Hip Contact Load and Muscle Force in Femoroacetabular Impingement Population
Bibliographic record
Abstract
With a prevalence of 17% in men and 4% in women, Femoroacetabular Impingement (FAI) of type cam is characterized by a decreased femoral head-neck offset and/or asphericity of the lateral femoral head, associated with groin pain and reduced hip range of motion. Since the aetiology is still unclear, the mechanisms of development, progression and degeneration of FAI are largely investigated. Musculoskeletal modeling can support the development of a biomechanical framework to advance the research on FAI pathomechanisms, expand the knowledge about hip contact load distribution in FAI population, and relate the muscle and hip contact forces to the alterations observed during functional tasks. Therefore, this thesis is composed of two parts: the development of a methodological framework, and its application to the investigation of FAI pathomechanisms. The variability of the modelling outcomes (i.e.., body kinematics, torques, contact and muscle forces) to different marker sets, pelvic marker misplacements, and hip joint center (HJC) location was investigated within an inverse kinematic framework. The findings from such studies supported the modelling choices for the clinical investigation of FAI pathomechanisms. In particular, the performance of three different marker sets (Plug-in-Gait, University of Ottawa Motion Analysis Model and a 3-marker-cluster marker set) was compared, and absolute and relative reliability indices were calculated with the purpose of finding a simple yet reliable marker set to be used within an inverse kinematic framework in a clinical study. Thereafter, the sensitivity of joint angles, moments and hip contact forces to simulated inaccurate pelvic tilt was analyzed. The resulting variability indices were high with variations up to 1.3 times the body weight in hip contact forces. The kinematic variations propagated non-linearly to all planes and joints, showing the importance of adjusting possible pelvic misalignments. A methodology was presented to correct the pelvic alignment when the relative position of surface pelvic markers with respect to bony landmarks is known from medical images. The HJC location is a crucial modelling parameter in the analysis of hip kinematics and forces. A certain degree of customization could be introduced in the model by using HJC measured from medical images. Therefore, the performance of a generic musculoskeletal model with customized or non-customized HJC was compared during walking. Hip contact forces were highly sensitive to HJC location, especially because of the dependency of muscle moment arms to HJC changes. However, the variation of HJC without consistent muscle anatomy customization introduced artifacts that could potentially produce inaccurate muscle and joint contact forces estimation. When HJC cannot be measured from medical images, regression equations can be used instead. Therefore, the validity of two popular HJC regression equations (Harrington and Davis) was tested on FAI participants using non-parametric statistical and Bland-Altman tests. The results indicated that the equations were valid for FAI population. In addition, skin thickness measurements were provided for pelvic bony landmarks, and their correlation with body mass index was proposed for systematic error reduction. New adult-specific regression equations were developed from medical images. The described methodological framework was then applied to investigate the functional alterations observed in FAI population. The differences in muscle and hip contact forces were compared between FAI and healthy control groups during level walking. The FAI group showed reduced muscle and hip contact forces, which were linked to the lower normalized walking speed and shorter step length. These results can be interpreted as a protective mechanism developed by FAI patients to prevent high compression at the site of impingement, given that the compressing hip contact force was directed towards the anterior-superior quadrant of the acetabulum, consistent with the localization of the cam-type deformity and the cartilage and labrum damages. Based on these findings, a possible FAI pathomechanism was proposed, which could be used to support the development of preventive treatment and intervention for symptomatic FAI patients.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".