Effect of walking on in vivo tibiofemoral cartilage strain in ACL-deficient versus intact knees

Chronic ACLD Knees with Early Developmental Cartilage Lesions Exhibited Increased Posterior Tibial Translation during Level Walking

OBJECTIVE

Early articular cartilage lesion (CL) is a vital sign in the onset of posttraumatic knee osteoarthritis (PTOA) in patients with anterior cruciate ligament deficiency (ACLD). Researchers have suggested that altered kinematics could accelerate CLs and, therefore, lead to the onset of PTOA. However, little is known about whether specific knee kinematics exist that lead to early CL in chronic ACLD knees. Level walking is the most frequent and relevant in vivo activity, which greatly impacts knee health. We hypothesized that the knee kinematics during level walking in chronic ACLD knees with early tibiofemoral CL would significantly differ from those of chronic ACLD knees without early tibiofemoral CL.

METHODS

Thirty patients with a chronic ACLD history, including 18 subjects with CLs and 12 subjects without CLs, and 35 healthy control subjects were recruited for the study from July 2020 to August 2022. The knee kinematic data during level walking were collected using a three-dimensional motion analysis system. The kinematic differences between groups were compared using statistical parametric mapping with one dimension for One-Way ANOVA. The cartilage statuses of the ACLD knees were assessed via MRI examination. The CLs distribution of subjects was evaluated using a modified Noyes scale and analyzed by chi-square tests.

RESULTS

ACLD knees with CLs had significantly greater posterior tibial translation (7.7-8.0mm, 12%-18% gait cycle GC, p = 0.014) compared to ACLD knees without CLs during level walking. ACLD knees with CLs had greater posterior tibial translation (4.6-5.5mm, 0%-23% GC, p < 0.001; 5.8-8.0mm, 86%-100% GC, p < 0.001) than healthy controls during level walking. In the group of ACLD knees with CLs, CL is mainly located in the back of the tibia plateau and front of load bearing area of the medial femoral condyle (p < 0.05).

CONCLUSION

Chronic anterior cruciate ligament deficient knees with cartilage lesions have increased posterior tibial translation compared to anterior cruciate ligament deficient knees without cartilage lesions and healthy subjects. The posterior tibial translation may play an important role in knee cartilage degeneration in ACLD knees. The increased posterior tibial translation and cartilage lesion characteristics may improve our understanding of the role of knee kinematics in cartilage degeneration and could be a helpful potential reference for anterior cruciate ligament deficient therapy, such as physical training to improve abnormal kinematic behavior.

Effect of sensor number and location on accelerometry-based vertical ground reaction force estimation during walking

Knee osteoarthritis is a major cause of global disability and is a major cost for the healthcare system. Lower extremity loading is a determinant of knee osteoarthritis onset and progression; however, technology that assists rehabilitative clinicians in optimizing key metrics of lower extremity loading is significantly limited. The peak vertical component of the ground reaction force (vGRF) in the first 50% of stance is highly associated with biological and patient-reported outcomes linked to knee osteoarthritis symptoms. Monitoring and maintaining typical vGRF profiles may support healthy gait biomechanics and joint tissue loading to prevent the onset and progression of knee osteoarthritis. Yet, the optimal number of sensors and sensor placements for predicting accurate vGRF from accelerometry remains unknown. Our goals were to: 1) determine how many sensors and what sensor locations yielded the most accurate vGRF loading peak estimates during walking; and 2) characterize how prescribing different loading conditions affected vGRF loading peak estimates. We asked 20 young adult participants to wear 5 accelerometers on their waist, shanks, and feet and walk on a force-instrumented treadmill during control and targeted biofeedback conditions prompting 5% underloading and overloading vGRFs. We trained and tested machine learning models to estimate vGRF from the various sensor accelerometer inputs and identified which combinations were most accurate. We found that a neural network using one accelerometer at the waist yielded the most accurate loading peak vGRF estimates during walking, with average errors of 4.4% body weight. The waist-only configuration was able to distinguish between control and overloading conditions prescribed using biofeedback, matching measured vGRF outcomes. Including foot or shank acceleration signals in the model reduced accuracy, particularly for the overloading condition. Our results suggest that a system designed to monitor changes in walking vGRF or to deploy targeted biofeedback may only need a single accelerometer located at the waist for healthy participants.

MRI-derived Articular Cartilage Strains Predict Patient-Reported Outcomes Six Months Post Anterior Cruciate Ligament Reconstruction

Key terms

Multicontrast and Multiparametric, Magnetic Resonance Imaging, Osteoarthritis, Functional Biomechanical Imaging, Knee Joint Degeneration What is known about the subject: dualMRI has been used to quantify strains in a healthy human population in vivo and in cartilage explant models. Previously, OA severity, as determined by histology, has been positively correlated to increased shear and transverse strains in cartilage explants. What this study adds to existing knowledge: This is the first in vivo use of dualMRI in a participant demographic post-ACL reconstruction and at risk for developing osteoarthritis. This study shows that dualMRI-derived strains are more significantly correlated with patient-reported outcomes than any MRI relaxometry metric.

Background

Anterior cruciate ligament (ACL) injuries lead to an increased risk of osteoarthritis, characterized by altered cartilage tissue structure and function. Displacements under applied loading by magnetic resonance imaging (dualMRI) is a novel MRI technique that can be used to quantify mechanical strain in cartilage while undergoing a physiological load.

Purpose

To determine if strains derived by dualMRI and relaxometry measures correlate with patient-reported outcomes at six months post unilateral ACL reconstruction.

Study Design

Cohort study.

Methods

Quantitative MRI (T2, T2*, T1ρ) measurements and transverse, axial, and shear strains were quantified in the medial articular tibiofemoral cartilage of 35 participants at six-months post unilateral ACL reconstruction. The relationships between patient-reported outcomes (WOMAC, KOOS, MARS) and all qMRI relaxation times were quantified using general linear mixed-effects models. A combined best-fit multicontrast MRI model was then developed using backwards regression to determine the patient features and MRI metrics that are most predictive of patient-reported outcome scores.

Results

Higher femoral strains were significantly correlated with worse patient-reported functional outcomes. Femoral shear and transverse strains were positively correlated with six-month KOOS and WOMAC scores, after controlling for covariates. No relaxometry measures were correlated with patient-reported outcome scores. We identified the best-fit model for predicting WOMAC score using multiple MRI measures and patient-specific information, including sex, age, graft type, femoral transverse strain, femoral axial strain, and femoral shear strain. The best-fit model significantly predicted WOMAC score (p<0.001) better than any one individual MRI metric alone. When we regressed the model-predicted WOMAC scores against the patient-reported WOMAC scores, we found that our model achieved a goodness of fit exceeding 0.52.

Conclusions

This work presents the first use of dualMRI in vivo in a cohort of participants at risk for developing osteoarthritis. Our results indicate that both shear and transverse strains are highly correlated with patient-reported outcome severity could serve as novel imaging biomarkers to predict the development of osteoarthritis.

Immediate and Delayed Effects of Joint Loading Activities on Knee and Hip Cartilage: A Systematic Review and Meta-analysis

BACKGROUND

The impact of activity-related joint loading on cartilage is not clear. Abnormal loading is considered to be a mechanical driver of osteoarthritis (OA), yet moderate amounts of physical activity and rehabilitation exercise can have positive effects on articular cartilage. Our aim was to investigate the immediate effects of joint loading activities on knee and hip cartilage in healthy adults, as assessed using magnetic resonance imaging. We also investigated delayed effects of activities on healthy cartilage and the effects of activities on cartilage in adults with, or at risk of, OA. We explored the association of sex, age and loading duration with cartilage changes.

METHODS

A systematic review of six databases identified studies assessing change in adult hip and knee cartilage using MRI within 48 h before and after application of a joint loading intervention/activity. Studies included adults with healthy cartilage or those with, or at risk of, OA. Joint loading activities included walking, hopping, cycling, weightbearing knee bends and simulated standing within the scanner. Risk of bias was assessed using the Newcastle-Ottawa Scale. Random-effects meta-analysis estimated the percentage change in compartment-specific cartilage thickness or volume and composition (T2 relaxation time) outcomes. The Grading of Recommendations Assessment, Development and Evaluation (GRADE) system evaluated certainty of evidence.

RESULTS

Forty studies of 653 participants were included after screening 5159 retrieved studies. Knee cartilage thickness or volume decreased immediately following all loading activities investigating healthy adults; however, GRADE assessment indicated very low certainty evidence. Patellar cartilage thickness and volume reduced 5.0% (95% CI 3.5, 6.4, I² = 89.3%) after body weight knee bends, and tibial cartilage composition (T2 relaxation time) decreased 5.1% (95% CI 3.7, 6.5, I² = 0.0%) after simulated standing within the scanner. Hip cartilage data were insufficient for pooling. Secondary outcomes synthesised narratively suggest knee cartilage recovers within 30 min of walking and 90 min of 100 knee bends. We found contrasting effects of simulated standing and walking in adults with, or at risk of, OA. An increase of 10 knee bend repetitions was associated with 2% greater reduction in patellar thickness or volume.

CONCLUSION

There is very low certainty evidence that minimal knee cartilage thickness and volume and composition (T2 relaxation time) reductions (0-5%) occur after weightbearing knee bends, simulated standing, walking, hopping/jumping and cycling, and the impact of knee bends may be dose dependent. Our findings provide a framework of cartilage responses to loading in healthy adults which may have utility for clinicians when designing and prescribing rehabilitation programs and providing exercise advice.

Trimethylamine-N-oxide sensitizes chondrocytes to mechanical loading through the upregulation of Piezo1

BACKGROUND

Mechanical strain plays a crucial role in chondrocyte apoptosis and osteoarthritis (OA) disease progression through Piezo1. Trimethylamine-N-oxide (TMAO) is a diet-derived metabolite that correlates positively with multiple chronic diseases. Herein, we explored the potential role of TMAO in sensitizing chondrocytes to Piezo1-mediated mechanotransduction.

METHODS

The cytotoxicity of TMAO on chondrocytes was assayed. Piezo1 expression was measured after TMAO intervention. Pathological mechanical loading or Yoda1 (a specific Piezo1 channel activator) was administered in chondrocytes. The calcium levels and cytoskeleton in chondrocytes were observed by fluorescence microscopy. Flow cytometry, western blotting, and mitochondrial membrane potential assays were utilized to evaluate apoptosis. A rat OA model was constructed by anterior cruciate ligament transection. Hematoxylin-eosin staining, Safranin-O/Fast Green staining, immunochemistry, and TUNEL were applied to estimate OA severity.

RESULTS

TMAO intervention alone did not affect chondrocyte viability up to 600 μM. TMAO significantly increased Piezo1 expression and up-regulated intracellular calcium levels, further leading to cytoskeletal damage. Mechanical strain or Yoda1 treatment significantly induced chondrocyte apoptosis. Notably, TMAO intervention further aggravated chondrocyte apoptosis and cartilage destruction under pathological mechanical loading.

CONCLUSION

TMAO significantly up-regulated Piezo1 expression and sensitized chondrocytes to mechanical loading, which may be closely related to the pathogenesis of OA.

Auto-segmentation of the tibia and femur from knee MR images via deep learning and its application to cartilage strain and recovery

The ability to efficiently and reproducibly generate subject-specific 3D models of bone and soft tissue is important to many areas of musculoskeletal research. However, methodologies requiring such models have largely been limited by lengthy manual segmentation times. Recently, machine learning, and more specifically, convolutional neural networks, have shown potential to alleviate this bottleneck in research throughput. Thus, the purpose of this work was to develop a modified version of the convolutional neural network architecture U-Net to automate segmentation of the tibia and femur from double echo steady state knee magnetic resonance (MR) images. Our model was trained on a dataset of over 4,000 MR images from 34 subjects, segmented by three experienced researchers, and reviewed by a musculoskeletal radiologist. For our validation and testing sets, we achieved dice coefficients of 0.985 and 0.984, respectively. As further testing, we applied our trained model to a prior study of tibial cartilage strain and recovery. In this analysis, across all subjects, there were no statistically significant differences in cartilage strain between the machine learning and ground truth bone models, with a mean difference of 0.2 ± 0.7 % (mean ± 95 % confidence interval). This difference is within the measurement resolution of previous cartilage strain studies from our lab using manual segmentation. In summary, we successfully trained, validated, and tested a machine learning model capable of segmenting MR images of the knee, achieving results that are comparable to trained human segmenters.

Dynamic knee stiffness during walking is increased in individuals with anterior cruciate ligament reconstruction

Individuals with anterior cruciate ligament (ACL) reconstruction often display abnormal gait mechanics reflective of a "stiff-knee" gait (i.e., reduced knee flexion angles and moments). However, dynamic knee stiffness, which is the dynamic relationship between the position of the knee and the moment acting on it, has not been directly examined during walking in individuals with ACL reconstruction. Here, we aimed to evaluate dynamic knee stiffness in the involved compared to the uninvolved limb during weight-acceptance and mid-stance phases of walking. Twenty-six individuals who underwent ACL reconstruction (Age: 20.2 ± 5.1 yrs., Time post-op: 7.2 ± 0.9 mo.) completed an overground walking assessment using a three-dimensional motion capture system and two force plates. Dynamic knee stiffness (Nm/°) was calculated as the slope of the regression line during weight-acceptance and midstance, obtained by plotting the sagittal plane knee angle versus knee moment. Paired t-tests with Bonferroni corrections were used to compare differences in dynamic stiffness, knee excursions, and moment ranges between limbs during both stance phases. Greater dynamic knee stiffness was found in the involved compared with the uninvolved limb during weight-acceptance and mid-stance (p < 0.01). Knee flexion and extension excursions were reduced in the involved limb during both weight-acceptance and mid-stance, respectively (p < 0.01). Sagittal plane knee moment ranges were not different between limbs during weight-acceptance (p = 0.1); however, the involved limb moment range was reduced relative to the uninvolved limb during mid-stance (p < 0.01). These results indicate that individuals with ACL reconstruction walk with a stiffer knee throughout stance, which may influence knee contact forces and could contribute to the high propensity for post-traumatic knee osteoarthritis development in this population.

Osteoarthritis year in review 2021: mechanics

Osteoarthritis (OA) has a complex, heterogeneous and only partly understood etiology. There is a definite role of joint cartilage pathomechanics in originating and progressing of the disease. Although it is still not identified precisely enough to design or select targeted treatments, the progress of this year's research demonstrates that this goal became much closer. On multiple scales - tissue, joint and whole body - an increasing number of studies were done, with impressive results. (1) Technology based instrument innovations, especially when combined with machine learning models, have broadened the applicability of biomechanics. (2) Combinations with imaging make biomechanics much more precise & personalized. (3) The combination of Musculoskeletal & Finite Element Models yield valid personalized cartilage loads. (4) Mechanical outcomes are becoming increasingly meaningful to inform and evaluate treatments, including predictive power from biomechanical models. Since most recent advancements in the field of biomechanics in OA are at the level of a proof op principle, future research should not only continue on this successful path of innovation, but also aim to develop clinical workflows that would facilitate including precision biomechanics in large scale studies. Eventually this will yield clinical tools for decision making and a rationale for new therapies in OA.

Exercise to Mend Aged-tissue Crosstalk in Bone Targeting Osteoporosis & Osteoarthritis

Aging induces alterations in bone structure and strength through a multitude of processes, exacerbating common aging- related diseases like osteoporosis and osteoarthritis. Cellular hallmarks of aging are examined, as related to bone and the marrow microenvironment, and ways in which these might contribute to a variety of age-related perturbations in osteoblasts, osteocytes, marrow adipocytes, chondrocytes, osteoclasts, and their respective progenitors. Cellular senescence, stem cell exhaustion, mitochondrial dysfunction, epigenetic and intracellular communication changes are central pathways and recognized as associated and potentially causal in aging. We focus on these in musculoskeletal system and highlight knowledge gaps in the literature regarding cellular and tissue crosstalk in bone, cartilage, and the bone marrow niche. While senolytics have been utilized to target aging pathways, here we propose non-pharmacologic, exercise-based interventions as prospective "senolytics" against aging effects on the skeleton. Increased bone mass and delayed onset or progression of osteoporosis and osteoarthritis are some of the recognized benefits of regular exercise across the lifespan. Further investigation is needed to delineate how cellular indicators of aging manifest in bone and the marrow niche and how altered cellular and tissue crosstalk impact disease progression, as well as consideration of exercise as a therapeutic modality, as a means to enhance discovery of bone-targeted therapies.

Obesity impacts the mechanical response and biochemical composition of patellofemoral cartilage: An in vivo, MRI-based investigation

Obesity is a primary risk factor for osteoarthritis. While previous work has addressed relationships between in vivo cartilage mechanics, composition, and obesity in the tibiofemoral joint, there is limited information on these relationships in the patellofemoral joint. The purpose of this study was to compare the patellofemoral cartilage mechanical response to walking in participants with normal and obese body mass indices (BMIs). Additionally, patellar cartilage T1rho relaxation times were measured before exercise to characterize the biochemical composition of the tissue. Fifteen participants (eight with normal BMI and seven with obese BMI) underwent baseline magnetic resonance imaging (MRI) of their right knee. They then walked on a treadmill for 20 min at a speed normalized to their leg length before a second MRI scan. Subsequently, three-dimensional models of the bones and articular surfaces of the patellofemoral joint were created via manual segmentation of the pre- and post-exercise MR images to compute cartilage thickness and strain. Strain was defined as the change in patellofemoral cartilage thickness normalized to the baseline thickness. Results showed that participants with an obese BMI exhibited significantly increased patellofemoral cartilage strain compared to those with a normal BMI (5.4 ± 4% vs. 1.7 ± 3%, respectively; p = 0.003). Furthermore, patellar cartilage T1rho values were significantly higher in participants with obese versus normal BMIs (95 ms vs. 83 ms, respectively; p = 0.049), indicative of decreased proteoglycan content in those with an obese BMI. In summary, the altered patellofemoral cartilage strain and composition observed in those with an obese BMI may be indicative of cartilage degeneration.

Immune cell profiles in synovial fluid after anterior cruciate ligament and meniscus injuries

Background

Anterior cruciate ligament (ACL) and meniscus tears are common knee injuries. Despite the high rate of post-traumatic osteoarthritis (PTOA) following these injuries, the contributing factors remain unclear. In this study, we characterized the immune cell profiles of normal and injured joints at the time of ACL and meniscal surgeries.

Methods

Twenty-nine patients (14 meniscus-injured and 15 ACL-injured) undergoing ACL and/or meniscus surgery but with a normal contralateral knee were recruited. During surgery, synovial fluid was aspirated from both normal and injured knees. Synovial fluid cells were pelleted, washed, and stained with an antibody cocktail consisting of fluorescent antibodies for cell surface proteins. Analysis of immune cells in the synovial fluid was performed by polychromatic flow cytometry. A broad spectrum immune cell panel was used in the first 10 subjects. Based on these results, a T cell-specific panel was used in the subsequent 19 subjects.

Results

Using the broad spectrum immune cell panel, we detected significantly more total viable cells and CD3 T cells in the injured compared to the paired normal knees. In addition, there were significantly more injured knees with T cells above a 500-cell threshold. Within the injured knees, CD4 and CD8 T cells were able to be differentiated into subsets. The frequency of total CD4 T cells was significantly different among injury types, but no statistical differences were detected among CD4 and CD8 T cell subsets by injury type.

Conclusions

Our findings provide foundational data showing that ACL and meniscus injuries induce an immune cell-rich microenvironment that consists primarily of T cells with multiple T helper phenotypes. Future studies investigating the relationship between immune cells and joint degeneration may provide an enhanced understanding of the pathophysiology of PTOA following joint injury.