ORCID Profile
0000-0002-1975-5433
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Publisher: Elsevier BV
Date: 07-2021
Publisher: Cold Spring Harbor Laboratory
Date: 23-02-2021
DOI: 10.1101/2021.02.22.432159
Abstract: Musculoskeletal (MSK) models based on literature data are meant to represent a generic anatomy and are a popular tool employed by biomechanists to estimate the internal loads occurring in the lower limb joints, such as joint reaction forces (JRFs). However, since these models are normally just linearly scaled to an in idual’s anthropometry, it is unclear how their estimations would be affected by the personalization of key features of the MSK anatomy, one of which is the femoral anteversion angle. How are the lower limb JRF magnitudes computed through a generic MSK model affected by changes in the femoral anteversion? We developed a bone-deformation tool in MATLAB ( rojects/bone_deformity ) and used it to create a set of seven OpenSim models spanning from 2° femoral retroversion to 40° anteversion. We used these models to simulate the gait of an elderly in idual with an instrumented prosthesis implanted at their knee joint (5 th Grand Challenge dataset) and quantified both the changes in JRFs magnitude due to varying the skeletal anatomy and their accuracy against the correspondent in vivo measurements at the knee joint. Hip and knee JRF magnitudes were affected by the femoral anteversion with variations from the unmodified generic model up to 11.7±5.5% at the hip and 42.6±31.0% at the knee joint. The ankle joint was unaffected by the femoral geometry. The MSK models providing the most accurate knee JRFs (root mean squared error: 0.370±0.069 body weight, coefficient of determination: 0.764±0.104, largest peak error: 0.36±0.16 body weight) were those with the femoral anteversion angle closer to that measured on the segmented bone of the in idual. Femoral anteversion substantially affects hip and knee JRFs estimated with generic MSK models, suggesting that personalizing key MSK anatomical features might be necessary for accurate estimation of JRFs with these models.
Publisher: Elsevier BV
Date: 08-2019
DOI: 10.1016/J.JBIOMECH.2019.07.001
Abstract: Computational knee models that replicate the joint motion are important tools to discern difficult-to-measure functional joint biomechanics. Numerous knee kinematic models of different complexity, with either generic or subject-specific anatomy, have been presented and used to predict three-dimensional tibiofemoral (TFJ) and patellofemoral (PFJ) joint kinematics of cadavers or healthy adults, but not pediatric populations. The aims of this study were: (i) to develop subject-specific TFJ and PFJ kinematic models, with TFJ models having either rigid or extensible ligament constraints, for eight healthy pediatric participants and (ii) to validate the estimated joint and ligament kinematics against in vivo kinematics measured from magnetic resonance imaging (MRI) at four TFJ flexion angles. Three different TFJ models were created from MRIs and used to solve the TFJ kinematics: (i) 5-rigid-link parallel mechanism with rigid surface contact and isometric anterior cruciate (ACL), posterior cruciate (PCL) and medial collateral (MCL) ligaments (ΔL
Publisher: Springer Science and Business Media LLC
Date: 16-07-2020
Publisher: Elsevier BV
Date: 09-2018
Publisher: Springer Science and Business Media LLC
Date: 05-11-2019
DOI: 10.1007/S10237-019-01245-Y
Abstract: In biomechanical simulations, generic linearly scaled musculoskeletal anatomies are commonly used to represent children, often neglecting or oversimplifying subject-specific features that may affect model estimates. Inappropriate bone sizing may influence joint angles due to erroneous joint centre identification. Alternatively, subject-specific image-based musculoskeletal models allow for more realistic representations of the skeletal system. To this end, statistical shape modelling (SSM) and morphing techniques may help to reconstruct bones rapidly and accurately. Specifically, the musculoskeletal atlas project (MAP) Client, which employs magnetic resonance imaging (MRI) and/or motion capture data to inform SSM and nonrigid morphing techniques, proved able to accurately reconstruct adult pelvis and femur bones. Nonetheless, to date, the above methods have never been applied to paediatric data. In this study, pelvis, femurs and tibiofibular bones of 18 typically developing children were reconstructed using the MAP Client. Ten different combinations of SSM and morphing techniques, i.e. pipelines, were developed. Generic bone geometries from the gait2392 OpenSim model were linearly scaled for comparisons. Jaccard index, root mean square distance error and Hausdorff distance were computed to quantify reconstruction accuracy. For the pelvis bone, colour maps were produced to identify areas prone to inaccuracies and hip joint centres (HJC) location was compared. Finally, per cent difference between MRI- and MAP-measured left-to-right HJC distances was computed. Pipelines informed by MRI data, alone or in combination with motion capture data, accurately reconstructed paediatric lower limb bones (i.e. Jaccard index > 0.8). Scaled OpenSim geometries provided the least accurate reconstructions. Principal component-based scaling methods produced size-dependent results, which were worse for smaller children.
Publisher: Elsevier BV
Date: 09-2021
Publisher: Elsevier BV
Date: 10-2022
DOI: 10.1016/J.CMPB.2022.107002
Abstract: Accurate representation of bone shape is important for subject-specific musculoskeletal models as it may influence modelling of joint kinematics, kinetics, and muscle dynamics. Statistical shape modelling is a method to estimate bone shape from minimal information, such as anatomical landmarks, and to avoid the time and cost associated with reconstructing bone shapes from comprehensive medical imaging. Statistical shape models (SSM) of lower limb bones have been developed and validated for adult populations but are not applicable to paediatric populations. This study aimed to develop SSM for paediatric lower limb bones and evaluate their reconstruction accuracy using sparse anatomical landmarks. We created three-dimensional models of 56 femurs, 29 pelves, 56 tibias, 56 fibulas, and 56 patellae through segmentation of magnetic resonance images taken from 29 typically developing children (15 females 13 ± 3.5 years). The SSM for femur, pelvis, tibia, fibula, patella, haunch (i.e., combined femur and pelvis), and shank (i.e., combined tibia and fibula) were generated from manual segmentation of comprehensive magnetic resonance images to describe the shape variance of the cohort. We implemented a leave-one-out cross-validation method wherein SSM were used to reconstruct novel bones (i.e., those not included in SSM generation) using full- (i.e., full segmentation) and sparse- (i.e., anatomical landmarks) input, and then compared these reconstructions against bones segmented from magnetic resonance imaging. Reconstruction performance was evaluated using root mean squared errors (RMSE, mm), Jaccard index (0-1), Dice similarity coefficient (DSC) (0-1), and Hausdorff distance (mm). All results reported in this abstract are mean ± standard deviation. Femurs, pelves, tibias, fibulas, and patellae reconstructed via SSM using full-input had RMSE between 0.89 ± 0.10 mm (patella) and 1.98 ± 0.38 mm (pelvis), Jaccard indices between 0.77 ± 0.03 (pelvis) and 0.90 ± 0.02 (tibia), DSC between 0.87 ± 0.02 (pelvis) and 0.95 ± 0.01 (tibia), and Hausdorff distances between 2.45 ± 0.57 mm (patella) and 9.01 ± 2.36 mm (pelvis). Reconstruction using sparse-input had RMSE ranging from 1.33 ± 0.61 mm (patella) to 3.60 ± 1.05 mm (pelvis), Jaccard indices ranging from 0.59 ± 0.10 (pelvis) to 0.83 ± 0.03 (tibia), DSC ranging from 0.74 ± 0.08 (pelvis) to 0.90 ± 0.02 (tibia), and Hausdorff distances ranging from 3.21 ± 1.19 mm (patella) to 12.85 ± 3.24 mm (pelvis). The SSM of paediatric lower limb bones showed reconstruction accuracy consistent with previously developed SSM and outperformed adult-based SSM when used to reconstruct paediatric bones.
Publisher: Ovid Technologies (Wolters Kluwer Health)
Date: 2019
Abstract: Osseous rotational malalignment of the lower limb is widely accepted as a factor contributing to patellofemoral instability, particularly in pediatric patients. Patellar instability occurs when the lateral force vector generated by the quadriceps exceeds the restraints provided by osseous and soft-tissue anatomy. The anatomy and activation of the quadriceps are responsible for the force applied across the patellofemoral joint, which has previously been measured using the quadriceps (Q)-angle. To our knowledge, the contribution of the quadriceps anatomy in generating a force vector in the axial plane has not previously been assessed. The primary aim of this study was to introduce the quadriceps torsion angle, a measure of quadriceps rotational alignment in the juvenile population. The secondary aims of this study were to determine the inter-assessor and intra-assessor reliability of the quadriceps torsion angle in the juvenile population and to investigate whether a large quadriceps torsion angle is a classifier of patellar dislocator group membership in a mixed cohort of patellar dislocators and typically developing controls. Participants between the ages of 8 and 19 years were recruited as either controls or recurrent patellar dislocators. A total of 58 knees in both groups were assessed from magnetic resonance imaging scans of the entire lower limbs. Axial cuts midway between the superior aspect of the femoral head and the articular surface of the medial femoral condyle were used to calculate the proximal reference for the quadriceps torsion angle. The quadriceps torsion angle was defined as the angle between the line connecting the anterior aspect of the sartorius and the junction of the anterior and posterior compartments at the lateral intermuscular septum and the posterior condylar axis line. Inter-assessor reliability was calculated using the intraclass correlation coefficient. The relationship between the quadriceps torsion angle and the femoral torsion was assessed in the entire cohort. These values were compared between the control group and the dislocator group to determine if the raw values or an interplay between the 2 factors played a role in the pathoanatomy of recurrent patellofemoral dislocation. The quadriceps torsion angle was a reproducible assessment in both inter-assessor and intra-assessor reliability analyses. A moderate positive correlation (r = 0.624 p 0.01) was found between the femoral torsion and the quadriceps torsion angle. Although the quadriceps torsion angle was a fair classifier of patellar dislocation group membership, femoral torsion was not. This study has quantified the rotational alignment of the extensor mechanism using the quadriceps torsion angle. The measurement is shown to be reliable and reproducible and a fair classifier of patellofemoral instability. This article introduces an objective measure of soft-tissue rotational malalignment in the pathogenesis of recurrent patellar dislocation.
Location: United Kingdom of Great Britain and Northern Ireland
No related grants have been discovered for Martina Barzan.