Patellofemoral contact forces and knee gait mechanics 3 months after ACL reconstruction are associated with cartilage degradation 24 months after surgery

Relationships Between Running Biomechanics and Femoral Articular Cartilage Thickness and Composition in Anterior Cruciate Ligament Reconstruction Patients

BACKGROUND

Although individuals with anterior cruciate ligament reconstruction (ACLR) are at high risk for posttraumatic osteoarthritis, mechanisms underlying the relationship between running and knee cartilage health remain unclear.

OBJECTIVE

We aimed to investigate how 30 min of running influences femoral cartilage thickness and composition and their relationships with running biomechanics in patients with ACLR and controls.

METHODS

Twenty patients with ACLR (time post-ACLR: 14.6 ± 6.1 months) and 20 matched controls participated in the study. A running session required both groups to run for 30 min at a self-selected speed. Before and after running, we measured femoral cartilage thickness via ultrasound imaging. A MRI session consisted of T2 mapping.

RESULTS

The ACLR group showed longer T2 relaxation times in the medial femoral condyle at resting compared with the control group (central: 51.2 ± 16.6 vs. 34.9 ± 13.2 ms, p = 0.006; posterior: 50.2 ± 10.1 vs. 39.8 ± 7.4 ms, p = 0.006). Following the run, the ACLR group showed greater deformation in the medial femoral cartilage than the control group (0.03 ± 0.01 vs. 0.01 ± 0.01 cm, p = 0.001). Additionally, the ACLR group showed significant negative correlations between resting T2 relaxation time in the medial femoral condyle and vertical impulse (standardized regression coefficients = -0.99 and p = 0.004) during running.

CONCLUSIONS

Our findings suggest that those who are between 6 and 24 months post-ACLR have degraded cartilage composition and their cartilage deforms more due to running vGRF.

Osteoarthritis year in review 2023: Biomechanics

Biomechanics plays a significant yet complex role in osteoarthritis (OA) onset and progression. Identifying alterations in biomechanical factors and their complex interactions is critical for gaining new insights into OA pathophysiology and identification of clearly defined and modifiable mechanical treatment targets. This review synthesized biomechanics studies from March 2022 to April 2023, from which three themes relating to human gait emerged: (1) new insights into the pathogenesis of OA using computational modeling and machine learning, (2) technology-enhanced biomechanical interventions for OA, and (3) out-of-lab biomechanical assessments of OA. We further highlighted future-focused areas which may continue to advance the field of biomechanics in OA, with a particular emphasis on exploiting technology to understand and treat biomechanical mechanisms of OA outside the laboratory. The breadth of studies included in this review highlights the complex role of biomechanics in OA and showcase numerous innovative and outstanding contributions to the field. Exciting cross-disciplinary efforts integrating computational modeling, mobile sensors, and machine learning methods show great promise for streamlining in vivo multi-scale biomechanics workflows and are expected to underpin future breakthroughs in the understanding and treatment of biomechanics in OA.

Is quadriceps strength associated with patellofemoral joint loading after anterior cruciate ligament reconstruction?

OBJECTIVE

To test whether quadriceps strength is associated with measures of patellofemoral (PF) joint loading during running and hopping in people after an anterior cruciate ligament reconstruction (ACLR).

DESIGN

Cross-sectional study.

SETTING

Biomechanics laboratory.

PARTICIPANTS

Sixty-five participants (24 women; 41 men) 1-2 years post-ACLR.

MAIN OUTCOME MEASURES

Peak isometric quadriceps strength for the surgical limb was measured using a dynamometer. Motion analysis and ground reaction force data were combined with musculoskeletal modelling to measure PF joint loading variables for the reconstructed knee (peak knee flexion angle; peak/impulse of the PF joint contact force; time to peak PF joint contact force) during the stance phase of running and during the landing phase of a standardised forward hop. Linear regression analysis (adjusting for age and sex) assessed the association between quadriceps strength and PF joint loading variables.

RESULTS

Two significant, albeit modest, associations were revealed. Quadriceps strength was associated with the time to peak PF joint contact force during running (β = -0.001; 95%CI -0.002 to -0.000; R2 = 0.179) and the impulse of the PF joint contact force during hopping (β = 0.014; 95%CI 0.003 to 0.024; R2 = 0.159).

CONCLUSIONS

A strong link between quadriceps strength and PF joint loading was not evident in people 1-2 years post-ACLR.