Biology subjects

Lloyd, D. G.

Publications and source records attributed to Lloyd, D. G..

3 recordsLinked to original sources

bioRxiv2023

An Automated and Robust Tool for Musculoskeletal and Finite Element Modeling of the Knee Joint

ObjectiveTo develop and assess an automatic and robust knee musculoskeletal finite element (MSK-FE) modeling pipeline. MethodsMagnetic resonance images (MRI) were used to train nnU-Net networks for auto-segmentation of knee bones (femur, tibia, patella, and fibula), cartilages (femur, tibia, and patella), menisci, and major knee ligaments. Two different MRI sequences were used to broaden applicability. Next, we created MSK-FE models of an unseen dataset using two MSK-FE modeling pipelines: template-based and auto-meshing. MSK models had personalized knee geometries with multi-degree-of-freedom elastic foundation contacts. FE models used fibril-reinforced poroviscoelastic swelling material models for cartilages and menisci. ResultsVolumes of knee bones, cartilages, and menisci did not significantly differ (p>0.05) across MRI sequences. MSK models estimated secondary knee kinematics during passive knee flexion tests consistent with in vivo and simulation-based values from the literature. Between the template-based and auto-meshing FE models, estimated cartilage mechanics often differed significantly (p<0.05), though differences were <15% (considering peaks during walking), i.e., <1.5 MPa for maximum principal stress, <1 percentage point for collagen fibril strain, and <3 percentage points for maximum shear strain. ConclusionThe template-based modeling provided a more rapid and robust tool than the auto-meshing approach, while the estimated knee biomechanics were comparable. Nonetheless, the auto-meshing approach might provide more accurate estimates in subjects with distinct knee irregularities, e.g., cartilage lesions. SignificanceThe MSK-FE modeling tool provides a rapid, easy-to-use, and robust approach to investigating task- and person-specific mechanical responses of the knee cartilage and menisci, holding significant promise, e.g., in personalized rehabilitation planning.

bioengineering↗

bioRxiv2021

An EMG-assisted Muscle-Force Driven Finite Element Analysis Pipeline to Investigate Joint- and Tissue-Level Mechanical Responses in Functional Activities: Towards a Rapid Assessment Toolbox

Joint tissue mechanics (e.g., stress and strain) are believed to have a major involvement in the onset and progression of musculoskeletal disorders, e.g., knee osteoarthritis (KOA). Accordingly, considerable efforts have been made to develop musculoskeletal finite element (MS-FE) models to estimate highly-detailed tissue mechanics that predict cartilage degeneration. However, creating such models is time-consuming and requires advanced expertise. This limits these complex, yet promising MS-FE models to research applications with few participants and making the models impractical for clinical assessments. Also, these previously developed MS-FE models are not assessed for any activities other than the gait. This study introduces and validates a semi-automated rapid state-of-the-art MS-FE modeling and simulation toolbox incorporating an electromyography (EMG) assisted MS model and a muscle-force driven FE model of the knee with fibril-reinforced poro(visco)elastic cartilages and menisci. To showcase the usability of the pipeline, we estimated joint- and tissue-level knee mechanics in 15 KOA individuals performing different daily activities. The pipeline was validated by comparing the estimated muscle activations and joint mechanics to existing experimental data. Also, to examine the importance of EMG-assisted MS analyses, results were compared against outputs from the same FE models but driven by static-optimization-based MS models. The EMG-assisted MS-FE pipeline bore a closer resemblance to experiments, compared to the static-optimization-based MS-FE pipeline. More importantly, the developed pipeline showed great potentials as a rapid MS-FE analysis toolbox to investigate multiscale knee mechanics during different activities of individuals with KOA.

biophysics↗

bioRxiv2020

MECHANISM OF ANTERIOR CRUCIATE LIGAMENT LOADING DURING DYNAMIC MOTOR TASKS

This study determined anterior cruciate ligament (ACL) force and its contributors during a standardized drop-land-lateral jump task using a validated computational model. Healthy females (n=24) who were recreationally active performed drop-land-lateral jump and straight run tasks. Three-dimensional whole-body kinematics, ground reaction forces, and muscle activation patterns from eight lower limb muscles were collected concurrently during both tasks, but only the jump was analyzed computationally, with the run included for model calibration. External biomechanics, muscle-tendon unit kinematics, and muscle activation patterns were used to model lower limb muscle and ACL forces. Peak ACL force (2.3{+/-}0.5 BW) was observed at 13% of the stance phase during the drop-land-lateral jump task. The ACL force was primarily developed through the sagittal plane, and muscle was the dominant source of ACL loading. The gastrocnemii and quadriceps were main ACL antagonists (i.e., loaders), while hamstrings were the main ACL agonists (i.e., supporters).

bioengineering↗