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The morphological variation of acetabular defects in revision total hip arthroplasty-A statistical shape modeling approach.

Alexander MeynenGeorges F VlesAmir A ZadpoorMichiel MulierLennart Scheys
Published in: Journal of orthopaedic research : official publication of the Orthopaedic Research Society (2021)
Classification and evaluation of acetabular defects remain challenging and are primarily based on qualitative classification methods. That is because quantitative techniques describing variations of acetabular defects and accompanying bone loss volume are not available. This study introduces a new method based on statistical shape models (SSMs) to quantitively describe acetabular defects. This method is then applied to 87 acetabular defects to objectively describe the variations in acetabular defects typically encountered during revision total hip arthroplasty. The absolute bone loss volume, relative bone loss volume, and relative bone loss surface area with respect to the SSM-based pre-diseased anatomy were used to quantify the acetabular bone defects in different segments of the acetabular surface. The absolute bone loss volume of the average defect shape was equal to 37.0 cm3 . The first three principal modes, accounting for 62% of the total shape variation, were found to represent variations in acetabular defect morphology. The first, second, and third principal modes described, respectively, the size of the bone defects, the difference between superomedially and superolaterally migrated defects, and the degree of involvement of the posterior or anterior column. The developed SSM and the introduced approach could be used to create automated and unbiased classification methods based on quantitative data. Moreover, the proposed model and the underlying data provide the basis for a quantitative design approach where the shape and size of new acetabular implants are determined according to clinical variation present in acetabular defects.
Keyphrases
  • total hip arthroplasty
  • bone loss
  • total hip
  • total knee arthroplasty
  • deep learning
  • machine learning
  • high resolution
  • systematic review
  • high throughput
  • mass spectrometry
  • liquid chromatography
  • soft tissue
  • single cell