no change in the dGEMRIC index at day 1; but a significant increase at week 1. Six weeks after the race, values had returned to pre-race levels. Because no change in cartilage thickness was observed immediately after the race (Kunz et al. 2005) and therefore also is unlikely to have occurred 1 day, 1 week or 6 weeks after the race, these data indicate that there may be a loss of GAG after intense physical activity, and that this may evoke a biological response that increases cell metabolism and production of GAG.

Mosher et al. (2005) obtained T2 maps of weight-bearing femoral and tibial articular cartilage in young healthy men before and immediately after 30 min of running. They found no statistically significant change in T2 profiles of tibial cartilage, but a significant decrease in T2 of the superficial 40% of weight-bearing femoral cartilage after exercise. The authors concluded that these results support the hypothesis that cartilage compression results in greater anisotropy of superficial collagen fibres.

In vivo deformation of cartilage as related to cartilage mechanical properties

As in vivo cartilage deformation is a complex event that is determined by (1) the load applied to the joint, (2) the load distribution within the joint during the specific activity and (3) cartilage mechanical properties, and because measurements of it are additionally confounded by precision errors, one cannot equate the deformational behaviour of cartilage directly with its material properties. However, in a study of cartilage recovery after 100 knee bends (Eckstein et al. 1999) we found that the fluid flux during recovery (no weight bearing) was highly correlated (r = 0.87) with the magnitude of deformation observed after the knee bends. Because the recovery was found to be approximately linear throughout the 90-min observation period, and because no external forces acted on the joint during the recovery period, it is reasonable to assume that the individual fluid flux throughout the surface observed during cartilage recovery after knee bends reflects the specific mechanical properties of the cartilage in this individual. The high correlation of the flux during recovery with the magnitude of deformation after knee bends suggests therefore that MRI-based measurement of in vivo deformation gives at least some insight into the individual mechanical properties of the cartilage in vivo.

When investigating non-osteoarthritic subjects aged 50–75 years, Hudelmaier et al. (2001) found a smaller degree of patellar cartilage deformation than in younger subjects aged 20–30 years. A potential explanation for the reduced deformation is that older individuals exhibit different motor strategies (Papa & Cappozzo, 2000) and subject their knee joints to smaller loads during knee bending. It has, however, been demonstrated that due to non-enzymatic glycolisation, collagen cross-links increase with aging (pentosidine), both in animals and in humans (Takahashi et al. 1995; Brama et al. 1999), a process that has been found to render the cartilage matrix stiffer than in the young (Chen et al. 2002; Verzijl et al. 2002; Saudek & Kay, 2003). The finding of reduced cartilage deformation after exercise in the 50–75-year-old subjects therefore lends support to the concept that changes in cartilage mechanical properties can be detected in vivo, by examining deformational behaviour of cartilage after exercise. No difference in cartilage deformational behaviour between women and men was observed in this study (Hudelmaier et al. 2001), either in the 20–30-year-olds or in the 50–75-year-olds.

In one of the studies previously mentioned (Eckstein et al. 2005c) we tested the hypothesis that the in vivo deformation of patellar cartilage is smaller in professional athletes than in non-athletic volunteers. This hypothesis was based on the observation that cartilage composition and mechanical properties functionally adapt to mechanical stimulation in some animal experiments (reviewed by Vanwanseele et al. 2002b), whereas another study showed that continuous training of dogs did not alter the compositional or mechanical properties of articular cartilage, even though the animal had been training throughout life (Newton et al. 1997). These different outcomes of animal models may be potentially explained by differences in susceptibility to mechanical stimuli at different levels of skeletal maturity. However, there is as yet no convincing evidence that human cartilage composition can be changed by mechanical stimulation, and in particular changed to a degree that it affects its in vivo deformational behaviour. We therefore compared patellar cartilage deformational behaviour in 14 men who had never performed regular training of muscle strength with seven professional weightlifters, and seven professional bobsleigh sprinters. The weightlifters were regional champions and included one world champion. The bobsleigh sprinters were national finalists and included three world champions and one Olympic medallist. The reduction in patellar cartilage volume after 30 knee bends was 4.1 ± 2.6% in the non-athletic participants, 2.9% ± 1.9% in the weightlifters and 3.9 ± 1.8% in the bobsleigh sprinters. Although there was a trend for the weightlifters to display a lower magnitude of deformation, the difference between the groups was not statistically significant.

To date, there are no data on in vivo cartilage deformation in osteoarthritic patients, and obviously there are ethical problems in subjecting patients with knee pain to intense exercise protocols. However, cartilage is known to become more compliant (less stiff) with osteoarthritis, and standardized in vivo loading protocols may eventually be used clinically to evaluate functional properties over the course of joint disease, or even to study the effects of different types of therapy on cartilage quality (Burstein & Gray, 2003).

Long-term effects of exercise on articular cartilage (functional adaptation)

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methodological background of qMRI of cartilage
  5. Short-term effects of exercise on articular cartilage (deformational behaviour)
  6. Long-term effects of exercise on articular cartilage (functional adaptation)
  7. Conclusion
  8. References

Intersubject variability, side differences and correlation with anthropometric measures

Numerous studies have reported a high degree of intersubject variability in cartilage volume, thickness and surface areas of the human knee (Jones et al. 2000; Eckstein et al. 2001a,b; Hudelmaier et al. 2001, 2003; Cicuttini et al. 2002, 2003; Burgkart et al. 2003), and also in other joints of the body (Springer et al. 1998; Graichen et al. 2000, 2003; Al Ali et al. 2002). Hudelmaier et al. (2003) showed that muscle cross-sectional areas (MCSAs) of the thigh and calves can be reproducibly measured using a spin echo magnetic resonance sequence and are more highly correlated with cartilage morphology than body height or body weight. Also, MCSAs contributed significant, independent information in multiple regression models, with cartilage morphology as the dependent varaible and body weight and height as independent variables. These models predicted approximately 75% of the variability in cartilage volume (Hudelmaier et al. 2003). No significant differences were found in knee cartilage morphology of the left and right limbs of volunteers, and the left–right differences were substantially lower than the intersubject variability. This applied to cartilage volume, thickness and surface area (Eckstein et al. 2002c). The side differences were not associated with lower limb dominance, i.e. subjects with dominance of the right lower limb did not display systematically higher cartilage volume, thickness or surface areas on that side. However, side differences in MCSAs were moderately correlated with side differences in cartilage volume, thickness and surface areas, i.e. subjects with higher thigh MCSAs on the right tended to have higher cartilage volume, thickness and joint surface areas in the right knee (Eckstein et al. 2002c).

Cicuttini et al. (1999) reported sex differences of cartilage volume in adults, and Jones et al. (2000) in children and adolescents. The sex differences remained significant after adjusting for age, body weight, height and femoral (condylar) bone volume. Faber et al. (2001) also observed significant sex differences of cartilage volume in the medial tibia (+43% in men) and lateral tibia (+47%), and smaller (albeit significant) differences in the patella (+20%) and femur (+27%). It was shown, however, that gender differences in cartilage volume originated mainly from differences in the joint surface area size (total knee = +23% in men; P < 0.01), but to a lesser extent from differences in cartilage thickness (total knee = +8% in men; difference not statistically significant) (Faber et al. 2001). Eckstein et al. (2001a) reported that after matching men and women with identical body weight and height, men did not display significantly higher cartilage thickness than women, but still had significantly larger joint surface areas. This suggests that even when being matched for body height and weight, women have smaller knee joint surfaces than men. Eckstein et al. (2004) further examined whether gender differences in joint surface areas of the ankle joint were smaller than in the knee (based on the notion that women suffer more often from knee osteoarthritis than men, but men more often from osteoarthritic changes in the ankle). However, the authors found the sex differences to be similar for both joints.

A source of controversy has been whether cartilage thinning occurs during the normal aging process (possibly as a result of reduction in mechanical loading) or whether the decrease only affects people with arthritis. In human specimens, Meachim (1971) found no significant decrease of cartilage thickness in the human shoulder with age, whereas in the patella Meachim et al. (1977) observed cartilage thinning, in particular in women over the age of 50 years. These changes were attributed to osteoarthritis rather than to aging as such. Karvonen et al. (1994) concluded from local measurements in MR images that age accounted for a significant linear decrease in knee cartilage thickness both in the presence and in the absence of osteoarthritis. These findings were, however, confined to the site of most frequent femorotibial contact of the lateral and medial femoral condyle but did not apply to the patella, the tibia or the posterior aspects of the femoral condyles. Hudelmaier et al. (2001) examined men and women aged 50–75 years with no history of knee pain, trauma or surgery. In the patella, they found no significant difference in cartilage thickness compared with men aged 18–40 years (−6%), but a significantly lower thickness (−12%; P < 0.05) compared with women aged 18–40 years. Interestingly, women also displayed a larger decrease of the quadriceps cross-sectional area with age than men. For other joint surfaces of the knee they estimated the amount of cartilage thinning with age to be approximately 4% per decade and rates were similar for both sexes (Hudelmaier et al. 2003).

Reduced loading conditions

As stated above, mechanical stimuli are known to represent potent regulators of muscle and bone tissue mass. Animal studies have suggested that cartilage thickness decreases during immobilization but investigations in animals with increased levels of exercise have produced inconclusive and partly contradictory results (Helminen et al. 1992; Newton et al. 1997; for a recent review see Vanwanseele et al. 2002b). In a cross-sectional study, Vanwanseele et al. (2002a) examined the knee joints of paraplegic patients at 6, 12 and 24 months after injury and found the cartilage thickness to be significantly reduced in relation to healthy subjects of the same sex. The authors confirmed a reduction in cartilage thickness in paraplegic patients in a 12-month longitudinal study (Vanwanseele et al. 2003), in which they reported an annual reduction in cartilage thickness of > 10% in all compartments of the knee, whereas no significant changes of cartilage thickness were found in the shoulder (Vanwanseele et al. 2004). Hinterwimmer et al. (2004) recently showed that even during short-term reduced loading conditions (7 weeks of partial weight bearing at the knee, after a surgical intervention at the ankle) there was a significant degree of cartilage thinning (Fig. 9). Partial unloading was associated with an average reduction of the quadriceps muscle cross-sectional area (as measured with MRI) of 11% (Fig. 9), but no significant increase or decrease in cartilage volume or thickness was observed in the contra-lateral limb that was subject to increased loading during the 7-week period. These data indicate that cartilage undergoes some process of atrophy in the absence of mechanical stimulation. The findings may have important implications for the clinical management of the postoperative period in bone and joint surgery, and also for long-term space travel in the context of the international space station or a journey to Mars. These observations in particular raise the question as to what extent morphological changes (cartilage thinning) during reduced weight-bearing conditions are reversible.

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Figure 9. Graph showing the average change in quadriceps cross-sectional area and in cartilage thickness during 7 weeks of partial weight bearing of the knee (sole contact) in a group of 20 volunteers following a fracture of the ankle joint.

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In immature beagle dogs, Kiviranta et al. (1994) reported that after 11 weeks of immobilization and 15 weeks of remobilization, the GAG content was fully restored in most joint compartments, but not in the peripheral regions of the femoral condyles. They also found an incomplete restoration of femoral cartilage thickness after remobilization and reasoned that there was an inability of previously unloaded cartilage to withstand physiological loads during the remobilization process (Kiviranta et al. 1994). The same group reported a decrease in indentation stiffness after 11 weeks of immobilization, which was not fully restored during a 50-week remobilization period (Haapala et al. 1999). The authors claimed that extended immobilization of a joint may cause long-lasting biochemical and biomechanical alterations of the cartilage, specifically the proteoglycans, that may jeopardize its morphological integrity and mechanical competence (Haapala et al. 1999).

Hudelmaier et al. (2001) examined a single volunteer after 6 weeks of complete non-load-bearing and restriction of knee joint motion to 0–30° of flexion. They found a 14% lower patellar cartilage thickness on the immobilized side, but no side differences in tibial cartilage morphology. At the same time, side differences in quadriceps cross-sectional area amounted to 36% after immobilization. During a 24-month remobilization period with intensive physiotherapy and weight training over the first 7 months, side differences in patellar cartilage thickness and quadriceps cross-sectional area reduced to 2 and 9%, respectively, within the first 9 months, and to 8 and 4%, respectively, over the entire observation period (24 months) (Fig. 10). Patellar cartilage deformation was 9% 4 weeks after immobilization (the first time point at which the participant was able to perform deep knee bends) and was lower at later time points (1–6% at 6–18 months). These findings indicate that the stiffness of the patellar cartilage may be reduced after immobilization, probably as a consequence of biochemical alterations of the cartilage.

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Figure 10. Graph showing the side differences of quadriceps cross-sectional area (CSA) and mean patellar cartilage thickness (in percentage left vs. right) during a 24-month remobilization period in one subject, after 6 weeks of immobilization of the left limb, with no weight bearing and restriction of knee movement from 0° to 30° of flexion.

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Increased loading conditions

In a cross-sectional study of 92 children (age 9–18 years), Jones et al. (2000) reported a significant association between cartilage volume and self-reported level of exercise in children. The authors observed that physical activity was a significant explanatory factor for cartilage volume at all sites in the knee (r2 = 7–14%, P < 0.05) and that the most consistent association was with vigorous activity in the 2 weeks prior to imaging. In a longitudinal study of 74 children of the same cohort (observation period 1.3–1.9 years) the authors (Jones et al. 2003) found an association of average intensity of sport (again evaluated by responses to a questionnaire). Subjects above the median were found to gain approximately twice as much cartilage as those below the median at tibial (but not patellar) cartilage. From these studies, the authors concluded that cartilage development is amenable to modification. Note, however, that analysis of cartilage volume does not permit one to separate the effect on cartilage development (thickness) and bone growth (epiphyseal joint surface area).

When investigating mature adults, however, Eckstein et al. (2002a) found no difference in cartilage thickness in triathletes, who had been training for at least 10 h per week over the last 3 years and had also been physically active throughout childhood and adolescence in comparison with individuals who had never been physically active (< 1 h sport per week throughout life), had no job that involved physical activity, and had a normal body mass index (Eckstein et al. 2002a). The latter findings suggest that the relatively great variability in cartilage thickness observed between subjects is not readily explained by variability in mechanical loading history (Carter et al. 1991). Interestingly, however, triathletes displayed somewhat larger knee joint surface areas (+9%, P < 0.01 in men; +7%, P = 0.08 in women). These observations indicate that the biological mechanism to reduce high stress at the articular surface may be by an increase in the area of the load-bearing surface rather than an increase in cartilage thickness (Eckstein et al. 2002a). A potential reason for this is that beyond a certain thickness the nutritive situation of the cartilage becomes critical, and/or that the stress distribution (load partitioning) within the cartilage becomes unfavourable with thicker cartilage. With thicker cartilage, there is more space for the interstitial fluid to escape laterally from the site of contact and hydrostatic pressurization is reduced. With larger contact areas, by contrast, the force is distributed onto a wider area, keeping the stress at the joint surface within reasonable limits, and the mechanism of hydrostatic pressurization of the interstitial fluid is enhanced.

Tiderius et al. (2003) compared the dGEMRIC index in (1) non-exercising individuals, (2) individuals physically exercising twice per week and (3) elite runners. The index was found to be significantly higher in individuals who exercised regularly, and still higher in the elite runners. The authors concluded that human knee cartilage may adapt to exercise by increasing the GAG content, but that a higher proportion of extracellular body water (a larger distribution volume for the contrast agent applied) may also to some extent explain the higher dGEMRIC index values in elite runners. Recently, the same group (Roos & Dahlberg, 2005) reported that the dGEMRIC index increased over 4 months in 30 subjects (who had undergone partial medial meniscectomy 3–5 years previously) during a supervised, three-times weekly exercise protocol. There also was a relatively high correlation (r = 0.74) between change in T1 (Gd) and the self-reported change in physical activity level, over the 4-month period. These results indicate that compositional adaptation (increase in GAG content) of cartilage may occur over relatively short time intervals in response to exercise and mechanical loading.

Gratzke et al. (2002) compared knee cartilage morphology in 14 elite athletes (seven weightlifters and seven bobsleigh sprinters) with 14 men who had never performed strength training (for a more detailed description of the participants see above). All athletes had been actively training throughout adolescence, well before reaching skeletal maturity. The weightlifters displayed 26% higher (P < 0.01) extensor forces, as measured with a Cybex dynamometer, and 30% higher (P < 0.001) extensor MCSAs than the non-athletic volunteers. The same applied to the bobsleigh sprinters (+ 43%/+23%, P < 0.001, respectively). The cartilage thickness, articular joint surface area and chondro-osseous interface area were not significantly greater in the group of athletes compared with the group of non-athletic volunteers, except for the cartilage thickness of the patella. This was 14% greater (P < 0.01) in the weightlifters and 17% greater (P < 0.01) in the sprinters. Nevertheless, there was still a wide overlap in patellar cartilage thickness values between the athletes and non-athletic participants. The findings of this (and previously cited) studies indicate that differences in mechanical environment may not readily explain the relatively large variability of cartilage morphology observed between human subjects, despite enormous interindividual differences in mechanical loading history throughout the relevant developmental period (adolescence) in which endochondral ossification is completed and cartilage form is determined. These findings, however, refer to the average cartilage thickness throughout joint surfaces, and adaptation at a regional level cannot be discounted. Why there was a trend towards increased patellar cartilage thickness in athletes with high muscle strength, and a trend towards larger joint surface areas in athletes with high endurance is currently unclear, but these findings will have to be confirmed in larger samples and in athletes with different types of specializations. Future studies should also include regional analyses of cartilage thickness, which have so far not been presented in the context of the response of cartilage to exercise.

Genetic influence

In the interpretation of the cumulative data reviewed in this article, environmental (mechanical) factors appear to play only a small (if any) role in determining cartilage morphology in adults, although a wide variability of cartilage thickness is observed in the population, even in the absence of arthritic changes (Eckstein et al. 2001a; Burgkart et al. 2003; Hudelmaier et al. 2003). One potential explanation for the intersubject differences observed in cartilage morphology is genetic differences between individuals.

Antoniades et al. (2001) examined the minimal joint space width of hip radiographs of 222 monozygotic (MZ) and 240 dizygotic (DZ) twins. They found that genetic factors accounted for most of the variation in joint space width, but were not able to make direct measurements of cartilage thickness. Hunter et al. (2003) examined 31 MZ and 37 DZ twin pairs to assess the relative contribution of genetic and environmental factors to knee cartilage volume. The heritability was estimated to range from 61 to 76% for different compartments of the knee. However, the authors used an MR sequence (T2-weighted, fat-saturated sagittal gradient echo) that has not been validated for the purpose of cartilage volume measurements, and cartilage volume is strongly dependent on bone size, so that the genetic contribution to cartilage (thickness) formation is difficult to estimate.

Zhai et al. (2004) investigated the heritability of cartilage volume and bone size by examining sibling pairs. They estimated the heritability of cartilage volume to be 65–84% for various knee compartments, and that of bone size to be 57–85%. Again, however, cartilage thickness was not determined directly.

Siedek et al. (2002) examined 12 MZ twin pairs to determine knee cartilage thickness and joint surface areas as separate entities. They observed a remarkable similarity in cartilage morphology between twins (coefficient of variation 3.2% for cartilage thickness and 2.2% for joint surface area), in comparison with the substantially larger variability between subjects for a young reference population of 117 subjects (CV 12 and 11% for cartilage thickness in women and men, respectively, and 10 and 9% for joint surface areas). These findings suggest that not only bone size (or joint surface areas), but also cartilage thickness appears to be strongly determined by genetics. The lack of correlation in cartilage thickness between the knee and ankle (Eckstein et al. 2004), however, indicates that different genes may be responsible for cartilage thickness in different joints of the human body.

Conclusion

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methodological background of qMRI of cartilage
  5. Short-term effects of exercise on articular cartilage (deformational behaviour)
  6. Long-term effects of exercise on articular cartilage (functional adaptation)
  7. Conclusion
  8. References

Taken together, these findings indicate that differences in cartilage form between individuals cannot be readily explained by functional adaptation to mechanics, and that the emergence and maintenance of cartilage form appears to depend on information from the genome. Although hyaline articular cartilage appears to display atrophic changes (thinning) during unloading and may exhibit compositional changes (increase in GAG) after exercise, it seems to differ from other musculoskeletal tissues with load-bearing function as it cannot increase tissue mass postnatally as a result of mechanical stimulation (Lamarck, 1809; Darwin, 1872; Roux, 1881; Wolff, 1892; Pauwels, 1980; Carter et al. 1991; Huiskes et al. 2000). The specific signals that stop the ossification front from progressing to the joint surface (and that preserve a cartilage layer of given thickness) remain enigmatic. However, our results clearly suggest that, contrary to general expectation, mechanical feedback does not play a relevant role in this process and, in contrast to bone, does not serve to regulate the complex biochemical metabolic machinery towards lasting optimality of cartilage form (Huiskes et al. 2000). In attempting to address the question of why (in contrast to muscle and bone) cartilage does not appear to adapt its mass to mechanical stimulation, the following aspects need to be considered. (1) Loss of cartilage and joint function is a problem generally encountered by individuals after their reproductive period and – in contrast to bone fracture and muscle weakness – this may have not created evolutionary pressures for the tissue to be able to adapt to mechanical usage. (2) Whereas too much bone or too much muscle are metabolically expensive and provide a clear disadvantage for fast locomotion, a slight increase in cartilage thickness has no known negative consequences on metabolism and speed of locomotion. Therefore, there may have been less of an evolutionary pressure to adapt cartilage morphology to the immediate mechanical demands encountered by the individual. (3) Lastly, whereas ‘more’ muscle provides more tensile strength, and ‘more’ bone provides higher structural compressive and bending strength and hence better protection against fractures, ‘more’ cartilage is not known to be associated with improved mechanical competence of joints. There may thus exist a decoupling between functional competence and tissue mass. Hydrostatic pressurization provides a mechanism by which cartilage is able to distribute joint forces evenly onto the subchondral bone (Ateshian et al. 1994; Mow et al. 2003), protect itself from mechanical damage, and probably also provides almost frictionless surfaces during dynamic motion (Krishnan et al. 2003). This mechanism is probably more difficult to accomplish in a thick cartilage layer, in which the interstitial fluid can escape laterally from the site of contact. These aspects may provide some explanation as to why cartilage is less (if at all) responsive to increased mechanical loading. However, the inability of cartilage to adapt to its mechanical environment may be coupled with its inability to repair following mechanical and other insults (Hunziker et al. 2002). This inability may be essential in understanding the deleterious consequences of cartilage loss in degenerative joint disease and the large burden of osteoarthritis on the aging population (Yelin & Callahan, 1995).

References

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methodological background of qMRI of cartilage
  5. Short-term effects of exercise on articular cartilage (deformational behaviour)
  6. Long-term effects of exercise on articular cartilage (functional adaptation)
  7. Conclusion
  8. References