Imaging of knee osteoarthritis

Comprehensive Study on Scoring and Grading Systems for Predicting the Severity of Knee Osteoarthritis

Knee Osteoarthritis (KOA) is a degenerative joint ailment characterized by cartilage loss, which can be seen using imaging modalities and converted into imaging features. The older population is the most affected by knee OA, which affects 16% of people worldwide who are 15 years of age and older. Due to cartilage tissue degradation, primary knee OA develops in older people. In contrast, joint overuse or trauma in younger people can cause secondary knee OA. Early identification of knee OA, according to research, may be a successful management tactic for the condition. Scoring scales and grading systems are important tools for the management of knee osteoarthritis as they allow clinicians to measure the progression of the disease's severity and provide suggestions on suitable treatment at identified stages. The comprehensive study reviews various subjective and objective knee evaluation scoring systems that effectively score and grade the KOA based on where defects or changes in articular cartilage occur. Recent studies reveal that AI-based approaches, such as that of DenseNet, integrating the concept of deep learning for scoring and grading the KOA, outperform various state-of-the-art methods in order to predict the KOA at an early stage.

Magnetic Resonance Imaging in the Year Prior to Total Knee Arthroplasty: A Potential Overutilization of Healthcare Resources

BACKGROUND

Total knee arthroplasty (TKA) is a common procedure for late-stage degenerative changes, a situation for which magnetic resonance imaging (MRI) is typically not considered useful. In an era attempting to contain healthcare expenditures, the rate, timing, and predictors for MRI before TKA were assessed in a large, national, administrative data set.

METHODS

The 2010 to Q3 2020 MKnee PearlDiver data set was used to identify patients undergoing TKA for osteoarthritis. Those with lower extremity MRI for knee indications within 1 year before TKA were then defined. Patient age, sex, Elixhauser Comorbidity Index, region in the country, and insurance plan were characterized. Predictors of having had an MRI were assessed by univariate and multivariate analyses. The costs and timing of the obtained MRIs were also assessed.

RESULTS

Of 731,066 TKAs, MRI was obtained within 1 year prior for 56,180 (7.68%) with 28,963 (51.9%) within the 3 months of TKA. Independent predictors of having had an MRI included younger age (odds ratio [OR], 0.74 per decade increase), female sex (OR, 1.10), higher Elixhauser Comorbidity Index (OR, 1.15), region of the country (relative to South, Northeast OR, 1.08, West OR, 1.22, Midwest OR, 1.36), and insurance (relative to Medicare, Medicaid OR, 1.36 and Commercial OR, 1.35) with P < 0.0001 for each. The total cost of MRIs among patients who received a TKA is $44,686,308.

CONCLUSION

Noting that TKA is typically done for advanced degenerative changes, MRI should rarely be indicated in the preoperative period for this procedure. Nonetheless, this study found that MRI was done within the year before TKA for 7.68% of the study cohort. In an era striving for evidence-based medicine, the almost $45 million dollars spent on MRI in the year before TKA may represent overutilization.

An automated, web-based triage tool may optimise referral pathways in elective orthopaedic surgery: A proof-of-concept study

Introduction

Knee pain is caused by various pathologies, making evaluation in primary-care challenging. Subsequently, an over-reliance on imaging, such as radiographs and MRI exists. Electronic-triage tools represent an innovative solution to this problem. The aims of this study were to establish the magnitude of unnecessary knee imaging prior to orthopaedic surgeon referral, and ascertain whether an e-triage tool outperforms existing clinical pathways to recommend correct imaging.

Methods

Patients ≥18 years presenting with knee pain treated with arthroscopy or arthroplasty at a single academic hospital between 2015 and 2020 were retrospectively identified. The timing and appropriateness of imaging were assessed according to national guidelines, and classified as 'necessary', 'unnecessary' or 'required MRI'. Based on an eDelphi consensus study, a symptom-based e-triage tool was developed and piloted to preliminarily diagnose five common knee pathologies and suggest appropriate imaging.

Results

1462 patients were identified. 17.2% (n = 132) of arthroplasty patients received an 'unnecessary MRI', 27.6% (n = 192) of arthroscopy patients did not have a 'necessary MRI', requiring follow-up. Forty-one patients trialled the e-triage pilot (mean age: 58.4 years, 58.5% female). Preliminary diagnoses were available for 33 patients. The e-triage tool correctly identified three of the four knee pathologies (one pathology did not present). 79.2% (n = 19) of participants would use the tool again.

Conclusion

A substantial number of knee pain patients receive incorrect imaging, incurring delays and unnecessary costs. A symptom-based e-triage tool was developed, with promising performance and user feedback. With refinement using larger datasets, this tool has the potential to improve wait-times, referral quality and reduce cost.

Single nucleotide polymorphism genes and mitochondrial DNA haplogroups as biomarkers for early prediction of knee osteoarthritis structural progressors: use of supervised machine learning classifiers

BACKGROUND

Knee osteoarthritis is the most prevalent chronic musculoskeletal debilitating disease. Current treatments are only symptomatic, and to improve this, we need a robust prediction model to stratify patients at an early stage according to the risk of joint structure disease progression. Some genetic factors, including single nucleotide polymorphism (SNP) genes and mitochondrial (mt)DNA haplogroups/clusters, have been linked to this disease. For the first time, we aim to determine, by using machine learning, whether some SNP genes and mtDNA haplogroups/clusters alone or combined could predict early knee osteoarthritis structural progressors.

METHODS

Participants (901) were first classified for the probability of being structural progressors. Genotyping included SNP genes TP63, FTO, GNL3, DUS4L, GDF5, SUPT3H, MCF2L, and TGFA; mtDNA haplogroups H, J, T, Uk, and others; and clusters HV, TJ, KU, and C-others. They were considered for prediction with major risk factors of osteoarthritis, namely, age and body mass index (BMI). Seven supervised machine learning methodologies were evaluated. The support vector machine was used to generate gender-based models. The best input combination was assessed using sensitivity and synergy analyses. Validation was performed using tenfold cross-validation and an external cohort (TASOAC).

RESULTS

From 277 models, two were defined. Both used age and BMI in addition for the first one of the SNP genes TP63, DUS4L, GDF5, and FTO with an accuracy of 85.0%; the second profits from the association of mtDNA haplogroups and SNP genes FTO and SUPT3H with 82.5% accuracy. The highest impact was associated with the haplogroup H, the presence of CT alleles for rs8044769 at FTO, and the absence of AA for rs10948172 at SUPT3H. Validation accuracy with the cross-validation (about 95%) and the external cohort (90.5%, 85.7%, respectively) was excellent for both models.

CONCLUSIONS

This study introduces a novel source of decision support in precision medicine in which, for the first time, two models were developed consisting of (i) age, BMI, TP63, DUS4L, GDF5, and FTO and (ii) the optimum one as it has one less variable: age, BMI, mtDNA haplogroup, FTO, and SUPT3H. Such a framework is translational and would benefit patients at risk of structural progressive knee osteoarthritis.

A Machine Learning Model to Predict Knee Osteoarthritis Cartilage Volume Changes over Time Using Baseline Bone Curvature

The hallmark of osteoarthritis (OA), the most prevalent musculoskeletal disease, is the loss of cartilage. By using machine learning (ML), we aimed to assess if baseline knee bone curvature (BC) could predict cartilage volume loss (CVL) at one year, and to develop a gender-based model. BC and cartilage volume were assessed on 1246 participants using magnetic resonance imaging. Variables included age, body mass index, and baseline values of eight BC regions. The outcome consisted of CVL at one year in 12 regions. Five ML methods were evaluated. Validation demonstrated very good accuracy for both genders (R ≥ 0.78), except the medial tibial plateau for the woman. In conclusion, we demonstrated, for the first time, that knee CVL at one year could be predicted using five baseline BC region values. This would benefit patients at risk of structural progressive knee OA.

Comparison of high-resolution magnetic resonance imaging and micro-computed tomography arthrography for in-vivo assessment of cartilage in non-human primate models

Background

Non-human primate (NHP) could be an interesting model for osteoarthritis (OA) longitudinal studies but standard medical imaging protocols are not able to acquire sufficiently high-resolution images to depict the thinner cartilage (compared to human) in an in vivo context. The aim of this study was thus to develop and validate the acquisition protocols for knee joint examination of NHP using magnetic resonance imaging (MRI) at 1.5 T and X-ray micro-computed tomography arthrography (µCTA).

Methods

The first phase of the study focused on developing dedicated in vivo HR-MRI and µCTA protocols for simultaneous acquisitions of both knee joints on NHP. For MR, a dedicated two-channel receiver array coil and acquisition sequence were developed on a 1.5 T Siemens Sonata system and tuned to respect safety issues and reasonable examination time. For µCTA, an experimental setup was devised so as to fulfill similar requirements. The two imaging protocols were used during a longitudinal study so as to confirm that repeated injections of loxaglic acid (contrast agent used for µCTA) didn't induce any bias in cartilage assessment and to compare segmentation results from the two modalities. Lateral and medial cartilage tibial plateaus were assessed using a common image processing protocol leading to a 3D estimation of the cartilage thickness.

Results

From HR-MRI and µCTA images, thickness distributions were extracted allowing for proper evaluation of knee cartilage thickness of the primates. Results obtained in vivo indicated that the µCTA protocol did not induce any bias in the measured cartilage parameters and moreover, segmentation results obtained from the two imaging modalities were consistent.

Conclusions

MR and µCTA are valuable imaging tools for the morphological evaluation of cartilage in NHP models which in turn can be used for OA studies.

Peptidomic analysis of cartilage and subchondral bone in OA patients

BACKGROUND

The objective of this study was to develop a method for directly analysing osteochondral samples straight out of the operating room without cell culturing, thereby enabling identification of potential peptide biomarkers to better understand the mechanisms involved in the development of osteoarthritis and pain.

MATERIAL AND METHODS

Osteochondral plugs from wounded and macroscopically nonwounded zones of the femur condyle were collected from six patients with manifest osteoarthritis (OA) undergoing total knee arthroplasty (TKA). The samples were demineralized and supernatant was collected and isotopically marked with Tandem Mass Tag (TMT) labelling and analysed using liquid chromatography coupled with tandem mass spectrometry LC-MS/MS.

RESULTS

Using peptidomics, 6292 endogenous peptides were identified. Five hundred sixty-six peptides (8 identified endogenous peptides) differed significantly (P-value 0.10) from wounded zones compared to nonwounded zones.

CONCLUSION

This pilot study shows promising results for enabling peptidomic analysis of cartilage and bone straight out of the operating room. With further refinement, peptidomics can potentially become a diagnostic tool for OA, and improve the knowledge of disease progression and genesis of pain.

Circulating levels of proinflammatory mediators as potential biomarkers of post-traumatic knee osteoarthritis development

Background

The identification of biomarkers of post-traumatic osteoarthritis (PTOA) progression is of clinical importance. The aims of this study were: (1) to assess the abilities of various soluble proinflammatory mediators in plasma to distinguish patients with knee PTOA from controls; (2) to determine the correlations between the mediators in plasma and those mediators in synovial fluid (SF); and (3) to explore the associations of the mediators with radiographic PTOA severity.

Materials and methods

The concentrations of IL-1β, IL-6, IL-18, TNFα, and leptin were measured using ELISA. Nitric oxide was determined as nitrite/nitrate (NO_x) using the Griess reaction.

Results

We included 171 subjects (134 PTOA patients and 37 controls) and excluded patients with rheumatoid arthritis or gout. The ROC curve of plasma NO_x had the highest AUC, a specificity of 100%, and a sensitivity of 84.4%. The combination of IL-6 and leptin proved to be the most discriminatory, with an AUC value of 0.933, a specificity of 96.7%, and a sensitivity of 85.7%. The levels of NO_x, IL-6, IL-18, and leptin in plasma were significantly correlated with their levels in SF. Leptin levels in both plasma (p = 0.036) and SF (p = 0.041) and the synovial IL-18 level (p = 0.045) were correlated with the Kellgren–Lawrence (KL) grade. Early-stage PTOA (KL 1–2) was associated with a high concentration of IL-1β in plasma before and after (OR 6.235, 95% CI 1.362 to 28.552, p = 0.018) adjusting for age, gender, and BMI.

Conclusions

Circulating NO_x level and a combination of IL-6 and leptin permitted the strongest discrimination of patients with PTOA from controls. PTOA severity was correlated with leptin levels in plasma and SF and with the synovial IL-18 level. Early PTOA was associated with the circulating level of IL-1β.

Level of evidence

III (case–control study).

Lumbar disc degeneration is associated with modic change and high paraspinal fat content - a 3.0T magnetic resonance imaging study

Background

Degenerative disc disease of the lumbar spine is common, with severe disease increasing the risk for chronic low back pain. This cross-sectional study examined whether disc degeneration is representative of a ‘whole-organ’ pathology, by examining its association with bone (vertebral endplate) and soft tissue (paraspinal muscle fat) abnormalities.

Methods

Seventy-two community-based individuals unselected for low back pain, had Magnetic Resonance Imaging (MRI). Lumbosacral disc degeneration was determined via the Pfirrmann grading system, a validated method to assess the intervertebral disc, distinguishing the nucleus and annulus, the signal intensity and the height of the intervertebral disc. Modic change and high paraspinal muscle fat content was also measured from MRI.

Results

Severe disc degeneration was associated, or tended to be associated with type 2 Modic change from L2 to L5 (OR range 3.5 to 25.3, p ≤ 0.06). Moreover, severe disc degeneration at all intervertebral levels was associated with or tended to be associated with high fat content of the paraspinal muscles (OR range 3.7 to 14.3, p ≤ 0.09).

Conclusion

These data demonstrate that disc degeneration of the lumbar spine is commonly accompanied by Modic change and high fat content of paraspinal muscles, thus representing a ‘whole-organ’ pathology. Longitudinal studies are required to determine the temporal relationship between these structural abnormalities. Understanding this may have the potential to identify novel targets for the treatment and prevention of lumbosacral disc degeneration.

A large infrapatellar fat pad protects against knee pain and lateral tibial cartilage volume loss

INTRODUCTION

The infrapatellar fat pad (IPFP) is commonly resected during knee joint arthroplasty, but the ramifications of doing so are unclear. This longitudinal study determined whether the size of the IPFP (maximum cross-sectional area (CSA)) was associated with knee cartilage loss and the development of knee pain in adults without knee osteoarthritis (OA).

METHODS

A total of 297 adults without American College of Rheumatology clinical criteria for a diagnosis of knee OA were recruited. Knee MRI was performed at baseline and an average of 2.3 years later. IPFP maximal CSA and tibial cartilage volume were measured from MRI. A large and small IPFP were defined by the median split, with a large IPFP defined by being in the highest 50%. Body composition was performed at baseline using bio-impedance. Knee pain was assessed at follow-up using the Western Ontario and McMaster University Osteoarthritis Index (WOMAC).

RESULTS

A larger IPFP at baseline was associated with reduced knee pain at follow-up (OR 0.5, 95% CI: 0.3 to 0.9, p = 0.02) and lateral tibial cartilage volume loss (β: -0.9% (95% CI: -1.6, -0.1%) per annum, p = 0.03). The maximal CSA of the IPFP was predominantly located in the lateral (54.2%), rather than the medial tibiofemoral compartment (1.7%). Male gender (OR 12.0, 95% CI: 6.5 to 22.0, p < 0.001) and fat free mass (OR 1.15, 95% CI 1.04 to 1.28, p = 0.007) were both associated with a large IPFP.

CONCLUSION

A larger IPFP predicts reduced lateral tibial cartilage volume loss and development of knee pain and mechanistically might function as a local shock-absorber. The lack of association between measures of adiposity and the size of the IPFP might suggest that the IPFP size is not simply a marker of systemic obesity.

Structural changes of hip osteoarthritis using magnetic resonance imaging

INTRODUCTION

Few data are available concerning structural changes at the hip observed by magnetic resonance imaging (MRI) in people with or without hip osteoarthritis (OA). The aim of this study was to compare cartilage volume and the presence of cartilage defects and bone marrow lesions (BMLs) in participants with and without diagnosed hip OA.

METHODS

Femoral head cartilage volume was measured by MRI for 141 community-based persons with no diagnosed hip OA, and 19 with diagnosed hip OA. Cartilage defects and BMLs were regionally scored at the femoral head and acetabulum.

RESULTS

Compared with those without diagnosed hip OA, people with diagnosed hip OA had less femoral head cartilage volume (1763 mm3 versus 3343 mm3; p < 0.001) and more prevalent cartilage defects and BMLs (all p ≤ 0.05) at all sites other than the central inferomedial region of the femoral head. In those with no diagnosed hip OA, cartilage defects in the anterior and central superolateral region of the femoral head were associated with reduced femoral head cartilage volume (all p ≤ 0.02). Central superolateral BMLs at all sites were associated with reduced femoral head cartilage volume (all p ≤ 0.003), with a similar trend occurring when BMLs were located in the anterior region of the hip (all p ≤ 0.08).

CONCLUSIONS

Compared with community-based adults with no diagnosed hip OA, people with diagnosed hip OA have less femoral head cartilage volume and a higher prevalence of cartilage defects and BMLs. For people with no diagnosed hip OA, femoral head cartilage volume was reduced where cartilage defects and/or BMLs were present in the anterior and central superolateral regions of the hip joint. Cartilage defects and BMLs present in the anterior and central superolateral regions may represent early structural damage in the pathogenesis of hip OA.

Non-invasive and in vivo assessment of osteoarthritic articular cartilage: a review on MRI investigations

Early detection of knee osteoarthritis (OA) is of great interest to orthopaedic surgeons, rheumatologists, radiologists, and researchers because it would allow physicians to provide patients with treatments and advice to slow the onset or progression of the disease. Early detection can be achieved by identifying early changes in selected features of degenerative articular cartilage (AC) using non-invasive imaging modalities. Magnetic resonance imaging (MRI) is becoming the standard for assessment of OA. The aim of this paper was to review the influence of MRI on the selection, detection, and measurement of AC features associated with early OA. Our review of the literature indicates that the changes associated with early OA are in cartilage thickness, cartilage volume, cartilage water content, and proteoglycan content that can be accurately, consistently, and non-invasively measured using MRI. Choosing an MR pulse sequence that provides the capability to assess cartilage physiology and morphology in a single acquisition and advanced multi-nuclei MRI is desirable. The results of the review indicate that using an ultra-high magnetic strength, MR imager does not affect early OA detection. In conclusion, MRI is currently the most suitable modality for early detection of knee OA, and future research should focus on the quantitative evaluation of early OA features using advances in MR hardware, software, and data processing with sophisticated image/pattern recognition techniques.

What is the predictive value of MRI for the occurrence of knee replacement surgery in knee osteoarthritis?

Knee osteoarthritis is associated with structural changes in the joint. Despite its many drawbacks, radiography is the current standard for evaluating joint structure in trials of potential disease-modifying osteoarthritis drugs. MRI is a non-invasive alternative that provides comprehensive imaging of the whole joint. Frequently used MRI measurements in knee osteoarthritis are cartilage volume and thickness; others include synovitis, synovial fluid effusions, bone marrow lesions (BML) and meniscal damage. Joint replacement is considered a clinically relevant outcome in knee osteoarthritis; however, its utility in clinical trials is limited. An alternative is virtual knee replacement on the basis of symptoms and structural damage. MRI may prove to be a good alternative to radiography in definitions of knee replacement. One of the MRI parameters that predicts knee replacement is medial compartment cartilage volume/thickness, which correlates with radiographic joint space width, is sensitive to change, and predicts outcomes in a continuous manner. Other MRI parameters include BML and meniscal lesions. MRI appears to be a viable alternative to radiography for the evaluation of structural changes in knee osteoarthritis and prediction of joint replacement.

In vivo quantitative ultrasound image analysis of femoral subchondral bone in knee osteoarthritis

A potential of quantitative noninvasive knee ultrasonography (US) for detecting changes in femoral subchondral bone related to knee osteoarthritis (OA) was investigated. Thirty-nine patients referred to a knee arthroscopy underwent dynamic noninvasive US examination of the knee joint. The subchondral bone was semiautomatically segmented from representative US images of femoral medial and lateral condyles and intercondylar notch area. Subsequently, the normalized mean gray-level intensity profile, starting from the cartilage-bone interface and extending to the subchondral bone depth of -1.7 mm, was calculated. The obtained profile was divided into 5 depth levels and the mean of each level, as well as the slope of the profile within the first two levels, was calculated. The US quantitative data were compared with the arthroscopic Noyes' grading and radiographic Kellgren-Lawrence (K-L) grading. Qualitatively, an increase in relative subchondral bone US gray-level values was observed as OA progressed. Statistically significant correlations were observed between normalized US mean intensity or intensity slope especially in subchondral bone depth level 2 and K-L grading (r = 0.600, P < 0.001; r = 0.486, P = 0.006, resp.) or femoral arthroscopic scoring (r = 0.332, P = 0.039; r = 0.335, P = 0.037, resp.). This novel quantitative noninvasive US analysis technique is promising for detection of femoral subchondral bone changes in knee OA.

The interobserver reliability of ultrasound in knee osteoarthritis

OBJECTIVE

To assess the interobserver reliability between sonographers with different levels of experience in detecting inflammatory and structural damage abnormalities in patients with knee OA.

METHODS

After achieving consensus on definitions and scanning protocols, three ultrasonographers with different levels of experience in musculoskeletal US examined the knees of nine patients with OA. US examinations were conducted with independent blinded evaluations of inflammatory (joint effusion, synovial hypertrophy, power Doppler signal, Baker's cysts) and structural (osteophytes, cortical bone irregularities, femoral hyaline cartilage abnormalities, protrusion of the medial meniscus) lesions. All abnormalities were scored by applying a dichotomous scale (0-1). In addition, at each knee joint site global scores for joint inflammation, cortical bone abnormalities and cartilage damage were calculated by summing the single-lesion scores. Reliability was assessed using kappa (κ) coefficients.

RESULTS

Seventeen knees were examined. Inflammatory abnormalities were observed with moderate to very good agreement (κ = 0.55-0.88) between the observers. From fair to very good agreement (κ = 0.31-0.82) was registered between sonographers for structural damage lesions. The overall κ was 0.716 for junior and 0.571 for beginner sonographers comparing their findings with those of senior sonographers.

CONCLUSION

This represents the first ultrasonographic study focusing on the analysis of interobserver reliability between sonographers with different levels of experience in demonstrating inflammatory and structural abnormalities in knee OA. Globally, even considering some variable results that were mainly obtained by the evaluation of single components of bone involvement, US offered a reliable assessment of a wide set of abnormalities in knee OA.

Disease severity and knee extensor force in knee osteoarthritis: data from the Osteoarthritis Initiative

OBJECTIVE

To determine whether the method of disease severity measurement influences the magnitude of knee extensor force deficits in knee osteoarthritis (OA).

METHODS

Data from the Osteoarthritis Initiative (n = 659) were analyzed. Knee extensor force was assessed with isometric contractions. Clinical severity was measured with the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC). Patients were stratified into tertiles of severity (i.e., moderate, mild, and severe OA) based on the lowest, middle, and highest WOMAC scores, respectively. Kellgren/Lawrence (K/L) grading was used to assess radiographic severity of the tibiofemoral compartment and patients were again stratified into mild (K/L grade <2), moderate (K/L grade 2), and severe (K/L grade >2) knee OA.

RESULTS

When stratifying with the WOMAC, force was significantly lower in the severe group compared to the mild (~18% lower; P < 0.001) and moderate groups (~9% lower; P = 0.03), and in the moderate group compared to the mild group (∼10% lower; P = 0.03). When stratifying with K/L grade, small nonsignificant differences were observed in the severe (~7% lower; P = 0.19) and moderate groups (~8% lower; P = 0.08) compared to the mild group. Large intragroup variability was observed when comparing WOMAC scores across radiographic severity (coefficients of variation were 79.3%, 74.6%, and 61.6% for K/L grade <2, K/L grade 2, and K/L grade >2, respectively).

CONCLUSION

The method of disease severity stratification influences the magnitude of knee extensor force deficits because no difference in force between disease subgroups was observed when stratifying with K/L grade. Furthermore, there was large variability in the WOMAC score within each radiographic subgroup, highlighting the limitations in using radiographic measures to reflect symptom severity.

A phenomenological mathematical model of the articular cartilage damage

Articular cartilage (AC) is a biological tissue that allows the distribution of mechanical loads and movement of joints. The presence of these mechanical loads influences the behavior and physiological condition of AC. The loads may cause damaged by fatigue through injuries due to repeated accumulated stresses. The aim of this work is to introduce a phenomenological mathematical model of damage caused by mechanical action. It is considered that tissue failure is a consequence of chondrocyte death and matrix loss, taking into account factors modifying fatigue resistance such as age, body mass index (BMI) and metabolic activity. The model was numerically implemented using the finite elements method and the results obtained allowed us to predict tissue failure at different loading frequencies, different damage sites and variations in damage magnitude. Qualitative concordance between numerical results and experimental data led us to conclude that the model may be useful for physicians and therapists as a prediction tool for prescribing physical exercise and prognosis of joint failure.