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Abstract

Finite element models can predict subject-specific chondrolabral stresses and help to elucidate the effect of under-coverage and incongruency of the hip joint in patients with dysplasia. However, complex stress patterns are difficult to generalize and evaluate statistically. With an established correspondence across shapes from statistical shape modeling (SSM), statistical parametric mapping (SPM) allows for evaluation of local variability while preserving model subject-specificity. Herein, we evaluated the combined application of SSM and SPM to compare cartilage contact stress between control subjects and patients with dysplasia.

Previously published hip joint contact stresses were mapped onto chondrolabral surface meshes and incorporated into an SSM. Principal component analysis (PCA) quantified shape variation. Contact stress values from heel-strike of stair ascent (AH), stair descent (DH), and level walking (WH) and mid-stance of level walking (WM) were evaluated. Using SPM, regions of significant contact stress variation were identified based on test statistics from general linear statistical models and corrected for multiple comparisons using Gaussian random fields.

Shape differences of the femoral and acetabular cartilage with labrum were captured by two and one PCA mode, respectively. Contact stress differences were observed in anterosuperior regions of the femoral cartilage for AH and DH and of the acetabular cartilage for DH and WM (Figure 1). The SPM identified regions of varied contact stresses were small and likely would have been diluted through averaging or region-splitting using traditional analysis methods. The combined application of SSM and SPM provides a method to generalize and statistically-compare subject-specific mechanics and joint morphology.

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Combination of Statistical Shape Modeling and Statistical Parametric Mapping to Quantify Cartilage Contact Mechanics in Hip Dysplasia

Finite element models can predict subject-specific chondrolabral stresses and help to elucidate the effect of under-coverage and incongruency of the hip joint in patients with dysplasia. However, complex stress patterns are difficult to generalize and evaluate statistically. With an established correspondence across shapes from statistical shape modeling (SSM), statistical parametric mapping (SPM) allows for evaluation of local variability while preserving model subject-specificity. Herein, we evaluated the combined application of SSM and SPM to compare cartilage contact stress between control subjects and patients with dysplasia.

Previously published hip joint contact stresses were mapped onto chondrolabral surface meshes and incorporated into an SSM. Principal component analysis (PCA) quantified shape variation. Contact stress values from heel-strike of stair ascent (AH), stair descent (DH), and level walking (WH) and mid-stance of level walking (WM) were evaluated. Using SPM, regions of significant contact stress variation were identified based on test statistics from general linear statistical models and corrected for multiple comparisons using Gaussian random fields.

Shape differences of the femoral and acetabular cartilage with labrum were captured by two and one PCA mode, respectively. Contact stress differences were observed in anterosuperior regions of the femoral cartilage for AH and DH and of the acetabular cartilage for DH and WM (Figure 1). The SPM identified regions of varied contact stresses were small and likely would have been diluted through averaging or region-splitting using traditional analysis methods. The combined application of SSM and SPM provides a method to generalize and statistically-compare subject-specific mechanics and joint morphology.

 

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